The IEEE International Conference on Big Data in July will feature a workshop on Big Data in digital humanities scholarship–which its organizers refer to as Big Humanities.
It’s hard to tell what big data means these days. Is 30,000 British people enough? How about 50,000 species in a biodiversity database? Or 2600 diaries from an archaeological dig? What about ORBIS? There are only 2000 or so official route segments, but given all the permutations, there are trillions of possible “routes”. The simple fact is that big data in the big data world is very big (Twitter is up to 400 million tweets a day at last count) and that means you need to deal with the sum total of human writing or all the anime ever produced to even hope to claim that kind of big data status.
But I’m starting to think “big data” is just another way of saying “distant reading” or “macroanalysis” or “global perspective”. If that’s the case, then the you-must-be-this-tall to get into big data isn’t really that much of a restriction at all, because these techniques and methods can be deployed for quite small data. The real identifying trait is that all of these represent a computational approach to newly available data that are infeasible to analyze individually and which require some processing methods to transform from relatively unstructured data to aggregated, categorized, and/or quantified data.