A System for Ontology-Based Sharing of Expert Knowledge in Sustainability Science

Work towards creation of a knowledge sharing system for sustainability science through the application of semantic data modeling is described. An ontology grounded in description logics was developed based on the ISO 15926 data model to describe three types of sustainability science conceptualizatio...

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Main Authors: Steven Kraines, Weisen Guo
Format: Article
Language:English
Published: Ubiquity Press 2011-01-01
Series:Data Science Journal
Subjects:
Online Access:http://datascience.codata.org/articles/141
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spelling doaj-7401a9c5ef924e628fc580099ed704122020-11-24T21:45:46ZengUbiquity PressData Science Journal1683-14702011-01-01910712310.2481/dsj.Kraines141A System for Ontology-Based Sharing of Expert Knowledge in Sustainability ScienceSteven Kraines0Weisen Guo1Science Integration Programme – Human, Division of Project Coordination, Univ. of Tokyo, 5-1-5 Kashiwano-ha, Kashiwa-shi, Chiba Prefecture, 277-8568, JapanScience Integration Programme – Human, Division of Project Coordination, Univ. of Tokyo, 5-1-5 Kashiwa-noha, Kashiwa-shi, Chiba Prefecture, 277-8568, Japan Inst. of Systems Eng. of Dalian University of Technology, Dalian 116024, ChinaWork towards creation of a knowledge sharing system for sustainability science through the application of semantic data modeling is described. An ontology grounded in description logics was developed based on the ISO 15926 data model to describe three types of sustainability science conceptualizations: situational knowledge, analytic methods, and scenario frameworks. Semantic statements were then created using this ontology to describe expert knowledge expressed in research proposals and papers related to sustainability science and in scenarios for achieving sustainable societies. Semantic matching based on logic and rule-based inference was used to quantify the conceptual overlap of semantic statements, which shows the semantic similarity of topics studied by different researchers in sustainability science, similarities that might be unknown to the researchers themselves.http://datascience.codata.org/articles/141Expert knowledgeKnowledge sharingSemantic webSemantic searchKnowledge descriptionSustainability scienceOntology
collection DOAJ
language English
format Article
sources DOAJ
author Steven Kraines
Weisen Guo
spellingShingle Steven Kraines
Weisen Guo
A System for Ontology-Based Sharing of Expert Knowledge in Sustainability Science
Data Science Journal
Expert knowledge
Knowledge sharing
Semantic web
Semantic search
Knowledge description
Sustainability science
Ontology
author_facet Steven Kraines
Weisen Guo
author_sort Steven Kraines
title A System for Ontology-Based Sharing of Expert Knowledge in Sustainability Science
title_short A System for Ontology-Based Sharing of Expert Knowledge in Sustainability Science
title_full A System for Ontology-Based Sharing of Expert Knowledge in Sustainability Science
title_fullStr A System for Ontology-Based Sharing of Expert Knowledge in Sustainability Science
title_full_unstemmed A System for Ontology-Based Sharing of Expert Knowledge in Sustainability Science
title_sort system for ontology-based sharing of expert knowledge in sustainability science
publisher Ubiquity Press
series Data Science Journal
issn 1683-1470
publishDate 2011-01-01
description Work towards creation of a knowledge sharing system for sustainability science through the application of semantic data modeling is described. An ontology grounded in description logics was developed based on the ISO 15926 data model to describe three types of sustainability science conceptualizations: situational knowledge, analytic methods, and scenario frameworks. Semantic statements were then created using this ontology to describe expert knowledge expressed in research proposals and papers related to sustainability science and in scenarios for achieving sustainable societies. Semantic matching based on logic and rule-based inference was used to quantify the conceptual overlap of semantic statements, which shows the semantic similarity of topics studied by different researchers in sustainability science, similarities that might be unknown to the researchers themselves.
topic Expert knowledge
Knowledge sharing
Semantic web
Semantic search
Knowledge description
Sustainability science
Ontology
url http://datascience.codata.org/articles/141
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