Do bridges dream of water pollutants? Towards DreamsKG, a knowledge graph to make digital access for sustainable environmental assessment come true

Dario Garigliotti, Johannes Bjerva, Finn Årup Nielsen, Annika Butzbach, Ivar Lyhne, Lone Kørnøv, Katja Hose

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

2 Citations (Scopus)
14 Downloads (Pure)

Abstract

An environmental assessment (EA) report describes and assesses the environmental impact of a series of activities involved in the development of a project. As such, EA is a key tool for sustainability. Improving information access to EA reporting is a billion-euro untapped business opportunity to build an engaging, efficient digital experience for EA. We aim to become a landmark initiative in making this experience come true, by transforming the traditional manual assessment of numerous heterogeneous reports by experts into a computer-assisted approach. Specifically, a knowledge graph that represents and stores facts about EA practice allows for what it is so far only accessible manually to become machine-readable, and by this, to enable downstream information access services. This paper describes the ongoing process of building DreamsKG, a knowledge graph that stores relevant data- and expert-driven EA reporting and practicing in Denmark. Representation of cause-effect relations in EA and integration of Sustainable Developmental Goals (SDGs) are among its prominent features.
Original languageEnglish
Title of host publicationACM Web Conference 2023 - Proceedings of the Comopanion of the : 2023 World Wide Web Conference
Number of pages7
PublisherAssociation for Computing Machinery
Publication date30 Apr 2023
Pages724-730
ISBN (Electronic)978-1-4503-9416-1
DOIs
Publication statusPublished - 30 Apr 2023
EventThe ACM Web Conference 2023 - Austin, United States
Duration: 30 Apr 20234 May 2023

Conference

ConferenceThe ACM Web Conference 2023
Country/TerritoryUnited States
CityAustin
Period30/04/202304/05/2023

Keywords

  • Cause-effect relations
  • Knowledge graph construction
  • Knowledge graphs
  • Sustainability

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