See Yourself in Data: Building a framework for data-based community engagement events
Over the past decade, government data has been released through open data portals to improve efficiency, enable data-driven policy research and decision-making, increase transparency, and open a new avenue for citizen engagement with the public sector. While open data has been a boon for researchers, journalists, technologists, and entrepreneurs, benefits from their publication have not necessarily flowed down to community organizations and residents. As unequal access to open data threatens to widen information gaps, models of citizen participation in the data-driven city have not fully developed. This thesis synthesizes a general framework for community-based data events, based on insights from Public Participatory GIS, Data Feminism, Data Activism, and Data and Digital Justice. That framework is used to consider open data awareness- and literacy-raising events in Pittsburgh and Los Angeles. Compared to these two cases, the framework holds as a guide for meaningful considerations that future events may take into account.