2019/04/04 by Alex Singleton, Daniel Arribas‐Bel · 115 citations
Engineering · Medicine · Social Sciences · #Big data #Computer science #Context (archaeology) #Data mining #Data science #Data-Driven Disease Surveillance #Engineering #Engineering ethics #Epistemology #Geographic Information Systems Studies #Geography #Human Mobility and Location-Based Analysis #Knowledge management #Knowledge production #Order (exchange) #Science and engineering #Sociology #Work (physics)
paper · pdf · doi:10.1111/gean.12194
published in Geographical Analysis 53(1), 61-75 (Wiley)
openalex publication_date 2019/04/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/25
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.