Participatory data stewardship: A framework for involving people in the use of data 

How to Use

This report is prepared primarily with business leaders and policymakers in mind, but community science practitioners will find plenty of applicable guidance as it pertains to using data for individual and collective benefit (see “How to read this report” for dedicated excerpts). Of greatest applicability will be efforts involving big data and/or AI. 

Advancing community priorities through community science projects involves an enhanced level of public participation and ownership over data governance. Use Table 1: Participatory Mechanisms to clarify what people can expect when it comes to your project’s data governance. Will project participants simply be informed of how data is being used (“Informing”), or will participants’ input be sought to the maximum extent possible (“Collaborating”)? 

Explore the participatory mechanisms, methods, and activities associated with each level of involvement and their associated case studies. While some techniques may be familiar to community science practitioners (community consultation, one-off public deliberations), examples from the business, government, and legal sectors may provide creative inspiration for new directions (deliberative consensus conference model, data cooperatives).