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A minimal ontology pattern for life cycle assessment data

  • Krzysztof Janowicz
  • , Adila A. Krisnadhi
  • , Yingjie Hu
  • , Sangwon Suh
  • , Bo Pedersen Weidema
  • , Beatriz Rivela
  • , Johan Tivander
  • , David E. Meyer
  • , Gary Berg-Cross
  • , Pascal Hitzler
  • , Wesley Ingwersen
  • , Brandon Kuczenski
  • , Charles Vardeman
  • , Yiting Ju
  • , Michelle Cheatham
  • University of California at Santa Barbara
  • Wright State University
  • Aalborg University
  • InViable
  • Chalmers
  • United States Environmental Protection Agency
  • SOCoP
  • University of Notre Dame

Research output: Contribution to journalConference articlepeer-review

11 Scopus citations

Abstract

Life Cycle Assessment (LCA) studies the environmental impact of products taking into account their entire life-span and production chain. This requires gathering data from a variety of heterogeneous sources into a Life Cycle Inventory (LCI). LCI preparation involves the integration of observations and engineering models with reference data and literature results from around the world, from different domains, and at varying levels of granularity. Existing LCA data formats only address syntactic interoperability, thereby ignoring semantics. This leads to a variety of challenges, e.g., difficulties in reproducing assessments published in the literature. In this work, we present an ontology pattern that specifies key aspects of LCA/LCI data models, namely the notions of ows, activities, agents, and products, as well as their properties.

Original languageEnglish
JournalCEUR Workshop Proceedings
Volume1461
StatePublished - 2015
Event6th Workshop on Ontology and Semantic Web Patterns, WOP 2015 - Bethlehem, United States
Duration: Oct 11 2015 → …

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