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Open AccessArticle

Assessment and Benchmarking of Spatially Enabled RDF Stores for the Next Generation of Spatial Data Infrastructure

1
Department of Physical Geography and Ecosystem Science, Lund University, 223 62 Lund, Sweden
2
ICOS Carbon Portal, Lund University, 223 62 Lund, Sweden
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(7), 310; https://doi.org/10.3390/ijgi8070310
Received: 27 May 2019 / Revised: 23 June 2019 / Accepted: 12 July 2019 / Published: 19 July 2019
(This article belongs to the Special Issue SDI and the Revolutionary Technological Trends)
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Abstract

Geospatial information is indispensable for various real-world applications and is thus a prominent part of today’s data science landscape. Geospatial data is primarily maintained and disseminated through spatial data infrastructures (SDIs). However, current SDIs are facing challenges in terms of data integration and semantic heterogeneity because of their partially siloed data organization. In this context, linked data provides a promising means to unravel these challenges, and it is seen as one of the key factors moving SDIs toward the next generation. In this study, we investigate the technical environment of the support for geospatial linked data by assessing and benchmarking some popular and well-known spatially enabled RDF stores (RDF4J, GeoSPARQL-Jena, Virtuoso, Stardog, and GraphDB), with a focus on GeoSPARQL compliance and query performance. The tests were performed in two different scenarios. In the first scenario, geospatial data forms a part of a large-scale data infrastructure and is integrated with other types of data. In this scenario, we used ICOS Carbon Portal’s metadata—a real-world Earth Science linked data infrastructure. In the second scenario, we benchmarked the RDF stores in a dedicated SDI environment that contains purely geospatial data, and we used geospatial datasets with both crowd-sourced and authoritative data (the same test data used in a previous benchmark study, the Geographica benchmark). The assessment and benchmarking results demonstrate that the GeoSPARQL compliance of the RDF stores has encouragingly advanced in the last several years. The query performances are generally acceptable, and spatial indexing is imperative when handling a large number of geospatial objects. Nevertheless, query correctness remains a challenge for cross-database interoperability. In conclusion, the results indicate that the spatial capacity of the RDF stores has become increasingly mature, which could benefit the development of future SDIs. View Full-Text
Keywords: linked data benchmark; RDF stores; geospatial data; GeoSPARQL; spatial data infrastructure linked data benchmark; RDF stores; geospatial data; GeoSPARQL; spatial data infrastructure
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Supplementary material

  • Externally hosted supplementary file 1
    Doi: https://doi.org/10.18160/9D9W-WT2P
    Description: Test data from ICOS CP.
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Huang, W.; Raza, S.A.; Mirzov, O.; Harrie, L. Assessment and Benchmarking of Spatially Enabled RDF Stores for the Next Generation of Spatial Data Infrastructure. ISPRS Int. J. Geo-Inf. 2019, 8, 310.

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