Building Capacity
and
Disrupting Data Science
Jeri E. Wieringa
Overview
2008
BA in Philosophy and English.
Wanted to continue but in a more publicly engaged way.
2009-2011
MAR from Yale Divinity. Discovered Public Humanities and Digital Public Humanities.
2011-2019
PhD in History at George Mason University.
Research Assistant with the Roy Rosenzweig Center for History and New Media.
2019
Completed and defended my digital dissertation, a computational study of 13,000 SDA periodicals
2015-2016
Joined the Mason Libraries as the Digital Publishing Production Lead
2020-
Assistant Professor of Digital Humanities and Social Theory of Religion at University of Alabama
What is DH?
the critical application of computational methods and tools within humanities research AND the critical development of computational systems informed by the research priorities of the humanities.
Key Priorities for DH
Data Science and
Machine Learning
Infrastructure
Education
How do we develop methods and tools that emphasize data (and any resulting model) as complex, contingent, and contextual?
How do we bring those values into data science?
Data Science and Machine Learning
Infrastructure
What are the resources needed to support digital projects throughout their lifecycle?
How do those become institutionalized, as they are for print?
How do we make collaboration a key aspect of education in the digital humanities?
How do we develop research agendas that can support multiple projects?
Can there be a collaborative dissertation in the humanities?
Education
Assistant Director
- Creating context for these areas by building relationships and collaborations, both internally and externally
- Encouraging projects that emphasize complexity, context, and contingency while engaging with data science
- Work toward shared understandings of the problems and creating space for developing creative solutions
Minimal
By Jeri Wieringa
