Research Ethics: What should OLS take into account?

TL;DR: You’re invited to share your thoughts about what is important in research ethics on this GitHub discussion, or via Slack in #general.

Longer: One of OLS’s three core pillars of activity is research, focusing on creating and understanding a better evidence base for equity-serving open research. Some of our previous work includes Paz Bernaldo’s Open Seeds Impact paper (currently in press with Wellcome Open Research), and our Alan Turing Institute funded “Widening participation in data science” policy briefs: Widening participation in data science: implementing policy for well-being in the workplace and Equitable & Inclusive Team Science.

What we’ve done for ethics in the past

For the work listed above, we used Pearl IRB’s independent ethical review board. In both cases, we were given ethics “waivers”. That is, we still had to fill out a large number of forms asking us what we were doing, what our consent form looked like, what our research protocols were, how we’d store our data, etc. - but after this was reviewed we weren’t asked for much else, and were told we could go ahead with the work. The process worked well, and was reasonably fast and easy to use, prompting us to think of important things and making sure we were ready to really do a good job.

We’d like to get a little bit more robust in our ethics processes.

OLS currently has research components built into two projects: OSPARK and Seeds to Systems. One thing we’ve learned while we were talking about this research is that our team comes from different backgrounds with very different experiences approaching when ethics reviews happen, and how they happen. Whilst many of us have conducted social research (e.g. interviews and focus groups), some of us have repeatedly been through ethics review processes, and others have done similar research in places where ethical review isn’t expected outside a clinical setting.

Where we stand

I’m sure it won’t surprise anyone when we say that research ethics is incredibly important to us as a team and as a community! In some research settings, the term “ethics” doubles as “ensuring legal liabilities are met”. In others, it might mean the difference between publishing in a peer-reviewed journal (with proof of an ethics process) or not being allowed to publish (without ethics). To OLS, it’s probably both of those: but we also aim to be trustworthy, thoughtful researchers. That means we want to be responsible for our own work and behaviour, regardless of any other review processes we might take part in. Which leads to the next question!

Looking for community input and opinions: What should we think about for OLS’s formal research ethics process?

As a researcher, what would you like to see in a compassionate, carefully thought-out research ethics policy? What would you like us to avoid? Some examples based on discussion at our recent Seeds to Systems meeting:

“Ethics” behaviours we want to avoid:

• “This is not human research, because it only involves talking to people, and doesn’t involve any clinical interventions”. (You can read about the University of Minnesota getting banned from contributing to the linux kernel if you’d like to understand the motivation for this one…)
• Assuming that just because something is legal or compliant with terms of service, that it is therefore okay.
• Focusing on procedural formalities, for example, “Your form doesn’t have a phone number on it. Please revise and resubmit with a phone number.” (8 months later, the ethics review passes, once they’ve had a phone installed in the lab, even though they never intend to use it); or “One of your forms says last updated on yesterday’s date and not today’s date. Please revise and resubmit. “

Do:

• Think carefully about how you would feel if you were a research participant in a given situation.
• Review research protocols and data management plans (DMPs) as a team to make them as robust as possible, before submitting to the independent review board (IRB).
• Share experiences from different scientific domains and legal systems.
• Check that the research is as open as is possible whilst respecting other tensions such as privacy, conservation, and indigenous sovereignty.
• Use open data formats wherever possible.
• Prepare consent forms that are accessible (for example, that don’t use jargon) to the people who will need to consent for the research to go ahead.

Where is the line - what requires ethics review and what doesn’t?

Given our varying experiences with research ethics, and the way we enjoy working with community, we want to formalise exactly which types of interaction and knowledge gathering should go through the ethics process and how much. Here’s a hypothetical scale, from least strict to most strict:

1. No ethics needed
   • An interactive online cohort call
   • Some informal or pilot research intended to shape formal research questions. Examples might be a “dry run” of an interview script, documenting our own experiences as reviewers or participants in grant funding processes, and synthesizing lessons learned.
2. Some minimal ethics process, possibly just consent to share:
   • A cohort mid-term or end-of-cohort survey that is published under a CC-BY license on OLS’s site, with participant consent.
3. OLS internal review, DMP, consent, and protocol, but no review board needed:
   • Surveys or focus groups that cover only non-sensitive topics that fall within a participant’s professional remit.
4. Formal research that needs a full internal (OLS) and external ethics (Pearl) review:
   • A focus group that might cover sensitive topics like diversity, inclusion, and equity (i.e. almost everything OLS does…)
   • Recorded interviews about a topic that is personal, dangerous, or illegal.

How does that hypothetical scale sound? If you think something falls on the wrong side of the line, tell us why. We intentionally haven’t included clinical research, lab research, or research with children on this list, but maybe some other areas SHOULD be included?

Other sub-questions we have:

• What about when it’s hard to be honest about what the study is (e.g. when explaining might be too technical, and/or it might impact the results of the study)?
• Are there any national or international “gotchas” we’re not aware of?

Ready to offer feedback, ask questions, or something else? feel free to contribute to the thread in the OLS Slack, and/or comment on this discussion