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Data Studies
Multiple Roles

Addressing data divides introduces new ways of creating and sharing knowledge in the humanities. It also provides a corrective for data initiatives by emphasizing human and social concerns.

Data Literacy
Pan-campus approaches to data
Qualitative and quantitative methods

Through digital humanities and campus program, I drive efforts to promote data literacy in the humanities and to ensure that initiatives pay attention to the human and social impacts of data. I push a view that representation, interpretation, and human and social engagements play out at every stage of the data life cycle; that data science is both quantitative and qualitative; that data at scale has powerful value for developing knowledge but equal danger as nuance is lost and individuality is eliminated; that even the benefits of scale can be applied in ways that can be dangerous; that, from a humanistic perspective, responsible work with data must foreground human and social concerns.

Key aspects of this work include participation in the Provost's Data Science Steering Committee and the development of humanities data literacy micro-credentialing programs.

Data science is both quantitative and qualitative--all the way down