Geographic Data Science



Singleton, Alex and Arribas-Bel, Daniel ORCID: 0000-0002-6274-1619
(2019) Geographic Data Science. Geographical Analysis: an international journal of theoretical geography, Specia. pp. 1-15.

This is the latest version of this item.

Access the full-text of this item by clicking on the Open Access link.
[img] Text
Singleton_et_al-2019-Geographical_Analysis.pdf - Published version

Download (265kB) | Preview

Abstract

It is widely acknowledged that the emergence of “Big Data” is having a profound and often controversial impact on the production of knowledge. In this context, Data Science has developed as an interdisciplinary approach that turns such “Big Data” into information. This article argues for the positive role that Geography can have on Data Science when being applied to spatially explicit problems; and inversely, makes the case that there is much that Geography and Geographical Analysis could learn from Data Science. We propose a deeper integration through an ambitious research agenda, including systems engineering, new methodological development, and work toward addressing some acute challenges around epistemology. We argue that such issues must be resolved in order to realize a Geographic Data Science, and that such goal would be a desirable one.

Item Type: Article
Depositing User: Symplectic Admin
Date Deposited: 21 Jun 2019 07:13
Last Modified: 19 Jan 2023 00:39
DOI: 10.1111/gean.12194
Open Access URL: https://onlinelibrary.wiley.com/doi/full/10.1111/g...
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3046829

Available Versions of this Item