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The Democratization of Data: How the Internet is Shaping the Work of Data Intermediaries

Abstract

This report looks at the efforts of nonprofit data intermediaries to provide the institutions and individuals working in low-income urban neighborhoods with access to neighborhood-level data resources and the ability to use them to effect positive social change. The rise of data intermediaries has been propelled by the rise and diffusion of advanced information and computing technologies, including the Internet and Geographic Information Systems (GIS). In the decade or so since data intermediaries first arose on the scene, they have overwhelmingly adopted the Internet as their primary means for disseminating data resources, creating online “neighborhood information systems” that can be freely accessed by the broad public. In this study, the author investigates the development of data intermediaries within the community development and community building fields and looks at how they are harnessing the Internet and GIS toward these ends.

The work of data intermediaries fits within the broader action frameworks of community capacity building and community technology. Operating at the intersection of these agendas, the activities of data intermediaries primarily address what has been called the “organizational divide,” or the gap between community organizations’ potential use for digital technologies and their ability to access and use these technologies. As community groups have taken on greater responsibilities in providing services and public goods to urban constituencies, they have become more professionalized and have demanded access to data and data analysis tools such as GIS. Despite the utility of these resources for community groups, they are resource-poor and often lack both access to these tools and the capacity required to apply them to their planning, service delivery and advocacy activities.

The ability of data intermediaries to “democratize data”—defined as enabling community actors to access data and to use it to build community capacity to effect social change—is influenced by the availability of financial resources, the local political context and the local organizational culture. One of the challenges faced by data intermediaries is the attitude toward data on the part of the communities they seek to serve. These are often the same communities that data has historically been used against through practices such as redlining. Because of this challenge, the author hypothesizes that trust is an important bridging factor that allows data intermediaries to attain their goal of democratizing data.

Through a comparative case study analysis of data intermediaries in Oakland and New Orleans, the author looks at the practice of democratizing data and the constraints and opportunities faced by data intermediaries. In doing so, she pays particular attention to the ways in which each organization perceives the variable of trust and acts to foster trust between itself, its online data resources and its target audiences. She finds that the process of democratizing data via the Internet is underwritten by trust-building efforts on the part of data intermediaries. In each case, trust-building is an important component of the data intermediary’s work.

Each organization, however, has developed different methods of incorporating trust-building into their programs, methods which resonate with its overall organizing logic. Each provides a sort of model by which data intermediaries shape information and information technologies in ways that make them useful for the communities they seek to serve. In describing these models, the author characterizes the New Orleans group as design-based and the Oakland group as partnership-based. These cases illustrate a palette of methods by which data intermediaries can build trust and show the diversity of forms of practice within the field.

Activities engaged in by data intermediaries to build trust include collaborative program development, outreach and networking, iterative site design and user testing, culturally-relevant and community-specific site content, and online and in-person training modules. Through these methods, data intermediaries mitigate the negative unintended consequences involved in bringing expert spatial data technologies to marginalized communities and remake information technologies into community technologies.

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