Big Data in the Humanities

Published by Tyne Sumner on

At a time when concepts of bigness, fairness, infrastructure and scale are at the forefront of discussions around data-driven research in the Humanities, Arts and Social Sciences, the HASS DEVL project sought to gather a group of interdisciplinary researchers, data scientists and eResearch specialists to ask: What do we mean by ‘big data’ in the context of HASS? The recent ‘Big Data in the Humanities’ symposium at the Australian National University in Canberra on October 17th also presented an opportunity to explore the future successes that can be harnessed for HASS by working more collaboratively across platforms, data sets, projects and collecting institutions. 

Across the day the participants also considered how we can achieve ethical and sustainable practices around the collection and use of large HASS data sets and how we can best enable researchers in the field to share their data with others. 

Some key findings and topics of focus included the definitional issue of ‘bigness’ when it comes to Humanities research, with many noting that the volume of data used by researchers in HASS does not necessarily relate to the impact (and value proposition) of the outputs created. 

Axel Bruns, Ingrid Mason and Shawn Ross spoke of the need for us to critically assess the structure of data sets in HASS insofar as big data sets are generally regulated, however, smaller datasets tend to live by their own rules. Additionally, the group discussed the scope for the standardisation of workflows from GLAM through a national body in order to build better data and understanding. 

The day’s conversations made it clear that the concerns around data in HASS are universal and that, increasingly, we need to investigate and look at the ideas presented by those working at the intersection of data-driven and traditional methods. This surfaced in a talk by Hamish Maxwell-Stewart who spoke of the reticence of history researchers to embrace new technologies, particularly around the close reading of texts and the nuance of history. 

Have a look through the many excellent, thought-provoking tweets at #bigdatahumanities for more of the day’s conversation.