The “data ownership & sharing decision tree” (https://hdl.handle.net/11299/269486) is a research tool that helps researchers decide 1) if they own the data they wish to share and 2) whether there are other factors beyond ownership that impact data sharing. This tool is especially helpful for those considering whether they can share human participant data. The PDF also links out to important background information and guidelines in certain decision pathways. This was developed by members of the Data Curation Network (https://datacurationnetwork.org/).
Thanks so much for sharing this resource, @Shanda, and welcome to the community! Given the complexity of all the factors that can impact data sharing, it’s great to have a guidance roadmap like this.
I’m curious if other community members with interest in data security and data governance (@mejoh, @blehallier, @dlewis, @clinmed9) have thoughts about this resource, or have similar materials that have helped them think through these issues?
HI @gginnan and colleagues - this resource is quite interesting, and I will keep it for reference! Perhaps I missed it, but I would have liked to see a short text document alongside, explaining how the decision tree was prepared, considerations, etc. and going into more depth on some of the trickier questions being asked. For example, what exactly is meant by “restrictive language”. All in all, thanks for sharing @Shanda!
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Hi Cheryl, thanks for your interest and comments. The digital record does give a bit of context about the chart’s creation, but a simple answer is that we (the authors) are all data management educators and data curators at higher ed institutions. We created the workflow based on our personal experiences of helping researchers navigate the barriers they face when attempting to share their data. We did include links to learning opportunities in some paths; for example, the restrictive language decision path points users to the DCN’s Consent Forms Primer which details problematic consent form language when data sharing is the end-goal. We just released this and will continue to collect great feedback like yours to inform future iterations (I’m already thinking that the “explanatory” links may not be prominent enough). I welcome any recommendations.
Hi @Shanda keep up the great work! I think it would be great to develop this into a manuscript (with the accompanying figure of course). If you and your team are interested in further collaboration, I’d be happy to join the effort.
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