Nicholas John Car’s research while affiliated with Simplot Australia Pty. Ltd. and other places

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Publications (5)


Figure 1: Examples of DGGS based on the mapping of the faces of Platonic solids to the surface model of the Earth, after Figure C.2 from [15]
Implementation and Compliance Benchmarking of a DGGS-enabled, GeoSPARQL-aware Triplestore
  • Conference Paper
  • Full-text available

June 2022

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179 Reads

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1 Citation

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Nicholas J Car

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We set out to determine the feasibility of implementing Discrete Global Grid System (DGGS) representations of geometry support in a GeoSPARQL-enabled triplestore, and test the GeoSPARQL compliance for it. The implementation is a variant of Apache Jena's existing GeoSPARQL support. Compliance is tested using an adapted implementation of the GeoSPARQL Compliance Benchmark testing system developed previously to test for GeoSPARQL 1.0 compliance. The benchmark results confirm that a majority of the functions which were set out to be implemented in the course of this paper were implemented correctly and points out possible future work for full compliance.

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GeoSPARQL 1.1: Motivations, Details and Applications of the Decadal Update to the Most Important Geospatial LOD Standard

February 2022

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289 Reads

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18 Citations

ISPRS International Journal of Geo-Information

In 2012 the Open Geospatial Consortium published GeoSPARQL defining ``an RDF/OWL ontology for [spatial] information'', ``SPARQL extension functions'' for performing spatial operations on RDF data and ``RIF rules'' defining entailments to be drawn from graph pattern matching. In the 8+ years since its publication, GeoSPARQL has become the most important spatial Semantic Web standard, as judged by references to it in other Semantic Web standards and its wide use for Semantic Web data. An update to GeoSPARQL was proposed in 2019 to deliver a version 1.1 with a charter to: handle outstanding change requests and source new ones from the user community and to "better present" the standard, that is to better link all the standard's parts and better document \& exemplify elements. Expected updates included new geometry representations, alignments to other ontologies, handling of new spatial referencing systems, and new artifact presentation. This paper describes motivating change requests and actual resultant updates in the candidate version 1.1 of the standard alongside reference implementations and usage examples. We also describe the theory behind particular updates, initial implementations of many parts of the standard, and our expectations for GeoSPARQL 1.1's use.


Figure 1. GeoSPARQL 1.1 ontology overview diagram including classes new properties. After GeoSPARQL 1.1's own overview diagram
Figure 3. Geometries of the Australian federal electoral district of Brisbane. GeoSPARQL 1.0 contained only the property geo:hasGeometry to indicate a geo:Geometry instance for a geo:Feature instance. GeoSPARQL 1.1 contains the specialised properties of geo:hasCentroid & geo:hasBoundingBox which can indicate geometries with particular roles. See Listing 2 for an RDF representation of this figure's elements.
Figure 7. The SPARQL Unicorn QGIS Plugin extended with support for FeatureCollections and GeometryCollections as defined in GeoSPARQL 1.1
GeoSPARQL 1.1: An Almost Decadal Update to the Most Important Geospatial LOD Standard

November 2021

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147 Reads

In 2012 the Open Geospatial Consortium published GeoSPARQL defining “an RDF/OWL ontology for [spatial] information”, “SPARQL extension functions” for performing spatial operations on RDF data and “RIF rules” defining entailments to be drawn from graph pattern matching. In the 8+ years since its publication, GeoSPARQL has become the most important spatial Semantic Web standard, as judged by references to it in other Semantic Web standards and its wide use for Semantic Web data. An update to GeoSPARQL was proposed in 2019 to deliver a version 1.1 with a charter to: handle outstanding change requests and source new ones from the user community and to “better present” the standard, that is to better link all the standard’s parts and better document & exemplify elements. Expected updates included new geometry representations, alignments to other ontologies, handling of new spatial referencing systems, and new artifact presentation. In this paper, we describe motivating change requests and actual resultant updates in the candidate version 1.1 of the standard alongside reference implementations and usage examples. We also describe the theory behind particular updates, initial implementations of many parts of the standard, and our expectations for GeoSPARQL 1.1’s use.


Fig. 1. Excerpt of the GeoSPARQL 1.1 ontology including one example feature
GeoSPARQL 1.1: An Almost Decadal Update to the Most Important Geospatial LOD Standard

In 2012 the Open Geospatial Consortium published GeoSPARQL defining “SPARQL extension functions”, “RIF rules” and “an RDF/OWL ontology for [spatial] information”. In the 8+ years since its publication, GeoSPARQL has become the most important spatial Semantic Web standard, as judged by references to it in other Semantic Web standards and its wide use in Semantic Web data. An update to GeoSPARQL was proposed in 2019 to deliver 1.1 in 2021 with a charter to: handle outstanding change requests and source new ones from the user community and to “better present” the standard, that is to better link all the standard’s parts and better document & exemplify elements. Expected updates included alignments to other ontologies, handling of new spatial referencing systems, new geometry representations, and new artifact presentation. In this paper, we will discuss the submitted change requests and resulting updates to the standard. We will also discuss the theory behind updates and our expectations for GeoSPARQL 1.1’s use. Published at: https://ceur-ws.org/Vol-2977/paper4.pdf


OGC Benefits of Representing Spatial Data Using Semantic and Graph Technologies

October 2020

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236 Reads

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11 Citations

Joseph Abhayaratna

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Linda van den Brink

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Nicholas Car

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[...]

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http://docs.ogc.org/wp/19-078r1/19-078r1.html The purpose of this document is to outline the benefits of representing geospatial data using semantic and graph technologies. It aims to provide motivation for OGC members to consider the publication of geospatial data using these technologies.

Citations (3)


... While GeoSPARQL 1.1 [Car et al., 2023] introduces a generic format for DGGS geometry serialization , it does not yet provide the ability to interpret specific cell IDs according to the various DGGS frameworks available. Furthermore, testing this implementation in RDF databases is still in its early stages [Habgood et al., 2022]. Few graph databases support DGGS-based indexing, such as those using S2 and H3 (e.g., NebulaGraphDB), but these are not RDF-based or GeoSPARQL-compliant [Jovanovik et al., 2021]. ...

Reference:

The S2 Hierarchical Discrete Global Grid as a Nexus for Data Representation, Integration, and Querying Across Geospatial Knowledge Graphs
Implementation and Compliance Benchmarking of a DGGS-enabled, GeoSPARQL-aware Triplestore

... As the state-of-the-art section has shown, a significant body of knowledge on ontology development in the AEC industry already exists, and best practices suggest reusing those ontologies. Since a global standard for Linked Building Data does not exist yet, we stick to ontologies commonly used in the W3C Linked Building Data Community Group, being BOT [24], BPO [25], GeoSPARQL, OMG and FOG [26,27], OPM [28], NEO [29], and a simple OWL representation of IndoorGML. Figure 4 shows how the reused ontologies in the FireBIM stack align. ...

GeoSPARQL 1.1: Motivations, Details and Applications of the Decadal Update to the Most Important Geospatial LOD Standard

ISPRS International Journal of Geo-Information

... Due to the anchoring of references in predefined tables, relational modelling does not have the flexibility and openness required to create a Digital Twin. In contrast, with the help of an ontology, semantic modelling has advantages through graph technologies, such as flexibility and freedom for modelling, openness and transparency for reproducibility, and standardisation through ontologies and (geo-)vocabularies [118]. Semantics allows possible flexibility in the connection of archaeological and geometrical content and the possible application of a (changeable) set of rules that connects geometry and archaeology and provides the basis for conclusions. ...

OGC Benefits of Representing Spatial Data Using Semantic and Graph Technologies