GeoSPARQL+: Syntax, Semantics and System for Integrated Querying of Graph, Raster and Vector Data -- Technical Report
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Abstract (arXiv)
We introduce an approach to semantically represent and query raster data in a Semantic Web graph. We extend the GeoSPARQL vocabulary and query language to support raster data as a new type of geospatial data. We define new filter functions and illustrate our approach using several use cases on real-world data sets. Finally, we describe a prototypical implementation and validate the feasibility of our approach.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 10 Sep 2020.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 1.
3 papers.
- 2021GeoVectors: A Linked Open Corpus of OpenStreetMap Embeddings on World Scalecited by 12
- 2024The S2 Hierarchical Discrete Global Grid as a Nexus for Data Representation, Integration, and Querying Across Geospatial Knowledge Graphscited by 1
- 2022Region-Based Merging of Open-Domain Terminological Knowledgecited by 0
- 2024The S2 Hierarchical Discrete Global Grid as a Nexus for Data Representation, Integration, and Querying Across Geospatial Knowledge Graphs18 Oct 2024
- 2022Region-Based Merging of Open-Domain Terminological Knowledge5 May 2022
- 2021GeoVectors: A Linked Open Corpus of OpenStreetMap Embeddings on World Scale30 Aug 2021