I discuss four data-intensive activist projects as "successor systems," discussing the political and epistemological implications of using data to advance activist projects. The concept of successor systems extends Harding (1987) and Haraway’s (1988) call for feminist “successor sciences” – ways of knowing that critically blend objectivity with situatedness – to the field of “Big Data.” I argue that successor systems involve a different form of data-intensive knowledge production, in which counterpublic collectives (Fraser, 1990) reflectively deploy algorithmic routines to build “a better account of the world” (Haraway, 579). I discuss four data-intensive activist projects as successor systems, discussing political and epistemological implications of such tactics. These successor systems have much to teach scholars and practitioners of “Big Data,” giving concrete and theoretical alternatives to the more dominant practices in academia and industry.
Former BIDS Ethnographer Stuart Geiger is now a faculty member at the University of California, San Diego, jointly appointed in the Department of Communication and the Halıcıoğlu Data Science Institute. At BIDS, as an ethnographer of science and technology, he studied the infrastructures and institutions that support the production of knowledge. He launched the Best Practices in Data Science discussion group in 2019, having been one of the original members of the MSDSE Data Science Studies Working Group. Previously, his work on Wikipedia focused on the community of volunteer editors who produce and maintain an open encyclopedia. He also studied distributed scientific research networks and projects, including the Long-Term Ecological Research Network and the Open Science Grid. In Wikipedia and scientific research, he studied topics including newcomer socialization, community governance, specialization and professionalization, quality control and verification, cooperation and conflict, the roles of support staff and technicians, and diversity and inclusion. And, as these communities are made possible through software systems, he studied how the design of software tools and systems intersect with all of these issues. He received an undergraduate degree at UT Austin, and an MA in Communication, Culture, and Technology at Georgetown University, where he began empirically studying communities using qualitative and ethnographic methods. As part of receiving his PhD from the UC Berkeley School of Information, he worked with anthropologists, sociologists, psychologists, historians, organizational and management scholars, designers, and computer scientists.