Big data and human geography

TLDR

Big data, characterized by high volume, velocity, variety, exhaustivity, resolution, indexicality, relationality, and flexibility, offers spatially and temporally referenced datasets that can enhance geographical understanding but also pose epistemological, methodological, and ethical challenges. Geographers must seize opportunities, address challenges, mitigate risks, and critically engage with big data to conduct robust studies. Failure to do so risks leaving geography behind as other disciplines exploit the data deluge.

Abstract

We are entering an era of big data – data sets that are characterised by high volume, velocity, variety, exhaustivity, resolution and indexicality, relationality and flexibility. Much of these data are spatially and temporally referenced and offer many possibilities for enhancing geographical understanding, including for post-positivist scholars. Big data also, however, poses a number of challenges and risks to geographic scholarship and raises a number of taxing epistemological, methodological and ethical questions. Geographers need to grasp the opportunities whilst at the same time tackling the challenges, ameliorating the risks and thinking critically about big data as well as conducting big data studies. Failing to do so could be quite costly as the discipline gets left behind as others leverage insights from the growing data deluge.