This week I will be one of the participants at a three-day workshop on “Knowledge Organization and Data Modeling in the Humanities” co-sponsored by the Centre for Digital Editions at the University of Würzburg and the Brown University Center for Digital Scholarship, and hosted by Brown. The workshop was organized by Julia Flanders (Brown University) and Fotis Jannidis (University of Würzburg) and is being supported through generous funding from the DFG/NEH Bilateral Digital Humanities Program.
The roster of other speakers at the event is top-notch and all the presentations promise to be engaging. For my part, I was asked to contibute to a more practically-oriented section on “Research Ontologies”—focusing on how data modeling happens in humanities projects—and also, to talk a little about the similarities and differences related to modeling data in a DH context versus a library one.
I’ll be speaking about the process we’re engaged in now here at MITH for developing the data models that underlie our transcriptions of materials for the Shelley-Godwin Archive. Data modeling is an immensely-important but largely under-discussed topic in digital humanities (it’s certainly under-represented in the published literature—though this conference is part of an effort to change that). Data modeling is part of the crucial “DH-specific” intellectual work of translating between the (often implicit) understandings that scholars have of the objects they study and the affordances of a particular digital technology (which might be a relational database or TEI XML or any number of things). For projects that are attempting to conform to standards and best practices, data modeling never begins from a blank slate. I’m particularly interested in the ways—social, conceptual, and technical—that we use to build (and hopefully share) data models for our projects within an ecology of “received ideas” in the form of something like the TEI Guidelines.
The workshop is intended to engage remote participants as well as those of us who will be in Providence this week. I strongly encourage interested members of MITH’s community to follow along on the web and via Twitter.