Business rationale for linked data at governments: A case study at the netherlands' kadaster data platform

Erwin Folmer, Stanislav Ronzhin*, Jos Van Hillegersberg, Wouter Beek, Rob Lemmens

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Linked Data is an innovative approach for publishing heterogeneous data sources on the web. As such, it can transcend the traditional confines of separate databases, as well as the confines of separate institutions. At the same time, businesses and governmental organizations alike are trying to cope with ever-increasing quantities of heterogeneous data that must be used across multiple departments, manufacturing locations, and governmental bodies. Linked Data would, therefore, be a great technological solution for today's organizational problems. However, we observe that a serious gap exists between Linked Data research and business research. While Linked Data research is almost exclusively technologically oriented, the business research literature has not devoted much attention to the use of Linked Data solutions yet. In this paper, we seek to bridge this gap, by introducing a real-world use case where Linked Data technologies are applied in large-scale government settings. We argue in detail that Linked Data provides a major contribution to the business vision of a modern governmental institution based on the experience of the Netherlands' Cadastre Land Registry and Mapping Agency (Kadaster), so far, the largest implementation of Linked Data in the governments of the Netherlands.

Original languageEnglish
Article number9051837
Pages (from-to)70822-70835
Number of pages14
JournalIEEE Access
Volume8
Early online date31 Mar 2020
DOIs
Publication statusE-pub ahead of print - 31 Mar 2020

Keywords

  • data systems
  • Government
  • information management

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    Folmer, E., Ronzhin, S., Van Hillegersberg, J., Beek, W., & Lemmens, R. (2020). Business rationale for linked data at governments: A case study at the netherlands' kadaster data platform. IEEE Access, 8, 70822-70835. [9051837]. https://doi.org/10.1109/ACCESS.2020.2984691