Transparent Integration and Sharing of Life Cycle Sustainability Data with Provenance

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Abstract

Life Cycle Sustainability Analysis (LCSA) studies the complex processes describing product life cycles and their impact on the environment, economy, and society. Effective and transparent sustainability assessment requires access to data from a variety of heterogeneous sources across countries, scientific and ecsonomic sectors, and institutions. Moreover, given their important role for governments and policymakers, the results of many different steps of this analysis should be made freely available, alongside the information about how they have been computed in order to ensure accountability. In this paper, we describe how Semantic Web technologies in general and PROV-O in particular, are used to enable transparent sharing and integration of datasets for LCSA. We describe the challenges we encountered in helping a community of domain experts with no prior expertise in Semantic Web technologies to fully overcome the limitations of their current practice in integrating and sharing open data. This resulted in the first nucleus of an open data repository of information about global production. Furthermore, we describe how we enable domain experts to track the provenance of particular pieces of information that are crucial in higher-level analysis.
Original languageEnglish
Title of host publicationThe Semantic Web – ISWC 2020 - 19th International Semantic Web Conference, 2020, Proceedings
EditorsJeff Z. Pan, Valentina Tamma, Claudia d’Amato, Krzysztof Janowicz, Bo Fu, Axel Polleres, Oshani Seneviratne, Lalana Kagal
Number of pages17
PublisherSpringer
Publication date2020
Pages378-394
ISBN (Print)9783030624651
DOIs
Publication statusPublished - 2020
Event19th International Semantic Web Conference, ISWC 2020 - Athens, Greece
Duration: 2 Nov 20206 Nov 2020

Conference

Conference19th International Semantic Web Conference, ISWC 2020
Country/TerritoryGreece
CityAthens
Period02/11/202006/11/2020
SeriesLecture Notes in Computer Science
Volume12507
ISSN0302-9743

Keywords

  • Open data
  • Provenance
  • Sustainability analysis

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