A Linked Data Perspective for BIM
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This document discusses how linked data and semantic web technologies can help simplify data models, queries, and implementations in the architecture, engineering, and construction industry. It presents examples of simple queries over linked building product data. It also describes how rules can be used to map concepts between existing ontology standards for building information modeling like IfcOWL and COBieOWL in a federated architecture. This allows queries to retrieve and integrate building product data from different standards and systems in a semantically consistent way. Measurements show queries over linked ontologies complete significantly faster than isolated systems due to semantic mappings between concepts.
A Linked Data Perspective for BIM
- 2. AnaROXIN–ana-maria.roxin@u-bourgogne.fr Linked Data is not Semantic Web 2 Source: https://baojiebaojie.files.wordpress.com/2011/04/semantic_web_technology_stack.png
- 4. AnaROXIN–ana-maria.roxin@u-bourgogne.fr Linked Open Data Principles 4 Source: https://www.w3.org/DesignIssues/LinkedData.html
- 5. AnaROXIN–ana-maria.roxin@u-bourgogne.fr Problem: Martec's Law 5 Technology is changing very rapidly… … but changing an organization — how it thinks and behaves — is still hard and slow. Time Quantity of change
- 6. AnaROXIN–ana-maria.roxin@u-bourgogne.fr How Linked Data could help… Simple models Simple queries Simple rules Simple implementations 6
- 7. AnaROXIN–ana-maria.roxin@u-bourgogne.fr SIMPLE MODELS 7 Pieter Pauwles, Ana Roxin. simpleBIM. In Proceedings of ECPPM, Sept 2016, CIC-Press.
- 8. AnaROXIN–ana-maria.roxin@u-bourgogne.fr Why we need to go further ? Industry standards • IFC • COBie • bSDD • etc. Adapted to ontologies • ifcOWL • COBieOWL • etc. Interlinking ! 8 … but their practical use remains complex and difficult !
- 9. AnaROXIN–ana-maria.roxin@u-bourgogne.fr Applications Vision 9 Linked Open Data Model Window^^@EN Fenêtre^^@FR Door Stairs … …… Ontologies ifcOWL COBieOWL bSDD … Query, Manipulate Map, Expose
- 11. AnaROXIN–ana-maria.roxin@u-bourgogne.fr Query 1 ◼ Show me all the doors and the stairs in this building ! 11
- 12. AnaROXIN–ana-maria.roxin@u-bourgogne.fr Query 2 ◼ Show me all doors and windows in the building ! 12
- 13. AnaROXIN–ana-maria.roxin@u-bourgogne.fr Still.. ◼ A simple query takes around 10ms in our environment ◼ View extraction cannot be done real-time Query 1: >19 hours Query 2: 17 min ◼ Mainly impacted by disk access time & memory load ◼ Could be improved by: parallelizing queries "trade-off" between simple and complex queries 13
- 14. AnaROXIN–ana-maria.roxin@u-bourgogne.fr SIMPLE RULES User Views OWL Ontology Interoperability 14
- 16. AnaROXIN–ana-maria.roxin@u-bourgogne.fr Adapting MVDs into logical rules mvdXML • Gathering of MVD data constraints for the considered case (e.g. COBie) Rule file • Mapping of constraints into logical rules (IF→ THEN) • Using URIs of ifcOWL concepts Triple store • Use a query language to retrieve data, originally described using the IFC model April MVD16 → A rule-based system to construct building views
- 17. AnaROXIN–ana-maria.roxin@u-bourgogne.fr Case study : COBieMVD ◼ We can directly use a query language to retrieve COBie data that is originally described using the IFC model ?x a cobieowl:Contact . ?x cobieowl:email ?email. ?x a ifcowl:IfcActor . ?x ifcowl:name_IfcRoot ?y. ?y expr:hasString ?z becomes 17
- 18. AnaROXIN–ana-maria.roxin@u-bourgogne.fr Defining Views through Rules 18 Abstract views • Pre-defined, stored and exchanged Concrete views • Built from IFC data • Using abstract view definitions (i.e. rules). Easily configurable • Set of concepts (C) • Set of GUIDs (G) • Set of IFC relationships (R) A rule-based system to construct building views
- 19. AnaROXIN–ana-maria.roxin@u-bourgogne.fr Building Enveloppe View 19 C = {BuildingEnvelope} G = { } R = { IfcRelDecomposes, IfcRelContainedInSpatialStructure, IfcRelVoidsElement, IfcRelFillsElement, IfcRelDefinesByProperties }.
- 22. AnaROXIN–ana-maria.roxin@u-bourgogne.fr Federated Architecture for OWL Ontologies 22 Autonomous ontologies Mapped through rules Controlled by inference FOWLA OntoN Onto2 Onto1 ifcOWL COBie OWL Rule inference: - automatic "translation" between formats - automatic inference of modifications in aligned ontologies COBieMVD Tarcisio Mendes de Farias, Ana Roxin, Christophe Nicolle. SWRL-rule Selection Methodology for Ontology Interoperability. In Data and Knowledge Engineering, Oct 2015, Elsevier.
- 23. AnaROXIN–ana-maria.roxin@u-bourgogne.fr Query Execution 23 Onto 1 Onto 2 Onto N How to express queries ? How long does it take to get an answer ?
- 24. AnaROXIN–ana-maria.roxin@u-bourgogne.fr So let's see query execution time… Query name SPARQL Query Q1 SELECT ?x ?y WHERE { ?x cobieowl:name ?y . } Q2 SELECT ?x ?y WHERE { ?x a ifcowl:IfcElement. ?x cobieowl:name ?y.} Q3 SELECT ?x ?u WHERE { ?x a onto1:C11 . ?y a onto2:C22 . ?x onto1:p12 ?y . ?y onto1:p11 ?x . } 24 Query KB Mean execution time (s) Standard deviation (σσσσ) #RuleSet #Results Q1 KB1 - - 474 0 KB2 - - 266 0 KB3 9.25 12.21 178 1683 KB4 2.23 1.78 16 38318 Q2 KB1 - - 474 0 KB2 - - 266 0 KB3 32.99 0.75 178 74 KB4 0.16 0.04 2 74 Q3 KB1 - - 474 0 KB2 - - 266 0 KB3 71.62 0.95 178 0 KB4 0.88 0.43 5 9
- 25. AnaROXIN–ana-maria.roxin@u-bourgogne.fr Conclusions – Collective Effort 25 Editors • Reuse standard vocabulary terms • Help in defining mapping among ontologies' concepts Consumers • Integrate the so-modelled data Industrials & researchers • Define use cases ! • Define mappings among the standards' terms
- 26. AnaROXIN–ana-maria.roxin@u-bourgogne.fr Ana Roxin ana-maria.roxin@u-bourgogne.fr Thank you for your attention !