automated ontology matching in the architecture ... · automated ontology matching in aec/fm domain...

© G.F. Schneider

Automated Ontology Matching in the Architecture, Engineering and Construction Domain - A Case Study

Georg Ferdinand Schneider

Technische Hochschule Nürnberg, Nürnberg, Germany

Fraunhofer Institute for Building Physics IBP, Nürnberg, Germany

7th Linked Data in Architecure and Construction Workshop (LDAC)

19 – 21 June 2019 | Lisbon, Portugal

© G.F. Schneider

Agenda

• Introduction and Motivation

• Methodology for Case Study

• Manually Defined/ Revised Alignments

• Results from Automated Ontology Matching

• Conclusion and Future Work

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Agenda






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Introduction and MotivationHeterogeneity of the domain

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Geometry

Process/ Project

Elements & Equipment

MaterialBuilding

Automation

Conservation

Product Data/ eCommerce

…

• Model-based information exchange in the built environment: Multi-* challenge

– Multiple domains

– Multiple stakeholders

– Multiple information silos

– Multiple tools and formats

Linked Data & Semantic Web Technologies to address these challenges1G. F. Schneider, A. Bougain, P. S. Noisten, and M. Mitterhofer. Information Requirement Definition for BIM: A Life Cycle Perspective. In Proceedings of the 11th European Conference on Product and Process Modelling (ECPPM), Limassol, Cyprus, September 7-9 2016.

Adapted from: 1

© G.F. Schneider

Introduction and MotivationPlethora of domain ontologies

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• Proliferating development of domain ontologies in AEC/FM domain

• Ontology reuse as stipulated by ontology engineering methods often neglected

• 'Thus, merely using ontologies, like using XML, does not reduce heterogeneity: it raises heterogeneity problems to a higher level.‘1

• Defining manually alignments is almost as difficult as creating ontologies from scratch

Strong need to use automated ontology

matching methods

Figure source: Rasmussen, M. H., Pauwels, P., Hviid, C. A., & Karlshøj, J. (2017). Proposing a central AEC ontology that allows for domain specific extensions. In 2017 Lean and Computing in Construction Congress.

1Euzenat, J., & Shvaiko, P. (2007). Ontology matching (Vol. 18). Heidelberg: Springer.

BOT

ThinkHome

BRICK

BRICK DogOnt

IFC

EEPSA

SimModel gbXML

SAREF4Bldg

© G.F. Schneider

Introduction and MotivationOntology Matching, Correspondences and Alignments

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‚Ontology matching is the process of finding relations between the entities of different ontologies, e.g., identifying the entities that represent the same (or similar) semantics in these ontologies.‘1

‘Correspondence is the expression of a relation holding between entities (classes,

properties, or individuals) of different ontologies.’ 1

‘Alignment is a set of correspondences between two ontologies. The alignment is the output of the ontology matching process.’1

1Kovalenko, O., & Euzenat, J. (2016). Semantic matching of engineering data structures. In Semantic web technologies for intelligent engineering applications (pp. 137-157). Springer, Cham.

© G.F. Schneider

Introduction and MotivationAutomated Ontology Matching in AEC/FM Domain

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• Demand for automated matching methods to facilitateinteroperability

• Knowledge-based data integration in smart city domain, Automated method ‚OntoPhil‘

• Reoccuring ontology design patterns identified, smart citydomain

No dedicated study to AEC/FM domain on automatedontology matching

Costin, A. & Eastman, C.

Otero-Cerdeira et al.

Bellini et al.

Gyrard et al.

Espinoza-Arias et al.

© G.F. Schneider

Agenda






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© G.F. Schneider

Methodology

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Step 1

• Manual definition/ revision of class and object property levelalignments

• Six domain ontologies to BOT

• Subsumption

Step 2

• Use of ontology matching tool (AlignmentMakerLight)

• Match six domain ontologies to BOT

• Default settings

Step 3• Compare results

© G.F. Schneider

Agenda






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© G.F. Schneider

Manually Defined Alignments to BOTDERIRoom2BOT

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bot:Spacebot:Building

rdfs:subPropertyOf

rdfs:subPropertyOf

Figure source: http://vocab.deri.ie/rooms

bot:Site

rdfs:subClassOfrdfs:subClassOf

bot:Storey

rdfs:subClassOf

rdfs:subClassOf

rdfs:subClassOf

bot:Element

rdfs:subClassOf

bot:containsZone

Alignments for all classes and object properties of DERI rooms found!

© G.F. Schneider

Manually Defined Alignments to BOTSAREF4Building2BOT

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bot:Element

bot:Space

rdfs:subClassOf

bot:Building

rdfs:subClassOf

bot:containsZone

rdfs:subPropertyOf

bot:containsElement

rdfs:subPropertyOf

Figure source: http://ontoology.linkeddata.es/publish/saref4bldg/index-en.html

rdfs:subClassOf

© G.F. Schneider

Manually Defined Alignments to BOTOverview

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Total number of alignments does not qualify as metric that v0.3.0 is better

Number of object property level alignments increased

© G.F. Schneider

Automated AlignmentAlignmentMakerLight

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– Default settings

– Well-documented, open source

– Source ontology BOT

– Target ontology six domain ontologies

– Tool implements primary and secondary matching algorithms

© G.F. Schneider

Conclusion

• Findings:

– Revision of manual alignments to BOT (v0.3.0)

– Comparison between manually and automatically obtained alignments

• Limitations

– Only single matching tool with default settings

– Set of domain ontologies biased by authors expertise and interest

• Future work:

– Call for participation: Well-defined benchmark for AEC/FM domain -> OAEI

• Additional sub-domains

– What if ontologies (incrementally) evolve? -> “Hot-start” possibility of matching methods?

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>>> https://github.com/w3c-lbd-cg/bot/tree/AlignmentRevision <<<

© G.F. Schneider

AcknowledgementsThank you very much for your attention

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Parts of this research have been supported by initiative Mittelstand 4.0 by the German Federal Ministry for Economic Affairs and Energy. (https://www.kompetenzzentrum-planen-und-bauen.digital/)

Georg Ferdinand SchneiderTechnische Hochschule Nürnberg & Fraunhofer Institute for Building Physics IBPFürther Straße 25090429 NürnbergGermany

Phone: +49 911 56854-9145Mail: [email protected]: [email protected]: Georg_Schneider3ORCID: 0000-0002-2033-859X

Parts of this research have been supported by the MOEEBIUS project, a Horizon 2020 research and innovation program under grant agreement No 680517. (http://www.moeebius.eu/)

http://www.moeebius.eu/

automated ontology matching in the architecture ... · automated ontology matching in aec/fm domain...

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