Work

Smart data, information geographies and intelligent data services

Year: 2025

Type: article

Abstract: We review the supplementation and partial replacement of survey-driven investigations to today's dynamic, geographically-enabled data ecosystems and the role of smart data within them. This raises critical challenges in the smart data paradigm, arising from data ownership, fragmented digital personas, coverage biases and algorithmic risks. In response, we propose a work-flow model for “smart data services”, prioritizing academic sector-wide licensing agreements, cross-source data linkage and assessment of data provenance. This also requires use of trusted research environments and standardized preprocessing procedures, culminating in the production and delivery of “research-ready data”. We describe how such data can mitigate ecological fallacies, bridging theoretical and practical advances in information geography and leveraging smart data to enhance social science's relevance and inclusivity in the digital age. • Reviews the transformation in data-led social science investigation. • Outlines the growth of smart data services which facilitate this step change. • Presents an agenda for the development of social science data research.

Source: Information Geography

DOI: 10.1016/j.infgeo.2025.100013

Authors: Paul Longley, Min Chen

Institutions: Nanjing Normal University, University College London

Language: English

Topic: Data Analysis and Archiving

Subfield: Sociology and Political Science

Field: Social Sciences

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $2,200

Funders: Economic and Social Research Council, Humanities and Social Science Fund of Ministry of Education of China