Geo-Semantic Labelling of Open Data. SEMANTiCS 2018-14th International Conference on Semantic Systems

Publikation: Wissenschaftliche FachzeitschriftOriginalbeitrag in FachzeitschriftBegutachtung

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In the past years Open Data has become a trend among governments to increase transparency and public engagement by opening up
national, regional, and local datasets. However, while many of these datasets come in semi-structured file formats, they use di
schemata and lack geo-references or semantically meaningful links and descriptions of the corresponding geo-entities. We aim to
address this by detecting and establishing links to geo-entities in the datasets found in Open Data catalogs and their respective
metadata descriptions and link them to a knowledge graph of geo-entities. This knowledge graph does not yet readily exist, though,
or at least, not a single one: so, we integrate and interlink several datasets to construct our (extensible) base geo-entities knowledge
graph: (i) the openly available geospatial data repository GeoNames, (ii) the map service OpenStreetMap, (iii) country-specific sets
of postal codes, and (iv) the European Union's classification system NUTS. As a second step, this base knowledge graph is used
to add semantic labels to the open datasets, i.e., we heuristically disambiguate the geo-entities in CSV columns using the context
of the labels and the hierarchical graph structure of our base knowledge graph. Finally, in order to interact with and retrieve the
content, we index the datasets and provide a demo user interface. Currently we indexed resources from four Open Data portals, and
allow search queries for geo-entities as well as full-text matches at
FachzeitschriftProcedia Computer Science
PublikationsstatusVeröffentlicht - 2018