Degraded Data in Nonprofit Homebrew Databases

Researchers have characterized contexts for information work that are supported by often-messy ecosystems of information systems. Although important infrastructures for information work, little is known about how these less-than-perfect systems affect the data that is managed. We present results of an interview study of these information ecosystems in the nonprofit context. We find that the quality of data is often systematically degraded in five ways: incomplete data, out-of-date data, “bulk” data, “anecdotal" numbers, and “garbage" data. These forms of degraded data result from informants having other, legitimate priorities in their work—each more important than managing data. We discuss how degraded data often has little effect on organizations’ existing data practices, but forecloses alternate possible uses moving forward. Finally, we reflect on how we might be able to address these challenges while still respecting the legitimacy of choosing other priorities and explore what it would mean to design for a data imagination.