GeoTriples: Transforming geospatial data into RDF graphs using R2RML and RML mappings

Kyzirakos, Kostis; Savva, Dimitrianos; Vlachopoulos, Ioannis; Vasileiou, Alexandros; Karalis, Nikolaos; Koubarakis, Manolis; Manegold, Stefan

doi:10.1016/j.websem.2018.08.003

Cited by 79 publications

(37 citation statements)

References 16 publications

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“…This section describes the mapping of spatial data into RDF aimed at providing LOD for Brussels. Although there are proposals to map geospatial data to RDF automatically [12,13], based on R2RML and RML, in the remainder, it will become clear that the problem is too complex to be solved just using automated tools. Further, as explained above, RML is not a standard, and a design decision was to work with standard tools.…”

Section: Mapping Spatial Datamentioning

confidence: 99%

Mapping Spatiotemporal Data to RDF: A SPARQL Endpoint for Brussels

Vaisman

Chentout²

2019

IJGI

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This paper describes how a platform for publishing and querying linked open data for the Brussels Capital region in Belgium is built. Data are provided as relational tables or XML documents and are mapped into the RDF data model using R2RML, a standard language that allows defining customized mappings from relational databases to RDF datasets. In this work, data are spatiotemporal in nature; therefore, R2RML must be adapted to allow producing spatiotemporal Linked Open Data.Data generated in this way are used to populate a SPARQL endpoint, where queries are submitted and the result can be displayed on a map. This endpoint is implemented using Strabon, a spatiotemporal RDF triple store built by extending the RDF store Sesame. The first part of the paper describes how R2RML is adapted to allow producing spatial RDF data and to support XML data sources. These techniques are then used to map data about cultural events and public transport in Brussels into RDF. Spatial data are stored in the form of stRDF triples, the format required by Strabon. In addition, the endpoint is enriched with external data obtained from the Linked Open Data Cloud, from sites like DBpedia, Geonames, and LinkedGeoData, to provide context for analysis. The second part of the paper shows, through a comprehensive set of the spatial extension to SPARQL (stSPARQL) queries, how the endpoint can be exploited.

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Section: Mapping Spatial Datamentioning

confidence: 99%

Mapping Spatiotemporal Data to RDF: A SPARQL Endpoint for Brussels

Vaisman

Chentout²

2019

IJGI

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“…This tool is based on Geometry2RDF and uses the WGS84 vocabulary and several geometric types of GeoSPARQL. Kyzirakos, Vlachopoulos, Savva, Manegold, and Koubarakis () describe GeoTriples, a tool that allows the transformation of geospatial data stored in spatially enabled relational databases and raw files. This tool is implemented as an extension to the D2RQ platform (https://d2rq.org/) and uses GeoSPARQL and stSPARQL as the target vocabulary.…”

Section: Background and Related Workmentioning

confidence: 99%

A framework for connecting two interoperability universes: OGC Web Feature Services and Linked Data

Vilches‐Blázquez

Saavedra

2018

Transactions in GIS

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Diverse studies have shown that about 80% of all available data are related to a spatial location. Most of these geospatial data are available as structured and semi-structured datasets, and often use distinct data models, are encoded using ad-hoc vocabularies, and sometimes are being published in non-standard formats. Hence, these data are isolated within silos and cannot be shared and integrated across organizations and communities. Spatial Data Infrastructures (SDIs) have emerged and contributed to significantly enhance data discovery and accessibility based on OGC (Open Geospatial Consortium) Web services. However, finding, accessing, and using data disseminated through SDIs are still difficult for non-expert users.Overcoming the current geospatial data challenges involves adopting the best practices to expose, share, and integrate data on the Web, that is, Linked Data. In this article, we have developed a framework for generating, enriching, and exploiting geospatial Linked Data from multiple and heterogeneous geospatial data sources. This proposal allows connecting two interoperability universes (SDIs, more specifically Web Feature Services, WFS, and Semantic Web technologies), which is evaluated through a study case in the (geo)biodiversity domain. | 23VILCHES-BLÁZQUEZ and SAAVEDRA

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“…Furthermore, it requires no underlying SPARQL engine, and it inherently supports parallelization and streaming data sources (e.g. compared to SPARQL-Generate [5] and GeoTriples [4]). In addition to these, the variables vector enables the RDF generation method to establish mappings to data "to-be-generated", and they are not explicitly available in the source (e.g., the MBR or the WKT of a geometry).…”

Section: Rdf Generation and Data Integrationmentioning

confidence: 99%

Increasing Maritime Situation Awareness via Trajectory Detection, Enrichment and Recognition of Events

Vouros

Vlachou

Santipantakis

et al. 2018

Web and Wireless Geographical Information Systems

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The research presented in this paper aims to show the deployment and use of advanced technologies towards processing surveillance data for the detection of events, contributing to maritime situation awareness via trajectories' detection, synopses generation and semantic enrichment of trajectories. We first introduce the context of the maritime domain and then the main principles of the big data architecture developed so far within the European funded H2020 datAcron project. From the integration of large maritime trajectory datasets, to the generation of synopses and the detection of events, the main functions of the datAcron architecture are developed and discussed. The potential for detection and forecasting of complex events at sea is illustrated by preliminary experimental results.

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GeoTriples: Transforming geospatial data into RDF graphs using R2RML and RML mappings

Cited by 79 publications

References 16 publications

Mapping Spatiotemporal Data to RDF: A SPARQL Endpoint for Brussels

Mapping Spatiotemporal Data to RDF: A SPARQL Endpoint for Brussels

A framework for connecting two interoperability universes: OGC Web Feature Services and Linked Data

Increasing Maritime Situation Awareness via Trajectory Detection, Enrichment and Recognition of Events

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