On Saturday, November 9, Washington University in St. Louis hosted a lively (and successful?) THATCamp: THATCamp St. Louis, 2013. One of the first sessions combined two suggested topics: “Beginners in the Digital Humanities” and “Subject Librarian DH boot camp,” which I volunteered to co-facilitate with Twyla Gibson. I hope that discussing some of the broad outlines of digital humanities was helpful, but there was a lot to follow-up on. The thin list here leads to pages and resources with pointers to many, many more resources for exploring DH.
Overview of DH
In the “Beginners” session, we discussed some of the broad outlines of digital humanities: the dispute over “hack vs. yack”—the practical creation of tools and resources (especially scholarly digital editions) versus broad theoretical considerations. Within the “hack” camp of DH is another division—not less contentious, but with slightly differing aims and perspectives: scholars involved with scholarly editing (and “digital projects” more broadly) on the one hand, and scholars interested in text mining, on the other. The following are good resources for anyone getting started in DH:
- Patrik Svensson, “The Landscape of Digital Humanities“
- Lisa Spiro, “Getting Started in Digital Humanities“
- The CUNY Digital Humanities Resource Guide—exploding with links
TEI, XML, encoding
Not all XML that might be relevant for faculty members, archivists, librarians and others in cultural heritage organizations is necessarily DH, but certainly deserves mentioning, such as EAD (Encoded Archival Description) for encoding of finding aids, PREMIS for describing objects in a digital preservation environments, and many others! On the other hand, as prevalent as TEI (Text Encoding Initiative) is, it is is also not the only XML standard relevant to DH, as others have grown up out of it, such as the Charters Encoding Initiative (CEI) and EpiDoc, for Epigraphic Document Encoding.
- TEI: Text Encoding Initiative
- A very gentle introduction to the TEI markup language
- TEI Tools
- TEI By Example
- <oXygen/> XML Editor commercial XML editor, but economically priced and probably most widely-used
Text Mining
- Ted Underwood’s The Stone and the Shell blog on Where to start with text mining
- Steve Ramsay, Reading Machines: Toward an Algorithmic Imperative (theory, but also dealing with text mining)
- Drew Conway, Machine Learning for Hackers
- The Metadata Offer New Knowledge (MONK) project
—Andrew Rouner
