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TheyBuyForYou platform and knowledge graph: Expanding horizons in public procurement with open linked data

Abstract

Public procurement is a large market affecting almost every organisation and individual; therefore, governments need to ensure its efficiency, transparency, and accountability, while creating healthy, competitive, and vibrant economies. In this context, open data initiatives and integration of data from multiple sources across national borders could transform the procurement market by such as lowering the barriers of entry for smaller suppliers and encouraging healthier competition, in particular by enabling cross-border bids. Increasingly more open data is published in the public sector; however, these are created and maintained in siloes and are not straightforward to reuse or maintain because of technical heterogeneity, lack of quality, insufficient metadata, or missing links to related domains. To this end, we developed an open linked data platform, called TheyBuyForYou, consisting of a set of modular APIs and ontologies to publish, curate, integrate, analyse, and visualise an EU-wide, cross-border, and cross-lingual procurement knowledge graph. We developed advanced tools and services on top of the knowledge graph for anomaly detection, cross-lingual document search, and data storytelling. This article describes the TheyBuyForYou platform and knowledge graph, reports their adoption by different stakeholders and challenges and experiences we went through while creating them, and demonstrates the usefulness of Semantic Web and Linked Data technologies for enhancing public procurement.
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Category

Academic article

Client

  • EC/H2020 / 780247

Language

English

Author(s)

Affiliation

  • OsloMet - Oslo Metropolitan University
  • Technical University of Madrid
  • SINTEF Digital / Sustainable Communication Technologies
  • University of Southampton
  • Josef Stefan Institute
  • United Kingdom
  • King's College London

Year

2022

Published in

Semantic Web Journal

ISSN

1570-0844

Publisher

IOS Press

Volume

13

Issue

2

Page(s)

265 - 291

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