Version 1
: Received: 30 January 2024 / Approved: 30 January 2024 / Online: 31 January 2024 (02:53:28 CET)
How to cite:
Osorno-Covarrubias, F.J.; Couturier, S.; Martínez-Zazueta, I.; López-Quiroz, P.; Ferrari, L.; Suárez Lastra, M. Cartographic Journals in the Era of Artificial Intelligence: Terra Digitalis and the Emergence of Peer-Reviewed FAIR Geospatial Data. Preprints2024, 2024012139. https://doi.org/10.20944/preprints202401.2139.v1
Osorno-Covarrubias, F.J.; Couturier, S.; Martínez-Zazueta, I.; López-Quiroz, P.; Ferrari, L.; Suárez Lastra, M. Cartographic Journals in the Era of Artificial Intelligence: Terra Digitalis and the Emergence of Peer-Reviewed FAIR Geospatial Data. Preprints 2024, 2024012139. https://doi.org/10.20944/preprints202401.2139.v1
Osorno-Covarrubias, F.J.; Couturier, S.; Martínez-Zazueta, I.; López-Quiroz, P.; Ferrari, L.; Suárez Lastra, M. Cartographic Journals in the Era of Artificial Intelligence: Terra Digitalis and the Emergence of Peer-Reviewed FAIR Geospatial Data. Preprints2024, 2024012139. https://doi.org/10.20944/preprints202401.2139.v1
APA Style
Osorno-Covarrubias, F.J., Couturier, S., Martínez-Zazueta, I., López-Quiroz, P., Ferrari, L., & Suárez Lastra, M. (2024). Cartographic Journals in the Era of Artificial Intelligence: <em>Terra Digitalis</em> and the Emergence of Peer-Reviewed FAIR Geospatial Data. Preprints. https://doi.org/10.20944/preprints202401.2139.v1
Chicago/Turabian Style
Osorno-Covarrubias, F.J., Luca Ferrari and Manuel Suárez Lastra. 2024 "Cartographic Journals in the Era of Artificial Intelligence: <em>Terra Digitalis</em> and the Emergence of Peer-Reviewed FAIR Geospatial Data" Preprints. https://doi.org/10.20944/preprints202401.2139.v1
Abstract
The ongoing expansion in volume, velocity and variety of geospatial data has stimulated the development of artificial intelligence applications and associated online cartographic visualizations. In this context, the cartographic communication through peer-reviewed media evolved to incorporate Findability, Accessibility, Interoperability and Re-usability (FAIR) principles. In this paper, we review the functionalities proposed by current international peer-reviewed media for accessing, exploring and re-using geospatial data, and situate them on a diagram conceived for peer-reviewed cartography in the artificial intelligence era. We then present an overview of the cartographic infrastructure and workflow currently available in the Terra Digitalis journal for the online publication of massive spatiotemporal data. This free and opensource based solution allows a smooth integration, from data submission to final peer reviewed publication, of dynamic, interactive 2D and 3D maps. As a proof of concept, we present two maps derived from massive spatiotemporal data, related, respectively, to a climate numerical model (raster data) and a bike sharing system’s origin-destination dataset (vector data). We argue that the combination of technologies used in the journal provides an efficient and low-cost solution, unmatched by other publication media, to boost the accessibility and FAIR principles for geospatial big data.
Keywords
geospatial big data; FAIR; OJS; digital earth; OGC web services; data sharing and re-using
Subject
Environmental and Earth Sciences, Geography
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
