Information system support in construction industry with semantic web technologies and/or autonomous...
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Information system support in construction industry with semantic web technologies
and/or autonomous reasoning agents
Pieter Pauwels, University of Amsterdam
Ronald De Meyer, Ghent University
Jan Van Campenhout, Ghent University
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Interoperability: sharing information in the wild?
Information loss-
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• Sharing information in the wild• Manual remodelling of information• Negotiation with top-level ontologies• Central information structure• Linked data approach
Possible strategies to the interoperability challenge
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LINKED DATA APPROACHSEMANTIC WEB TECHNOLOGIES
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links at level of information structure
one generic language with basis in Description Logic (DL)
worldwide usage
+Linking information structures with semantic web technologies
++
=> Semantic web technologies
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Worldwide web of information (‘Linked Open Data cloud’)
+worldwide usage
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Resource Description Framework (RDF)
+one generic language with basis in Description Logic (DL)
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CultureSampo: Finnish Culture on the Semantic Webwww.kulttuurisampo.fi
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+links at level of information structure
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Implementation in an AEC context
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• Sharing information in the wild• Manual remodelling of information• Negotiation with top-level ontologies• Central information structure• Linked data approach
=> How to get the right information at the right time?
Possible strategies to the interoperability challenge
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Design thinking process
Information
Information
Information
Information
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Design as an iterative and interactive processInformation systems as environments for design tryouts
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AUTONOMOUS REASONING AGENTS
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Design as an iterative and interactive processAutonomous reasoning agents
Abductive reasoning
Deductive reasoning
Inductive reasoning
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Implementation in JAVA
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Conclusion
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Thank you
Information system support in construction industry with semantic web technologies
and/or autonomous reasoning agents
Pieter Pauwels - [email protected]
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Background knowledge
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Implementation in JAVA
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New design situation
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Implementation in JAVA
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e:possibleModel – e:falseModel – e:counterModel
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100 relevant previous experiences
100 models generated for each query (‘insulation’ – ‘windows’ – ‘heater’)
> belief in ‘insulation’: 0.84
> belief in ‘windows’: 0.58
> belief in ‘heater’: 0.54
The abduction