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/ / Series: Working Papers on Information Systems, Information Business and Operations
| Identifer | oai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:6764 |
| Date | 04 April 2018 |
| Creators | Neumaier, Sebastian, Polleres, Axel |
| Publisher | Department fĂĽr Informationsverarbeitung und Prozessmanagement, WU Vienna University of Economics and Business |
| Source Sets | Wirtschaftsuniversität Wien |
| Language | English |
| Detected Language | English |
| Type | Paper, NonPeerReviewed |
| Format | application/pdf |
| Rights | Creative Commons: Attribution 4.0 International (CC BY 4.0) |
| Relation | http://data.wu.ac.at/odgraphsearch/, http://epub.wu.ac.at/6764/ |
Page generated in 0.0014 seconds