T164
The Potential Futures of Data Science: A Roundtable Intervention
Convenor:
Brian Beaton (California Polytechnic State University)
Stream:
Tracks
Location:
117a
Start time:
1 September, 2016 at 9:00
Session slots:
1

Short abstract:

This panel focuses on new and breaking STS research on data science. Panel participants will present research on data science's communication patterns, tools, styles of work, analytical habits, standards, visual strategies, professional ethics, and on data science research cultures.

Long abstract:

This panel will focus on new and breaking STS research on data science: the systematic process of creating, building, and structuring knowledge with data. Panel participants will present research on data science's communication patterns, tools, styles of work, analytical habits, standards, visual strategies, professional ethics, and on the social facets of data science research cultures. Each paper will be drawing on historical, philosophical, and social scientific methods. The larger goal of the panel is to advance critical understanding of data science among students and scholars in STS. Another goal is to continue building a coherent STS research agenda on data science. Because of data science's relative newness as a scientific profession, the research to be presented on this panel has the potential to advance data science as it formalizes: helping the profession to become an ethical, self-aware, and conscientious domain of expertise that more deeply understands the implications of how it produces and presents knowledge, and a profession that understands how its knowledge production practices are quietly changing notions of what counts as scientific evidence. This panel builds directly on a panel called "Debating Data Science" that was held at 4S 2015 in Denver. The 2015 panel focused on mapping potential obstacles to making data science researchable on STS terms. The 2015 panel also focused on debating what a broader STS research agenda on data science might look like. This panel will focus on how data science fits within larger shifts in scientific communications, computing, and consulting.