Open Data Settings: A Conceptual Framework Explored through the Map Room Project

Abstract

In recent years, researchers have sought more effective ways of making data open, for purposes of accountability, engagement, and reuse. Often, such efforts focus on making existing data sets available to broad audiences. The expression data set itself suggests something discrete, complete, and easily transferable. But data are none of those things. In this paper, we argue that open data projects could benefit from a more contextual understanding of what open means. Instead of focusing on open data sets, researchers can seek to create and understand open data settings: contexts in which things of public significance can be presented as evidence. We share our experiences creating and analyzing open data settings for the Map Room Project, a research through design initiative that establishes local spaces for collaborative data exploration and mapping. Our contribution is to offer a conceptual framework through which researchers, as well as designers, might think about the openness of data settings. This framework emerged from our situational analysis of comparative empirical case studies. In Map Rooms, we found that open can mean accessible, inclusive, or indeterminate. Three practices of contextualization, which we call configuring, convening, and claim-making, shape these dimensions of openness by defining all of the following: where data can work, who is empowered to use them, and what can count as data.