Title: Towards linked open government data in Canada

Authors: Enayat Rajabi

Addresses: Shannon School of Business, Cape Breton University, Sydney, Nova Scotia, Canada

Abstract: Governments are publishing enormous amounts of open data on the web every day in an effort to increase transparency and reusability. Linking data from multiple sources on the web enables the performance of advanced data analytics, which can lead to the development of valuable services and data products. However, Canada's open government data portals are isolated from one another and remain unlinked to other resources on the web. In this paper, we first expose the statistical data sets in Canadian provincial open data portals as Linked Data, and then integrate them using RDF Cube vocabulary, thereby making different open data portals available through a single search endpoint. We leverage Semantic Web Technologies to publish open data sets taken from two provincial portals (Nova Scotia and Alberta) as RDF (the Linked Data format), and to connect them to one another. The success of our approach illustrates its high potential for linking open government data sets across Canada, which will in turn enable greater data accessibility and improved search results.

Keywords: open data; RDF cube; linked data; Semantic Web.

DOI: 10.1504/IJMSO.2020.112802

International Journal of Metadata, Semantics and Ontologies, 2020 Vol.14 No.3, pp.209 - 217

Received: 13 May 2020
Accepted: 17 Sep 2020

Published online: 26 Jan 2021 *

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