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Article

GeoLOD: A Spatial Linked Data Catalog and Recommender

Department of Geography, University of the Aegean, GR-811 00 Mytilene, Greece
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Author to whom correspondence should be addressed.
Current address: Department of Geography, University Hill, GR-811 00 Mytilene, Greece.
Academic Editor: Min Chen
Big Data Cogn. Comput. 2021, 5(2), 17; https://doi.org/10.3390/bdcc5020017
Received: 31 January 2021 / Revised: 2 April 2021 / Accepted: 15 April 2021 / Published: 19 April 2021
(This article belongs to the Special Issue Semantic Web Technology and Recommender Systems)
The increasing availability of linked data poses new challenges for the identification and retrieval of the most appropriate data sources that meet user needs. Recent dataset catalogs and recommenders provide advanced methods that facilitate linked data search, but none exploits the spatial characteristics of datasets. In this paper, we present GeoLOD, a web catalog of spatial datasets and classes and a recommender for spatial datasets and classes possibly relevant for link discovery processes. GeoLOD Catalog parses, maintains and generates metadata about datasets and classes provided by SPARQL endpoints that contain georeferenced point instances. It offers text and map-based search functionality and dataset descriptions in GeoVoID, a spatial dataset metadata template that extends VoID. GeoLOD Recommender pre-computes and maintains, for all identified spatial classes in the Web of Data (WoD), ranked lists of classes relevant for link discovery. In addition, the on-the-fly Recommender allows users to define an uncatalogued SPARQL endpoint, a GeoJSON or a Shapefile and get class recommendations in real time. Furthermore, generated recommendations can be automatically exported in SILK and LIMES configuration files in order to be used for a link discovery task. In the results, we provide statistics about the status and potential connectivity of spatial datasets in the WoD, we assess the applicability of the recommender, and we present the outcome of a system usability study. GeoLOD is the first catalog that targets both linked data experts and geographic information systems professionals, exploits geographical characteristics of datasets and provides an exhaustive list of WoD spatial datasets and classes along with class recommendations for link discovery. View Full-Text
Keywords: linked data; spatial datasets; data catalog; dataset recommender linked data; spatial datasets; data catalog; dataset recommender
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MDPI and ACS Style

Kopsachilis, V.; Vaitis, M. GeoLOD: A Spatial Linked Data Catalog and Recommender. Big Data Cogn. Comput. 2021, 5, 17. https://doi.org/10.3390/bdcc5020017

AMA Style

Kopsachilis V, Vaitis M. GeoLOD: A Spatial Linked Data Catalog and Recommender. Big Data and Cognitive Computing. 2021; 5(2):17. https://doi.org/10.3390/bdcc5020017

Chicago/Turabian Style

Kopsachilis, Vasilis, and Michail Vaitis. 2021. "GeoLOD: A Spatial Linked Data Catalog and Recommender" Big Data and Cognitive Computing 5, no. 2: 17. https://doi.org/10.3390/bdcc5020017

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