A lightweight approach to explore, enrich and use data with a geospatial dimension with semantic web technologies

ABSTRACT

The concept of "location" provides one a useful dimension to explore, align, combine, and analyze data. Though one can rely on bespoke GIS systems to conduct their data analyses, we aim to investigate the feasibility of using Semantic Web technologies to leverage the exploration and enrichment of data in CSV files with the vast amount of geographic and geospatial data that are available on the Linked Data Web. In this paper, we propose a lightweight method and set of tools for: uplift - transforming non-RDF resources into RDF documents; creating links between RDF datasets; client-side processing of geospatial functions; and downlift - transforming (enriched) RDF documents back into a non-RDF format. With this approach, people who wish to avail of the spatial dimension in data can do so from their client (e.g., in a browser) without the need to rely on bespoke technology. This could be of great utility for decision makers and scholars, amongst others. We applied our approach on datasets that are hosted on the Irish open data portal, and combined it with authoritative geospatial data made available by Ordnance Survey Ireland (OSi). Albeit aware that our approach cannot compete with specialist tools, we do demonstrate its feasibility. Though currently conducted for enriching datasets hosted on the Irish open data portal, future work will look into broader governance and provenance aspects of geospatial data enriched dataset management.

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Index Terms

• Information systems

  • Information systems applications

    • Spatial-temporal systems

      • Geographic information systems

  • World Wide Web

    • Web data description languages

      • Semantic web description languages

        • Resource Description Framework (RDF)