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FAIR geovisualizations: definitions, challenges, and the road ahead

2021/10/28 by Auriol Degbelo
Computer Science · Decision Sciences · Social Sciences · #Data visualization #Fair share #Geographic Information Systems Studies #Geovisualization #Open data #Open source #Research Data Management Practices #Scientific Computing and Data Management #Visualization #Work (physics) #cs.HC #cs.IR

paper · pdf · doi:10.1080/13658816.2021.1983579

Article accepted for publication in the International Journal of Geographical Information Science

openalex publication_date 2021/10/28 · openalex created_date 2021/11/08 · arxiv created 2021/11/14 · arxiv updated 2021/11/16 · openalex updated_date 2026/08/05

Abstract

The availability of open data and of tools to create visualizations on top of these open datasets have led to an ever-growing amount of geovisualizations on the Web. There is thus an increasing need for techniques to make geovisualizations FAIR – Findable, Accessible, Interoperable, and Reusable. This article explores what it would mean for a geovisualization to be FAIR, presents relevant approaches to FAIR geovisualizations and lists open research questions on the road towards FAIR geovisualizations. The discussion is done using three complementary perspectives: the computer, which stores geovisualizations digitally; the analyst, who uses them for sensemaking; and the developer, who creates them. The framework for FAIR geovisualizations proposed, and the open questions identified are relevant to researchers working on findable, accessible, interoperable, and reusable online visualizations of geographic information.

Citations