1. Modelling and Linking Guide for the application of W3C Linked Data (LD) / Semantic Web (SW) concepts and technologies in the AEC/FM industry sector Michel Böhms

2. Context bSI Technical Room, Linked Data Working Group (LDWG)
• Michel Böhms – TNO (NL) – lead
• Ana Roxin – uB (FR) – contributor
• Pieter Pauwels – UG (BE) – contributor
• Jakob Beetz – TUE (NL) – contributor
• Hans Schevers – BuildingBits (NL) – contributor
• Seppo Törmä – Aalto University (FI) – contributor
• Lars WikStröm – Triona (SE) – contributor
• Peter Bonsma – RDF (BG) – contributor
• Leif Granholm – Trimble (FI) – contributor
• Eilif Hjelseth – HiOA (NO) – contributor
+ Input from the European V-Con Project’s MLG
2 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

3. background Resolution in bSI Technical Room/LDWG, 2016 Jeju:
“Prepare a modelling and linking guide that can be used across the bSI rooms (top-down)”
Overall Strategy
Linked Data Tutorial for AEC/FM !
Evaluation Service” X
3 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

4. Links internally bsi The Technical Room / LDWG itself
ifcOWL, driven by backward compatability
The Building Room
Model View Definition (MVD) > White Paper Matthias Weise (aec3)
The Product Room
buildingSmart Data Dictionary (bSDD) > White Paper Jakob Beetz (TU/e)
The Regulatory Room
Regulations, Requirements and Recommendations (RRR)
The Infrastructure Room
Key ‘application area’ for this guide because of its strong natural data links with areas such as GIS, Systems Engineering and Monitoring
4 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

5. LD/SW in bsi: 3 roles STATIC: IFC >>>ifcOWL
EXTENSION: bSDD >>> bsddOWL
See: Overall Architecture André Borrmann (TUM)
LINKING beyond bSI >>> Modelling and Linking Guide (MLG)
GIS
PLM/SE
IoT/WoT
Robotics, Big Data, 3D Scanning Drones, …
Asset Information Management (AIM) bringing different worlds and their “Information Silos” together
5 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

6. Many relevant semantic resources to link to beyond bsi
6 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

7. Overview MLG 7 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

8. Glossary, example Ontology
An ontology is an abstract, formal, explicit, simplified view of a part of reality to be represented for some specific purpose.
An ontology is essentially (in LD/SW-terminology) a set of Classes, Properties (Datatype Properties as ‘attributes’ and Object Properties as ‘relationships’) and Individuals as instances of the classes.
Furthermore, an ontology might contain Datatypes (as potential value type ‘ranges’ for the Datatype Properties) and all kinds of Restrictions (cardinality restrictions - universal/existential value restrictions) on both classes and properties. An sometimes used synonym for ‘ontology’ is Object Type Library (OTL).
8 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

9. Idea
9 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

10. Consequence 10 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

11. Scope of MLG 11 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

12. Data grouping mechanisms like Containers
NOT in scope!
Data grouping mechanisms like Containers
Regulation/Requirement/Recommendation (RRR) Specifications
Data Set level Versioning
Importing Strategies
Publishing Aspects
Typically already covered by W3C Best Practices documents
12 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

13. Need for connecting all data inspired by Jakob Beetz, Phil Jackson, V-CON/CEDR INTERLINK projects
BIM standard
Industry ‘standard’
Regulations standard
GIS standard
IoT standard
Jakob Beetz
2016
13 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

14. Life-cycle view 14 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

15. Use cases benefitting: Total Life-cycle + supply-chain
15 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

16. General linking idea 16 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

17. Data modelling 18 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

18. Example: now for ifc 19 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

19. W3C Linked data / semantic web
Fully web-based, founded in logic, widely supported
Many standards are heading in this direction
20 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

20. LD/SW-based data modelling
21 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

21. What’s special? Data-driven Multi-Meta Level
Independent Classes & Properties
Open World Assumption (OWA)
No Unique Name Assumption (UNA)
Ultimate Normalization
Logic Inference
22 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

22. Tutorial material 23 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

23. Tutorial material 24 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

24. Tutorial material, scientific background
25 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

25. The actual modelling guidelines semantic resource defined
Modelling Styles
Naming & Annotations (like ‘labels’)
Quantity and Unit modelling
Individual level decomposition modelling
Typical (class-level) decomposition via Qualified Cardinality Restrictions (QCRs) for the previous individual level decomposition
Concept Modelling Ontology (CMO)
Several constructs supporting objectified Modelling Style (“the powerful Way”)
skos:prefLabel/altLabel
Importing QUDT (TQ/NASA)
hasDirectPart
26 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

26. Modelling Styles Concepts >>> owl:Classes Value Types
>>> rdfs:Datatypes (>>>owl:Classes for enumeration types)
Attributes (quantitative or qualitative) for Concepts having underlying Types
>>> DatatypeProperties (SIMPLE) or Classs (POWERFUL)
Relationships between Concepts
>>> ObjectProperties (SIMPLE) or Classes (POWERFUL)
Instances of Concepts
>>> owl:NamedIndividuals
Constraints (with respect to values or logic)
>>> Restrictions
27 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

27. Linking guidelines 28 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

28. Linking for two scenarios
Data Alignment
Data Conversion
29 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

29. Translation (syntax conversion) Example
30 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

30. ‘Implementation’ guidelines
Formats
Access
Ontology Versioning
Try it yourself Tips
Available Open Source/Commercial Software for
Ontology Development & Publishing
Ontology Deployment
31 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

31. Example: format Turtle
32 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

32. Example: Implementation architecture
33 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

33. What’s next? Final Draft (1 Sep2017)
Review (till 15 Sep 2017), extent and finalize
Show bSI London 2017 (end of October)
Discuss future actions/usage
Link ifcOWL, bsddOWL etc.
34 | InfraRoom Vision and Strategy on Linked Data
01 March 2017

34. Thank you for your attention
Take a look:
TIME.TNO.NL