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Communication Dans Un Congrès Année : 2023

Computing and Visualizing Agro-Meteorological Parameters based on an Observational Weather Knowledge Graph

Résumé

Linked-data principles are more and more adopted to integrate and publish semantically described open data using W3C standards resulting in a large amount of available resources [7]. In particular, meteorological sensor data have been uplifted into public RDF graphs, such as WeKG-MF which offers access to a large set of meteorological variables described through spatial and temporal dimensions. Nevertheless, these resources include huge numbers of raw observations that are tedious to be explored and reused by lay users. In this paper, we leverage WeKG-MF to compute important agro-meteorological parameters and views with SPARQL queries. As a result, we deployed a LOD platform as a web application to allow users to navigate, consume and produce linked datasets of agro-meterological parameters calculated on-the-fly.
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hal-04230234 , version 1 (05-10-2023)

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Nadia Yacoubi Ayadi, Catherine Faron, Franck Michel, Fabien Gandon, Olivier Corby. Computing and Visualizing Agro-Meteorological Parameters based on an Observational Weather Knowledge Graph. WWW 2023 - ACM Web Conference 2023 - International World Wide Web Conference, Apr 2023, Austin (TX), United States. ⟨10.1145/3543873.3587357⟩. ⟨hal-04230234⟩
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