Enabling Spatio-Temporal Search in Open Data

Neumaier, Sebastian and Polleres, Axel ORCID: https://orcid.org/0000-0001-5670-1146 (2018) Enabling Spatio-Temporal Search in Open Data. Working Papers on Information Systems, Information Business and Operations, 01/2018. Department für Informationsverarbeitung und Prozessmanagement, WU Vienna University of Economics and Business, Vienna. ISSN 2518-6809

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Intuitively, most datasets found on governmental Open Data portals are organized by spatio-temporal criteria, that is, single datasets provide data for a certain region, valid for a certain time period. Likewise, for many use cases (such as, for instance, data journalism and fact checking) a pre-dominant need is to scope down the relevant datasets to a particular period or region. Rich spatio-temporal annotations are therefore a crucial need to enable semantic search for (and across) Open Data portals along those dimensions, yet -- to the best of our knowledge -- no working solution exists. To this end, in the present paper we (i) present a scalable approach to construct a spatio-temporal knowledge graph that hierarchically structures geographical as well as temporal entities, (ii) annotate a large corpus of tabular datasets from open data portals with entities from this knowledge graph, and (iii) enable structured, spatio-temporal search and querying over Open Data catalogs, both via a search interface as well as via a SPARQL endpoint, available at http://data.wu.ac.at/odgraphsearch/

Item Type: Paper
Keywords: open data, spatio-temporal labelling, spatio-temporal knowledge graph
Divisions: Departments > Informationsverarbeitung u Prozessmanag. > Informationswirtschaft > Polleres
Version of the Document: Submitted
Variance from Published Version: Typographical
Depositing User: Sebastian Neumaier
Date Deposited: 07 Jan 2019 11:55
Last Modified: 24 Aug 2020 11:18
Related URLs:
URI: https://epub.wu.ac.at/id/eprint/6764

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