Play 16 - Develop a readymade workflow for employing and maintaining data sharing agreements

#extractivism #misuse #capacity #collaboration #legal

When developing data sharing agreements, understanding what a working relationship looks like before and during the #collaboration is just as important as what is contained in the agreement itself. Data stewards can build out their own Partnership Protocol, a basic rubric for determining the validity of a new sharing partner. Questions to include in a protocol like this include:

In introductory or exploratory meetings, do you need to have a conversation about goals, purpose, and values, and how many of those need to align before sharing data?
Should formalizing the partnership require a vote, consensus, or other explicit form of decision making?

Upon determining the validity of a new partnership and setting up a data sharing agreement (ideally with legal counsel), data stewards can create a checklist within the Partnership Protocol to maintain the agreement. At scheduled intervals, data stewards can review this checklist to detail a partner’s compliance and uses of the data. The checklist can be derived from the language in the data sharing agreement, which may include questions regarding how the partner is sharing the data, how they are using it in research, or how and if they have credited the data’s source.

🌱 Each play stems from a takeaway from an case study, workshop, or other learning source.

Takeaway: Data sharing agreements are contracts. They don't build relationships, but rather maintain existing relationships.
While data sharing agreements are essential tools in #collaboration, they are only one aspect of a larger relationship or partnership. Especially with environmental data, there can be power asymmetries between the two data-sharing parties, such as community based organizations and university-affiliated researchers. These power asymmetries materialize as differing levels of #capacity, funding, access to legal resources, and incentives, which have disadvantaged smaller community-based organizations and led to data #misuse and extractive relationships. Power asymmetries don’t necessarily stall a collaboration, but they should prompt the two parties to align on the central purpose and goals of the data sharing and use. In other words, they need to be able to build a strong working relationship before sharing.

Source: Community Data Playbook (Full report)