Editors’ Note: Mia Ridge has written extensive notes from the inaugural Astralasian Association for Digital Humanities meeting in March 2012: Day 1, Day 2, Day 3. The following is a selection from Day 2.
Keynote panel, ‘Big Digital Humanities?’
Day 2 was introduced by Craig Bellamy, and began with a keynote panel with Peter Robinson, Harold Short and John Unsworth, chaired by Hugh Craig. [See also Snurb’s liveblogs for Robinson, Short and Unsworth.] Robinson asked ‘what constitutes success for the digital humanities?’ and further, what does the visible successes of digital humanities mask? He said it’s harder for scholars to do high quality research with digital methods now than it was 20 years ago. But the answer isn’t more digital humanists, it’s having the ingredients to allow anyone to build bridges… He called for a new generation of tools and methods to support the scholarship that people want to do: ‘It should be as easy to make a digital edition (of a document/book) as it is to make a Facebook page’, it shouldn’t require collaboration with a digital humanist. To allow data made by one person to be made available to others, all digital scholarship should be made available under a Creative Commons licence (publishers can’t publish it now if it’s under a non-commercial licence), and digital humanities data should be structured and enriched with metadata and made available for re-use with other tools. The model for sustainability depends on anyone and everyone being able to access data.
Harold Short talked about big (or at least unescapable) data and the ‘Svensson challenge’ – rather than trying to work out how to take advantage of infrastructure created by and for the sciences, use your imagination to figure out what’s needed for the arts and humanities. He called for a focus on infrastructure and content rather than ‘data’.
John Unsworth reminded us that digital humanities is a certain kind of work in the humanities that uses computational methods as its research methods. It’s not just using digital materials, though it does require large collections of data – it also requires a sense of how how the tools work.