Openness in science is hard to disagree with as an abstract principle, but what exactly do we mean when we call for science to be made open – or more open than before? In this talk, I introduce and unpack the many different goals, strategies, products, values, and assumptions of the broad open science movement. It can be hard to make sense of all the different ways people are calling for science to be made more open: free-to-download publication PDFs, datasets re-usable by anyone, documented workflows or lab notebooks to support reproducibility, open source scientific software packages, publicly-funded computing infrastructure, public peer reviewing platforms, citizen science research projects, alternative metrics for publications and researchers, diversity and inclusion initiatives, and better public-facing science communication. Instead of pursuing openness simply for openness’ sake or focusing too closely on any single specific problem or solution, I call for scientists to think broadly about why openness is a value for science in society and who will benefit from making science more open in different ways.
R. Stuart Geiger
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.