Next Article in Journal
Identifying Influential Nodes in Complex Networks Based on Local Effective Distance
Previous Article in Journal
Barriers Faced by Women in Software Development Projects
Open AccessArticle

Kadaster Knowledge Graph: Beyond the Fifth Star of Open Data

1
Faculty of Geo-Information Science and Earth Observation, University of Twente, 7514 AE Enschede, The Netherlands
2
Behavioral, Management and Social Sciences, University of Twente, 7522 NH Enschede, The Netherlands
3
Kadaster Dataplatform, Kadaster, 7311 KZ Apeldoorn, The Netherlands
4
Knowledge Representation and Reasoning Group, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
*
Author to whom correspondence should be addressed.
Information 2019, 10(10), 310; https://doi.org/10.3390/info10100310
Received: 23 August 2019 / Revised: 19 September 2019 / Accepted: 26 September 2019 / Published: 9 October 2019
(This article belongs to the Special Issue Geo Information and Knowledge Graphs)
After more than a decade, the supply-driven approach to publishing public (open) data has resulted in an ever-growing number of data silos. Hundreds of thousands of datasets have been catalogued and can be accessed at data portals at different administrative levels. However, usually, users do not think in terms of datasets when they search for information. Instead, they are interested in information that is most likely scattered across several datasets. In the world of proprietary in-company data, organizations invest heavily in connecting data in knowledge graphs and/or store data in data lakes with the intention of having an integrated view of the data for analysis. With the rise of machine learning, it is a common belief that governments can improve their services, for example, by allowing citizens to get answers related to government information from virtual assistants like Alexa or Siri. To provide high-quality answers, these systems need to be fed with knowledge graphs. In this paper, we share our experience of constructing and using the first open government knowledge graph in the Netherlands. Based on the developed demonstrators, we elaborate on the value of having such a graph and demonstrate its use in the context of improved data browsing, multicriteria analysis for urban planning, and the development of location-aware chat bots.
Keywords: linked data; knowledge graph; semantic enrichment; location-aware chat bots; governmental open data linked data; knowledge graph; semantic enrichment; location-aware chat bots; governmental open data
MDPI and ACS Style

Ronzhin, S.; Folmer, E.; Maria, P.; Brattinga, M.; Beek, W.; Lemmens, R.; van’t Veer, R. Kadaster Knowledge Graph: Beyond the Fifth Star of Open Data. Information 2019, 10, 310.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop