header

Improving Discoverability of Open Government Data with Rich Metadata Descriptions Using Semantic Government Vocabulary

26 Pages Posted: 18 Dec 2018 First Look: Accepted

See all articles by Petr Kremen

Petr Kremen

Czech Technical University - Faculty of Electrical Engineering

Martin Necasky

Charles University in Prague - Faculty of Mathematics and Physics

Abstract

The descriptive metadata gathered by open data catalogs are often simple key-value pairs that describe provenance information, but not concepts from the domain of the described dataset. Search engines relying on such metadata cannot make use of semantic connections among datasets. In this paper, we present a Semantic Government Vocabulary that is used for creating rich annotations of Open Government Data, allowing to find their mutual interconnections, as well as document their meaning in the machine readable form. We discuss how the Semantic Government Vocabulary is layered based on the different ontological types of terms occurring in the Open Government Data. Next, we show how the vocabularies can be used to annotate Open Government Data on different levels of detail and how to formalize the whole stack in the Web Ontology Language. We evaluate feasibility and usability of our approach using a study in the elections domain.

Keywords: Linked Data, Open Data, Ontology, Data Catalog, Dataset Discovery

Suggested Citation

Kremen, Petr and Necasky, Martin, Improving Discoverability of Open Government Data with Rich Metadata Descriptions Using Semantic Government Vocabulary (December 18, 2018). Available at SSRN: https://ssrn.com/abstract=3303148 or http://dx.doi.org/10.2139/ssrn.3303148

Petr Kremen (Contact Author)

Czech Technical University - Faculty of Electrical Engineering ( email )

Prague, 166 27
Czech Republic

Martin Necasky

Charles University in Prague - Faculty of Mathematics and Physics ( email )

Sokolovska 83
Prague, 186 75
Czech Republic

Register to save articles to
your library

Register

Paper statistics

Abstract Views
325
Downloads
40