A minimal ontology pattern for life cycle assessment data

Krzysztof Janowicz; Adila Alfa 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

A minimal ontology pattern for life cycle assessment data

Krzysztof Janowicz, Adila Alfa 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

Department of Computer Science

Research output: Contribution to journal › Conference article › peer-review

6 Citations (Scopus)

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 language	English
Journal	CEUR Workshop Proceedings
Volume	1461
Publication status	Published - 2015
Event	6th Workshop on Ontology and Semantic Web Patterns, WOP 2015 - Bethlehem, United States Duration: 11 Oct 2015 → …

Cite this

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title = "A minimal ontology pattern for life cycle assessment data",

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.",

author = "Krzysztof Janowicz and Krisnadhi, {Adila Alfa} and Yingjie Hu and Sangwon Suh and Weidema, {Bo Pedersen} and Beatriz Rivela and Johan Tivander and Meyer, {David E.} and Gary Berg-Cross and Pascal Hitzler and Wesley Ingwersen and Brandon Kuczenski and Charles Vardeman and Yiting Ju and Michelle Cheatham",

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T1 - A minimal ontology pattern for life cycle assessment data

AU - Janowicz, Krzysztof

AU - Krisnadhi, Adila Alfa

AU - Hu, Yingjie

AU - Suh, Sangwon

AU - Weidema, Bo Pedersen

AU - Rivela, Beatriz

AU - Tivander, Johan

AU - Meyer, David E.

AU - Berg-Cross, Gary

AU - Hitzler, Pascal

AU - Ingwersen, Wesley

AU - Kuczenski, Brandon

AU - Vardeman, Charles

AU - Ju, Yiting

AU - Cheatham, Michelle

PY - 2015

Y1 - 2015

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84949818206&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:84949818206

SN - 1613-0073

VL - 1461

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

T2 - 6th Workshop on Ontology and Semantic Web Patterns, WOP 2015

Y2 - 11 October 2015

ER -

A minimal ontology pattern for life cycle assessment data

Abstract

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