This evening I attended an excellent talk by Lorraine Dalston, a History of Science scholar.
Many great ideas, starting from the very current ideas of big data and digital humanities. The concept I found most resonating was the idea of distinct paces: empirical discoveries happen at quick pace, the pace of publishable results, maybe of grants and theses. At a slower pace is that of theories, the questions and themes that I suppose underlie careers and national priorities (though these were not examples proposed by Dalston). And at a much slower pace is the time of different approaches and methods of science. It seems from this that we are currently in the era of data collection and retrieval, according to Dalston the Sciences of Archives – and she traced this era of cataloguing information from mid 19th century efforts to catalogue stars and Latin inscriptions upto our current efforts to build large databases, of genomes and so on. This has echoes of Paul Nurse’s statement that “Biologists prefer to deal in particulars and details; they like catalogues and descriptions, such as lists of species in particular habitats, the number of hairs on a beetle leg, or determining the sequences of genes.”
This also resonated a lot with my experience, particularly when trying to connect with colleagues in natural sciences and humanities. When trying to build links, talk usually goes towards how computer science can help them build databases, or retrieve and visualize information. Computer science is seen just as one more tool to follow the same approach to science, in Dalston’s words the Sciences of Archives. And yet, my hope in my interdisciplinary attempts is to explore how computational thinking might actually change the approach to discovery, somehow – from moving from the contribution of empirical results to a more synergetic way of getting broader insights.
Dalston used some terms to talk about other approaches to scientific endeavours, such as critique and organization, and I would have liked her to have explored these more. Interestingly, she pointed out the weakness in organizing academic studies (embodied rather facetiously on the names and groupings of buildings on University campuses) by subject matter. I asked her what is the alternative – how else could the whole range of academia be organized – and while she said that Archiving could be one “building”, it wasn’t clear to me what the other buildings would be. Some possibilities might be theory formation (where all the machine learning crowd as well as historians and philosophers could sit), and imagination, where the creative writers and engineers and so on could hang out and design or brave new future.
Anyway, it is wonderful to have an opportunity to end the day by attending a thought-provoking lecture by a great speaker – one of the things that makes working at a University worthwhile.