An Open Source Dataset and Ontology for Product Footprinting

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

Abstract

Product footprint describes the environmental impacts of a product system. To identify such impact, Life Cycle Assessment (LCA) takes into account the entire lifespan and production chain, from material extraction to final disposal or recycling. This requires gathering data from a variety of heterogeneous sources, but current access to those is limited and often expensive. The BONSAI project, instead, aims to build a shared resource where the community can contribute to data generation, validation, and management decisions. In particular, its first goal is to produce an open dataset and an open source toolchain capable of supporting LCA calculations. This will allow the science of lifecycle assessment to perform in a more transparent and more reproducible way, and will foster data integration and sharing. Linked Open Data and semantic technologies are a natural choice for achieving this goal. In this work, we present the first results of this effort: (1) the core of a comprehensive ontology for industrial ecology and associated relevant data; and (2) the first steps towards an RDF dataset and associated tools to incorporate several large LCA data sources.
Original languageEnglish
Title of host publication The Semantic Web: ESWC 2019 Satellite Events
Publication date2019
Publication statusPublished - 2019
Event16th International Semantic Web Conference, ESWC 2019 - Portorož, Slovenia
Duration: 2 Jun 20196 Jun 2019

Conference

Conference16th International Semantic Web Conference, ESWC 2019
CountrySlovenia
CityPortorož
Period02/06/201906/06/2019
SponsorElsevier, et al., QualiChain, Semantic Web Company, Siemens, STI International

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life cycle
industrial ecology
footprint
product
environmental impact
recycling
resource
science
calculation
material
project
decision

Cite this

@inproceedings{aaadef98e8e34da8983d7ff4ee31b9d9,
title = "An Open Source Dataset and Ontology for Product Footprinting",
abstract = "Product footprint describes the environmental impacts of a product system. To identify such impact, Life Cycle Assessment (LCA) takes into account the entire lifespan and production chain, from material extraction to final disposal or recycling. This requires gathering data from a variety of heterogeneous sources, but current access to those is limited and often expensive. The BONSAI project, instead, aims to build a shared resource where the community can contribute to data generation, validation, and management decisions. In particular, its first goal is to produce an open dataset and an open source toolchain capable of supporting LCA calculations. This will allow the science of lifecycle assessment to perform in a more transparent and more reproducible way, and will foster data integration and sharing. Linked Open Data and semantic technologies are a natural choice for achieving this goal. In this work, we present the first results of this effort: (1) the core of a comprehensive ontology for industrial ecology and associated relevant data; and (2) the first steps towards an RDF dataset and associated tools to incorporate several large LCA data sources.",
author = "Katja Hose and Matteo Lissandrini and Agneta Ghose and Weidema, {Bo Pedersen}",
year = "2019",
language = "English",
booktitle = "The Semantic Web: ESWC 2019 Satellite Events",

}

Hose, K, Lissandrini, M, Ghose, A & Weidema, BP 2019, An Open Source Dataset and Ontology for Product Footprinting. in The Semantic Web: ESWC 2019 Satellite Events. 16th International Semantic Web Conference, ESWC 2019, Portorož, Slovenia, 02/06/2019.

An Open Source Dataset and Ontology for Product Footprinting. / Hose, Katja; Lissandrini, Matteo; Ghose, Agneta; Weidema, Bo Pedersen.

The Semantic Web: ESWC 2019 Satellite Events. 2019.

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

TY - GEN

T1 - An Open Source Dataset and Ontology for Product Footprinting

AU - Hose, Katja

AU - Lissandrini, Matteo

AU - Ghose, Agneta

AU - Weidema, Bo Pedersen

PY - 2019

Y1 - 2019

N2 - Product footprint describes the environmental impacts of a product system. To identify such impact, Life Cycle Assessment (LCA) takes into account the entire lifespan and production chain, from material extraction to final disposal or recycling. This requires gathering data from a variety of heterogeneous sources, but current access to those is limited and often expensive. The BONSAI project, instead, aims to build a shared resource where the community can contribute to data generation, validation, and management decisions. In particular, its first goal is to produce an open dataset and an open source toolchain capable of supporting LCA calculations. This will allow the science of lifecycle assessment to perform in a more transparent and more reproducible way, and will foster data integration and sharing. Linked Open Data and semantic technologies are a natural choice for achieving this goal. In this work, we present the first results of this effort: (1) the core of a comprehensive ontology for industrial ecology and associated relevant data; and (2) the first steps towards an RDF dataset and associated tools to incorporate several large LCA data sources.

AB - Product footprint describes the environmental impacts of a product system. To identify such impact, Life Cycle Assessment (LCA) takes into account the entire lifespan and production chain, from material extraction to final disposal or recycling. This requires gathering data from a variety of heterogeneous sources, but current access to those is limited and often expensive. The BONSAI project, instead, aims to build a shared resource where the community can contribute to data generation, validation, and management decisions. In particular, its first goal is to produce an open dataset and an open source toolchain capable of supporting LCA calculations. This will allow the science of lifecycle assessment to perform in a more transparent and more reproducible way, and will foster data integration and sharing. Linked Open Data and semantic technologies are a natural choice for achieving this goal. In this work, we present the first results of this effort: (1) the core of a comprehensive ontology for industrial ecology and associated relevant data; and (2) the first steps towards an RDF dataset and associated tools to incorporate several large LCA data sources.

M3 - Article in proceeding

BT - The Semantic Web: ESWC 2019 Satellite Events

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