Enabling Spatio-Temporal Search in Open Data

Publikation: Working/Discussion PaperWU Working Paper

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Abstract

Intuitively, most datasets found in Open Data are organised by spatio-temporal scope, that is, single datasets provide data for a certain region, valid for a certain time period. 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. Therefore, we argue that spatio-temporal search is a crucial need for Open Data portals and across Open Data portals, yet - to the best of our knowledge - no working solution exists. We argue that - just like for for regular Web search - knowledge graphs can be helpful to significantly improve search: in fact, the ingredients for a public knowledge graph of geographic entities as well as time periods and events exist already on the Web of Data, although they have not yet been integrated and applied - in a principled manner - to the use case of Open Data search. In the present paper we aim at doing just that: 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, (iii) enable structured, spatio-temporal search over Open Data catalogs through our spatio-temporal knowledge graph, both via a search interface as well as via a SPARQL endpoint, available at data.wu.ac.at/odgraphsearch/
OriginalspracheEnglisch
ErscheinungsortVienna
HerausgeberDepartment für Informationsverarbeitung und Prozessmanagement, WU Vienna University of Economics and Business
PublikationsstatusVeröffentlicht - 4 Apr. 2018

Publikationsreihe

NameWorking Papers on Information Systems, Information Business and Operations
Nr.01/2018
ISSN (Druck)2518-6809

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