Data versus method (data needs heads!)

I have been thinking a little more about the relationship between eResearch and Digital Humanities of late, partly because it is the subject of my talk at the Digital Humanities conference in Hamburg in July, and I want to do justice to what I see as a critical topic that hasn’t been mainly well handled in the past.

There are unique challenges in Australia in that the eResearch agenda is quite established, but the digital humanities still need to be. This has caused quite a lot of conflict in the past in that many in societies have seen themselves as being locked out of the eResearch agenda by Science, and many in eResearch have viewed the humanities as high-risk and being ill-prepared to lead significant infrastructural developments in their disciplines.

There is some truth in both these assertions. Still, I do see a way forward. eResearch is primarily an infrastructural movement (led mainly by science) and thus often needs a theoretical base and set of arguments to communicate its worth within humanities research convincingly. But if there is a theoretical base or conceptual core to the eResearch agenda, then is its data: data management, data reuse, and data interoperability? But there is a problem here: the data collected by agencies within the eResearch agenda is often only collected and only a little else. Data is an idea (not a thing), and statements can never speak for themselves; pictures (data) must be attached to the arguments in scholarly research (humanities research is interpretive, not positivist).

This is where the digital humanities can lead. If eResearch is building a data commons (i.e. through agencies such as the Australian National Data Service), then the digital humanities are building a methodological common. A method is vital to the research process; if we develop many ways, we can use lots of data. So, the digital humanities need to be strengthened to rise to the challenges; otherwise, we have lots of data (and lots of ideas) with no heads to put them in. And if data doesn’t have a leader, then the data doesn’t exist (i.e. data is interpretative and doesn’t live outside of that interpretation). And yes, I am not such a relativist to believe that there is no world outside of performance, but data is not of this world. It is merely someone’s interpretation of the world.

A ‘methodological commons’ developed by Professor Willard McCarty et al.



One response to “Data versus method (data needs heads!)”

Leave a Reply