CRAMP OK

*Plan / Would you have described your research team as <a href="https://www.collinsdictionary.com/dictionary/english/interdisciplinary">interdisciplinary</a> (y/n)? [[No |P1_01_wave2_1_no_details]] [[Yes |P1_01_wave2_1_yes_details]] [[No |P1_01_wave2_2_no_details]] [[Yes |P1_01_wave2_2_yes_details]]

Warning: Do not conclude from the non-interdisciplinarity of your project, that its results and research question could only be relevant/interesting to members of your particular discipline!

Follow-Up: Are or were you aware of any aspects of your research that are contested between disciplines? [[No |P1_01_wave2_2_no_details]] [[Yes |P1_01_wave2_2_yes_details]]

No further recommendations

Advise: In case you are dealing with terms and/or concepts that are being interpreted fundamentally different between disciplines involved in your Research, this should not automatically mean you have to “pick a side”. It is however useful to be aware of any such conflicts and establish a common understanding of the key terms and how they are being used in connection with your Research.

*Plan / Would you have described your research team as <a href="https://www.collinsdictionary.com/dictionary/english/international">international</a> or <a href="https://www.collinsdictionary.com/dictionary/english/cultural-diversity">culturally diverse</a>(y/n)? [[No |P1_02_wave2_1_no_details]] [[Yes |P1_02_wave2_1_yes_details]]

Advise: Generally speaking, greater diversity of a group is often associated with a larger set of capabilities . Should your Research focus on particular cultures or regions, differing from your own, you might want to cooperate with local Researchers, in order to expand your understanding of the subject.

No further recommendations

*Plan / Would you have described your research team as <a href="https://www.britannica.com/topic/neurodiversity">neurodiverse</a> (y/n)? [[No |P1_03_wave2_1_no_details]] [[Yes |P1_03_wave2_1_yes_details]] [[No |P1_03_wave2_2_no_details]] [[Yes |P1_03_wave2_2_yes_details]]

Advise: Generally speaking, greater diversity of a group is often associated with a larger set of capabilities . Keep in mind your lack thereof, if questions related to matters concerning neurodiversity, occur during your research-work. If you are unfamiliar to the subject, but want to start to learn more about the concept, see <a href="https://www.doi.org/10.1111/jcpp.13534">this reference</a>.

Follow-Up: Do or did you apply any procedures to address neurotypical persons’ needs in your Research Project? [[No |P1_03_wave2_2_no_details]] [[Yes |P1_03_wave2_2_yes_details]]

Advise: Even if you might be convinced, that these kind of questions have nothing to do with your particular Research and should be treated as personal matters, you might be well-advised to prepare safe-spaces and apply strategies to address neurotypical persons’ characteristics. This could result in an improved working situation and thus reduce the risk of stress-induced errors or worse. If you are looking for more concrete strategies, you may start <a href="https://www.cipd.org/globalassets/media/knowledge/knowledge-hub/guides/neurodiversity-at-work_2018_tcm18-37852.pdf">here</a>.

No further recommendations

*Plan / Would you have assessed your research team as diverse concerning Age and Gender (y/n)? [[No |P1_04_wave2_1_no_details]] [[Yes |P1_04_wave2_1_yes_details]] [[No |P1_04_wave2_2_no_details]] [[Yes |P1_04_wave2_2_yes_details]]

Advise: Generally speaking, greater diversity of a group is often associated with a larger set of capabilities . It also might reduce unnoticed group biases, if the group does not exclusively consist of members of the same social categories. If you need further reading on this subject, you will find a vast collection of examples and resources <a href="https://www.nature.com/collections/qsgnpdtgbr">here</a>.

Follow-Up: Does or did this diversity come along with a certain, unarticulated internal hierarchy (y/n)? [[No |P1_04_wave2_2_no_details]] [[Yes |P1_04_wave2_2_yes_details]]

No further recommendations

Warning: Any notions about age, ethnicity or gender as “superior” qualities, that deserve to make a higher impact on Research Project related decisions, should be transparently articulated with colleagues, before the cooperation starts.

*Plan / Did your Research Team involve <a href="https://www.who.int/health-topics/disability#tab=tab_1">Persons of Disability</a> (y/n)? [[No |P1_05_wave2_1_no_details]] [[Yes |P1_05_wave2_1_yes_details]] [[No |P1_05_wave2_2_no_details]] [[Yes |P1_05_wave2_2_yes_details]]

Follow-Up: Did you consider or are you considering inclusive measures to open up your research project to People of Disability (y/n)? [[No |P1_05_wave2_2_no_details]] [[Yes |P1_05_wave2_2_yes_details]]

No further recommendations

Warning: Then the lack of Persons of Disability in your team might also be explainable with your project’s lack of barrier-freedom. Even if you might not be able to counter all existing disabilities by technical means, you certainly have the option to do this with some. For more information, for instance on how to address such problems in digital contexts, you can start Research <a href="https://www.w3.org/WAI/standards-guidelines/">here</a>.

No further recommendations

*QA / Were you aware and/or suspicious of any kind of misconduct happening within your research team (y/n)? [[No |P1_06_wave2_1_no_details]] [[Yes |P1_06_wave2_1_yes_details]] [[No |P1_06_wave2_2_no_details]] [[Yes |P1_06_wave2_2_yes_details]] [[No |P1_06_wave2_3_no_details]] [[Yes |P1_06_wave2_3_yes_details]]

Follow-Up: Are or were you interested in becoming aware of any kind of misconduct happening within your research team (y/n)? [[No |P1_06_wave2_2_no_details]] [[Yes |P1_06_wave2_2_yes_details]] [[No |P1_06_wave2_3_no_details]] [[Yes |P1_06_wave2_3_yes_details]]

Advise: Depending on the gravity of your suspicions, you may not want to discuss this topic directly with the suspected individuals, to offer them no chance to manipulate possible evidence. This is at least, what the US Office of Research Integrity (ORI) <a href="https://ori.hhs.gov/sites/default/files/2017-12/9_Suspect_Misconduct.pdf">recommends</a>. You could consult your local equivalent of this institution in secrecy, in order to receive qualified counseling, before making any allegations public.

Warning: If you not even tried to get aware of such incidents, you cannot expect to have any knowledge about it. Perhaps start listening to your colleagues (Research collaborators).

Follow-Up: Were you, or are you being trained to adequately react to such situations (y/n)? [[No |P1_06_wave2_3_no_details]] [[Yes |P1_06_wave2_3_yes_details]]

Advise: It might be a good idea not to overestimate your individual competence, to find an adequate solution for this problem all by yourself. However, if you have the opportunity to attend courses and/or workshops for misconduct prevention at your institution or partnering institutions, you might be well advised to do so, anyway.

No further recommendations

*Share / Did you actively attempt to use <a href="https://www.collinsdictionary.com/dictionary/english/inclusive-language">inclusive language</a>, while communicating within your research team (y/n)? [[No |P1_07_wave2_1_no_details]] [[Yes |P1_07_wave2_1_yes_details]]

Advise: Should you lack any interest in the concept of inclusive language and its potential benefits, you perhaps could have a look at data from practical <a href="https://www.doi.org/10.2105/AJPH.2021.306602">examples</a> which seem to suggest, that there is indeed a correlation between inclusive language and well-being/productivity at work. Would it, given your context, be more costly to pay attention to inclusive language, than to explain why you are not (or to exclude people altogether)?

No further recommendations

Warning: If not already qualified as plagiarism, this situation at least violates any principles of good research. If you experienced technical difficulties in referencing the works of individuals, services or collectives within your project context, you might get inspired by the idea of movie-type credits, that could supplement the more traditional lists of academic references. <a href="https://medium.com/@sjb015/when-pigs-fly-changing-author-lists-on-scientific-papers-c143af826bcb">Read more</a>.

Follow-Up: Do or did you further not credit individuals who did not actively contribute to your project (y/n)? [[No |P1_08_wave2_2_no_details]] [[Yes |P1_08_wave2_2_yes_details]] [[No |P1_08_wave2_3_no_details]] [[Yes |P1_08_wave2_3_yes_details]]

Follow-Up: Do or did you still reference contributions by persons who explicitly wished to be treated as anonymous contributors (y/n)? [[No |P1_08_wave2_3_no_details]] [[Yes |P1_08_wave2_3_yes_details]]

Warning: While it might be tempting to include superiors, teachers or other scientific peers in a publication’s list of authors, i.e. for reasons of reverence, doing so, without them having actively committed to the work, is a practice conflicting with the very principle of academic authorship defined in most literature about <a href="https://www.dfg.de/download/pdf/foerderung/rechtliche_rahmenbedingungen/gute_wissenschaftliche_praxis/kodex_gwp_en.pdf">good scientific practice</a>. There are other, more adequate ways of honouring support, than a fake co-authorship (the DFG recommends “footnotes”, “introductions” or “acknowledgements”). More data about the phenomenon of <a href="https://doi.org/10.1371/journal.pone.0187394">honorary quotations</a>.

Advise: It is still important to not claim contributions for yourself, which are not. You can quote anonymous sources; how to do this is individually defined in your used quotation scheme.

Warning: Depending on your research context, you might have Research contributors, who, for any personal reasons, wish to remain anonymous. Adequately crediting their contributions would still require to credit anonymous contributions, that are not yours. However, fulfilling this task, while providing valid research results at the same time, can be a complex and sometimes impossible matter. So you might want to plan and coordinate, what you can and cannot do, directly with the relevant people in question. If you need an example for understanding the underlying problems, you cand find further reading <a href="https://doi.org/10.1177%2F1468794114550439">here</a>.

*Share / Did you explicitly communicate with relevant Research contributors, how you were going to credit them (y/n)? [[No |P1_09_wave2_1_no_details]] [[Yes |P1_09_wave2_1_yes_details]] [[No |P1_09_wave2_2_no_details]] [[Yes |P1_09_wave2_2_yes_details]]

Advise: Discussing the matter of crediting people, actively involved in a Research (Data Stewardship) scenario, makes sense in order to avoid misunderstandings. Perhaps you did not realize someone‘s will to be treated anonymously, because you had no understanding of their personal motivations for it (while they might have assumed their anonymity in your publication as a given). Or maybe, your personal perception of how workload and efforts have been distributed among your team is inaccurate. Dealing with these issues before publication, might avoid problems later.

Follow-Up: Are you planning to or did you briefly explain the decision on whom to credit how, in the respective publication (y/n)? [[No |P1_09_wave2_2_no_details]] [[Yes |P1_09_wave2_2_yes_details]]

Advise: While not legally binding, documenting any internal agreements from just-before-publication, in the metadata to a publication, might help later, in case of conflict, to reconstruct the initial situation. It might be of particular use to verify, if prior internal agreements had been implemented as discussed.

No further recommendations

*QA / Did you have any motivation to contribute more to your Research Team’s work, than the required minimum (y/n)? [[No |P1_10_wave2_1_no_details]] [[Yes |P1_10_wave2_1_yes_details]] [[No |P1_10_wave2_2_no_details]] [[Yes |P1_10_wave2_2_yes_details]]

Follow-Up: Do or did you have the feeling that this condition changed over the time, you spent in the project team (y/n)? [[No |P1_10_wave2_2_no_details]] [[Yes |P1_10_wave2_2_yes_details]]

Advise: If you keep contributing more to your work than you are required to (in measurable working hours), you may want to familiarize yourself with the concept of <a href="https://www.nature.com/collections/fgbafieaad">Work-Life-Balance</a>. Since serious health risks are attributed to the phenomenon, it is advisable to make adjustments if you work too much. If you are in a position of being responsible for others, you should also avoid expecting this kind of behaviour from them.

No further recommendations

Advise: This condition may qualify as the phenomenon of quiet quitting, which is not necessarily connected to a loss of research/work quality, but may as well indicate an unhealthy working environment. In order to start getting an understanding of the phenomenon, and what you can possibly do about it, you may want to start further research <a href="https://doi.org/10.1038/d41586-023-00633-w">here</a>.

*QA / Were there any risks of your research data being manipulated by internal or external attacks (y/n)? [[No |P1_11_wave2_1_no_details]] [[Yes |P1_11_wave2_1_yes_details]] [[No |P1_11_wave2_2_no_details]] [[Yes |P1_11_wave2_2_yes_details]]

No further recommendations

Follow-Up: Did you or do you apply any strategies to protect the research project’s data from being manipulated by team members and externals (y/n)? [[No |P1_11_wave2_2_no_details]] [[Yes |P1_11_wave2_2_yes_details]]

Advise: Of course, your influence on this is limited, however you could try applying certain technical mechanisms, to secure your Research Data from tampering. If you are not an expert on data security, you can start familiarizing yourself with the matter <a href="http://dx.doi.org/10.1109/TSE.2002.1027797">here</a>. However, it could be advisable to further consult specialised experts and perhaps receive some professional counseling.

No further recommendations

*QA / Did any of your team members review the work of other team members for reasons of quality control (y/n)? [[No |P1_12_wave2_1_no_details]] [[Yes |P1_12_wave2_1_yes_details]]

Advise: The underlying <a href="https://www.collinsdictionary.com/dictionary/english/four-eyes-principle">four eyes principle</a>, if implemented in practice, can lead to phenomena like so called <a href="https://doi.org/10.1016/j.infsof.2009.02.001">Pair Programming</a> in software development.

Advise: It might not come to you as a new information, but the whole concept, as for example in peer programming, only turns out productively, if the skill-levels of collaborating team members are equally high. Otherwise you might risk quality reduction, or a waste of resources, instead of the desired Quality Assurance. To get a further understanding of potential issues, and what you perhaps should double-check, you may want to have a look at <a href="https://doi.org/10.1016/j.infsof.2009.02.001">this resource</a>.

*Share / Did you explicitly communicate your results to regions and/or communities to whom they are directly relevant (y/n)? [[No |P2_01_wave2_1_no_details]] [[Yes |P2_01_wave2_1_yes_details]] [[No |P2_01_wave2_2_no_details]] [[Yes |P2_01_wave2_2_yes_details]]

Warning: The very legitimation of your research [if conducted with public funds] might be founded on the expectation that you did. If you could not adequately make this happen on your own, you might want to seek help from public authorities or relevant communities, directly. For an example, on how the planful transfer of relevant knowledge to relevant adresses could happen, see <a href="https://doi.org/10.3390/geosciences9060250">this resource</a>.

Follow-Up: Do you or did you keep monitoring how your research results impact the region and/or community (y/n)? [[No |P2_01_wave2_2_no_details]] [[Yes |P2_01_wave2_2_yes_details]]

Advise: It might be interesting, also scientifically, to monitor such consequences. Perhaps future Research ideas may occur as a follow-up, or you become able to discover potential weaknesses in your work. Therefore, it is recommended to try becoming aware of such consequences.

No further recommendations

*Analyze / Were you aware of any threats to the interests of a particular community or individual, caused by your research (y/n)? [[No |P2_02_wave2_1_no_details]] [[Yes |P2_02_wave2_1_yes_details]] [[No |P2_02_wave2_2_no_details]] [[Yes |P2_02_wave2_2_yes_details]] [[No |P2_02_wave2_3_no_details]] [[Yes |P2_02_wave2_3_yes_details]]

No further recommendations

Follow-Up: Did you communicate these circumstances to the relevant people, before beginning with your research (y/n)? [[No |P2_02_wave2_2_no_details]] [[Yes |P2_02_wave2_2_yes_details]] [[No |P2_02_wave2_3_no_details]] [[Yes |P2_02_wave2_3_yes_details]]

Warning: By not doing so, you most probably act illegally, based on your area’s respective legislation.

Follow-Up: Did you or are you communicating these risks in your usual scientific language style (y/n)? [[No |P2_02_wave2_3_no_details]] [[Yes |P2_02_wave2_3_yes_details]]

Advise: If you felt conflicted between phrasing too technical (<a href="https://doi.org/10.1093/biosci/biz152">"tell it like it is"</a>) and sounding too broad or alarmist (and thereby risking to induce negative reactions), perhaps try to understand who your audience is, before you decide how to get the same message across as best as possible.

*Analyze /Did you apply any measures to prevent avoidable misrepresentations of particular communities and/or individuals through your research(y/n)? [[No |P2_03_wave2_1_no_details]] [[Yes |P2_03_wave2_1_yes_details]] [[No |P2_03_wave2_2_no_details]] [[Yes |P2_03_wave2_2_yes_details]]

Warning: Misrepresentation, as a term used here, does not exclusively refer to a legal definition, but it also describes social and scientific effects. It may be described as: "Communicating honestly reported data in a deceptive manner“, as phrased <a href="https://doi.org/10.1016/B0-08-043076-7/00157-1">here</a>. As a general rule, it might be advisable for good Research (Data Managent) to refrain from any attempts of representation, where ever this is possible.

Follow-Up: Did you, or are you planning to verify the effectiveness of your measures, by collecting relevant feedback (y/n)? [[No |P2_03_wave2_2_no_details]] [[Yes |P2_03_wave2_2_yes_details]]

Advise: If you wish to become aware of individual context dependant instances of misrepresentation, that might not have been covered on a theoretic level elsewhere, you might be interested in having concrete feedback on what you are doing and how it resonates with relevant people.

No further recommendations

Plan / Were your Research (Data) especially relevant to a particular region and/or community (y/n)? [[Yes |P2_01_question]] [[Yes |P2_02_question]] [[Yes |P2_03_question]]

*Plan / Did your Research Question require methods and/or decisions, you would understand as controversial to particular communities or individuals (y/n)? [[No |P3_01_wave2_1_no_details]] [[Yes |P3_01_wave2_1_yes_details]] [[No |P3_01_wave2_2_no_details]] [[Yes |P3_01_wave2_2_yes_details]]

Advise: Be sure to double-check this evaluation of yours, with other relevant entities (e.g. scientific peers, collaboration partners, other Domain Experts). A highly polarizing controversy could turn out as damning to a Research project, as no controversy at all. If you seek for a „healthy“ middle-ground it could help to put some effort in understanding the concept of (public) scientific controversies. A good point to start: DOI: 10.17226/23674

Follow-Up: Is or was any level of civil disobedience necessary to conduct your Research (y/n)? [[No |P3_01_wave2_2_no_details]] [[Yes |P3_01_wave2_2_yes_details]]

No further recommendations

Advise: If you decided for civil disobedience, you might still want to be transparent about it and have your facts right. This avoids the notion of secretly covering up illegal activities. See as an example on how it can be done: https://scientistrebellion.org/

*Share / Did you feel the need to paraphrase or obscure your research, in order to avoid negative public reactions (y/n)? [[No |P3_02_wave2_1_no_details]] [[Yes |P3_02_wave2_1_yes_details]] [[No |P3_02_wave2_2_no_details]] [[Yes |P3_02_wave2_2_yes_details]]

No further recommendations

Follow-Up: Did you, or are you planning to, seek qualified support in finding a compromise between self-protection and intellectual honesty (y/n)? [[No |P3_02_wave2_2_no_details]] [[Yes |P3_02_wave2_2_yes_details]]

Advise: It could be helpful to verify if and how your changes affected the consequences of your Research Data (Stewardship) Sharing. Asking for qualified opinions, might be a useful indicator that you could use to verify the effects of your changes.

No further recommendations

*Re-Use / Did your Research use any explicitly political literature as source (y/n)? [[No |P3_03_wave2_1_no_details]] [[Yes |P3_03_wave2_1_yes_details]] [[No |P3_03_wave2_2_no_details]] [[Yes |P3_03_wave2_2_yes_details]]

Advise: Doing so should not generally be disregarded as unscientific. The context matters: If you use political literature for reconstructing historic realities, you might need to be more cautious than if you just use the same sources for analysing their psychological effects.

Follow-Up: Were you or are you trying to convey a political message yourself, by using these materials as sources (y/n)? [[No |P3_03_wave2_2_no_details]] [[Yes |P3_03_wave2_2_yes_details]]

Advise: If you do not intend to convey any particular political messages via your research, you may want to double check that you are not doing so uncontrolled, via your sources. If in doubt, you could try an approach with critical annotations of the sources. Perhaps check out <a href="https://www.ifz-muenchen.de/mein-kampf">this example</a> to get an idea.

Warning: Please make sure to clearly differentiate in any of your publications between data and political demands. This is not to say that political demands are less valuable to a society than scientific results, but in the interest of both, they should not be confused for each other.

*Share / Did the knowledge of moral controversies regarding your Research Topic influence your publication process (y/n)? [[No |P3_04_wave2_1_no_details]] [[Yes |P3_04_wave2_1_yes_details]] [[No |P3_04_wave2_2_no_details]] [[Yes |P3_04_wave2_2_yes_details]] [[No |P3_04_wave2_3_no_details]] [[Yes |P3_04_wave2_3_yes_details]]

Follow-Up: Did you, or are you planning to address, moral controversies related to your research topic, in your publication (y/n)? [[No |P3_04_wave2_2_no_details]] [[Yes |P3_04_wave2_2_yes_details]] [[No |P3_04_wave2_3_no_details]] [[Yes |P3_04_wave2_3_yes_details]]

Advise: While it can be a good idea to re-consider planned publications on the basis of existing controversies (perhaps you did or got something fundamentally wrong), this does not necessarily need to result in self-censorship. If you observe yourself trying to self-censor your or your teams’ work where this feels scientifically unjustified, you perhaps should reconsider whether you want to publish elsewhere or later, if this helps to keep the original research results intact.

Advise: Showing no awareness of any moral controversies, associated with the context of your Research Topic, while you published results, might make you look ignorant. There is nothing wrong with a neutral opinion per se, but it can be recommended to actively refer to the ongoing controversy and explain your decisions, given this background.

Follow-Up: Was, or is your publication planned, as a reaction towards the named moral controversies (y/n)? [[No |P3_04_wave2_3_no_details]] [[Yes |P3_04_wave2_3_yes_details]]

No further recommendations

Advise: Take care to not confuse your desire to make a political or moral argument with a genuine Research Result.

Plan / Were you aware of any broader moral controversies in your society, accompanying your chosen Research Topic (y/n)? [[Yes |P3_01_question]] [[Yes |P3_02_question]] [[Yes |P3_03_question]] [[Yes |P3_04_question]]

*Were you looking for concrete advice on how to deal with a specific situation (y/n)? [[No |P4_01_wave2_1_no_details]] [[Yes |P4_01_wave2_1_yes_details]]

Advise: If you consulted ethical guidelines just to be prepared, before even running into a specific problem, you should receive additional Honour Points. But be aware that reality will most likely turn out different than the idealised guidelines suggest. Try not to become dependent of a single tool.

No further recommendations

Plan / Did you consult any particular ethical guideline before or while working at your Research Project (y/n)? [[Yes |P4_01_question]]

*Analyze / Did you try to contact researchers and/or Research (Data Stewardship) Projects working on the same Research Questions as you do (y/n)? [[No |P5_01_wave2_1_no_details]] [[Yes |P5_01_wave2_1_yes_details]] [[No |P5_01_wave2_2_no_details]] [[Yes |P5_01_wave2_2_yes_details]]

Advise: It may be scientifically beneficial to do so, especially in order to share resources and coordinate efforts. Should you fear the risk of theft of ideas, you could remain reluctant in sharing all details of your Research (Data Stewardship) at once, before having agreed upon any contracts. In case you are further interested in this matter, consider seeking Legal Counseling and check out the details of your local jurisdiction, for <a href="https://intellectual-property-helpdesk.ec.europa.eu/system/files/2021-02/EU-IPR-Guide-IP-and-Contracts%283%29.pdf">example</a>.

Follow-Up: Were you able to share experiences and/or resources (y/n)? [[No |P5_01_wave2_2_no_details]] [[Yes |P5_01_wave2_2_yes_details]]

Advise: Please be aware, that you have actually tried/seriously considered the possibility, before having reached this answer.

No further recommendations

Plan / Were you aware of other researchers or Research (Data Stewardship) projects, who are in parallel, working on the same research question(s) as you do (y/n)? [[Yes |P5_01_question]]

*Collect / Did you and/or your team actively collect any Research Data from uninhabited natural ecosystems (y/n)? [[No |P6_01_wave2_1_no_details]] [[Yes |P6_01_wave2_1_yes_details]] [[No |P6_01_wave2_2_no_details]] [[Yes |P6_01_wave2_2_yes_details]]

No further recommendations

Follow-Up: Were or are you aware of the extent of your direct influence on the surrounding natural ecosystems (y/n)? [[No |P6_01_wave2_2_no_details]] [[Yes |P6_01_wave2_2_yes_details]]

Warning: Not being aware of one’s direct influence on the environment should, as such, be a red flag. It is very possible that you overlook risks, you are already taking, if not to the environment, so perhaps to your data or vice versa. Make sure to cautiously monitor this question. See as an <a href="https://doi.org/10.1016/j.jenvman.2022.114634">example</a>.

Advise: Even if this might not be relevant to your particular Research question or cast a bad light on your activities, you really should consider sharing this information. Future attempts to reproduce your measurements and/or experiments should know about your influence, in order to be as precise as possible.

*Collect / Did you and/or your team actively collect any Research Data from particular social environments (y/n)? [[No |P6_02_wave2_1_no_details]] [[Yes |P6_02_wave2_1_yes_details]] [[No |P6_02_wave2_2_no_details]] [[Yes |P6_02_wave2_2_yes_details]] [[No |P6_02_wave2_3_no_details]] [[Yes |P6_02_wave2_3_yes_details]]

No further recommendations

Follow-Up: Did you or are you planning to transparently inform members of this particular environment about your research activities and results (y/n)? [[No |P6_02_wave2_2_no_details]] [[Yes |P6_02_wave2_2_yes_details]] [[No |P6_02_wave2_3_no_details]] [[Yes |P6_02_wave2_3_yes_details]]

Follow-Up: Did you or do you have any concrete pragmatic or scientific reason, not to do so (y/n)? [[No |P6_02_wave2_3_no_details]] [[Yes |P6_02_wave2_3_yes_details]]

No further recommendations

Warning: In absence of a concrete scientific reason to not do so, you should properly inform the relevant human entities. Otherwise, you will risk participants’ trust right from the beginning.

Advise: If you needed an element of surprise or secrecy for your Research project to work, you may at least want to provide these information embedded into a proper de-briefing, after having conducted your Research Data collection and before publishing any of it. Should you need more information about the concept of scientific de-briefing, you may start further reading <a href="https://doi.org/10.1017/9781009010054.013">here</a>.

*Collect / Did you experience any unplanned need to interrupt or prematurely finish scientific field-work (y/n)? [[No |P6_03_wave2_1_no_details]] [[Yes |P6_03_wave2_1_yes_details]] [[No |P6_03_wave2_2_no_details]] [[Yes |P6_03_wave2_2_yes_details]] [[No |P6_03_wave2_3_no_details]] [[Yes |P6_03_wave2_3_yes_details]]

No further recommendations

Follow-Up: Did you or do you consider any alternative methods to supplement omitted scientific field-work (y/n)? [[No |P6_03_wave2_2_no_details]] [[Yes |P6_03_wave2_2_yes_details]] [[No |P6_03_wave2_3_no_details]] [[Yes |P6_03_wave2_3_yes_details]]

Advise: Depending on your concrete Research (Data Stewardship) setting, it may be possible to supplement field_work with less risky, less expensive and less effortful alternatives. Of course, this would have to be adjusted with your concrete setting, but you may find some inspirations <a href="https://doi.org/10.3390/geosciences11080316">here</a>.

Follow-Up: Did you apply and document these alternative methods, or are you planning to do so (y/n)? [[No |P6_03_wave2_3_no_details]] [[Yes |P6_03_wave2_3_yes_details]]

Warning: If you did not apply any alternative methods, without documenting why not (/why you preferred different ones), you risk generating the impression that you simply haven’t been aware of any alternative methods. The same happens, if you applied any, but decided not to document this properly (maybe because they failed to generate the desired results).

No further recommendations

*Collect / Were you and/or your team aware of collecting Research Data from natural or cultural sites that are of notable non-material importance to any community (e.g. sacred buildings) (y/n)? [[No |P6_04_wave2_1_no_details]] [[Yes |P6_04_wave2_1_yes_details]] [[No |P6_04_wave2_2_no_details]] [[Yes |P6_04_wave2_2_yes_details]] [[No |P6_04_wave2_3_no_details]] [[Yes |P6_04_wave2_3_yes_details]] [[No |P6_04_wave2_4_no_details]] [[Yes |P6_04_wave2_4_yes_details]]

No further recommendations

Follow-Up: Did you verify before, or are you verifying, whether Research Data, collected from alternative places, could be equally fitting for your research question (y/n)? [[No |P6_04_wave2_2_no_details]] [[Yes |P6_04_wave2_2_yes_details]] [[No |P6_04_wave2_3_no_details]] [[Yes |P6_04_wave2_3_yes_details]] [[No |P6_04_wave2_4_no_details]] [[Yes |P6_04_wave2_4_yes_details]]

Warning: If you did not even check this question, you are potentially at risk of overlooking less risky options for Research Data collection.

Follow-Up: Did you or are you planning to reach out to relevant communities, in order to inform them about your Research and potentially seek for collaboration and/or permission (y/n)? [[No |P6_04_wave2_3_no_details]] [[Yes |P6_04_wave2_3_yes_details]] [[No |P6_04_wave2_4_no_details]] [[Yes |P6_04_wave2_4_yes_details]]

Warning: Then you are displaying a great deal of disrespect for the culture in question, which risks to undermine any (future) potential collaborations and which already risks potential repercussions.

Follow-Up: Did you or are you planning to apply all adequate measures to minimize your impact on the relevant natural or cultural sites (y/n)? [[No |P6_04_wave2_4_no_details]] [[Yes |P6_04_wave2_4_yes_details]]

Warning: This means you most probably act potentially dangerously derelict. Please reconsider this behaviour, if you have any interest in avoiding harm.

Advise: It makes sense to monitor the situation and seek for qualified second opinions, so you can potentially apply even further measures, which you did not think about, initially.

*Analyze / Did your scientific field-work actively interfere with ongoing cultural and/or political processes (y/n)? [[No |P6_05_wave2_1_no_details]] [[Yes |P6_05_wave2_1_yes_details]] [[No |P6_05_wave2_2_no_details]] [[Yes |P6_05_wave2_2_yes_details]] [[No |P6_05_wave2_3_no_details]] [[Yes |P6_05_wave2_3_yes_details]] [[No |P6_05_wave2_4_no_details]] [[Yes |P6_05_wave2_4_yes_details]]

No further recommendations

Warning: If you can answer this question negatively, you are lacking reasons that would legitimize your actions. You should reconsider your approach.

Follow-Up: Did you verify before, or are you verifying, whether Research Data, equally fitting for your purpose, could be gathered without interfering in such processes (y/n)? [[No |P6_05_wave2_3_no_details]] [[Yes |P6_05_wave2_3_yes_details]] [[No |P6_05_wave2_4_no_details]] [[Yes |P6_05_wave2_4_yes_details]]

Warning: Checking this question could turn out to provide less risky and potentially less invasive Research opportunities, which could provide equally useful data.

Follow-Up: Did you or are you planning to apply any measures to minimize your impact on the namely processes and their outcome (y/n)? [[No |P6_05_wave2_4_no_details]] [[Yes |P6_05_wave2_4_yes_details]]

Warning: Such measures could for example include a limitation of research activity during the named processes and strategic management of the level of invasiveness your presence as researcher(s) unfolds.

Advise: Even so, it might be useful to not decide the adequate measures just by yourself, but to plan them beforehand, in connection with people involved in the namely social processes.

*Plan / Did your scientific field-work happen in <a href="https://doi.org/10.1177/08933189211058706">Difficult, Dangerous and/or Vulnerable (DDV)</a> contexts (y/n)? [[No |P6_06_wave2_1_no_details]] [[Yes |P6_06_wave2_1_yes_details]] [[No |P6_06_wave2_2_no_details]] [[Yes |P6_06_wave2_2_yes_details]] [[No |P6_06_wave2_3_no_details]] [[Yes |P6_06_wave2_3_yes_details]]

No further recommendations

Follow-Up: Did or does your field work put yourself and/or others in life-threatening situations (y/n)? [[No |P6_06_wave2_2_no_details]] [[Yes |P6_06_wave2_2_yes_details]] [[No |P6_06_wave2_3_no_details]] [[Yes |P6_06_wave2_3_yes_details]]

No further recommendations

Follow-Up: Were or are all involved individuals properly and adequately informed about expectable risks, beforehand (y/n)? [[No |P6_06_wave2_3_no_details]] [[Yes |P6_06_wave2_3_yes_details]]

Warning: Although you might believe it impossible to sufficiently prepare all involved individuals for all expectable risks and dangers of field-work, the safest time to do so is before the field-work has started, so do not underestimate this task. Depending on your specific Research interests, you can find guiding examples on how to prepare fieldwork and respective safety-plans <a href="http://www.jstor.com/stable/resrep02120.16">here</a> and <a href="https://doi.org/10.1016/B978-0-444-63402-3.00004-2">here</a>. It is important to share any such plans, with all of your colleagues and collaborators, in order to reduce the risk of chaos in case of an emergency.

No further recommendations

No further recommendations

Follow-Up: Are, or were, you or your team directly targetted by whistle blowers (y/n)? [[No |P7_01_wave2_2_no_details]] [[Yes |P7_01_wave2_2_yes_details]] [[No |P7_01_wave2_3_no_details]] [[Yes |P7_01_wave2_3_yes_details]]

Follow-Up: Are you, or were, you and/or members of your team active as scientific whistle blowers (y/n)? [[No |P7_01_wave2_3_no_details]] [[Yes |P7_01_wave2_3_yes_details]]

Advise: Then it might be in your best interest to take this seriously. If there is at least something true to what the whistle has been blown about, it is most likely in your hand to truly change the criticized circumstances. Or else, you could point out why it is not. Try not to automatically understand an act of whistle blowing as an aggressive measure to disrupt your work – it may as well help to improve circumstances you haven’t been aware about, yet.

Advise: If the whistle blowing disrupted your work, even without you being involved personally, it might turn out fruitful to be open for reasons and evidence that lead to the process of whistle blowing. This does not mean you have to support whistle blowers, or a pick a side in an ongoing public controversy, but you can offer a fair chance to listen to people’s motivations, who are most likely risking their own careers. Further reading on the dilemma you might feel confronted with can be found <a href="https://doi.org/10.1080/08989621.2017.1327814">here</a>.

Advise: Since blowing the whistle in research is not a fundamentally new phenomenon, researchers already had the time to categorize whistleblowers, depending on their <a href="https://doi.org/10.1038/503454a">behaviour</a>. Perhaps you find yourself in one of these phenotypes which could provide you with insights about what to expect. An important information to take from here: While anonymity might protect yourself from repercussions for blowing the whistle (at least partially), it also makes you vulnerable to being hijacked by others who claim to be you.

*Analyze / Were you able to reduce the mentioned controversy by scientific means (y/n)? )? [[No |P7_02_wave2_1_no_details]] [[Yes |P7_02_wave2_1_yes_details]] [[No |P7_02_wave2_2_no_details]] [[Yes |P7_02_wave2_2_yes_details]]

Follow-Up: Did you still apply the respective technologies and/or methodologies (y/n)? [[No |P7_02_wave2_2_no_details]] [[Yes |P7_02_wave2_2_yes_details]]

No further recommendations

Advise: If you considered the application of technologies and/or methodologies, you knew were risky, the only possible way for progressing your research, then you should at least have some plan for limiting/minimizing the potentially negative outcome.

Plan / Were you aware of any ongoing scientific or broader public controversies regarding technologies or methodologies used in the context of your Research Project (y/n)? [[Yes |P7_01_question]] [[Yes |P7_02_question]]

*Share / Did you apply all technically available methods to make your Research (Data Stewardship) Results accessible to People of Disability (y/n)? [[No |P8_01_wave2_1_no_details]] [[Yes |P8_01_wave2_1_yes_details]] [[No |P8_01_wave2_2_no_details]] [[Yes |P8_01_wave2_2_yes_details]]

Advise: If you have difficulties understanding, what „all technical methods“ could refer to, especially outside digital contexts, you could start further reading <a href="https://www.un.org/sites/un2.un.org/files/un_disability-inclusive_communication_guidelines.pdf">here</a>.

Follow-Up: Did you further apply the recommended technical measures directed at known types of impairing conditions, which do not qualify as “disabilities” (such as dyslexia) (y/n)? [[No |P8_01_wave2_2_no_details]] [[Yes |P8_01_wave2_2_yes_details]]

Advise: While, in some cases, the actual use of such measures seems to be scientifically <a href="https://doi.org/10.1007/s11881-017-0154-6">contested</a>, it could still help to provide them on an optional basis.

No further recommendations

*QA / Did you critically evaluate the degree of implementation of the named standard in the context of your work (y/n)? [[No |P8_02_wave2_1_no_details]] [[Yes |P8_02_wave2_1_yes_details]] [[No |P8_02_wave2_2_no_details]] [[Yes |P8_02_wave2_2_yes_details]]

Advise: In case you need additional tools before feeling able to do so, you may want to start further research <a href="https://www.w3.org/TR/WCAG-EM/">here</a>.

Follow-Up: Are you still ready to address any potential future issues regarding this type of accessibility of your research data and research results, which you could not yet know about (y/n)? [[No |P8_02_wave2_2_no_details]] [[Yes |P8_02_wave2_2_yes_details]]

Warning: Perhaps ask yourself, who should react to new insights and approaches in this regard, if not you, as a Research Data Steward in charge.

No further recommendations

Plan / Did you plan the accessibility of your Research Data and Research Results in accordance with <a href="https://www.w3.org/TR/wcag-3.0/">WCAG</a> guidelines (y/n)? [[Yes |P8_01_question]] [[Yes |P8_02_question]]

*Plan / Were you aware of any particular history between your predecessor(s) and Research collaborators that might influence your future interactions with your potential Research collaborators (y/n)? [[No |P9_01_wave2_1_no_details]] [[Yes |P9_01_wave2_1_yes_details]] [[No |P9_01_wave2_2_no_details]] [[Yes |P9_01_wave2_2_yes_details]]

Advise: If you are working, or planning to work, with a specific group of people who were treated unethical by your predecessor(s) in the name of science, this might have consequences for you personally, even if the event dates back a considerable amount of time and you have nothing to do with them. If you are representing this exact “science” in the eyes of members of the respective group, you are perhaps met with distrust or worse. So this could be an instance, where understanding past interactions could help to plan future ones and prepare you.

Follow-Up: Did or does the knowledge of this history influence your behaviour towards potential future Research collaborators (y/n)? [[No |P9_01_wave2_2_no_details]] [[Yes |P9_01_wave2_2_yes_details]]

No further recommendations

Advise: It is good to be aware of such things, however, you do not need to – and probably shouldn’t – feel guilty for events that happened completely out of your influence. So don’t overdo it, when you feel a responsibility to make amends.

*Plan / Were you aware of any prior ethical malpractices connected to the acquisition of Research Data and/or sources you inherited (y/n)? [[No |P9_02_wave2_1_no_details]] [[Yes |P9_02_wave2_1_yes_details]] [[No |P9_02_wave2_2_no_details]] [[Yes |P9_02_wave2_2_yes_details]] [[No |P9_02_wave2_3_no_details]] [[Yes |P9_02_wave2_3_yes_details]]

Advise: Finding out about such details can be difficult, uncomfortable and potentially even a threat to your Research Data Stewardship in its current state (for example, if physical objects relevant to your Research were to be returned to their rightful owners). However, not even investigating questions of provenance and righteous ownership, would result in an intellectual dishonesty that threatens to corrupt your work as a whole, if uncomfortable information about these matters, were simply not incorporated into the respective metadata. In this context, it seems advisable to ask the philosophical question, whether Research Data Stewardship, founded on suppressed information, could under any circumstances, contribute more to free science, than Research Data Stewardship that ceases to exist, out of respect for facts and legal principles.

Follow-Up: Were or are you aware of any past and/or ongoing reconciliation procedures, following the acquisition of relevant Research Data and/or sources (y/n)? [[No |P9_02_wave2_2_no_details]] [[Yes |P9_02_wave2_2_yes_details]] [[No |P9_02_wave2_3_no_details]] [[Yes |P9_02_wave2_3_yes_details]]

Advise: Perhaps it could be only your unique position, that would potentially allow the implementation of such procedures. You might want to clarify this question in accordance with the rest of your stakeholders. (Re-)Building trust could be beneficial for your Research (Data Stewardship) and potential future cooperations.

Follow-Up: Do you consider the reconciliation procedures complete, now (y/n)? [[No |P9_02_wave2_3_no_details]] [[Yes |P9_02_wave2_3_yes_details]]

Advise: It surely is a philosophical question, whether reconciliation can ever be completed – and when. The actual question behind this one, aims at your personal feelings and more specifically your urge to reconcile. Perhaps you can continue, until there is nothing “more” for you to do, except acting responsibly and respectfully as a Research Data Steward.

No further recommendations

Plan / Did you inherit Research Data and Research Data Stewardship duties by any predecessors (y/n)? [[Yes |P9_01_question]] [[Yes |P9_02_question]]

*QA / Did you verify and explicitly name all known limitations to your Research Data‘s capability to allow scientific predictions (y/n)? [[No |P10_01_wave2_1_no_details]] [[Yes |P10_01_wave2_1_yes_details]]

Warning: If you feel obliged to make any predictions, based on your Research (Data Stewardship), be sure to be accurate. This obviously includes acknowledging any incapabilities to make accurate predictions. If your predictions fail, this might negatively impact public trust in you and/or your scientific domain. If you need an <a href="https://doi.org/10.1504/IJGW.2021.112896">example</a>.

No further recommendations

*Analyze / Was your Research (Data Stewardship) Project designed to predict human behavior (y/n)? [[No |P10_02_wave2_1_no_details]] [[Yes |P10_02_wave2_1_yes_details]] [[No |P10_02_wave2_2_no_details]] [[Yes |P10_02_wave2_2_yes_details]]

No further recommendations

Follow-Up: Were or are you aware of any application areas outside science, where your Research Project‘s results are being used (y/n)? [[No |P10_02_wave2_2_no_details]] [[Yes |P10_02_wave2_2_yes_details]]

No further recommendations

Advise: If you see this happening, and wish to do something about it, a possible option would be publishing any “op-eds” (opinionated editorial essays) in which you could introduce the concrete problems with that applications to a larger audience. If you never heard about this kind of publication, here is a good starting point to familiarize yourself with the <a href="https://www.doi.org/10.1371/journal.pcbi.1008187">idea</a>.

*Share / Did you specify a concrete time or date for your prediction (y/n)? [[No |P10_03_wave2_1_no_details]] [[Yes |P10_03_wave2_1_yes_details]] [[No |P10_03_wave2_2_no_details]] [[Yes |P10_03_wave2_2_yes_details]]

No further recommendations

Follow-Up: Were you or will you be able to verify whether what you predicted occurred (y/n)? [[No |P10_03_wave2_2_no_details]] [[Yes |P10_03_wave2_2_yes_details]]

Warning: It could pose a problem to your credibility, if by the time of your prediction, it is already clear that you do not expect to witness the date of your prediction. Since you would not have to answer to the consequences of a wrong prediction then, you could manipulate it completely to your liking. Does your research question require a concrete prediction? If yes, why?

No further recommendations

Plan / Was your Research Data (Stewardship) Project meant to predict, at least to a certain degree, future risks, potentials and/or events (y/n)? [[Yes |P10_01_question]] [[Yes |P10_02_question]] [[Yes |P10_03_question]]

*Collect / Did you collect Research Data with the help of animals (y/n)? [[No |P11_01_wave2_1_no_details]] [[Yes |P11_01_wave2_1_yes_details]] [[No |P11_01_wave2_2_no_details]] [[Yes |P11_01_wave2_2_yes_details]]

No further recommendations

Follow-Up: Can or could you rule out that your desired Research Data could be collected in a ethical fashion, without involving animals (y/n)? [[No |P11_01_wave2_2_no_details]] [[Yes |P11_01_wave2_2_yes_details]]

Warning: If you did not even check this question, you are likely not on the state-of-the art regarding available research techniques. Maybe you want to double-check your methodologies <a href="https://doi.org/10.2981/wlb.00607">here</a>.

No further recommendations

*Collect / Did you apply any protocols, guidelines and/or practices to ensure a minimally invasive impact on animals during your research (y/n)? [[No |P11_02_wave2_1_no_details]] [[Yes |P11_02_wave2_1_yes_details]]

Warning: Even in case you do not care for non-human life, you should be aware that invasiveness/carelessness in the treatment of research animals can negatively impact research data. If you are interested in valid scientific outcomes, you may want to double-check, if you are risking such effects with your methods. More on the subject and on how to avoid it, if possible, can be read <a href="https://doi.org/10.2981/wlb.00607">here</a>.

Advise: Of course, always the least invasive option would to not conduct any animal experiments, whatsoever – although there are scientific disciplines where this is not (yet) possible. In any case you might want to cautiously double-check, if there really are no other promising methodologies, that may serve as an adequate “workaround”. Perhaps you can find inspirations that may also work for you, <a href="https://doi.org/10.2981/wlb.00607">here</a>.

Plan / Did your Research (Data Stewardship) involve any interactions with animals (y/n)? [[Yes |P11_01_question]] [[Yes |P11_02_question]]

*Plan / Did your backup-plan still include documenting and reporting about the failed initial research approach (y/n)? [[No |P12_01_wave2_1_no_details]] [[Yes |P12_01_wave2_1_yes_details]]

Advise: The lack of appropriate “error culture” in scientific environments is often being prominently discussed. This concept is in constant need of researchers, who openly admit to errors, they were responsible for. If you can present “a success story” about a failure at first, that may have cost you time and publication opportunities, but consequently lead to a much more substantial result later, you might be able to contribute to such an error culture. If you wish to delve further into the discussion, you could start further reading <a href="https://www.nature.com/articles/533147a#citeas">here</a>.

No further recommendations

Plan / Did you have a backup plan for your research project in case your first aproach failed (y/n)? [[Yes |P12_01_question]]

*Plan / Was the excessive time pressure of your Research project a result of technical and/or natural reasons (y/n)? [[No |P13_01_wave2_1_no_details]] [[Yes |P13_01_wave2_1_yes_details]]

Advise: If your time pressure has nothing to do with the research topic or the Research Data themselves, you might want to reconsider your (or your stakeholders’) expectations. Maybe research quality cannot afford to give in to a pre-defined schedule. If the schedule you now have is unrealistic for your purpose, you might have to convince funding agencies and/or colleagues that you need more time to do the work properly. If the alternative is, that stakeholders already paid for results that, at the current time will be unfinished or unvalidated, it might be more costly to them to accept the status quo, than it would be to finance another research period. Also: It might be wise not to automatically assume there would be no way to extend research funding, if this option is not being publicly mentioned by your stakeholder(s).

No further recommendations

Plan / Was your Research Project affected by excessive time pressure (y/n)? [[Yes |P13_01_question]]

*Plan / Did your interests as a Researcher/Research Data Steward collide with any of your interests in your other profession(s) (y/n)? [[No |P14_01_wave2_1_no_details]] [[Yes |P14_01_wave2_1_yes_details]] [[No |P14_01_wave2_2_no_details]] [[Yes |P14_01_wave2_2_yes_details]]

Warning: Experiencing conflicts of interests might be more subtle, than you perhaps expect. Verify also your understanding of synergies and dual-professions, so you will not end up like the examples described <a href="https://doi.org/10.1007/978-3-031-24060-7_2>here</a>.

Follow-Up: Did you or are you planning to apply any measures to indicate and dissolve such conflicts of interest (y/n)? [[No |P14_01_wave2_2_no_details]] [[Yes |P14_01_wave2_2_yes_details]]

Warning: Although conflicts of interest in science do not necessarily qualify as criminal offences, there are constellations possible, which can look quite similar to corruption - a few <a href="https://doi.org/10.5840/jpsl2007722">examples</a>. Even if the circumstances are far less extreme, you still risk to lose impartiality -- and therefore your ability to conduct proper science -- if you leave conflicts of interest unaddressed.

Advise: Many institutional guidelines primarily focus on financial Conflicts of Interest; be sure that you did not only focus on these aspects but also considered non-financial Conflicts of Interest. If you want to broaden your understanding of this concept, you could do so, starting <a href="https://www.doi.org/10.1177/17470161221148387">here</a>

Plan / Did you have an additional profession, apart from being a researcher and/or Research Data Steward, at the time of your Research Project (y/n)? [[Yes |P14_01_question]]

*QA / Did you alter any of your initial Research‘s hypotheses after you had generated results (y/n)? [[No |P15_01_wave2_1_no_details]] [[Yes |P15_01_wave2_1_yes_details]] [[No |P15_01_wave2_2_no_details]] [[Yes |P15_01_wave2_2_yes_details]]

Advise: There is no general problem with altering hypotheses later on, over the course of a Research project. However, you need to be transparent about this. The whole process of building and re-building hypotheses and your reasons for this need to be clearly communicated, so eventually it doesn’t look like you assumed from the beginning, what you received as a result. This practice could be misleading and would qualify as so called "HARKing". If you want to know more about it, you can start further reading <a href="https://doi.org/10.1207/s15327957pspr0203_4">here</a>.

Follow-Up: Did you or are you planning to transparently disclose this information in all relevant contexts (y/n)? [[No |P15_01_wave2_2_no_details]] [[Yes |P15_01_wave2_2_yes_details]]

Warning: Then, what you did is commonly known as ”HARK”ing and it is considered <a href="https://doi.org/10.1207/s15327957pspr0203_4">bad scientific practice</a>. You can clarify the situation, by transparently revealing more information about the individual steps in the process that lead to your hypotheses being aligned with your results.

No further recommendations

Plan / Did your Research involve any prior known Research hypotheses (y/n)? [[Yes |P15_01_question]]

*Plan / Did you understand neutrality as a necessary premise of good research (y/n)? [[No |P16_01_wave2_1_no_details]] [[Yes |P16_01_wave2_1_yes_details]]

Advise: Then you perhaps want to notice that certain guidelines on good scientific practice indeed do: https://www.dfg.de/resource/blob/174052/1a235cb138c77e353789263b8730b1df/kodex-gwp-en-data.pdfHowever, here the concept of neutrality is strictly context dependent. As a general rule, it makes sense to know about personal biases and potentially avoid tasks, where these could have negative impacts on the outcome of your work,

Advise: Most likely you are already aware, that your intention of being neutral does not necessarily translate into other people’s understanding of yourself as neutral. See as a practical example: 10.1177/1525822X0001200404 . Perhaps it could help to generally understand yourself as not neutral, but willing to approximate the ideal of neutrality as close as possible. Feedback by relevant third parties could support this process.

Plan / Would you have described yourself neutral as a researcher in your project context (y/n)? [[Yes |P16_01_question]]

*Plan / Were you able to dissolve this conflict of interest (y/n)? [[No |P17_01_wave2_1_no_details]] [[Yes |P17_01_wave2_1_yes_details]] [[No |P17_01_wave2_2_no_details]] [[Yes |P17_01_wave2_2_yes_details]]

Advise: If you still have ethical doubts concerning your Research Data Stewardship, it is recommendable to at least pause your activities until you could dissolve the situation. Perhaps it is possible to seek consultation at your institution‘s ethics counsil.

Follow-Up: Did you or are you planning to sufficiently document how and to what end you dissolved or are planning to dissolve this conflict of interest (y/n)? [[No |P17_01_wave2_2_no_details]] [[Yes |P17_01_wave2_2_yes_details]]

Warning: Not transparently documenting the dissolution of conflicts of interest communicates as if it was never solved, at all. You should provide insight in how you fixed the situation, and which of your decisions came at what cost. If you need some more input for further reading on the matter, you could start <a href="https://www.doi.org/10.1017/bpp.2016.9">here</a>.

No further recommendations

Plan / Did you feel conflicts of interest between any elements of your personal understanding of ethics and the sake of your project (y/n)? [[Yes |P17_01_question]]

*Plan / Did you have an exit-plan, in case your boundaries are being crossed (y/n)? [[No |P18_01_wave2_1_no_details]] [[Yes |P18_01_wave2_1_yes_details]]

Advise: Although it may seem anti-intuitive at first to generally consider such a question, you probably want to avoid a situation where not reacting to your boundaries being crossed (quickly enough) results in you being part of something you did not consent to. If you are, for instance, exposed to workplace harassment and decide to do nothing about it, until the project is finished, you may do your career a favour at the cost of your personal health. In return, leaving your workplace, because others make it unbearable for you, could ease your situation in a short-term, but compromise career opportunities you otherwise had. There is no justice in such a setting and seeking it may turn out to be unrealistic in practice. However, personal preparations in the form of connecting with people and organisations who are experienced in dealing with such situations, before you are acutely in need of support, could provide you with techniques to protect yourself and your work. If you are interested in further reading, you could start <a href="https://doi.org/10.1002/1873-3468.14473">here</a>.

No further recommendations

Plan / Did you have any personal boundaries, determining under which circumstances you would terminate your Research (Data Stewardship) activities (y/n)? [[Yes |P18_01_question]]

*Share / Did you consider any contributions, apart from adequate crediting, to the providers of free Open Source services you used for your project (y/n)? [[No |P19_01_wave2_1_no_details]] [[Yes |P19_01_wave2_1_yes_details]]

Advise: If you think a small contribution will not have any great positive impact on the present or future maintenance of frequently used Open Source Services, no contribution would be even worse. Depending on the scale and context of your project, you should definitely consider some <a href="https://dl.acm.org/doi/pdf/10.1145/3595879">contribution</a>.

No further recommendations

Plan / Did you use Open Source software at any stage of your Research Project (y/n)? [[Yes |P19_01_question]]

*Collect / Did you apply any security procedures to contain the risks you had been made aware of, at the beginning of your Research (y/n)? [[No |P20_01_wave2_1_no_details]] [[Yes |P20_01_wave2_1_yes_details]] [[No |P20_01_wave2_2_no_details]] [[Yes |P20_01_wave2_2_yes_details]]

Advise: Perhaps, given the detailed circumstances of your Research (Data Stewardship) no security mechanism would have averted the known risks, so you felt you had no choice but to accept them. However, it is highly advisable to constantly re-evaluate this state and to monitor the situation. You might want to ask yourself regularly, whether new methodologies or technologies might make some dilemmata obsolete by now, if applied in your context, and whether scientific benefits still sufficiently outweigh the risks, you took?

Follow-Up: Were you, within the limits of reasonable scientific certainty, able to deduce, that there were no further risks of comparable or worse gravity to be expected (y/n)? [[No |P20_01_wave2_2_no_details]] [[Yes |P20_01_wave2_2_yes_details]]

Warning: You should understand this as a clear warning sign, that you are currently incapable of estimating the risks of your own Research Data Stewardship sufficiently enough, to consider it as uncritical. It is highly recommendable to stall your project until this aspect is clarified, if you do not want to risk unforeseeable dangers.

Advise: Depending on the concrete context, you might not want to be on your own, with this responsibility, so if you can, it could be a good decision to ask qualified and trusted scientific peers to double-check your assessment.

Plan / Were you aware of any explicit, evidence-based, scientific warnings arguing against the Research Design you were planning (y/n)? [[Yes |P20_01_question]]

*Share / Did you purposefully try to avoid the stimulation of unrealistic expectations with your PR-activities (y/n)? [[No |P21_01_wave2_1_no_details]] [[Yes |P21_01_wave2_1_yes_details]] [[No |P21_01_wave2_2_no_details]] [[Yes |P21_01_wave2_2_yes_details]]

Advise: It might be an unrealistic ambition to control, which reactions and expectations are and are not stirred by your advertisement. However, you should be focused only on facts, when advertising your Research Data Stewardship – even if that threatens to be more boring. If you need some idea, what could be meant by „advertising“ for a concrete Research (Data Stewardship) project, you could start further reading <a href=" https://doi.org/10.31219/osf.io/87rg3">here</a>.

Follow-Up: Did your PR-strategies work in the interest of your Research and/or Research Topic, as planned (y/n)? [[No |P21_01_wave2_2_no_details]] [[Yes |P21_01_wave2_2_yes_details]]

Advise: It is likely, that you are unable to precisely determine an answer to this question. However, if you feel that your advertisement plan (“PR-strategy”) did not work sufficiently, you might want to expand your target audience. If you are looking to recruit Research participants, you could also set adequate financial incentives, but be aware of respective ethical risks, then. For getting an understanding of this you may find further reading <a href="https://doi.org/10.2147/MB.S70416">here</a>.

No further recommendations

Plan / Did you apply any PR-strategies, beyond publishing Research Results, to advertise for your work (y/n)? [[Yes |P21_01_question]]

*Plan / Did you reflect the possibility that you would have to hand your Research (Data Stewardship) responsibilities down to somebody else in the future (y/n)? [[No |P22_01_wave2_1_no_details]] [[Yes |P22_01_wave2_1_yes_details]] [[No |P22_01_wave2_2_no_details]] [[Yes |P22_01_wave2_2_yes_details]]

Advise: Without doubt, it can be an uncomfortable thought to have to pass on your Research (Data Stewardship) responsibilities to another person. However, if you wish to work sustainably for a result that ideally outlives yourself, there might be no way aorund this. So perhaps you should start familiarizing yourself with the idea, in order to be prepared once it becomes necessary.

Follow-Up: Do you or did you prepare everything you did as a Research Data Steward, so it could be passed onto the next generation at any moment (y/n)? [[No |P22_01_wave2_2_no_details]] [[Yes |P22_01_wave2_2_yes_details]]

Advise: You might feel totally capable of passing on your knowledge, without any specific preparations. But there is a chance, that over time, you became “blind” to routines which you developed or learned over the course of your work. It is highly advisable to actively try to reflect in granular detail on such routines, not only for reasons of knowledge transfer, but also in order to understand potential “blind spots” you may currently have. See as a reference for further <a href="https://journals.sagepub.com/doi/full/10.1177/26317877221075640>reading</a>.

No further recommendations

Plan / Did you understand your Research to be a life-long responsibility (y/n)? [[Yes |P22_01_question]]

*Collect / Did you plan to build <a href="https://www.collinsdictionary.com/dictionary/english/rapport">rapport</a> with Research Participants before acquiring Research Data (y/n)? [[No |C1_01_wave2_1_no_details]] [[Yes |C1_01_wave2_1_yes_details]] [[No |C1_01_wave2_2_no_details]] [[Yes |C1_01_wave2_2_yes_details]]

No further recommendations

Follow-Up: Are or were you aware of any resulting liabilities or promises, you may be expected to meet as a consequence (y/n)? [[No |C1_01_wave2_2_no_details]] [[Yes |C1_01_wave2_2_yes_details]]

Advise: If you have acquired no such knowledge, even after having tried to receive it, this might mean that there are no liabilities. However, even if there are, this does not necessarily mean, you have to keep them. The important factor is how and with whom you are communicating about these matters. Consult stakeholders, predecessors, research collaborators (including other domain experts) and research affected people/communities, alike.

Advise: Should you know about any concrete liabilities/promises, but consider them unrealistic to keep, it should be a priority to inform relevant people about this in detail, as soon as possible. It might still be possible, to re-negotiate or simply adjust expectations. You would not be the first to realize, over the course of a Research (Data Stewardship) project that it might yield less, than you initially expected (and perhaps promised).

*Share / Did you plan to keep adequate communication channels with your cooperation partners intact, even after your Data collection was finished (y/n)? [[No |C1_02_wave2_1_no_details]] [[Yes |C1_02_wave2_1_yes_details]]

Warning: For reasons of research sustainability and ethics it makes absolute sense to do so.If your collaboration partners are also sources, it might be relevant to be able to contact them, in order to verify your data. Also, in order to share outcomes of Research (Data Stewardship) or inform about future interests or changing conditions, a working communication channel is vital – even if you are not personally involved (any more). If you want to see examples on what can go wrong without such precautions, you can start <a href="https://doi.org/10.1186/s12910-020-00542-x">here</a>.

Advise: While this can absolutely make sense in the context of the research you do (or just did), you should be cautious to not overdo it. Cooperation in a specific matter is no commitment to any future interactions. Do not behave like an unrequested advertising newsletter.

*Collect / Did you acquire Research Data in cultural environments differing from the one you were used to, at the time (y/n)? [[No |C1_03_wave2_1_no_details]] [[Yes |C1_03_wave2_1_yes_details]] [[No |C1_03_wave2_2_no_details]] [[Yes |C1_03_wave2_2_yes_details]]

No further recommendations

Follow-Up: Are or were you familiar with social protocols and applying norms in these particular environments, that are or were relevant to your research here (y/n)? [[No |C1_03_wave2_2_no_details]] [[Yes |C1_03_wave2_2_yes_details]]

Warning: It is highly advisable to try and learn more about these questions, as early as possible. Maybe, consult qualified contact persons, before you cause cultural affronts, which – in the worst case – may not only be damaging to your Research project but potentially to your whole discipline. See as a reference: https://www.samhsa.gov/sites/default/files/nace-steps-conducting-research-evaluation-native-communities.pdf But of course, this is important not only in the context of indigenous societies.

No further recommendations

*Share / Did you adequately inform all relevant parties about the purpose and scope of your Research Project before it started (y/n)? [[No |C1_04_wave2_1_no_details]] [[Yes |C1_04_wave2_1_yes_details]] [[No |C1_04_wave2_2_no_details]] [[Yes |C1_04_wave2_2_yes_details]]

Warning: You definitely should do that, if you want to contribute to your Research (Data Stewardship)‘s reproducibility and if you are considering your work „collaboration“. Collaboration partners being aware of what they contribute to, are a necessary premise for collaboration now and in the future. If you need an example of what can happen, if collaboration fails and how this could affect research quality, see <a href="https://www.doi.org/10.1056/NEJMp1005203">this reference</a>.

Follow-Up: Did or do you further specify, to all relevant parties, the intended usage of your gathered Research Data (y/n)? [[No |C1_04_wave2_2_no_details]] [[Yes |C1_04_wave2_2_yes_details]]

Warning: Ideally, you could have combined this with your information about the scope and purpose of your Research Data project. Informing Research collaborators about what they actually contributed to, is significant for them, as a measure to track what you concretely used their contributions for. Only this way, “informed consent” can be guaranteed. If you need an example, for where and why this is relevant see <a href="https://www.doi.org/10.1056/NEJMp1005203">this reference</a>.

Advise: If you did that once, you may want to provide updates, in case the intended Research Data usage changes over the course of your project (perhaps by discovering new opportunities). Providing information once and then forgetting to share news about recent developments might make you look untrustworthy.

*Share / Did you attempt to use <a href="https://www.collinsdictionary.com/dictionary/english/inclusive-language">inclusive language</a> with all your project‘s collaborators (y/n)? [[No |C1_05_wave2_1_no_details]] [[Yes |C1_05_wave2_1_yes_details]]

Advise: If you fail to see why you should and what this could possibly have to do with Research (data), you might want to look at a practical example of easily misunderstood language and its social effects <a href="https://doi.org/10.1016/j.cognition.2022.105070">here</a>. Even <a href="https://www.apa.org/about/apa/equity-diversity-inclusion/language-guidelines.pdf">further reading</a>.

No further recommendations

*Collect / Did you collect any data via proxies speaking in the name(s) of other people (y/n)? [[No |C1_06_wave2_1_no_details]] [[Yes |C1_06_wave2_1_yes_details]] [[No |C1_06_wave2_2_no_details]] [[Yes |C1_06_wave2_2_yes_details]]

No further recommendations

Follow-Up: Were or are you aware of any biases and/or potential misrepresentations, resulting from this circumstance (y/n)? [[No |C1_06_wave2_2_no_details]] [[Yes |C1_06_wave2_2_yes_details]]

Warning: Since you did not have direct contact to the original sources you were interested in, your data are highly vulnerable to misrepresentations, caused by proxies. If you can avoid this, by choosing alternative methods of data collection, doing so might be advisable. However, if you wish to keep working with the status quo, you may be well advised to get a further understanding of proxy induced biases. Further reading on the subject can be found <a href="https://www.doi.org/10.1161/CIRCOUTCOMES.121.007960>here</a>.

Advise: Then there is a good chance, you already addressed any issues connected to proxy-included biases and you stick to this approach because you don’t see any practical alternative. However, if you still look for further reading on the matter, you may start <a href="https://www.doi.org/10.1161/CIRCOUTCOMES.121.007960">here</a>.

*Collect / Did you or your team collect Research Data by conducting interviews with <a href="https://www.collinsdictionary.com/dictionary/english/expert">experts</a> (y/n)? [[No |C1_07_wave2_1_no_details]] [[Yes |C1_07_wave2_1_yes_details]] [[No |C1_07_wave2_2_no_details]] [[Yes |C1_07_wave2_2_yes_details]] [[No |C1_07_wave2_3_no_details]] [[Yes |C1_07_wave2_3_yes_details]]

No further recommendations

Follow-Up: Did you or do you regard further indicators to determine expertise, apart from someone’s academic <a href="https://dictionary.cambridge.org/us/dictionary/english/prestige">prestige</a> (y/n)?

Advise: If you are collaborating with artists, politicians, craftspeople, sportspeople, witnesses, spiritual leaders and/or traditional knowledge bearers etc., it might not be helpful to your cause, to limit the concept of “expertise” on academic experience. If you need to see an example on how to benefit as a scientific discipline from expertise that was not generated in academia, see this <a href="https://doi.org/10.1007/s11273-022-09866-4">example</a>.

Follow-Up: Did you or do you have the option to independently (de-)validate the contents of expert interviews you gathered (y/n)? [[No |C1_07_wave2_3_no_details]] [[Yes |C1_07_wave2_3_yes_details]]

Warning: Be careful not to treat expert interviews’ content as facts, if you do not have the possibility to verify them. What you can and should however treat as a fact, is the interview as such. Try to avoid categorical mistakes here.

No further recommendations

*Share / Did you to re-phrase or omit any original statements from oral or written sources because you considered them problematic (y/n)? [[No |C1_08_wave2_1_no_details]] [[Yes |C1_08_wave2_1_yes_details]] [[No |C1_08_wave2_2_no_details]] [[Yes |C1_08_wave2_2_yes_details]]

No further recommendations

Follow-Up: Did you or do you nonetheless document the original quote(s) and your applied change(s) (y/n)? [[No |C1_08_wave2_2_no_details]] [[Yes |C1_08_wave2_2_yes_details]]

Warning: You are risking plagiarism, if you do not adequately document and describe the changes you made. Omissions may further lead to misquotations, if not adequately indicated. Potentially helpful <a href="https://www.jstor.org/stable/25835395">further reading</a>.

No further recommendations

*Collect / Did your collecting of Research Data require active experiments on living human beings (y/n)? [[No |C1_09_wave2_1_no_details]] [[Yes |C1_09_wave2_1_yes_details]] [[No |C1_09_wave2_2_no_details]] [[Yes |C1_09_wave2_2_yes_details]] [[No |C1_09_wave2_3_no_details]] [[Yes |C1_09_wave2_3_yes_details]]

No further recommendations

Follow-Up: Did you receive or are you expecting to receive informed consent from each participant (y/n)? [[No |C1_09_wave2_2_no_details]] [[Yes |C1_09_wave2_2_yes_details]] [[No |C1_09_wave2_3_no_details]] [[Yes |C1_09_wave2_3_yes_details]]

Warning: Do not do anything without informed consent! It is true, that the concept had been subjected to <a =”href=https://www.jstor.org/stable/29721639”>criticism</a> in the past, but this criticism actually focussed more on the way of gathering informed consent, than on the idea as such. If you are not working in a medical discipline and feel not obliged to the <a href="https://www.wma.net/policies-post/wma-declaration-of-helsinki-ethical-principles-for-medical-research-involving-human-subjects/">Helsinki Declaration</a> or comparable regulating documents, be aware that many publishers also demand informed consent from <a href="https://authorservices.taylorandfrancis.com/editorial-policies/research-ethics-guidelines-for-arts-humanities-and-social-sciences-journals/">other disciplines</a>.

Follow-Up: Were you or are you ready to cancel experiments altogether, in favour of participants‘ health or security, even if no consent was withdrawn (y/n)? [[No |C1_09_wave2_3_no_details]] [[Yes |C1_09_wave2_3_yes_details]]

Warning: Perhaps a person, whose health state or security situation deteriorated far enough, is no longer able to withdraw consent. Proceeding with your research, as if nothing happened, might not be worth the sacrifice. Even if you do not have to fear legal repercussions, your Research becomes hardly repeatable if it has dire consequences to participants.

No further recommendations

*Analyze / Did you plan to work with the same Research Participants over a larger period of time (> single occasion) (y/n)? [[No |C1_10_wave2_1_no_details]] [[Yes |C1_10_wave2_1_yes_details]] [[No |C1_10_wave2_2_no_details]] [[Yes |C1_10_wave2_2_yes_details]] [[No |C1_10_wave2_3_no_details]] [[Yes |C1_10_wave2_3_yes_details]] [[No |C1_10_wave2_4_no_details]] [[Yes |C1_10_wave2_4_yes_details]]

No further recommendations

Follow-Up: Did you notice or are you noticing any significant changes in your collaboration partners‘ behaviour, over time (y/n)? [[No |C1_10_wave2_2_no_details]] [[Yes |C1_10_wave2_2_yes_details]] [[No |C1_10_wave2_3_no_details]] [[Yes |C1_10_wave2_3_yes_details]] [[No |C1_10_wave2_4_no_details]] [[Yes |C1_10_wave2_4_yes_details]]

No further recommendations

Follow-Up: Did you or do you actively investigate reasons for these changes (y/n)? [[No |C1_10_wave2_3_no_details]] [[Yes |C1_10_wave2_3_yes_details]] [[No |C1_10_wave2_4_no_details]] [[Yes |C1_10_wave2_4_yes_details]]

Warning: Should you have refrained from that, due to a lack of expertise on your behalf, you should seek professional support. If you cannot exclude potential risks to collaboration partners, you might want to understand the situation before it gets out of control.

Follow-Up: Did you learn anything concrete about (probable) reasons for the noticed change(s) or do you have first theories (y/n)? [[No |C1_10_wave2_4_no_details]] [[Yes |C1_10_wave2_4_yes_details]]

Advise: Not understanding the effects of your work on collaboration partners, risks to blur your research results and might even be harmful to individuals, without you knowing Perhaps it could be wise to cancel the Research collaboration at this point..

Advise: If you know what caused the changes, if they are harmful to participants or your results and if there is a connection to your activity, you probably should react by halting the research at this point and evaluate what happened.

*Collect / Did you treat different Research Collaborators differently over the course of your Research Data collecting (y/n)? [[No |C1_11_wave2_1_no_details]] [[Yes |C1_11_wave2_1_yes_details]] [[No |C1_11_wave2_2_no_details]] [[Yes |C1_11_wave2_2_yes_details]] [[No |C1_11_wave2_3_no_details]] [[Yes |C1_11_wave2_3_yes_details]]

Advise: In general, different treatment of different Research collaborators during Research Data collection could make sense, depending on individual prerequisites and aims. The result would not necessarily be a harmful inequity, but the risk very-well exists. Both outcomes could unfold negative personal consequences on the affected people, therefore you should make sure if and how your treatment of Research collaborators could be adapted to real circumstances, and whether it could – to a degree – equalize unequal starting conditions. If you want to familiarize with the matter and read more about it, this is a good place to <a href="https://www.doi.org/10.1007/s11019-014-9569-6">start</a>.

Follow-Up: Did you or do you have any particular, evidence-based reason to do so (y/n)? [[No |C1_11_wave2_2_no_details]] [[Yes |C1_11_wave2_2_yes_details]] [[No |C1_11_wave2_3_no_details]] [[Yes |C1_11_wave2_3_yes_details]]

Warning: So, then your Research (Data Stewardship) Project is at high risk of applying “double-standards” which most probably violate the concept of “equal-treatment”, anchored in many contemporary justice systems. It is safe to assess such circumstances as immoral. See as a <a href="https://www.doi.org/10.1007/s11019-014-9569-6">reference</a>.

Follow-Up: Did you or are you planning to appropriately document why each Research Collaborator was treated how (y/n)? | [[No |C1_11_wave2_3_no_details]] [[Yes |C1_11_wave2_3_yes_details]]

Warning: This would be a vital step in order to make any claims about equal treatment (or adequate non-equal treatment) verifiable. Without these information, the situation would be comparable to not having provided any information on how Research participants were treated.

No further recommendations

*Collect / Were you aware of any cases within the context of your Research Project, in which initially confirmed consent to collaborate in Data collection has later been withdrawn (y/n)? [[No |C1_12_wave2_1_no_details]] [[Yes |C1_12_wave2_1_yes_details]] [[No |C1_12_wave2_2_no_details]] [[Yes |C1_12_wave2_2_yes_details]]

No further recommendations

Follow-Up: Did you try or are you trying to immediately apply all possible measures to comply (y/n)? [[No |C1_12_wave2_2_no_details]] [[Yes |C1_12_wave2_2_yes_details]]

Warning: Sometimes it can be legally unclear what should happen with collected data, that was acquired before the withdrawal, in a state of, then, informed consent. Though you might not necessarily have to delete everything, keeping the wrong kind of data because of legal insecurity could become more expensive than the respective data are worth. See as a <a href="https://doi.org/10.1093/idpl/ipad008">reference</a>.

No further recommendations

*Collect / Did you become aware of any acute conditions of your Research Participants that demanded urgent intervention (y/n)? [[No |C1_13_wave2_1_no_details]] [[Yes |C1_13_wave2_1_yes_details]] [[No |C1_13_wave2_2_no_details]] [[Yes |C1_13_wave2_2_yes_details]]

Advise: This is certainly positive, however, you should verify that this impression is based on and double-checked with the assessments of multiple qualified observers and not only your personal opinion.

Follow-Up: Did you prioritize or are you prioritizing individual collaborator‘s health and well-being interests over your Research, even if that required unplanned interventions into the research process (y/n)? [[No |C1_13_wave2_2_no_details]] [[Yes |C1_13_wave2_2_yes_details]]

Warning: It is highly likely – given your local legislation – that you are committing a felony, if you refrain from intervening in your participant’s best health interest. Should you not work with “high-risk participants” whose lingering and eventually terminal illness is known already (some stimulus, as to keep this particular process as ethical as possible: http://dx.doi.org/10.1136/medethics-2016-103428 ), deteriorating health conditions for your participants should be considered an immediate cause for intervention.

No further recommendations

*QA / Were you aware and/or suspiscious of any kind of misconduct happening among and/or through your Research Participants (y/n)? [[No |C1_14_wave2_1_no_details]] [[Yes |C1_14_wave2_1_yes_details]] [[No |C1_14_wave2_2_no_details]] [[Yes |C1_14_wave2_2_yes_details]] [[No |C1_14_wave2_3_no_details]] [[Yes |C1_14_wave2_3_yes_details]]

Follow-Up: Have you tried or are you trying to become aware of potential misconduct among or through your Research Participants (y/n)? [[No |C1_14_wave2_2_no_details]] [[Yes |C1_14_wave2_2_yes_details]] [[No |C1_14_wave2_3_no_details]] [[Yes |C1_14_wave2_3_yes_details]]

Advise: Generally, this is a reason to pause or stop your Research Data Stewardship until further notice. Depending on the scale and gravity of “misconduct” you might want to consider legal steps against the particular Research collaborators. Most probably, there are no concrete plans or protocols, that would help you to react “properly” on unforeseen events of such nature. If you can, surround yourself with trusted scientific peers, who have no particular interest in keeping silent over such developments. From a scientific point of view, it might also help knowledge-generation, to report about and understand events as they happened, even if they did not generate the initially expected Research Data (Stewardship) results. Do not forget, that failure neither has to be forever, nor is a necessary consequence of incompetent Research (Data Stewardship). If you need an <a href="https://doi.org/10.1177/0308275X20917272">example</a>.

Warning: If you did not even try to receive such knowledge, it comes as no surprise, that you are unaware of any such events. Try to address all your team members and research-collaborators and provide them a chance for submitting anonymized statements. If you – for any reason – still prefer to not get directly involved in the process of finding out about potential misconduct within your own Research Data Stewardship project, you might as well share specific Research Misconduct forms from your local Research Funding Organisations, (for <a href="https://www.bkms-system.com/bkwebanon/report/clientInfo?cin=WrdG4P&c=-1&language=eng">example</a>).

Follow-Up: Were you or are you further being trained to adequately respond to such situations (y/n)? [[No |C1_14_wave2_3_no_details]] [[Yes |C1_14_wave2_3_yes_details]]

Advise: You do not necessarily have to be, in order to be able to respond adequately on such situations. However, taking the chance to attend any qualified courses and/or workshops could potentially prepare you on any such situations. See for example “Academic Integrity” courses on individual University levels.

No further recommendations

*Collect / Did you buy collaboration in the form of Research Data related services delivered by third parties (lab Analyzes/satellite imagery etc.) (y/n)? [[No |C1_15_wave2_1_no_details]] [[Yes |C1_15_wave2_1_yes_details]] [[No |C1_15_wave2_2_no_details]] [[Yes |C1_15_wave2_2_yes_details]] [[No |C1_15_wave2_3_no_details]] [[Yes |C1_15_wave2_3_yes_details]]

No further recommendations

Follow-Up: Did you and do you have the competence to verify that the services you paid for, were actually delivered (y/n)? [[No |C1_15_wave2_2_no_details]] [[Yes |C1_15_wave2_2_yes_details]] [[No |C1_15_wave2_3_no_details]] [[Yes |C1_15_wave2_3_yes_details]]

Warning: You definitely should ensure, that this is the case, if you plan to rely on paid services. If you do lack the competence to assess this question on your own, you might want to address qualified scientific peers, to help you out.

Follow-Up: Do you or did you feel at least a partial responsibility for the means and methods, by which the services you paid for, had been delivered (y/n)? [[No |C1_15_wave2_3_no_details]] [[Yes |C1_15_wave2_3_yes_details]]

Warning: It is certainly true that you can’t directly influence how external service providers work, but it lies within your power (as a consumer) to not grant future orders, if you have doubts or suspicious about their work integrity. Depending on the context, you might even be legally obliged to monitor third parties and what they do with your money (especially if it comes from public research grants), because you could be held accountable for abuse of funding that happens under your watch. See as a case <a href="https://www.doi.org/10.1126/science.adj6184">example</a>.

No further recommendations

*Collect / Did you stimulate collaboration by granting financial incentives to Research Participants (y/n)? [[No |C1_16_wave2_1_no_details]] [[Yes |C1_16_wave2_1_yes_details]] [[No |C1_16_wave2_2_no_details]] [[Yes |C1_16_wave2_2_yes_details]]

No further recommendations

Follow-Up: Did you or do you reflect the possibility of your financial incentives, also stimulating cheating behaviour in Research Participants (y/n)? [[No |C1_16_wave2_2_no_details]] [[Yes |C1_16_wave2_2_yes_details]]

Warning: Participation that is only focussed at the financial reward you promised could provide unreliable answers. In the context of online surveys, you could receive answers from non-human entities that are supposed to look like actual feedback, but are in fact result of a fraudulent attempt to simulate participation without the actual commitment that means. Since this phenomenon is not new, there are technical measures that can be taken, in order to make cheating your survey more difficult and less attractive. For more information, see <a href="https://doi.org/10.1177/20597991211050467">for example</a>.

Advise: If you are still looking for information on how to prevent fraudulent survey feedback, you may want to consult the so called <a href="https://doi.org/10.1177/20597991211050467">REAL framework</a>.

*Collect / Did you apply evidence-based protocols for minimal invasive treatment of physical objects (y/n)? [[No |C2_01_wave2_1_no_details]] [[Yes |C2_01_wave2_1_yes_details]]

Warning: Risking the material integrity of your research objects, beyond minimal invasion, risks the quality of your Research Data in terms of reproducability, more than necessary. You might want to check, whether your planned approach really is necessary to gain the desired data and, depending on your research setting, if experimental methods for gaining the desired Research Data with less impact on physical objects of interest are in fact available. As an example, <a href="https://doi.org/10.1371/journal.pone.0250776">see</a>.

No further recommendations

*Analyze / Were you aware of existing legal and moral property claims regarding the physical items you used as sources of Research Data (y/n)? [[No |C2_02_wave2_1_no_details]] [[Yes |C2_02_wave2_1_yes_details]] [[No |C2_02_wave2_2_no_details]] [[Yes |C2_02_wave2_2_yes_details]]

Follow-Up: Did you try or are you trying to verify, whether the physical items you wish to use as sources, could still be actively used for other purposes (y/n)? [[No |C2_02_wave2_2_no_details]] [[Yes |C2_02_wave2_2_yes_details]]

Advise: It is good practice to verify any of such claims, as far as it is possible. A mere claim, does not automatically require any kind of consequence. Should any claims be founded on scientifically valid evidence and should you lack equally scientifically accurate reasons to doubt or falsify the respective argumentations, you should feel obliged to adequately react to the claim. This might mean repatriations of material sources, of property that is not yours to decide over, even if it will then no longer be availabe for Research (Data Stewardship).

Advise: If you can tell with certainty, that this is not the case, you can maybe skip that process. However, ethical Research (Data Stewardship) would require to justify why it would be more important than already existing purposes, associated with one or more physical items. Perhaps the most fruitful approach in this regard, would be to do do collaborative research, based on a mutual understanding of what should be done with the object(s) for how long. In any case, you should not simply take whatever you consider relevant to your research, regardless of its active purpose.

No further recommendations

*Analyze / Were you aware of provenance and object history of all physical sources you used (y/n)? [[No |C2_03_wave2_1_no_details]] [[Yes |C2_03_wave2_1_yes_details]] [[No |C2_03_wave2_2_no_details]] [[Yes |C2_03_wave2_2_yes_details]]

Warning: Not knowing about provenance and/or existing property claims towards items you use for your Research Data Stewardship isn‘t great from a Research Data Stewardship‘s perspective. Your Meta-Data concerning object-history, is therefore worse, than it could potentially be – which is a letdown for Research Disciplines interested in these questions. Moreover, you could actively contribute to false narratives/erroneous meta-data about these questions, by just claiming these relations as „unknown“, while you actually mean „unknown to you“. Putting some more effort into Provenance Research before publishing Research Results might be worthwile. A good point to <a href="https://www.pure.ed.ac.uk/ws/files/16509719/Provenance_Management_in_Curated_Databases.pdf">start</a>.

Follow-Up: Do you or did you transparently document and indicate both, even if the details raise questions that may be uncomfortable to you and/or your (collaborating) institution(s) (y/n)? [[No |C2_03_wave2_2_no_details]] [[Yes |C2_03_wave2_2_yes_details]]

Advise: Even if you consider it unnecessary now, what you miss to document, might be impossible to retrieve later. If you struggle to understand, how concepts of authorship should apply to a non-literary context, it might be useful to familiarize yourself with so called <a href="https://localcontexts.org/labels/traditional-knowledge-labels/">Traditional Knowledge Labels</a>.

No further recommendations

*Analyze / Were you aware of any current meaning and/or purpose beyond scientific interest which is attributed to your physical source(s) (y/n)? [[No |C2_04_wave2_1_no_details]] [[Yes |C2_04_wave2_1_yes_details]] [[No |C2_04_wave2_2_no_details]] [[Yes |C2_04_wave2_2_yes_details]]

No further recommendations

Follow-Up: Did you try or are you actively trying not to interfere with further purpose(s) and/or meaning(s) caused by your handling of the physical sources (y/n)? [[No |C2_04_wave2_2_no_details]] [[Yes |C2_04_wave2_2_yes_details]]

Warning: Regardless of damaging, destroying or removing objects from their initial context, all of these aspects would result in the items, no longer being available for their designed purpose. This is a consequential decision to make and therefore it should be based on informed consent and collaboration. Else, the line to robbery is vanishingly thin. Also, be cautious with the notion of <a href="https://www.preussischer-kulturbesitz.de/en/priorities/protection-of-cultural-heritage.html">protecting</a>cultural heritage, without having been asked to do so.

No further recommendations

Collect / Did you need physical items as sources of Research Data (y/n)? [[Yes |C2_01_question]] [[Yes |C2_02_question]] [[Yes |C2_03_question]] [[Yes |C2_04_question]]

*Share / Did you plan to register patents for your Research results, which are based on aliteral sources or traditional knowledge (y/n)? [[No |C3_01_wave2_1_no_details]] [[Yes |C3_01_wave2_1_yes_details]] [[No |C3_01_wave2_2_no_details]] [[Yes |C3_01_wave2_2_yes_details]] [[No |C3_01_wave2_3_no_details]] [[Yes |C3_01_wave2_3_yes_details]]

No further recommendations

Follow-Up: Were you or are you aware of potentially damaging implications your patents would have on traditional modes of living (y/n)? [[No |C3_01_wave2_2_no_details]] [[Yes |C3_01_wave2_2_yes_details]] [[No |C3_01_wave2_3_no_details]] [[Yes |C3_01_wave2_3_yes_details]]

Advise: For example the practice of patenting the use of natural resources, such as plants, as remedies for specific ailments could in fact have an impact on traditional ways of living. If purposefully done, this practice is called <a href="https://doi.org/10.1007/978-3-319-05544-2">biopiracy</a> and punishable by many national legislations. So for instance, <a href="https://www.doi.org/10.30954/0974-1712.12.2018.9">in India</a>. You will most likely notice, if you are engaging in such a practice, because it requires using traditional knowledge. Be cautious to properly share your research outcomes, if you are planning to do the latter.

Follow-Up: Did you or are you planning to apply any measures to avoid, or at least minimize, the expected damage (y/n)? [[No |C3_01_wave2_3_no_details]] [[Yes |C3_01_wave2_3_yes_details]]

Warning: It is not just considered highly unethical in many areas, to not do so, but it also endangers the very existence of traditional knowledge as such, if you prohibit its application – which is often an integral part of its “survival” and transfer. Depending on your local legislation, patents might even be negated, once the presence of traditional knowledge is considered an essential part of it (see as <a href="https://www.wipo.int/edocs/pubdocs/en/tk/920/wipo_pub_920.pdf">a reference</a> ) So what could be adequate to “minimize damage”? As described in the source: Sharing revenues and arranging adequate exceptions from patent rules for respective communities would be a start.

No further recommendations

Collect / Did use any aliteral sources or <a href="https://uis.unesco.org/en/glossary-term/traditional-knowledge">traditional knowledge</a> for generating Research Data (y/n)? [[Yes |C3_01_question]]

*Share / Did you sufficiently de-familiarize, anonymize or redact any <a href="https://commission.europa.eu/law/law-topic/data-protection/reform/what-personal-data_en">personal </a>, and/or human <a href="https://ico.org.uk/for-organisations/direct-marketing-and-privacy-and-electronic-communications/guide-to-pecr/communications-networks-and-services/location-data/">location data</a> before publishing your results (y/n)? [[No |C4_01_wave2_1_no_details]] [[Yes |C4_01_wave2_1_yes_details]] [[No |C4_01_wave2_2_no_details]] [[Yes |C4_01_wave2_2_yes_details]]

Warning: It is very well possible, that your area‘s law requires you to do so. If you need more information on how to technically de-familiarize, anonymize and/or redact Research Data and where this would be necessary, you can start further reading <a href="https://www.doi.org/10.1109/BigDataSecurity-HPSC-IDS.2019.00063>here</a>.

Follow-Up: Did you, or do you, further attempt to adequately protect <a href="https://commission.europa.eu/law/law-topic/data-protection/reform/what-personal-data_en">personal </a>, and/or human <a href="https://ico.org.uk/for-organisations/direct-marketing-and-privacy-and-electronic-communications/guide-to-pecr/communications-networks-and-services/location-data/">location data</a> from unauthorized de-anonymization (y/n)? [[No |C4_01_wave2_2_no_details]] [[Yes |C4_01_wave2_2_yes_details]]

Warning: If you lack the technical understanding on how to adequately protect such data, you may want to familiarize yourself with the concepts of “data masking” and “data de-identification”. Further, understanding the risk of de-anonymization in a given dataset could be very helpful, in order to apply reasonable measures. Further reading on the subject could be started <a href="https://www.doi.org/10.1038/s41467-019-10933-3">here</a> .

No further recommendations

Collect / Did you collect any <a href="https://commission.europa.eu/law/law-topic/data-protection/reform/what-personal-data_en">personal</a> and/or human <a href="https://ico.org.uk/for-organisations/direct-marketing-and-privacy-and-electronic-communications/guide-to-pecr/communications-networks-and-services/location-data/">location data</a> (y/n)? [[Yes |C4_01_question]]

*QA / Were you able to adequately make scientifically valid sense of the amount of collected data (y/n)? [[No |C5_01_wave2_1_no_details]] [[Yes |C5_01_wave2_1_yes_details]] [[No |C5_01_wave2_2_no_details]] [[Yes |C5_01_wave2_2_yes_details]] [[No |C5_01_wave2_3_no_details]] [[Yes |C5_01_wave2_3_yes_details]]

Advise: Be aware, that this does not automatically require dismissal or deletion of (Research) Data. Most probably, better filtering will help you overcome your problem.

Follow-Up: Could you or are you planning to further adequately secure the protection and sustainability of these data (y/n)? [[No |C5_01_wave2_2_no_details]] [[Yes |C5_01_wave2_2_yes_details]] [[No |C5_01_wave2_3_no_details]] [[Yes |C5_01_wave2_3_yes_details]]

Warning: So, you should perhaps not deal with an amount of data, of which you can not guarantee that it is sustainably and securely handled. If you are still planning to implement measures that would ensure both, make sure you experience no data leakage or premature publication in the meantime.

Follow-Up: Were or are you still aware of existing limitations concerning the meaningfulness of such Research Data (y/n)? [[No |C5_01_wave2_3_no_details]] [[Yes |C5_01_wave2_3_yes_details]]

Warning: Then you might be at risk of falling victim to a cognitive bias that leads to the conclusion, that because your Research Data were quantitatively and qualitatively valid (which they might were), they would no longer be dependent of context. But the contrary is the case – the “best” Research Data can only be as good as their connection to a particular Research Question, meaning: The “best” Research Data are only the “best” Research Data for a specific purpose. Perhaps, a broad conceptional overview such as this one, might <a href="https://rdm.mpdl.mpg.de/before-research/data-quality/">help</a>.

No further recommendations

Collect / Were you using publicly available <a href="https://www.dhi.ac.uk/san/waysofbeing/data/data-crone-demauro-2015.pdf">Big Data</a> for any of your Research goals (y/n)? [[Yes |C5_01_question]]

*Collect / Did you use any (academic or non-academic) critiques as Research Data (y/n)? [[No |C6_01_wave2_1_no_details]] [[Yes |C6_01_wave2_1_yes_details]]

No further recommendations

Advise: It might be useful to take authors’ bias and working contexts into account, when trying to draw conclusions from the critiques about any other phenomenon than the critiques themselves. Still, be very careful in doing so.

Collect / Were you using any secondary literature as Research Data (y/n)? [[Yes |C6_01_question]]

*Analyze / Were you fully aware of <a href="https://www.merriam-webster.com/dictionary/provenance">provenance </a> and object history of each source, or any lacks thereof (y/n)? [[No |C7_01_wave2_1_no_details]] [[Yes |C7_01_wave2_1_yes_details]] [[No |C7_01_wave2_2_no_details]] [[Yes |C7_01_wave2_2_yes_details]]

Advise: While it might be impossible to clarify all lacking knowledge concerning all of your sources, you perhaps still want to make sure, that your conclusions and interpretations always display awareness about any of such lacks. If you believe, that these do not exist, you can do your part in protecting the status quo, by comprehensively documenting known object history in your metadata.

Follow-Up: Did you or are you planning to transparently share scientifically evident information about object history and <a href="https://www.merriam-webster.com/dictionary/provenance">provenance</a> of your sources, as well as any lacks thereof (y/n) [[No |C7_01_wave2_2_no_details]] [[Yes |C7_01_wave2_2_yes_details]]

Warning: Documenting lacks of knowledge can be as important as documenting known object history – if not to yourself, maybe to other disciplines. Remember, that your unique position as a Data Steward allows for the unambiguous documentation of conditions such as “being aware of not-knowing”. Deciding not to share known, but perhaps very uncomfortable provenance/object history information out of fear for unbearable legal or financial consequences, only seems plausible at first sight. If you look deeper into <a href=”https://www.theguardian.com/world/2006/mar/21/austria.disputedart>examples</a> of known object history leading to legal consequences and eventual repatriations, it seems that these events did not <a href="https://de.statista.com/statistik/daten/studie/739198/umfrage/besuche-des-belvedere-museums/">compromise</a> the involved institution in an existence-threatening way (as was initially feared).

Advise: “Transparently”, in this context, means clear, unambiguous and on any given occasion (wherever the rest of your Research Data Stewardship results are visible, as well). There are many different ways to describe and share such information, especially by using particular kinds of <a href="https://www.w3.org/TR/2013/NOTE-prov-overview-20130430/">XML-namespaces </a> and comprehensive <a href="https://www.dublincore.org/">norm-vocabularies</a> for describing metadata. Regardless, what your solution looks like in detail, make sure that it reflects the particular needs of your Research context. As a rule of thumb, it is generally perceived more sustainable to commit to ongoing standardization efforts, rather than to create new XML-vocabularies from scratch. Especially if those only fit your particular context However, depending on your sources you might need a level of precision, that cannot be met by using current standards. If that is the case, you could still try to propose a suitable addition to the existing mechanism first, before you come up with your own solution.

Collect / Did you use any products of art and/or cultural media as Research Data (y/n)? [[Yes |C7_01_question]]

*Analyze / Did you experience difficulties explaining and/or understanding your measurements (y/n)? [[No |C8_01_wave2_1_no_details]] [[Yes |C8_01_wave2_1_yes_details]] [[No |C8_01_wave2_2_no_details]] [[Yes |C8_01_wave2_2_yes_details]] [[No |C8_01_wave2_3_no_details]] [[Yes |C8_01_wave2_3_yes_details]]

No further recommendations

Follow-Up: Could you and/or can you verify the proper function and calibration of applied measuring devices (y/n)? [[No |C8_01_wave2_2_no_details]] [[Yes |C8_01_wave2_2_yes_details]] [[No |C8_01_wave2_3_no_details]] [[Yes |C8_01_wave2_3_yes_details]]

Warning: Then your “measurements” are nothing more but speculation. You should urgently verify the proper function of all of your devices – and ideally not just once.

Follow-Up: Did you publish or are you planning to publish measurements before you managed to make sense of them, yourself (y/n)? [[No |C8_01_wave2_3_no_details]] [[Yes |C8_01_wave2_3_yes_details]]

No further recommendations

Advise: Be aware that you could fuel misinterpretations by not providing any substantial information on how to make sense of the data you gathered. If you fail to draw concrete conclusions out of the measurements yourself, please try to articulate that clearly and still explain the measuring conditions as precisely as possible.

Collect / Did you and or your Research Team, collect Research Data by personally conducting exact measurements (y/n)? [[Yes |C8_01_question]]

*Collect / Were you able to explain reasons and criteria for the pre-selection of literature, you used to prepare your Research with (y/n)? [[No |C9_01_wave2_1_no_details]] [[Yes |C9_01_wave2_1_yes_details]]

Warning: Pre-selecting without explaining why and in which way, makes you vulnerable to the effects of undetected <a href="https://www.oxfordreference.com/display/10.1093/oi/authority.20110803100452883">selection-bias</a>. There may be good reasons for not taking all existing literature concerning a given subject into account – depending on the subject, doing so could be very impractical, if even possible at all. But if this is a perception you share and a decision you make, it is considered good scientific practice to communicate this as transparently as you can.

No further recommendations

Collect / Did you use only a pre-selected body of literature for preparing your Research (y/n)? [[Yes |C9_01_question]]

*Share / Did you transparently disclose which Research Data you received via a remote party, without having contact to actual sources (y/n)? [[No |C10_01_wave2_1_no_details]] [[Yes |C10_01_wave2_1_yes_details]] [[No |C10_01_wave2_2_no_details]] [[Yes |C10_01_wave2_2_yes_details]] [[No |C10_01_wave2_3_no_details]] [[Yes |C10_01_wave2_3_yes_details]]

Warning: Any failure to report about such circumstances, will, at best, induce misconceptions about your research. If published like this, you could turn out to be unable to respond to further questions regarding your sources or your data, which can make you look untrustworthy.

Follow-Up: Were you and are you still able to independently verify the validity of the Research Data you receive(d) (y/n)? [[No |C10_01_wave2_2_no_details]] [[Yes |C10_01_wave2_2_yes_details]] [[No |C10_01_wave2_3_no_details]] [[Yes |C10_01_wave2_3_yes_details]]

Follow-Up: Did you or are you planning to transparently disclose whenever you were or are unable to verify the validity of the Research Data you received (y/n)? [[No |C10_01_wave2_3_no_details]] [[Yes |C10_01_wave2_3_yes_details]]

No further recommendations

Warning: Not disclosing this information will result in a situation, in which you insinuate, you could speak for the validity of the Research Data you worked with, while you most likely cannot. This can cause situations, very close to research fraud, and could even become potentially damaging to your research discipline – if results are suggested, where they actually do not truly exist. You might want to reconsider your process of data acquisition, if the amount of Research Data you would have to admit to be unverifiable by yourself, feels inconveniently large.

No further recommendations

Collect / Did you receive any of the Research Data you steward, via a remote party, from sources you had no direct contact to (y/n)? [[Yes |C10_01_question]]

*Re-Use / Did you apply all technical measures to secure a proper deletion of the relevant data (y/n)? [[No |C11_01_wave2_1_no_details]] [[Yes |C11_01_wave2_1_yes_details]]

Advise: If you feel unfamiliar with the matter and therefore do not know, what the ideal technical steps looked like, see <a href="https://www.datasanitization.org/data-sanitization-terminology/#">this reference</a> as a starting point for further research.

No further recommendations

Collect / Did you collect any data, you were legally obliged to delete after use (y/n)? [[Yes |C11_01_question]]

*Collect / Did you use any automated information processing for generating Research Data (y/n)? [[No |A1_01_wave2_1_no_details]] [[Yes |A1_01_wave2_1_yes_details]] [[No |A1_01_wave2_2_no_details]] [[Yes |A1_01_wave2_2_yes_details]]

No further recommendations

Follow-Up: Were you and are you able to explain in detail, what the used software is doing and how it generates your Research Data (y/n)? [[No |A1_01_wave2_2_no_details]] [[Yes |A1_01_wave2_2_yes_details]]

Warning: This information might – even in case it is not legally required – be necessary to reproduce your Research results later, therefore you should definitely provide it if you can. Should you personally lack understanding about a few or even most technical details, it is recommended to still report what – to your understanding – happened during automated information processing. It might be advisable to be open about what you did not understand as well, so potential sources of errors can be more easily identified if necessary.

No further recommendations

*QA / Did you use any automated information processing for reviewing/verifying your Research Results (y/n)? [[No |A1_02_wave2_1_no_details]] [[Yes |A1_02_wave2_1_yes_details]] [[No |A1_02_wave2_2_no_details]] [[Yes |A1_02_wave2_2_yes_details]]

Advise: A combination of human and automated verification techniques promises an efficient approach for identifying avoidable, technical errors within large(r) datasets -- especially if an automated validation technique is already approved to be reliable for a given task. Automated verification tools, such as data validation software, can be used effectively, if they are adapted to a given research scenario and applied within controllable limits. Recommended best practices and experiences in trying to apply such tools can be found, for example, <a href="https://arxiv.org/pdf/2103.04095.pdf">here</a>.

Follow-Up: Were you and are you able to explain in detail, what the used software is doing and how it reviews/verifies your Research Data (y/n)? [[No |A1_02_wave2_2_no_details]] [[Yes |A1_02_wave2_2_yes_details]]

No further recommendations

Analyze / Did you rely on any degree of automated <a href="https://www.britannica.com/technology/information-processing"> information processing</a> within the context of your Research (y/n)? [[Yes |A1_01_question]] [[Yes |A1_02_question]]

*Analyze / Were you aware of any concrete dangers of contamination to material waste generated as a by-product of your Research (y/n)? [[No |A2_01_wave2_1_no_details]] [[Yes |A2_01_wave2_1_yes_details]] [[No |A2_01_wave2_2_no_details]] [[Yes |A2_01_wave2_2_yes_details]]

Advise: Not being aware of particular dangers does not automatically imply, that your waste is harmless. If you are not legally required to do so anyway, taking responsibility for appropriate waste management after your actual data collection is done, could also enrich your research documentation with information about this step. If you only generated material by-products for which the disposal process does not seem to be worth mentioning (for instance: water), still trying to spend a few words in your publication about waste disposal, could be seen as a proactive attempt, to not behave indifferent about the issue.

Follow-Up: Did you or are you applying adequate security measures to prevent uncontrolled contamination of humans and the environment with your material Research by-product(s) (y/n)? [[No |A2_01_wave2_2_no_details]] [[Yes |A2_01_wave2_2_yes_details]]

Warning: If you picked this answer, because of insecurity about the term “adequate”, you might not be totally convinced, that the measures you applied or plan to apply, will work sufficiently. If that is the case, you could, depending on your context, consult specialized <a href="https://www.ptb.de/cms/fileadmin/internet/fachabteilungen/abteilung_9/9.3_internationale_zusammenarbeit/publikationen/PTB_Info_Chemical_Waste_Management_EN.pdf">waste management guidelines</a>, for example for chemical substances, to compare best practice recommendations with your context. If this isn’t helping, perhaps because your substance is not well enough researched, yet – “adequately” can translate to, “as best as possible, given the currently available knowledge”.

No further recommendations

*Analyze / Was the material waste generated by your Research detectable for humans without any further equipment (y/n)? [[No |A2_02_wave2_1_no_details]] [[Yes |A2_02_wave2_1_yes_details]] [[No |A2_02_wave2_2_no_details]] [[Yes |A2_02_wave2_2_yes_details]]

Follow-Up: Did you or are you planning to inform all relevant other parties about the material by-products of your research, their respective dangers and how to detect them (y/n)? [[No |A2_02_wave2_2_no_details]] [[Yes |A2_02_wave2_2_yes_details]]

No further recommendations

Warning: “All relevant other parties” refers to all persons (colleagues, research collaborators, non-research affiliated persons) who will be exposed to the respective materials. All of these actors should be properly briefed about the contamination risk and the substance(s) involved. Failing to do so, can qualify as a felony, depending on the concrete context.

No further recommendations

Analyze / Did your Research generate material waste as a by-product (y/n)? [[Yes |A2_01_question]] [[Yes |A2_02_question]]

*Re-Use / Did you inform individuals, to whom the <a href="https://commission.europa.eu/law/law-topic/data-protection/reform/what-personal-data_en">personal</a> and/or human <a href="https://ico.org.uk/for-organisations/direct-marketing-and-privacy-and-electronic-communications/guide-to-pecr/communications-networks-and-services/location-data/">location data</a> pertain, about your planned Research activity (y/n)? [[No |A3_01_wave2_1_no_details]] [[Yes |A3_01_wave2_1_yes_details]] [[No |A3_01_wave2_2_no_details]] [[Yes |A3_01_wave2_2_yes_details]]

Warning: It would be a fallacy to conclude, only from the fact that such data are already being made publicly available, their respective owners would not have to agree to any further use of it. Depending on your plans, you could still be legally obliged to seek informed consent 1) by the persons the data pertain to and 2) by the copyright holders of the data, which do not have to be identical. A helpful label to look out for, if you are not familiar with the issue but wish to avoid trouble, could be the so called Open Database License (ODL) or other examples, mentioned in <a href="https://doi.org/10.1162/dint_a_00042">this research article</a>.

Follow-Up: Were or are you ready to immediately comply to withdrawals of formerly granted informed consent (y/n)? [[No |A3_01_wave2_2_no_details]] [[Yes |A3_01_wave2_2_yes_details]]

Warning: Depending on your area, legislation could force you to comply. Though this could be highly impractical and perhaps even damaging to your intended research progress, the expectable legal consequences would most likely be as well. A useful practice could therefore be to initially plan with a certain withdrawal rate, that could be further approximated mathematically in relation to your context. If it is too late for this now, or was impossible due to your research context, documenting the withdrawals in relation to the rest of your data, might be insightful in and of itself.

No further recommendations

*Share / Did you share all collected personal, medical and/or human location data with the individuals they pertain to (y/n)? [[No |A3_02_wave2_1_no_details]] [[Yes |A3_02_wave2_1_yes_details]] [[No |A3_02_wave2_2_no_details]] [[Yes |A3_02_wave2_2_yes_details]]

Warning: If the people. these data pertain to, are still currently alive or highly likely to be alive, you should urgently try to get „informed consent“. This might not only be relevant for legal reasons, but also for Research Data Stewardship (keeping Research Data validatable). If you are unfamiliar with the concept of „informed consent“, this might be a good starting point for <a href="https://www.law.cornell.edu/wex/informed_consent">further reading</a>.

Follow-Up: Did you make sure to present these data, along with scientifically valid interpretations, designed to be understandable for the relevant individuals (y/n)? [[No |A3_02_wave2_2_no_details]] [[Yes |A3_02_wave2_2_yes_details]]

Advise: Depending on your Research collaborators, you might not be in a position to simply assume their research data literacy capabilities sufficient, for understanding your Research Data without further explanations. It would be best practice to not generally assume this, but be prepared to explain your Research Data to laypeople.

No further recommendations

*Analyze / Did any of the Research Data you use, provide real-time or near real-time insights about the behaviour of individuals to whom they pertain to (y/n)? [[No |A3_03_wave2_1_no_details]] [[Yes |A3_03_wave2_1_yes_details]] [[No |A3_03_wave2_2_no_details]] [[Yes |A3_03_wave2_2_yes_details]] [[No |A3_03_wave2_3_no_details]] [[Yes |A3_03_wave2_3_yes_details]]

No further recommendations

Follow-Up: Did you apply and are you applying all possible security measures to prevent abuse of these data (y/n)? [[No |A3_03_wave2_2_no_details]] [[Yes |A3_03_wave2_2_yes_details]] [[No |A3_03_wave2_3_no_details]] [[Yes |A3_03_wave2_3_yes_details]]

Warning: Since such data can make the real subjects, they are referring to, highly vulnerable, you should protect data as well as subjects by various security mechanisms. If in doubt about what such measures should look like, you could use international standards such as <a href="https://www.iso.org/standard/75652.html">ISO/IEC 27002:2022</a> as an orientation, and/or ask specialized colleagues.

Follow-Up: Did you further reflect, or are you reflecting the possibility, that your data may become vital to save human lives, in catastrophic scenarios (y/n)? [[No |A3_03_wave2_3_no_details]] [[Yes |A3_03_wave2_3_yes_details]]

Advise: In cases of natural disasters, real-time location data, originally collected for different purposes, have already contributed to efficient search and rescue operations, as is reported in <a href="http://ccitt.northwestern.edu/documents/Integration_of_real_time_data_in_urban_search_and_rescue.pdf ">this example</a>. Perhaps you want to consider, whether your project could act similarly in case of an unexpected catastrophic scenario and whether this should be manifested in any contracts/agreements between your project and the persons you have real-time data on.

No further recommendations

*Share / Did you consider data de-familiarization and anonymization before publishing your results, even if the original data you re-used, were neither (y/n)? [[No |A3_04_wave2_1_no_details]] [[Yes |A3_04_wave2_1_yes_details]] [[No |A3_04_wave2_2_no_details]] [[Yes |A3_04_wave2_2_yes_details]]

Advise: Given the context of your research, it can be extremely advisable to do so. If your research creates a new context, in which the data you re-used did not originally appear, this could cause undesired effects on the public perception of the persons connected to the data you are using. If you are willing to exclude this possibility as best as possible, de-familiarization and anonymization could be most effective.

Follow-Up: Did you or are you planning to protect the published data from de-anonymization by also protecting metadata, where necessary (y/n)? [[No |A3_04_wave2_2_no_details]] [[Yes |A3_04_wave2_2_yes_details]]

Advise: Easily forgotten, but, given the right context, almost equally telling can be metadata (data about data), Imagine you are using census data about a relatively small village population for answering demographical questions about religious behaviour. In order to avoid to refer to abstracted single individuals – who might still be easily identified (or believed to be identified) by members of the village community – you decide to only refer to groups of people, based on broader categories such as gender and age. However, this approach can only work as intended, if you provide large enough groups. If members of a group become easily identifiable just by their group affiliation (e.g. “Females, aged 110-115”), persons with more information on the community in question can use this metadata in order to de-anonymize the person(s) whose identity you attempted to protect.

No further recommendations

*Analyze / Did you - perhaps unintended - link the data and, consequently persons they pertain to, to information that might misrepresent the individuals (y/n)? [[No |A3_05_wave2_1_no_details]] [[Yes |A3_05_wave2_1_yes_details]]

No further recommendations

Advise: Imagine a situation that frequently occurs in journalistic texts – an article about some stigmatized phenomenon, such as alcoholism, paired with completely unrelated stock footage, to make the publication look more interesting. If persons are included in the stock footage, readers could inappropriately conclude from this constellation, that the depicted persons were alcoholics. If this fictional situation reminds you of any example within your own research project, you might be well advised to adapt it.

Analyze / Did you use any already published <a href="https://commission.europa.eu/law/law-topic/data-protection/reform/what-personal-data_en">personal</a> and/or human <a href="https://ico.org.uk/for-organisations/direct-marketing-and-privacy-and-electronic-communications/guide-to-pecr/communications-networks-and-services/location-data/">location data</a> for your Research (y/n)? [[Yes |A3_01_question]] [[Yes |A3_02_question]] [[Yes |A3_03_question]] [[Yes |A3_04_question]] [[Yes |A3_05_question]]

*QA / Were you aware of the possibility of <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4359000/">inflation bias</a> both in the statistical data used for and/or generated by your project (y/n)? [[No |A4_01_wave2_1_no_details]] [[Yes |A4_01_wave2_1_yes_details]] [[No |A4_01_wave2_2_no_details]] [[Yes |A4_01_wave2_2_yes_details]]

Advise: In other dictions also called p-hacking, the type of <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4359000/">inflation bias</a> described here, refers to a tendency of exaggerating statistical data while interpreting them. Since this behaviour has a great potential to spoil the quality of Research, even if not applied as a conscious cheating technique, you may be well advised to thoroughly review and reflect your work regarding this issue. For more reading on <a href="https://doi.org/10.1371/journal.pbio.1002106">the subject</a>.

Follow-Up: Did you apply or are you applying any measures to avoid and/or mitigate the effects of <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4359000/">inflation bias</a> on statistical data, you either used and/or generated (y/n)? [[No |A4_01_wave2_2_no_details]] [[Yes |A4_01_wave2_2_yes_details]]

Warning: If the problem occurred only in data you used/quoted, you should treat these with the same scrutiny, as you would your own generated data. This could potentially include a full reproduction of the experiments that lead to the data you quoted. More generally, getting familiar with <a href="https://doi.org/10.1098/rsos.220346">strategies of identifying</a> the phenomenon could be helpful for any critical reviews.

No further recommendations

Analyze / Were any Research Data, generated or used by your project, adequate for making valid statistically representative statements (y/n)? [[Yes |A4_01_question]]

*QA / Were you aware of any misrepresentation risks following your comparison(s) (y/n)? [[No |A5_01_wave2_1_no_details]] [[Yes |A5_01_wave2_1_yes_details]] [[No |A5_01_wave2_2_no_details]] [[Yes |A5_01_wave2_2_yes_details]]

Advise: Not being aware of problematic dimensions of a particular comparison is no guarantee of a lack thereof. As is pointed out throughout the body of literature concerning scientific comparisons: it is hard work to conduct a fair comparison. To familiarize with the issue as such you may want to begin further reading <a href="https://doi.org/10.1037/0021-9010.71.2.179"> here</a> or <a href="https://handsondataviz.org/comparisons.html"> here</a>.

Follow-Up: Did you apply or are you applying any measures to verify the validity of your comparisons (y/n)? [[No |A5_01_wave2_2_no_details]] [[Yes |A5_01_wave2_2_yes_details]]

Advise: Depending on the complexity of your research context, it might already help to review your own comparison(s) multiple times over the course of your research period. Given the fundamental limits of this design, validating your comparison could mean in practice, to adjust conclusions that can be drawn from this approach.

No further recommendations

Analyze / Did your Research include any <a href="https://doi.org/10.1017/CBO9780511819391.016"> comparative</a> designs (y/n)? [[Yes |A5_01_question]]

*Share / Did you conduct any of these measures in order to avoid negative public reactions (y/n)? [[No |A6_01_wave2_1_no_details]] [[Yes |A6_01_wave2_1_yes_details]]

No further recommendations

Advise: It is not generally considered bad scientific practice to do so, especially if your surrounding work context as a researcher does not support scientific freedom. However, in order to keep your results meaningful, despite applying self-protective measures, you should document the data manipulations you conducted yourself, at a separate place, so there will be a “key” to reconstruct your work at a later time or in another environment.

*Share / Did you re-phrase or omit any original statements from oral or written sources because you considered them problematic (y/n)? [[No |A6_02_wave2_1_no_details]] [[Yes |A6_02_wave2_1_yes_details]] [[No |A6_02_wave2_2_no_details]] [[Yes |A6_02_wave2_2_yes_details]]

No further recommendations

Follow-Up: Did you adequately document or are you planning to adequately document the original quotes and your applied changes (y/n)? [[No |A6_02_wave2_2_no_details]] [[Yes |A6_02_wave2_2_yes_details]]

Warning: You are risking plagiarism, if you do not adequately document and describe the changes you made. Not indicating omissions and changes in original sources qualifies as misquotation. Also, not drawing clear lines between quotes and own ideas – a practice sometimes referred to as <a href="https://www.uni-goettingen.de/de/document/download/20a425e38a8b351a91c5d808b7ada5e7.pdf/Recommendations%20for%20Dealing%20with%20Plagiarism.pdf">pawn sacrifice</a> -- causes misquotations. Should you need more information about the practice of omissions and its risks, <a href="https://www.jstor.org/stable/25835395">this</a> might provide a good starting point for further reading. If you feel the need to distance yourself from statements of your sources, you can potentially do so without omitting the parts you wish to distance yourself from.

No further recommendations

Analyze / Did you or your team edit, cut or filter any Research Data (y/n)? [[Yes |A6_01_question]] [[Yes |A6_02_question]]

*Analyze / Did you personally translate relevant sources and Research Data (y/n)? [[No |A7_01_wave2_1_no_details]] [[Yes |A7_01_wave2_1_yes_details]] [[No |A7_01_wave2_2_no_details]] [[Yes |A7_01_wave2_2_yes_details]]

Advise: If a literate translation between two concepts in two languages is not possible, so the interpreter needs to make a decision, any interest of using the source, could impact the nature and style of the interpretation as such. For instance, if further scientific work with a source is planned, conceptual equivalence between information in both languages may be prioritized. However, if that is the case, a respective translation could – as demonstrated in <a href="https://www.doi.org/10.2174/1874434600903010025">this example</a>-- be of such complexity, that even if it is not wrong in a linguistic sense, it remains largely incomprehensible to native speakers. This problem is common for professional interpreters, which is why it could be helpful, even for competent multilinguals, to seek assistance from such experts anyway.

Follow-Up: Were or are native speakers involved in the translation process, wherever possible (y/n)? [[No |A7_01_wave2_2_no_details]] [[Yes |A7_01_wave2_2_yes_details]]

Advise: If you have the opportunity to do so, it might be worth consulting native-speakers, even if you have sophisticated translation tools or a substantial personal language expertise at hand. If you don’t have the opportunity to ask native speakers for advice, consider investing in a professional translation service, if available. This way, you will end up with a selection of possible translations and gain an opportunity to clarify translation-induced errors, before you publish anything.

No further recommendations

*Analyze / Were translation efforts necessary between different <a href="https://www.collinsdictionary.com/dictionary/english/sociolect">sociolects </a> and/or <a href="https://www.collinsdictionary.com/dictionary/english/dialect">dialects</a> of the same language (y/n)? [[No |A7_02_wave2_1_no_details]] [[Yes |A7_02_wave2_1_yes_details]] [[No |A7_02_wave2_2_no_details]] [[Yes |A7_02_wave2_2_yes_details]]

No further recommendations

Follow-Up: Were or are native speakers involved in the translation process, wherever possible (y/n)? [[No |A7_02_wave2_2_no_details]] [[Yes |A7_02_wave2_2_yes_details]]

Advise: If you have the opportunity to do so, it might be worth consulting native-speakers, even if you have sophisticated translation tools at hand – potentially, they are not optimized for your use case.

No further recommendations

*Share / Did you transparently indicate in your publication, if you worked with translations, only (y/n)? [[No |A7_03_wave2_1_no_details]] [[Yes |A7_03_wave2_1_yes_details]]

Warning: Normally, this should become evident in your index of cited literature. If not, maybe because you used <a href="https://oxfordre.com/classics/page/3993">abbreviations pointing towards famous works of literature</a> you should find a way to clarify, that you in fact refer to a specific translation of this text. Depending on your citation scheme, different ways of indicating this information are legitimate.

No further recommendations

Analyze / Did your understanding of sources and Research Data require any translation efforts (y/n)? [[Yes |A7_01_question]] [[Yes |A7_02_question]] [[Yes |A7_03_question]]

*Analyze / Did you try to clarify your suspicions by consulting further Domain Experts in the field (y/n)? [[No |A8_01_wave2_1_no_details]] [[Yes |A8_01_wave2_1_yes_details]] [[No |A8_01_wave2_2_no_details]] [[Yes |A8_01_wave2_2_yes_details]]

Advise: This may be your only solution to find independent and qualified second opinions. If you cannot find adequate persons to address with these issues, try your local Research Integrity Officers. Should those not exist in your country or institution, try another institution or country.

Follow-Up: Would you continue to use the namely sources, even if your suspicions cannot be dispersed (y/n)? [[No |A8_01_wave2_2_no_details]] [[Yes |A8_01_wave2_2_yes_details]]

Advise: As long as you did not find concrete evidence of errors or research fraud – in both cases, you could have a professional interest in not ignoring, but rather clarifying the situation – your suspicions are a weak reason for ignoring existing literature on a given topic. It may even prove to be beneficial to your work (and perhaps discipline) to actively refer to unclear aspects within the current literature.

Advise: You could however still mention and explain your doubts or suspicions within your own research publication. This also implies, that you do not use the respective source as an integral foundation of your work, but contextualise it according to your capability of validating it.

Analyze / Were you suspicious of any kind of scientific misconduct in the sources you consulted for your Research (y/n)? [[Yes |A8_01_question]]

*Analyze / Did you inform relevant authorities about such findings (y/n)? [[No |A9_01_wave2_1_no_details]] [[Yes |A9_01_wave2_1_yes_details]]

Advise: To quote UCL:<a href="https://ethics.grad.ucl.ac.uk/forms/Research-Involving-illegal-activities.pdf">”This is a complex area”</a>.Witnessing crimes without informing authorities is rated as a criminal offence in and of itself, in many legislations. However, if you observed acts (like homosexuality) which are criminalized in local law, but protected by (not necessarily locally ratified) international agreements, such as the <a href="https://www.un.org/en/about-us/universal-declaration-of-human-rights">UNDHR</a> you have a strong moral and legal reason for not sharing the namely information with local authorities. Make sure to make an individual, context-based decision, you feel morally and legally confident to defend.

Advise: To quote UCL:<a href="https://ethics.grad.ucl.ac.uk/forms/Research-Involving-illegal-activities.pdf">This is a complex area”</a>.Witnessing crimes without informing authorities is rated as a criminal offence in and of itself, in many legislations. However, if you observed acts (like homosexuality) which are criminalized in local law, but protected by (not necessarily locally ratified) international agreements, such as the <a href="https://www.un.org/en/about-us/universal-declaration-of-human-rights">UDHR</a> you have a strong moral and legal reason for not sharing the namely information with local authorities. Make sure to make an individual, context-based decision, you feel morally and legally confident to defend.

Analyze / Did you gather any concrete scientific evidence of living human individuals committing crimes, by definition of their local legislation (y/n)? [[Yes |A9_01_question]]

*Analyze / Did your further Research still profit from the domain expertise of people without academic education (y/n)? [[No |A10_01_wave2_1_no_details]] [[Yes |A10_01_wave2_1_yes_details]]

Advise: Expertise is not necessarily reflected by qualification -- and relevant data might exist, before it turns out to be relevant (for your purpose). Therefore it might make sense for you, to widen your view and at least risk a look beyond your academic surroundings, before making up your mind regarding this question. Find some examples, where researchers could make use of non-academic expertise <a href="https://doi.org/10.1002/ldr.3400050406">here</a> or <a href="https://doi.org/10.1016/j.biocon.2022.109739">here</a>.

Advise: If you wish to further cooperate with non-academic domain experts, be aware that rewarding such cooperation might not work quite as is usual in academic contexts. While it may still be adequate and obligatory to mention non-academic domain experts as co-authors or contributors to your research publication, this alone will probably not equal to the same value for this person, as such a reference would to someone within an academic career. Therefore, you might want to try to find out on an individual level, what an adequate reward could be .

Analyze / Did you work with data that was generated by people without academic education (y/n)? [[Yes |A10_01_question]]

*Analyze / Did you explicitly consider, whether your Research Data could also be relevant to other scientific disciplines (y/n)? [[No |A11_01_wave2_1_no_details]] [[Yes |A11_01_wave2_1_yes_details]] [[No |A11_01_wave2_2_no_details]] [[Yes |A11_01_wave2_2_yes_details]]

Advise: If you did not consider this question, you might be currently unaware of other scientific fields that might be interested in your Research Data. Certainly it could be true, that there are no such disciplines at the moment, but the more of your data remains interpretable and accessible in the future, the higher is the chance, that it will serve some additional scientific purpose you could not predict. So don‘t feel invited to treat data, as if you were the only one who could make use of it. To get an impression on the vast quantity of scientific (sub-)fields with individual research interests, see <a href="https://doi.org/10.1073/pnas.2021636118">this reference</a>.

Follow-Up: Did you try or are you trying to establish contact to Domain Experts from respective disciplines (y/n)? [[No |A11_01_wave2_2_no_details]] [[Yes |A11_01_wave2_2_yes_details]]

Advise: It could turn out fruitful to do so, perhaps in order to understand future potentials/directions of your current Research, or in order to find potential support in areas of your project you are not an expert in.

No further recommendations

Analyze / Did you consider your Research Data exclusively relevant to your particular Research Domain (y/n)? [[Yes |A11_01_question]]

*QA / Were you ready to implement any research- and/or project-related changes, stimulated by the reviewing process (y/n)? [[No |Q1_01_wave2_1_no_details]] [[Yes |Q1_01_wave2_1_yes_details]] [[No |Q1_01_wave2_2_no_details]] [[Yes |Q1_01_wave2_2_yes_details]]

Advise: Then you should probably be able to firmly defend your methods and results, now. If this is not the result of the reviewing process, maybe have another look into the concrete details which caused your feeling of disturbance.

Follow-Up: Were or are all changes adequately documented and the reviewers adequately credited (y/n)? [[No |Q1_01_wave2_2_no_details]] [[Yes |Q1_01_wave2_2_yes_details]]

Warning: If someone’s professional reviewing shaped what your publication looked like, this is an intellectual effort, which should at least be properly documented. It is debatable and depends on the individual context of your work, whether this accumulates up to a co-authorship, but not mentioning such a contribution at all, would most likely seem dishonest.

No further recommendations

QA / Did your Research and/or Research Data experience qualified, independent and thorough scientific reviewing before being published (y/n)? [[Yes |Q1_01_question]]

*QA / Did you apply any strategies in order to identify effects of your personal emotional connection to your Research Data, Research Topic and/or affiliated persons (y/n)? [[No |Q2_01_wave2_1_no_details]] [[Yes |Q2_01_wave2_1_yes_details]] [[No |Q2_01_wave2_2_no_details]] [[Yes |Q2_01_wave2_2_yes_details]]

Advise: Such strategies could for instance include (video) diaries that document your research behaviour in detail, evaluations from trusted and independent colleagues, or self-evaluations by using existing tests. A short overview, which might serve as a starting point for further research, can be found <a href="https://handbook.gitlab.com/handbook/company/culture/inclusion/unconscious-bias/">here</a>.

Follow-Up: Did you identify any influence of your emotional connection to your Research Data, Research Topic and/or affiliated persons, which you were or are willing to change (y/n)? [[No |Q2_01_wave2_2_no_details]] [[Yes |Q2_01_wave2_2_yes_details]]

No further recommendations

Advise: Knowing about one’s emotional bias’ does not necessarily result in a need to eliminate them. If you already concluded that it does, finding your place -- for instance by sharing responsibilities within a team in a way, that keeps you from being confronted with topics where you would probably make harmfully unbalanced decisions – can perhaps avoid the worst expected damage in the context of your current research project. However, as long as you are capable to describe your bias’ and their effects, it should become transparent to readers, why your research was designed the way it was. If you have identified bias’ only after a publication had already happened, you could write an appendix or a newer edition of your publication, that explicitly refers to this initially overlooked phenomenon. Generally speaking, personal affliction, for instance to a particular cause or group of people for whom you wish to act as an advocate, neither proves bad science as such nor automatically turns you into an unreasonable person. Also, the described phenomenon is not new and falls under this <a href=”https://doi.org/10.1177/0038038523121920”>collection of concepts </a>, which are even further elaborated on, in <a href="https://doi.org/10.1515/9781478012542">this reference</a>.

QA / Did you reflect on the possibility of biases, emerging from emotional connections between you and your Research Data, Research Topic and/or affiliated persons (y/n)? [[Yes |Q2_01_question]]

*QA / Did you critically evaluate your own language as a scientist, by asking peers and/or partners for feedback (y/n)? [[No |Q3_01_wave2_1_no_details]] [[Yes |Q3_01_wave2_1_yes_details]] [[No |Q3_01_wave2_2_no_details]] [[Yes |Q3_01_wave2_2_yes_details]] [[No |Q3_01_wave2_3_no_details]] [[Yes |Q3_01_wave2_3_yes_details]]

Advise: If you feel uncomfortable asking others for language feedback, there are numerous different ways to improve your general communication style (non-professional language included). Without having to become an expert in psycholinguistics, you could familiarize yourself with subtle aspects of everyday-language, which you might have never thought about before (such as <a href=”https://doi.org/10.1187%2Fcbe.18-01-0011>micro-aggressions</a> ) or attend a conference workshops or university classes on the topic. Since language is evolving, as is scientific understanding, it may make sense to also evolve, unless you have a substantiated reason not do so.

Follow-Up: Did you, or are you further critically evaluating other people's language and point out, if you consider it not inclusive (y/n)? [[No |Q3_01_wave2_2_no_details]] [[Yes |Q3_01_wave2_2_yes_details]] [[No |Q3_01_wave2_3_no_details]] [[Yes |Q3_01_wave2_3_yes_details]]

Follow-Up: Are you, or would you be, ready to accept decisions of peers and colleagues to not pay any attention on inclusive language, within your project context (y/n)? [[No |Q3_01_wave2_3_no_details]] [[Yes |Q3_01_wave2_3_yes_details]]

Advise: You are free to do so, but perhaps you should have an eye at the circumstances. Interrupting someone mid-speech might turn out to be less effective in conveying the positive aspects of inclusive language, than structured, non-aggressive feedback that you have been asked for. This is not to say, that there were no legitimate reasons for interrupting someone mid-speech, but if contributing to a culture of respectful communication is your goal, such a measure might negatively affect your credibility towards that goal.

Advise: Enforcing a certain language policy might be reasonable for your particular research context. But even if it is not, and you simply wish yourself and your project to be associated with inclusive language, you can have the right to demand this communication style from your employees. However, a lack of someone’s compliance does not generally have to result in a hostile or aggressive treatment of that person. Perhaps researchers, who are unwilling to apply such language themselves, might be supportive of the idea, that someone else reviews and improves texts they authored with regard to this topic. And even if you are not in a position to have the slightest direct influence on colleagues or project policies, you can still stick to the principles you consider right and try to lead by personal example.

Advise: Keep the context of your project in mind; if you are (at least partially) dealing with a research topic that requires a certain level of language sensitivity to be as precise and as unbiased as possible, you perhaps do not want to let the writing style of such colleagues become representative of your whole project. Maybe in such a case, it would be an acceptable compromise to all parties, if someone else reviewed the texts authored by a person who does not wish to apply inclusive language, with this exact issue in mind.

QA / Were you trying to use <a href="https://www.collinsdictionary.com/dictionary/english/inclusive-language">inclusive language</a> at all stages of your Research Project (y/n)? [[Yes |Q3_01_question]]

*QA / Did you verify whether critiques and/or commentaries of scientific peers regarding your ongoing Research (Data Stewardship) Project actually influenced your and/or your teams work (y/n)? [[No |Q4_01_wave2_1_no_details]] [[Yes |Q4_01_wave2_1_yes_details]]

Advise: It can be useful to be aware of such influences, and not necessarily to avoid and minimize them. External impulses might stimulate Research (Data Stewardship) progress and should therefore not generally be ignored, but perhaps rather internally discussed.

No further recommendations

*QA / Are you ready to conduct future changes to the language you were using for your project, if plausible scientific arguments convinced you that this would be the right thing to do (y/n)? [[No |Q4_02_wave2_1_no_details]] [[Yes |Q4_02_wave2_1_yes_details]]

No further recommendations

QA / Were you aware of any critiques or commentaries by scientific peers, regarding your project, while it was ongoing (y/n)? [[Yes |Q4_01_question]] [[Yes |Q4_02_question]]

*QA / Did you consult any independent Domain Expert(s) in the same field to clarify your doubts (y/n)? [[No |Q5_01_wave2_1_no_details]] [[Yes |Q5_01_wave2_1_yes_details]] [[No |Q5_01_wave2_2_no_details]] [[Yes |Q5_01_wave2_2_yes_details]] [[No |Q5_01_wave2_3_no_details]]

Advise: This may be your only option to receive independent and qualified second opinions. If you cannot find adequate persons to address with these issues, maybe try it in related research disciplines, as well.

Follow-Up: Did this measure help to clarify your doubts (y/n)? [[No |Q5_01_wave2_2_no_details]] [[Yes |Q5_01_wave2_2_yes_details]] [[No |Q5_01_wave2_3_no_details]]

Follow-Up: Did you still publish any Results and Research Data (y/n)? [[No |Q5_01_wave2_3_no_details]]

No further recommendations

QA / Did you, at any point of your project, develop any reasonable scientific doubts about the validity of the Research Data used in or generated by your Project (y/n)? [[Yes |Q5_01_question]]

*QA / Did you reflect, whether such critiques and/or commentaries of scientific peers regarding your ongoing project could have an influence on your and/or your teams performance (y/n)? [[No |Q6_01_wave2_1_no_details]] [[Yes |Q6_01_wave2_1_yes_details]]

Advise: Although it is likely to face a fair amount of uncertainty here, you could try to find out, whether such events afflicted your colleagues or your personal motivation or working performance, by seeking dialogue. If you do not have a research team, you might be able to talk to a trusted but independent colleague from your field, who could be able to help you in interpreting the criticism.

No further recommendations

QA / Were you aware of any public critiques or commentaries by scientific peers, regarding your ongoing project (y/n)? [[Yes |Q6_01_question]]

*QA / Did you consult any independent Domain Expert(s) in the same field to verify this notion (y/n)? [[No |Q7_01_wave2_1_no_details]] [[Yes |Q7_01_wave2_1_yes_details]] [[No |Q7_01_wave2_2_no_details]] [[Yes |Q7_01_wave2_2_yes_details]]

Follow-Up: Did you already (re-)publish any of the erroneous Research Data or sources (y/n)? [[No |Q7_01_wave2_2_no_details]] [[Yes |Q7_01_wave2_2_yes_details]]

Advise: If the notion sustains and refers to one or more of your sources, it might be good practice to inform responsible authors directly about your discoveries. Of course, this is neither obligatory nor necessary for your Research. but perhaps such an exchange could be beneficial to you as well, if you just misunderstood something.

No further recommendations

Advise: If you did so, in order to point out the identified mistakes, there is nothing further to recommend about that. Should you not have realized the error in time, you can still intervene, by clarifying this incident in a transparent manner. If you do so pro-actively and perhaps publish a corresponding retraction note, the notion of attempted research fraud may be avoided.

*QA / Would it be adequate to consider yourself as at least one of the sources, responsible for the identified error (y/n)? [[No |Q7_02_wave2_1_no_details]] [[Yes |Q7_02_wave2_1_yes_details]] [[No |Q7_02_wave2_2_no_details]] [[Yes |Q7_02_wave2_2_yes_details]]

No further recommendations

Follow-Up: Did you, or are you planning to, adequately take responsibility for the identified error (y/n)? [[No |Q7_02_wave2_2_no_details]] [[Yes |Q7_02_wave2_2_yes_details]]

Warning: As a social role-model and scientist, you should definitely do so, even if this might have negative consequences. Furthermore, without taking responsibility for your decisions in science, you are actually denying your own Research, which could completely negate any trust in your work and question its overall legitimacy.

Advise: “Adequately”, in this context, implies that you actually took consequences for your mistakes, rather than just rhetorically claiming to do so. There is no scientifically valid point in trying to haggle yourself out of responsibilities, even if it worked as a strategy.

QA / Did you become aware of any technical or methodological errors within the Research Data of your project (y/n)? [[Yes |Q7_01_question]] [[Yes |Q7_02_question]]

*QA / Did you consult any independent Domain Expert(s) from the relevant field(s), to help you evaluate the risks you already assumed (y/n)? [[No |Q8_01_wave2_1_no_details]] [[Yes |Q8_01_wave2_1_yes_details]] [[No |Q8_01_wave2_2_no_details]] [[Yes |Q8_01_wave2_2_yes_details]]

Advise: Risk-assessment is a complex issue, that can profit from qualified double-checks. It is advisable to remain sceptical about own work, and at least look for other qualified, evidence-based and independent opinions.

Follow-Up: Did you further halt or are you halting any research activities based on the assumed risks (y/n)? [[No |Q8_01_wave2_2_no_details]] [[Yes |Q8_01_wave2_2_yes_details]]

Advise: Perhaps you should be ready to explain why you chose not to do so, despite the risks that have been foreseeable, before.

Advise: Perhaps you want to make sure to indicate the duration and character of the conducted research pause, in any potential future publications to your Research Data (Stewardship).

QA / Were you able to reasonably assume risks connected to your Research, which you were unable to assess in detail (y/n)? [[Yes |Q8_01_question]]

*QA / Did you deliberately avoid confronting yourself with aspects of your Research (Data Stewardship) Project, you were personally not interested in (y/n)? [[No |Q9_01_wave2_1_no_details]] [[Yes |Q9_01_wave2_1_yes_details]]

No further recommendations

Advise: Within a larger research team, this might be acceptable, given the right circumstances. As an individual researcher however, you probably do not have this opportunity. If you catch yourself actively avoiding uncomfortable aspects of your Research -- which would in fact deserve your attention -- you might be able to gain practical tips on how to deal with the situation, by undergoing a motivational coaching event for researchers.

QA / Were you aware of any aspects of your Research (Data Stewardship) Project you are personally not interested in (y/n)? [[Yes |Q9_01_question]]

*QA / Did you evaluate the FAIRness of your Research (Data Stewardship) by applying any <a href="https://fair-impact.eu/fair-assessment-tools">evaluation tool</a> (y/n)? [[No |Q10_01_wave2_1_no_details]] [[Yes |Q10_01_wave2_1_yes_details]] [[No |Q10_01_wave2_2_no_details]] [[Yes |Q10_01_wave2_2_yes_details]] [[No |Q10_01_wave2_3_no_details]] [[Yes |Q10_01_wave2_3_yes_details]]

Advise: Doing so might reveal concrete potentials for improving your Research Data Stewardship and its sustainability. If you need support in planning Research Data Stewardship aligned with FAIR Principles, you could use for example <a href="https://doi.org/10.5334/dsj-2019-059">this wizard</a>. If you do not know how to verify the FAIRness of your work, you can familiarize yourself with the <a href="https://www.go-fair.org/fair-principles/fairification-process/">process of FAIRification</a> contact local FAIRification or use broader self-evaluation tools like the <a href="https://www.rd-alliance.org/group/fair-data-maturity-model-wg/outcomes/fair-data-maturity-model-specification-and-guidelines-0">FAIR Data Maturity Model</a>. However, never confuse FAIRness of data with data quality.

Follow-Up: Did you further try or are you trying to let the FAIRness of your Research Data Stewardship be assessed by independent specialised organisation(s) and/or individual(s) (y/n)? [[No |Q10_01_wave2_2_no_details]] [[Yes |Q10_01_wave2_2_yes_details]] [[No |Q10_01_wave2_3_no_details]] [[Yes |Q10_01_wave2_3_yes_details]]

Advise: You may find such entities on national or international level, depending on your particular geographical and research area. An <a href="https://nfdi4culture.de/de/helpdesk.html">example</a> (for the Humanities in Germany).There is however no guarantee, that such entities will have the capacity to independently review your whole project (data).

Follow-Up: Do you further understand a high level of FAIRness as equivalent to high quality Research Data (y/n)? [[No |Q10_01_wave2_3_no_details]] [[Yes |Q10_01_wave2_3_yes_details]]

No further recommendations

Warning: The implementation of FAIR can be a good indicator for sustainable Research Data Stewardship, however you should not mistake it for an equivalent for Research Data quality. The latter is always dependant of the question it should be used to answer.

*QA / Did you and/or at least some of your team members receive adequate training in terms of <a href="https://www.go-fair.org/fair-principles/fairification-process/"> FAIRification</a>(y/n)? [[No |Q10_02_wave2_1_no_details]] [[Yes |Q10_02_wave2_1_yes_details]]

Advise: Since the FAIR Principles are widely adopted as best practices in Research Data Stewardship, it might make sense to receive specialised training, which is offered at many institutional levels, see <a href="https://www.go-fair.org/training/">for example</a>.

No further recommendations

*QA / Were you also stewarding your Research Data in full accordance with the <a href="https://www.gida-global.org/care"> CARE-Principles</a> (y/n)? [[No |Q10_03_wave2_1_no_details]] [[Yes |Q10_03_wave2_1_yes_details]] [[No |Q10_03_wave2_2_no_details]] [[Yes |Q10_03_wave2_2_yes_details]] [[No |Q10_03_wave2_3_no_details]] [[Yes |Q10_03_wave2_3_yes_details]]

Advise: You should be aware, that you do not necessarily have to work with indigenous data for the CARE Principles to provide useful tips towards sustainable and ethical Research Data Stewardship.

Follow-Up: Did you evaluate or are you evaluating the level of CARE implementation of your Research by applying any evaluation tool (y/n)? [[No |Q10_03_wave2_2_no_details]] [[Yes |Q10_03_wave2_2_yes_details]] [[No |Q10_03_wave2_3_no_details]] [[Yes |Q10_03_wave2_3_yes_details]]

Advise: A similar approach to the <a href="https://www.rd-alliance.org/group/fair-data-maturity-model-wg/outcomes/fair-data-maturity-model-specification-and-guidelines-0">FAIR Data Maturity Model</a> – that should help to understand the level of CARE implementation in a given project – can be tested <a href="https://cartong.pages.gitlab.cartong.org/learning-corner/en/7_sectoral_resources_RD/7_1_Care_RDMM">here</a>.

Follow-Up: Did you consider a high level of CARE equivalent to ethical Research (Data Stewardship) (y/n)? [[No |Q10_03_wave2_3_no_details]] [[Yes |Q10_03_wave2_3_yes_details]]

No further recommendations

Warning: The implementation of CARE can be a good indicator for ethical Research Data Stewardship, however you should not mistake it for an equivalent to ethical research. Due to the nature of ethics, which are usually determined “after the fact”, there is always potential for new developments and tips, you could not yet acknowledge.

QA / Were you stewarding your Research Data in full accordance with the <a href="https://www.go-fair.org/fair-principles/">FAIR-Principles</a> (y/n)? [[Yes |Q10_01_question]] [[Yes |Q10_02_question]] [[Yes |Q10_03_question]]

*Collect / Did you buy collaboration in the form of Research Data related services delivered by third parties (lab analyses/satellite imagery etc.) (y/n)? [[No |S1_01_wave2_1_no_details]] [[Yes |S1_01_wave2_1_yes_details]] [[No |S1_01_wave2_2_no_details]] [[Yes |S1_01_wave2_2_yes_details]]

No further recommendations

Follow-Up: Did you and do you have the competence to verify the quality of services you paid for (y/n)? [[No |S1_01_wave2_2_no_details]] [[Yes |S1_01_wave2_2_yes_details]]

No further recommendations

*Share / Did you transparently disclose all sponsors and/or contributors of your project (y/n)? [[No |S1_02_wave2_1_no_details]] [[Yes |S1_02_wave2_1_yes_details]]

Warning: Not disclosing all sponsors and/or contributors to a Research Project violates at least the <a href="https://allea.org/wp-content/uploads/2023/06/European-Code-of-Conduct-Revised-Edition-2023.pdf">European Code of Conduct for Research Integrity</a>. If you struggle to understand why this should be important in the first place, you might want to take your conclusions, by taking a look at a practical <a href="https://www.jstor.org/stable/23474436">example</a>.

No further recommendations

*Share / Were you aware of any possible conflicts of interest between your sponsors'/Research Stakeholders‘ interests and your scientific interests (y/n)? [[No |S1_03_wave2_1_no_details]] [[Yes |S1_03_wave2_1_yes_details]] [[No |S1_03_wave2_2_no_details]] [[Yes |S1_03_wave2_2_yes_details]] [[No |S1_03_wave2_3_no_details]] [[Yes |S1_03_wave2_3_yes_details]]

Advise: If in doubt about how a conflict of interest can be defined, maybe have a look at your institution’s policies. A broader definition can be found <a href="https://compliance.ucf.edu/understanding-conflict-of-interest/">here>/a>. Regardless of specific definitions, if you feel negatively impacted in your work as a researcher, by any sponsors or stakeholders, this might qualify as a conflict of interest for you personally.

Follow-Up: Did you, or are you planning to resolve, the conflict(s) of interest in favour of your scientific interest (y/n)? [[No |S1_03_wave2_2_no_details]] [[Yes |S1_03_wave2_2_yes_details]] [[No |S1_03_wave2_3_no_details]] [[Yes |S1_03_wave2_3_yes_details]]

Follow-Up: Did you find a compromise that you are confident to transparently share with the public and your research stakeholders (y/n)? [[No |S1_03_wave2_3_no_details]] [[Yes |S1_03_wave2_3_yes_details]]

Advise: Although this could risk your financial support through sponsorship, scientific independence might very well be worth the risk. Perhaps you need financial resources less urgently, than you need the freedom to describe findings independently. After all, losing financial support of sponsors can be supplemented to a certain degree by mechanisms such as crowdfunding, institutional/public research funding, citizen science or even lowering research ambitions for the time given – while the loss of scientific independence can never be supplemented by anything else. The decision you have to make concerns short-term ambitions and (material) possibilities vs. long-term scientific integrity and validity.

Warning: So you should prioritize the solution of this matter, before continuing any research.

No further recommendations

*Share / Would you feel comfortable presenting undesired Research (Data Stewardship) Results and/or Research (Data Stewardship) failures to your sponsors, if the factual situation demanded so (y/n)? [[No |S1_04_wave2_1_no_details]] [[Yes |S1_04_wave2_1_yes_details]]

Warning: Given this premise, you are unable to conduct impartial Research (Data Stewardship). If you leave this situation unaddressed, all your future Research Data Stewardship is based on this fundamental flaw and cannot ultimately get rid of respective weaknesses. You should consider changing your Research (Data Stewardship) environment to receive space, for reporting actual facts, regardless of how they are perceived.

No further recommendations

Share / Did you take any financial contributions for the Research Project (y/n)? [[Yes |S1_01_question]] [[Yes |S1_02_question]] [[Yes |S1_03_question]] [[Yes |S1_04_question]]

*Share / Did you provide any prior warnings, in order to prepare readers on the nature and context of your published Research (Data) (y/n)? [[No |S2_01_wave2_1_no_details]] [[Yes |S2_01_wave2_1_yes_details]]

Advise: There is ongoing scientific controversy regarding the question, when and how benefits to readers are provided, if „trigger warnings“ are included at the beginning of respective texts. Depending on your Research (Data Stewardship) scenario, you might want to include warnings, when detailed accounts of violence are present within your Data and not already expectable by the mere topic. However, it still is worth to closely follow ongoing research regarding the question, in order to prepare your Research Data Stewardship accordingly.

*Share / Did you edit research data as such, in an attempt to prepare themes of physical and/or psychological for an (academic) audience (y/n)? [[No |S2_02_wave2_1_no_details]] [[Yes |S2_02_wave2_1_yes_details]]

Advise: There are philosophical positions, describing the act of representation as such, as an <a href="https://doi.org/10.1057/9781137296900_2">act of violence</a>. In a concrete context this could mean, that whoever suffered the violence your Research refers to, could again be subjected to the way, in which you represent it. If you wish to reduce harm to personal dignity, editing of data could punctually make sense, where ever the context allows for it.

Warning: Even if studying the original source(s) and/or data might be unbearable, the risk of misrepresentation of facts – and perhaps trivialization of suffering – is realistic, if you edit or omit details for social reasons. <a href="https://www.corteidh.or.cr/tablas/r30885.pdf">Further Reading </a>.

Share / Did your Research Results or Research Data deal with themes of physical and/or psychological violence (y/n)? [[Yes |S2_01_question]] [[Yes |S2_02_question]]

*Share / Did you further consider teaching the results of your Research to academic laypeople (y/n)? [[No |S3_01_wave2_1_no_details]] [[Yes |S3_01_wave2_1_yes_details]] [[No |S3_01_wave2_2_no_details]] [[Yes |S3_01_wave2_2_yes_details]]

Advise: Perhaps this would be a way to raise attention for your research topic or project, if these things are in any way desired.

Follow-Up: Did these considerations also explicitly include educating minors (y/n)? [[No |S3_01_wave2_2_no_details]] [[Yes |S3_01_wave2_2_yes_details]]

No further recommendations

Advise: Even if your Research topic might be perfectly suitable for every population group, you still do not want to engage in educating minors unprepared. Please strongly consider a specialised training before, if you hadn't received one already.

*Share / Did you receive any scientifically valid training, regarding the teaching of scientific facts (y/n)? [[No |S3_02_wave2_1_no_details]] [[Yes |S3_02_wave2_1_yes_details]]

Advise: You should really consider to receive one. Even if you might not reach a professional teacher‘s skill level, the ability to teach your particular Research experience could be considered a part of the Sharing-process. Many universities offer seminars and programs for professionals, who have to teach their knowledge.

No further recommendations

*Share / Did you and/or your team create additional <a href="https://www.unesco.org/en/legal-affairs/recommendation-open-educational-resources-oer">Open Educational Resources</a> to supplement teaching (y/n)? [[No |S3_03_wave2_1_no_details]] [[Yes |S3_03_wave2_1_yes_details]]

Advise: If you picked this option because of the “Open” aspect, but are still planning to create or created educational resources, -- you might want to reconsider why your resources should be suitable for teaching a limited audience, previously unknown to you vs a theoretically unlimited audience, previously unknown to you. Be aware, that educational resources are not bound to specific types <a href="https://doi.org/10.1093/ahr/rhad488">of</a><a href="https://www.jstor.org/stable/43264355?seq=1">media</a> .

No further recommendations

Share / Were you adequately prepared and/or determined to teach the essence of your Research (y/n)? [[Yes |S3_01_question]] [[Yes |S3_02_question]] [[Yes |S3_03_question]]

*QA / Was your recommendation of behaviour to the public and/or scientific peers properly labelled as such, in order to not be mistaken for scientific facts (y/n)? [[No |S4_01_wave2_1_no_details]] [[Yes |S4_01_wave2_1_yes_details]] [[No |S4_01_wave2_2_no_details]] [[Yes |S4_01_wave2_2_yes_details]] [[No |S4_01_wave2_3_no_details]] [[Yes |S4_01_wave2_3_yes_details]]

Warning: For the sake of the validity and legitimacy of your Research, you should have a natural interest in thoroughly separating personal opinions and interpretations from actual facts. This might otherwise negatively influence public trust in your work.

Follow-Up: Did you reach your recommendation of behaviour, after consultations and discussions with further qualified Domain Experts (y/n)? [[No |S4_01_wave2_2_no_details]] [[Yes |S4_01_wave2_2_yes_details]] [[No |S4_01_wave2_3_no_details]] [[Yes |S4_01_wave2_3_yes_details]]

Advise: Even if your Research’s results are so conclusive, that you would like to immediately recommend change(s) to individual behaviour as a consequence, you still may want to discuss this with other qualified Domain Experts, first. And may it just be, in order to prepare a broader, more coordinated, maybe multi-disciplinary reaction to your findings.

Follow-Up: Are you still ready to withdraw or change your recommendations, if your initial understanding of the facts is challenged by new data (y/n)? [[No |S4_01_wave2_3_no_details]] [[Yes |S4_01_wave2_3_yes_details]]

Warning: Then you might risk to contribute to long-lasting misconceptions and leave potentials to correct earlier mistakes unused. This certainly does not serve any scientific purpose.

No further recommendations

Share / Did you recommend a particular behaviour to the public or scientific peers, based on your Research Data (Stewardship) (y/n)? [[Yes |S4_01_question]]

*Share / Did you become aware of any unintended humorous elements in your Research and/or its presentation (y/n)? [[No |S5_01_wave2_1_no_details]] [[Yes |S5_01_wave2_1_yes_details]] [[No |S5_01_wave2_2_no_details]] [[Yes |S5_01_wave2_2_yes_details]]

Follow-Up: Were, or are, you further aware of any intended humorous elements in your Research and/or its presentation (y/n)? [[No |S5_01_wave2_2_no_details]] [[Yes |S5_01_wave2_2_yes_details]]

Advise: If you believe, or initially believed, that unintended humorous elements should not disqualify research as invalid or worthless, you are <a href=”https://improbable.com/ig/winners/”>most likely correct</a>. If laughter is one possible but not the most common reaction you experience, and if it is not backed with evidence-based argumentations against your work, the amount of colleagues not taking your research seriously might be completely dispensable for your work.

No further recommendations

Advise: Be aware, that humour does not work as a universal concept, but is always contextual. There are <a href="https://doi.org/10.1177/0963662520915359">indications</a>, that humour might benefit the process of sharing scientific facts, but this process is not isolated from risks of misrepresentation. If you decide to apply humorous strategies, you should try not to overdo it.

*Share / Did you consider your, and/or your team's, personal background(s) the main reason for not being taken seriously (y/n)? [[No |S5_02_wave2_1_no_details]] [[Yes |S5_02_wave2_1_yes_details]] [[No |S5_02_wave2_2_no_details]] [[Yes |S5_02_wave2_2_yes_details]]

Follow-Up: Can you picture your Research Topic as such, the main reason for not being taken seriously (y/n)? [[No |S5_02_wave2_2_no_details]] [[Yes |S5_02_wave2_2_yes_details]]

Advise: Perhaps an academic pseudonym might temporarily help to overcome this potentially systemic injustice. The <a href="https://www.jstor.org/stable/21762">technique as such </a> is not new and might have been applied before out of reasons very similar to those, you face now.

Advise: If neither content (topic) nor responsible authors seem to be the problem, maybe form is. If you only published on a private website or did not pay attention to any style or structure, the content of your work may be valid, but you will most likely not receive the deserved attention for it.

Advise: If you work on a topic which already has a certain negative reputation, such as <a href="https://doi.org/10.15252/embr.201947761">homeopathy</a>, because it has been disproven on several accounts before, you may have to present a very substantial amount of unambiguous new scientific evidence, in order to be taken seriously.

Share / Did you feel not being taken seriously with your Research Question and/or Research (Data Stewardship) among scientific peers (y/n)? [[Yes |S5_01_question]] [[Yes |S5_02_question]]

*Share / Did you publish the same publication(s) in more than one language (y/n)? [[No |S6_01_wave2_1_no_details]] [[Yes |S6_01_wave2_1_yes_details]]

Advise: If you have any interest to optimize the Sharing of your Research (Data Stewardship) it might be recommendable to think beyond English, and also invest in properly translating your publication in other languages. This would be especially relevant, where ever you cooperated with people who are native speakers of another language.

No further recommendations

*Plan / Did you attempt to convince people, whom you thought they would not take you or your Research seriously otherwise (y/n)? [[No |S6_02_wave2_1_no_details]] [[Yes |S6_02_wave2_1_yes_details]]

Advise: To a certain degree, this might be the point of a publication. However, the quality of your research does not depend on others’ willingness to take it seriously.

Advise: Be however careful – it could turn into a problematic scenario if your wish to convince a scientific audience, makes you apply unfitting rhetoric.

Share / Did you release any regular scientific publication as a consequence of your Research (Data Stewardship) Project (y/n)? [[Yes |S6_01_question]] [[Yes |S6_02_question]]

*Share / Did you believe your Research Topic received too little public and/or academic attention (y/n)? [[No |S7_01_wave2_1_no_details]] [[Yes |S7_01_wave2_1_yes_details]] [[No |S7_01_wave2_2_no_details]] [[Yes |S7_01_wave2_2_yes_details]]

Advise: Since you seem to believe that your Research Topic (currently) receives too much public attention, you may want to reflect, whether you have a conclusive justification for raising it further with your own project. Perhaps, if you consider the amount of public attention for the topic problematic but want to do your research for this exact reason, you can afford to schedule your publication for a time, when public attention has moved on?

Follow-Up: Does or did your Research also intend to raise awareness for the Topic, with the aim of gaining more public and/or academic attention (y/n)? [[No |S7_01_wave2_2_no_details]] [[Yes |S7_01_wave2_2_yes_details]]

No further recommendations

Advise: Be aware that, as long as you do not publish with top-shelf publishers, your publication range might not be sufficient to achieve this affect just with a regular publication. Perhaps you may want to consider additional activities, such as presentations, educational videos (or other resources), further guest contributions etc.

Share / Did you believe, your Research Topic did not receive the amount of public and/or academic attention, it deserved (y/n)? [[Yes |S7_01_question]]

*Share / Did you properly cite all of the sources, used for your publication, consistent to the same scientific citation format (y/n)? [[No |S8_01_wave2_1_no_details]] [[Yes |S8_01_wave2_1_yes_details]] [[No |S8_01_wave2_2_no_details]] [[Yes |S8_01_wave2_2_yes_details]] [[No |S8_01_wave2_3_no_details]] [[Yes |S8_01_wave2_3_yes_details]]

Warning: Even if it might not particularly matter, which citation guideline you follow, it is extremely important to be consistent about whatever you picked. Not paying attention to this, violates most concepts of good scientific practice.

Follow-Up: Did you and do you further completely understand the content of each of your cited sources (y/n)? [[No |S8_01_wave2_2_no_details]] [[Yes |S8_01_wave2_2_yes_details]] [[No |S8_01_wave2_3_no_details]] [[Yes |S8_01_wave2_3_yes_details]]

Follow-Up: Did you and do you transparently indicate, if you failed to completely understand the content of a cited source, why you still decided to quote it (y/n)? [[No |S8_01_wave2_3_no_details]] [[Yes |S8_01_wave2_3_yes_details]]

No further recommendations

Warning: Then you have at least violated one of the basic principles of academic work. You should re-consider your sources, until you can answer this question affirmatively.

No further recommendations

*Share / Did you publish the same paper, article or monography in more than one language (y/n)? [[No |S8_02_wave2_1_no_details]] [[Yes |S8_02_wave2_1_yes_details]]

Advise: If you worked with a particular regional community, sharing research results could require to translate them. If this is not the case in your context, you may still decide to create future translation of your work, later.

Warning: Of course, the question implied that you would treat translations as different versions of the same publication – not as separate publications. If this is any different in your context, you are at risk of committing <a href="https://doi.org/10.1007/978-3-030-46711-1_2">translation plagiarism</a>.

Advise: If you are in doubt about the repository you should use, you may find a preference within the recommendations of your institution or large publishers. If none of this reflects your individual project’s needs, you can do further research using for example <a href="https://www.re3data.org/">this</a>resource.

Follow-Up: Did, or does, this also pertain to metadata (y/n)? [[No |S8_03_wave2_2_no_details]] [[Yes |S8_03_wave2_2_yes_details]] [[No |S8_03_wave2_3_no_details]] [[Yes |S8_03_wave2_3_yes_details]]

Advise: Do not underestimate the significance of metadata. As long as you have no particular reason not to do so, providing meaningful metadata to your Research data can be enormously useful to the visibility and many other aspects of your research. If you struggle to see why and how, <a href=”https://lod-cloud.net/”>this</a> could serve as an illustrative example, which would have been impossible without adequate metadata.

Follow-Up: Did you, or are you planning to put any license restrictions on access and/or usage of data and/or metadata (y/n)? [[No |S8_03_wave2_3_no_details]] [[Yes |S8_03_wave2_3_yes_details]]

Advise: Even if you do not intend to restrict the use of your data and/or metadata, you should still indicate this by attaching adequate <a href=”https://opendatacommons.org/licenses/>license information</a>. In any case, you may want to consider legal counselling before you make such a consequential decision.

Advise: Depending on your context, a hybrid-approach might be the best possible solution. Providing free access to metadata about a legally protected set of original data online, while the original data are stored elsewhere (as observable at the example of <a href=”https://www.europeanfilmgateway.eu/detail/Erbe%20desserter-reklame/nnb::53b9dbb2ec6cea33863f88985a7c46c3”>EFG</a>) has the advantage of keeping right owners’ interests balanced with the scientific ambition of not forgetting about the existence of namely data. In other context, if data is allowed to be fully available but you wish to protect specific metadata such as identities of interview partners, you could make metadata freely accessible that transparently indicates, that it contains pseudonyms instead of real names.

Share / Did you publish at least one paper, article or monography about the Research Project you are currently involved with (y/n)? [[Yes |S8_01_question]] [[Yes |S8_02_question]] [[Yes |S8_03_question]]

*Share / Did you put any restrictions on access and/or usage of that software application (y/n)? [[No |S9_01_wave2_1_no_details]] [[Yes |S9_01_wave2_1_yes_details]] [[No |S9_01_wave2_2_no_details]] [[Yes |S9_01_wave2_2_yes_details]]

No further recommendations

Follow-Up: Did you or do you intend to prevent specific kinds of abuse of your software with the namely restrictions (y/n)? [[No |S9_01_wave2_2_no_details]] [[Yes |S9_01_wave2_2_yes_details]]

No further recommendations

Advise: If you see a particular potential of your software being abused for a specific activity, you may want to consider not just legal protection for yourself and/or your team (via the license) but also, whether technical measures could reasonably prevent or limit this type of abuse. Effective age verification measures for software that could be at least risky in the hands of minors, may be more helpful against abusive software use, than an easily ignorable legal note, which primarily protects you. Of course, given your context, both can be equally necessary.

Share / Did you release any software application, connected to your research project (y/n)? [[Yes |S9_01_question]]

*Share / Did you have a scientific reason for your speculation(s) and properly indicated them as such (y/n)? [[No |S10_01_wave2_1_no_details]] [[Yes |S10_01_wave2_1_yes_details]] [[No |S10_01_wave2_2_no_details]] [[Yes |S10_01_wave2_2_yes_details]]

Follow-Up: Do or did you feel pressured into presenting any speculations as research results to third people (y/n)? [[No |S10_01_wave2_2_no_details]] [[Yes |S10_01_wave2_2_yes_details]]

Advise: Be careful to still draw a clear line between speculation and facts in your communication about your research.

No further recommendations

Advise: Giving in to such pressure, by engaging in speculations risks to just exchange the first problem with another. So you might want to pay close attention on the difference between speculation and <a href=”https://doi.org/10.1007/978-3-030-90913-0_118”>speculative research</a> and verify that you did not accidentally engaged in the undesired one.

Share / Did you engage in any kind of speculation over the course of your research Process (y/n)? [[Yes |S10_01_question]]

*Share / Did you assess the risk of your Research Results, if published in any Open context, contributing to pre-existing social inequalities (y/n)? [[No |S11_01_wave2_1_no_details]] [[Yes |S11_01_wave2_1_yes_details]]

Advise: It may sound contradictory, but even though Open Principles strive to foster public participation, democracy – and in doing so, also equality – in reality, it is possible that these effects, if they happen only within a limited part of a larger society, actually contribute to the opposite. This phenomenon, known as <a href=”https://dictionary.cambridge.org/de/worterbuch/englisch/digital-divide>digital divide</a> is no general argument against Open Principles, but emphasizes the importance to carefully consider such decisions, based on individual context.

Share / Did you submit your and/or your team's Research Data and Research Results to the principles of <a href="https://rea.ec.europa.eu/open-science_en"> Open Science</a> (y/n)? [[Yes |S11_01_question]]

*Share / Did you understand the legal implications and circumstances, connected to any of these choices, with respect to your Research Data and Research Results (y/n)?

Share / Did you use pop-cultural media formats (such as Science Slams, TED-Talks, Podcasts, documentary films etc.) to share your Research Results (y/n)? [[Yes |S12_01_question]]

*Analyze / Did you evaluate potential risks from your Research (Data Stewardship) Project to the unaffiliated people you were aware of (y/n)? [[No |S13_01_wave2_1_no_details]] [[Yes |S13_01_wave2_1_yes_details]] [[No |S13_01_wave2_2_no_details]] [[Yes |S13_01_wave2_2_yes_details]] [[No |S13_01_wave2_3_no_details]] [[Yes |S13_01_wave2_3_yes_details]]

Warning: At least some risk-assessment should be conducted, if unaffiliated people are or could be affected by your Research. If you do not feel qualified to do so, this is no excuse for simply not taking the matter seriously -- you may still be legally punishable if things really go wrong. If your institution / country does not require formal risk-assessment procedures, you may still find some guidance on what to pay attention to, in countries <a href="https://science.gc.ca/site/science/sites/default/files/attachments/2023/risk_assessment_form_ISED-ISDE3832E.pdf">that do</a>.

Follow-Up: Do you, or did you prioritize risk minimization for unaffiliated people over the success of your Research Project (y/n)? [[No |S13_01_wave2_2_no_details]] [[Yes |S13_01_wave2_2_yes_details]] [[No |S13_01_wave2_3_no_details]] [[Yes |S13_01_wave2_3_yes_details]]

Warning: If you somehow feel obliged to the <a href="https://www.britannica.com/topic/Hippocratic-oath">do no harm”- paradigm</a> you may want to reconsider your priorities.

Follow-Up: Are you or were you still ready to conduct your Research Project as planned, after considering the estimated risks for unaffiliated people acceptable (y/n)? [[No |S13_01_wave2_3_no_details]] [[Yes |S13_01_wave2_3_yes_details]]

Advise: A way out of the dilemma could be to turn unaffiliated people into affiliated people, by actively letting them participate in the process of deciding whether assessed risks are acceptable or not. Depending on your context, this may cause a lot of effort, but as a concept, this is not new. <a href=”https://bioethics.yale.edu/sites/default/files/files/fulltext.pdf”>Participatory Action Research (PAR) </a> with groups (not exclusively Peoples) provides some historical examples on how this could work.

No further recommendations

No further recommendations

Advise: Even if it might be impossible to reconstruct this question in detail, you can try to do so in a collaborative manner. Also keep in mind, that money may not necessarily be the only/the best option for compensation.

Follow-Up: Did you or do you apply adequate compensation measures to aggrieved parties (y/n)? [[No |S13_02_wave2_3_no_details]] [[Yes |S13_02_wave2_3_yes_details]] [[No |S13_02_wave2_4_no_details]] [[Yes |S13_02_wave2_4_yes_details]]

Advise: If you did not have the means or possibilities to provide any compensatory measures yourself, you can perhaps still support administrative superiors – or specialized institutions – in doing so. Also keep in mind, that money may not necessarily be the only/the best option for compensation.

Follow-Up: Is the risk of causing the same, or related kinds of, damage to unaffiliated people in the future, still present (y/n)? [[No |S13_02_wave2_4_no_details]] [[Yes |S13_02_wave2_4_yes_details]]

No further recommendations

Warning: Then there are perhaps conclusions left to be drawn from your Research Data Stewardship experiences, that could help to improve the process in the future. Perhaps you should re-consider this question.

Share / Were you aware of any people, who were in no way affiliated to your Research (Data Stewardship) Project, but still directly affected by it and/or its consequences (y/n)? [[Yes |S13_01_question]] [[Yes |S13_02_question]]

*Plan / Did you have a backup-plan, in case the contribution, or the joint project failed (y/n)? [[No |S14_01_wave2_1_no_details]] [[Yes |S14_01_wave2_1_yes_details]] [[No |S14_01_wave2_2_no_details]] [[Yes |S14_01_wave2_2_yes_details]]

Warning: If you want your Research (Data) to remain sustainable, you should not become completely dependent of the joint project. Even if you have to work with locally stored backup files -- which could later be published elsewhere again – this is preferable over losing the data altogether. Should you lack ideas on how to implement a backup strategy, you may use the so called <a href="https://www.cisa.gov/sites/default/files/publications/data_backup_options.pdf">3-2-1 rule</a> as a starting point.

Follow-Up: Do you or did you further have the necessary technical infrastructure and know-how to maintain Research Data Backups on your own (y/n)? [[No |S14_01_wave2_2_no_details]] [[Yes |S14_01_wave2_2_yes_details]]

Warning: So called<a href="https://doi.org/10.1007/978-0-387-39940-9_1333">RAIDs (Redundant Arrays of Inexpensive Disks), later (Redundant Arrays of Independent Disks)</a> are supposed to be inexpensive. If you lack the expertise on how to use such devices for a backup strategy, and if you can’t ask specialised experts, you may find inspiration <a href="https://www.cisa.gov/sites/default/files/publications/data_backup_options.pdf">here</a>.

No further recommendations

Share / Did you contribute your Research Results and Research Data to already existing joint project initiatives (y/n)? [[Yes |S14_01_question]]

*Share / Did you consider it adequate to personally answer qualified questions regarding your Research (Data Stewardship) Results and/or publication(s) (y/n)? [[No |S15_01_wave2_1_no_details]] [[Yes |S15_01_wave2_1_yes_details]]

Warning: Since you are responsible for your Research, you should also be responsible and best qualified to answer any questions that refer to it. If you do not do this, perhaps nobody will be able to. If dialogue and scientific dispute is considered a mechanism of scientific progress, not responding, would eliminate this possibility completely.

No further recommendations

Share / Did you share an active interest in noticing and participating in any discussions following your publication (y/n)? [[Yes |S15_01_question]]

*Share / Did you actively try to make practical use out of your or your Project's affiliates scientific renown (y/n)? [[No |S16_01_wave2_1_no_details]] [[Yes |S16_01_wave2_1_yes_details]]

No further recommendations

Advise: Be careful that you do not confuse scientific renown with invariable scientific quality. Even <a href=”https://www.youtube.com/watch?v=7hic_eGCA_0&t=1299s”>high-profile scientists</a> reach the limits of their expertise somewhere, but may still receive attention due to their individual nimbus.

Share / Would you have described yourself and/or some of your project's affiliates as renowned scientists (y/n)? [[Yes |S16_01_question]]

*QA / Did you feel capable of expectation management, in case the aspired fame did not emerge [during your lifetime] (y/n)? [[No |S17_01_wave2_1_no_details]] [[Yes |S17_01_wave2_1_yes_details]]

Advise: Recent research literature on <a href="https://doi.org/10.3389/fpsyg.2023.1108006"> ambition</a> outlines the potential behavioural risks, associated with this character trait. It may be good advice to watch closely, whether your ambition might incentivize you to unreasonable risk behaviour.

No further recommendations

Share / Was the prospect of becoming a famous scientist, an important motivation for your Research activity (y/n)? [[Yes |S17_01_question]]

*Re-Use / Were you aware of the terms and conditions under which these Research Data had originally been collected (y/n)? [[No |R1_01_wave2_1_no_details]] [[Yes |R1_01_wave2_1_yes_details]] [[No |R1_01_wave2_2_no_details]] [[Yes |R1_01_wave2_2_yes_details]]

Warning: This could be a very unpleasant lack of knowledge. If you did never pay attention to <a href="https://doi.org/10.1007/978-3-030-52829-4_12">provenance</a> or <a href="https://kulturgutverluste.de/sites/default/files/2023-04/Handreichung.pdf">provenance research</a> you may be well advised to do so now. Actively knowing about unknown provenance is important information as well.

Follow-Up: Were these Research Data originally collected under circumstances you would consider unethical (y/n)? [[No |R1_01_wave2_2_no_details]] [[Yes |R1_01_wave2_2_yes_details]]

No further recommendations

Advise: Although this does not necessarily have anything to do with your doing, you can embrace the opportunity to document this part of (object) history. One <a href="https://ezeml.edirepository.org/eml/about">possibility</a> to do so.

*Re-Use / Did you re-use these Research Data for a purpose that was not originally intended, when the data were first collected (y/n)? [[No |R1_02_wave2_1_no_details]] [[Yes |R1_02_wave2_1_yes_details]] [[No |R1_02_wave2_2_no_details]] [[Yes |R1_02_wave2_2_yes_details]] [[No |R1_02_wave2_3_no_details]] [[Yes |R1_02_wave2_3_yes_details]]

No further recommendations

Follow-Up: Do you or did you feel confident that no sources were harmed in this process (y/n)? [[No |R1_02_wave2_2_no_details]] [[Yes |R1_02_wave2_2_yes_details]] [[No |R1_02_wave2_3_no_details]] [[Yes |R1_02_wave2_3_yes_details]]

Advise: “Sources” also refers to persons here. If you re-used someone’s data for a purpose that was not originally intended, this might subject the person to unforeseen risks. If in doubt, you may want to clarify this question.

Follow-Up: Are or were you able to assess that the re-used data were as meaningful in your context, as desired (y/n)? [[No |R1_02_wave2_3_no_details]] [[Yes |R1_02_wave2_3_yes_details]]

Advise: Especially if those re-used data are the only ones you use for your research, you should be able to verify this question. It might be necessary to gather some additional data yourself, in order to be able to do reasonable science.

No further recommendations

*Plan / Were you aware or at least suspicious of any still applying <a href="https://www.wipo.int/about-ip/en/">Intellectual Property Rights</a> regarding the Research Data you intended to re-use (y/n)? [[No |R1_03_wave2_1_no_details]] [[Yes |R1_03_wave2_1_yes_details]] [[No |R1_03_wave2_2_no_details]] [[Yes |R1_03_wave2_2_yes_details]] [[No |R1_03_wave2_3_no_details]] [[Yes |R1_03_wave2_3_yes_details]]

Warning: If this answer was not intended to actually state: “Yes, I am aware that no such Rights applied to the respective data.” you really want to find out, before proceeding to use these data. Please notice that being unable to find out about applying Rights is no protection against consequences of Rights violations.

Follow-Up: Were or are you further aware of any claimed <a href="https://www.wipo.int/about-ip/en/">Intellectual Property Rights</a> regarding the Research Data you intend to re-use or re-used (y/n)? [[No |R1_03_wave2_2_no_details]] [[Yes |R1_03_wave2_2_yes_details]] [[No |R1_03_wave2_3_no_details]] [[Yes |R1_03_wave2_3_yes_details]]

No further recommendations

Follow-Up: Did you attempt or are you attempting to negotiate with any right-holders, about your intended re-use of the namely data (y/n)? [[No |R1_03_wave2_3_no_details]] [[Yes |R1_03_wave2_3_yes_details]]

Warning: An agreement might be the best way to achieve the desired aim of re-using the data legally. If this seems totally unrealistic, you can either wait until the legal protection expires or -- if that is also unrealistic – not re-use the data.

No further recommendations

*Analyze / Did you believe some of the Research Data you were re-using should be legally and technically protected, even if they weren't before (y/n)? [[No |R1_04_wave2_1_no_details]] [[Yes |R1_04_wave2_1_yes_details]]

No further recommendations

Advise: It might be useful to discuss such perceptions with data owners and potentially also with local Data Protection Authorities (see for <a href="https://www.edpb.europa.eu/about-edpb/about-edpb/members_en">EU</a>). Any effort, only limited to your activity with the namely data could, if legal in the first place, not solve the greater underlying problem.

Re-Use / Did you re-using any already published Research Data for your Research Project (y/n)? [[Yes |R1_01_question]] [[Yes |R1_02_question]] [[Yes |R1_03_question]] [[Yes |R1_04_question]]

*Re-Use / Did you publicly react to more recent Research Data, contradicting your earlier publication(s) (y/n)? [[No |R2_01_wave2_1_no_details]] [[Yes |R2_01_wave2_1_yes_details]] [[No |R2_01_wave2_2_no_details]] [[Yes |R2_01_wave2_2_yes_details]] [[No |R2_01_wave2_3_no_details]] [[Yes |R2_01_wave2_3_yes_details]]

Advise: It could be useful to do so, if you wish to fight misconceptions related to your work. Also, this kind of interaction may spark new possibilities or ideas for further research, if that is in your interest.

Follow-Up: Did you, or are you planning to, append this most recent reaction to where ever your original publication was published (y/n)? [[No |R2_01_wave2_2_no_details]] [[Yes |R2_01_wave2_2_yes_details]] [[No |R2_01_wave2_3_no_details]] [[Yes |R2_01_wave2_3_yes_details]]

Warning: Since the tendency of retraction notes, commentaries, revisions etc. receiving considerably less attention than an original publication, is already<a href="https://doi.org/10.1073/pnas.2119086119">well researched</a>, not taking care of placing a reaction where ever an original had been placed, may further contribute to this problem.

Follow-Up: Did you react, or are you planning to react, without having new valid scientific evidence (y/n)? [[No |R2_01_wave2_3_no_details]] [[Yes |R2_01_wave2_3_yes_details]]

No further recommendations

Advise: Without new valid scientific evidence, you will most likely not be able to defend your disproved work. So be careful, that you reaction does not happen out of personal defiance.

Re-Use / Were you aware of any qualified scientific indications or evidence, contradicting your already published Research Results (y/n)? [[Yes |R2_01_question]]

*Re-Use / Did you apply all technical measures to secure a proper deletion of the relevant data (y/n)? [[No |R3_01_wave2_1_no_details]] [[Yes |R3_01_wave2_1_yes_details]]

No further recommendations

Re-Use / Did you re-use any data, you were legally obliged to delete after use (y/n)? [[Yes |R3_01_question]]

*Share / Were you reflecting the possibility of hindering future scientific progress or cultural tradition with your planned or already registered patents (y/n)? [[No |R4_01_wave2_1_no_details]] [[Yes |R4_01_wave2_1_yes_details]] [[No |R4_01_wave2_2_no_details]] [[Yes |R4_01_wave2_2_yes_details]]

Warning: The practice of patenting the use of natural resources, such as plants, as remedies for specific ailments could in fact have an impact on traditional ways of living. This practice could qualify as the illegal act of <a href=”https://doi.org/10.1155/2021/8898842> biopiracy</a>. A collaborative process of sharing Research outcome and exceptions to the patent protection can avoid this.

Follow-Up: Could you or do you consider to grant exceptions of patent protection, if you become aware of a promising Research Project or an existing cultural tradition that would be hindered by it (y/n)? [[No |R4_01_wave2_2_no_details]] [[Yes |R4_01_wave2_2_yes_details]]

Warning: The practice of patenting the use of natural resources, such as plants, as remedies for specific ailments could in fact have an impact on traditional ways of living. This practice could qualify as the illegal act of <a href="https://doi.org/10.1155/2021/8898842">biopiracy</a>. A collaborative process of sharing Research outcome and exceptions to the patent protection can avoid this.

No further recommendations

*Plan / Did the aim of registering a patent exist, before the actual Research (Data Stewardship) started (y/n)? [[No |R4_02_wave2_1_no_details]] [[Yes |R4_02_wave2_1_yes_details]] [[No |R4_02_wave2_2_no_details]] [[Yes |R4_02_wave2_2_yes_details]]

No further recommendations

Follow-Up: Did you and do you feel confident to claim scientific usefulness for your Research, despite the pre-existing patent ambitions (y/n)? [[No |R4_02_wave2_2_no_details]] [[Yes |R4_02_wave2_2_yes_details]]

Advise: If this is not the case -- perhaps because you proactively want to protect novel chemicals of which you cannot tell what they may be useful for, yet – your patenting approaches could qualify as lacking <a href="https://www.epo.org/en/learning/learning-resources-profile/business-and-ip-managers/inventors-handbook/novelty-and-prior-art/why-novelty-important">novelty</a>.

No further recommendations

Re-Use / Did you register one or more patents as a result of your Research Project (y/n)? [[Yes |R4_01_question]] [[Yes |R4_02_question]]

*Re-Use / Were your Research Data and/or Research Publication(s) being re-used for reasons you personally object to (y/n)? [[No |R5_01_wave2_1_no_details]] [[Yes |R5_01_wave2_1_yes_details]]

No further recommendations

Advise: Most likely you will have no legal options to disrupt any of these purposes or activities – not in the least due to the <a href="https://doi.org/10.1007/s11948-009-9130-9">unenforceability</a> of any such regulations. What you can do however, is to publicly advocate against undesired applications using your results.

*Re-Use / Were your Research Data and/or Research Publication(s) being re-used as a foundation for art (y/n)? [[No |R5_02_wave2_1_no_details]] [[Yes |R5_02_wave2_1_yes_details]] [[No |R5_02_wave2_2_no_details]] [[Yes |R5_02_wave2_2_yes_details]]

No further recommendations

Follow-Up: Were you interested in scientifically counselling artists, re-using your Research (Data) (y/n)? [[No |R5_02_wave2_2_no_details]] [[Yes |R5_02_wave2_2_yes_details]]

Advise: This does not require to have an artistic talent yourself. The ways you could support artist, may focus on counseling, aimed at avoiding undesired misrepresentations. See as an <a href="https://www.npr.org/2021/05/12/996007048/no-bows-and-arrows-and-no-broken-english-on-the-updated-oregon-trail">example</a>.

No further recommendations

Re-Use / Did you become aware of your Research Data or Research Publication(s) being actively re-used (y/n)? [[Yes |R5_01_question]] [[Yes |R5_02_question]]

*Analyze / Were you aware of any new contexts thus created for your Research Data (y/n)? [[No |R6_01_wave2_1_no_details]] [[Yes |R6_01_wave2_1_yes_details]]

Warning: Not being aware of any new contexts thus created to your Research Data, is not a sign that there aren’t new contexts generated. But this might indicate that you perhaps lack fundamental insights into this process. Maybe you want to familiarize yourself with the risks and dangers of re-linking data, so you can avoid the worst possible consequences. A good place to <a href="https://doi.org/10.1177/2515245917747656">start</a>further research.

Advise: Then you perhaps want to make sure, that no unintended misrepresentations occur through these new contexts. If you need examples on what could go wrong here, you may find useful examples, <a href="https://doi.org/10.34879/gesisblog.2022.61">here</a>.

Re-Use / Did you plan to make your Research Data and Results reusable via already existing Online networks or collections (y/n)? [[Yes |R6_01_question]]

The story ends here.