Data sharing is an essential part of scientific research and collaboration and is a core principle of federally-funded research efforts, especially for large consortia (e.g. NIH BRAIN Initiative, NIH SPARC program, etc.). However, there are some issues around data sharing that can cause scientists to be hesitant to share their data. For example, many scientists receive research funding based on novel discoveries and innovations they make in their fields. Unregulated, public data sharing can allow other researchers to potentially "scoop" the findings of these scientists and disadvantage their chance at future funding. Furthermore, scientists may not want to share their data with others to avoid losing potential intellectual property (IP) claims on their discoveries. In an ideal world, all scientists and researchers would behave fairly towards their peers, but this is not a practical approach.
Data use agreements (DUAs) are a major way to protect the investment of money, samples, time, and other resources spent by researchers. Some data may be under embargo for a certain time, meaning that it’s submitted to public repositories but not available for download. Typically, if researchers want to access embargoed data, they can sign a DUA when requesting access from the data owners. The DUA establishes who is permitted to use and receive the embargoed data and also details the permitted uses and disclosures of such information by the recipient. Furthermore, the DUA usually demands that the recipients:
- not use or disclose the information other than as permitted by the DUA or as otherwise required by law,
- use appropriate safeguards to prevent uses or disclosures of the information that are inconsistent with the DUA,
- report to the data owner any uses or disclosures that are in violation of the DUA once they are aware of them,
- ensure that anyone to whom they provide the data agree to the same restrictions and conditions
In conclusion, DUAs allow for the free exchange of research data and information while protecting the investment and efforts spent by the scientists who generated the data.