Abstract
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.
Highlights
The Semantic Web aims at providing a common framework in order to allow data to be shared and reused across applications and to be consumed by machines rather than human beings
In light of the above, this paper addresses the problem of capturing data from different sources, e.g., relational databases, XML documents, web APIs, SPARQL endpoints, producing Resource Description Framework (RDF) data, and integrating and exposing such data in a spatially-enabled SPARQL endpoint
The paper studied the problem of capturing spatiotemporal data from different data sources, integrating these data, storing them in a geospatial RDF data store, and exposing the integrated data in a spatially-enabled SPARQL endpoint
Summary
The Semantic Web (a term coined by Tim Berners-Lee) aims at providing a common framework in order to allow data to be shared and reused across applications and to be consumed by machines rather than human beings. The paper provides an in-depth discussion and description of the deployment and querying of the spatial SPARQL endpoint, backed by the Strabon triple store, a geospatial database management system (DBMS) that supports the stRDF representation language (a spatiotemporal extension to RDF) and comes equipped with a spatial extension to SPARQL, called stSPARQL. (http://www.w3.org/TR/r2rml/) Since R2RML neither directly supports XML data sources, nor spatial data; the R2RML mapping language must be extended in order to tackle both issues, and this is discussed in the paper. It shows how this technique is applied to data provided by the partners in the project. The present paper substantially expands and updates such work, providing a full, detailed explanation of each step of the methodology and a comprehensive set of queries that shows the functionality and usefulness of the case study
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