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Deeply integrating linked data with geographic information systems / Gengchen Mai in Transactions in GIS, vol 23 n° 3 (June 2019)  

Public [article]  inTransactions in GIS > vol 23 n° 3 (June 2019) . - pp 579 - 600 Titre : Deeply integrating linked data with geographic information systems Type de document : Article/Communication Auteurs : Gengchen Mai, Auteur ; Krzysztof Janowicz, Auteur ; Bo Yan, Auteur ; Simon Scheider, Auteur Année de publication : 2019 Article en page(s) : pp 579 - 600 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] connecteur logiciel [Termes IGN] graphe [Termes IGN] ontologie [Termes IGN] réseau sémantique [Termes IGN] système d'information géographique [Termes IGN] web des données Résumé : (Auteur) The realization that knowledge often forms a densely interconnected graph has fueled the development of graph databases, Web‐scale knowledge graphs and query languages for them, novel visualization and query paradigms, as well as new machine learning methods tailored to graphs as data structures. One such example is the densely connected and global Linked Data cloud that contains billions of statements about numerous domains, including life science and geography. While Linked Data has found its way into everyday applications such as search engines and question answering systems, there is a growing disconnect between the classical ways in which Geographic Information Systems (GIS) are still used today and the open‐ended, exploratory approaches used to retrieve and consume data from knowledge graphs such as Linked Data. In this work, we conceptualize and prototypically implement a Linked Data connector framework as a set of toolboxes for Esri's ArcGIS to close this gap and enable the retrieval, integration, and analysis of Linked Data from within GIS. We discuss how to connect to Linked Data endpoints, how to use ontologies to probe data and derive appropriate GIS representations on the fly, how to make use of reasoning, how to derive data that are ready for spatial analysis out of RDF triples, and, most importantly, how to utilize the link structure of Linked Data to enable analysis. The proposed Linked Data connector framework can also be regarded as the first step toward a guided geographic question answering system over geographic knowledge graphs. Numéro de notice : A2019-255 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12538 Date de publication en ligne : 11/06/2019 En ligne : https://doi.org/10.1111/tgis.12538 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93013 [article]