The document discusses the significance of meaning in BIM (Building Information Modeling) data, emphasizing the need for effective specification of knowledge and reasoning processes to support decision-making. It explores the integration of AI and machine learning in managing complex decision systems, enhancing compliance checking, and optimizing construction processes. Additionally, it outlines various applications of BIM, including urban management and the development of expert systems incorporating human knowledge.

1. Bringing meaning to
BIM data
– why and how ?
Dr. Ana ROXIN
Associate Professor, Habilitated to conduct research
Univ. Bourgogne Franche-Comté (UBFC)
ana-maria.roxin@ubfc.fr

2. The need for
meaning
The need for
meaning
Specifying
knowledge
Specifying
knowledge
Reasoning
and
explanations
Reasoning
and
explanations
Pertinence
for BIM
Pertinence
for BIM
ConclusionConclusion
Summary
2

3. The lack of meaning…
3
▶ BIM = “A shared digital representation of physical and functional characteristics of any built object including
buildings, bridges, roads, process plants etc. forming a reliable basis for decisions”
(ISO 29481-1 2016 « Building information models — Information delivery manual — Part 1: Methodology and
format »)
How to specify …
… knowledge ?
… a reasoning process ?
How to explain …
… deductions ?
How to support …
… decision-making ?
… humans ?

4. Data
•Symbols representing
properties of objects,
events and their
environment.
•Produced from observation
Information
•Data placed within a
context
•Analysed data
Experience
•Actions or facts deduced
from information
Knowledge
•True beliefs or know-how
•Transforms information
into instructions
Specifying Knowledge
4
Explicit Implicit
Human knowledge and know-how needs to be
specified in a way that enables its
management by computers e.g. actionable
knowledge

5. Unsupervised learning
Partitioning : k means, KNN
Dimension reduction : artificial neuronal networks
Reinforcement learning
Genetic algorithms
TD Learning, Q Learning
Supervised learning
Discrete : classification or categorization
Continuous : regression
Programmed learningProgrammed learning Expert SystemsExpert Systems
Reasoning and explaining deductions
5
Systems based on
automatic learning
Machine learning
Systems based on
reasoning
Automatically identify
structure in unlabelled
data
Learning improved by
credit/blame assignment
Find specific relations or
structures in the input data
that allow us to effectively
produce correct output
data.
Expertly solving problems
in a given domain by
drawing inferences from a
knowledge base developed
from human expertise

6. Reasoning
engine
• Deduces implicit
knowledge
Set of rules
• Know-how
• Rules for expert
reasoning
Knowledge base
• Contains experts’
knowledge (formal
and explicit)
Expert or Knowledge-based Systems
6
The digital description must be a conceptualization of the world with enough detail
to support useful decision-making.
The rules allow one to track how the expert system “reasons”.
They ensure the final development of the reasoning process and then the
maintenance of the system. Rules must be managed efficiently.
In complex decision-making systems, AI must be at the service of humans.
The overall system must be fast and intuitive enough to be perceived as an
advantage by humans. Deductions are logical and justifiable.
Façade walls should be
18cm wide and made of
reinforced concrete
Façade walls are one
exterior side of a building,
usually the front.
Façade_wall_2 does not
comply
(Reason : width of 16cm)

7. From sensors
to knowledge
From sensors
to knowledge
Managing
urban rules
Managing
urban rules
Adding expert
concepts
Adding expert
concepts
Extracting
views
Extracting
views
Compliance
Checking
Compliance
Checking
DictionariesDictionaries
Product
Catalogues
Product
Catalogues
ClassificationsClassifications
Applications in the field of BIM
7

8. Sensors placed in concrete
Knowledge upload
From sensors to knowledge
8
Cette photo par Auteur inconnu est soumise à la licence CC BY-SA-NC
Cost optimization
CO2 Emissions
Urban networks
How do I extract information about
the concrete elements of a building?
Site management
Logistics
Traceability
Applications for:
• Concrete production
• Surveillance of building sites
• Structure monitoring
"Communicating Matter for BIM"
ANR ongoing project (2017-2020)
N° ANR-17-CE10-0014-03
Comfort
Productivity
Satisfaction

9. Management of Urban Rules (PLU)
9
CIFRE PhD with the CSTB
Candidate Elio HBEICH
(ongoing)
- Application of PLU rules at different
scales / abstractions
Advantages:
Elio Hbeich, Ana Roxin, Nicolas Bus. Aligning BIM and GIS – CityGML and
PLU to achieve compliance checking model. 18th Int. Conference on
INFORMATICS in ECONOMY, May 2019. pp.165-170.
⟨10.1016/j.autcon.2018.03.035⟩

10. Adding Expert Knowledge
10
Last Storey
Cette photo par Auteur inconnu est soumise à la licence CC BY-NC
Cette photo par Auteur inconnu est soumise à la licence CC BY-NC
Building Envelope
- Adding new concepts as needed by
the experts
- Ease of verification and checking
Advantages:
Presentation @buildingSmart International Standards Summit,
Technical Room, Rotterdam, April the 12th 2016 [Available online]

11. View Extraction
11
- Eased handling and verification of building
models
Advantages :
Building envelope ?
Tarcisio Mendes De Farias, Ana Roxin, Christophe Nicolle. A rule-based methodology to
extract building model views. Automation in Construction, Elsevier, 2018, 92, pp.214 -
229. ⟨10.1016/j.autcon.2018.03.035⟩

12. Compliance Checking
12
- Querying in natural language
- Explanation of deductions
Advantages :
Nicolas Bus, Muhammad Fahad, Bruno Fies, Ana Roxin. Semantic topological querying for
compliance checking. eWork and eBusiness in Architecture, Engineering and Construction:
ECPPM 2018, 2018 ⟨10.1016/j.autcon.2018.03.035⟩
Pieter Pauwles, Ana Roxin. Reasoning with Rules. Presentation @buildingSMART International
Standards Summit, Jeju, le 27 septembre 2016. [Available online]

13. Dictionary
Window^^@EN
Fenêtre^^@FR
Door Wall
…
Applications
Dictionnaries
13
Ontologies
Model 1 Model 2 Model 3
- Managing concepts in natural language,
without knowing their equivalents in a specific
model e.g. IFC.
Advantages :
Query,
manipulate
Map,
expose
Ana Roxin. A Linked Data Perspective for BIM. Présentation @buildingSMART
International Standards Summit, Building, Product and Technical Rooms joint session,
Jeju, 2016. [Available online]

14. Template objects
•Guide to produce generic and
product objects
•Unique 128-bit identifier (ISO 16739)
•At least one classification
•Low detail: extent, connections &
connectivity e.g. AIA LoD 200
•Characteristics measurements
(overall nominal dimensions, mass &
volume) + pref. units
•Specification properties
(select/replace the object without
ref. to external data assets), as
defined in specifications & schedules
from
consultants/contractors/maintainers.
•Values are not mandatory, can be
suggested
Generic objects
•Generalization of a product
•Medium detail: detailed shape for
object recognition, space allocation,
coordination and clash detection e.g.
AIA LoD 300
•+ Standard measurements (actual
main dimensions, areas & volume)
•+ Assessment properties (object’s
economic & environmental impact)
•Values are not mandatory, can be
suggested
•Units are named according to ISO
80000-1
Product objects
•Represents a product
•High detail: rendering of the usability
of equipment, simulation of
connections on equipment through
named ports e.g. AIA LoD 300-400
•+Method-based measurements (e.g.
effective area, efective length, ref.
service life)
•+ Simulation properties e.g.
performance properties
•Specifying & assessment properties
with values provided & units named
according to ISO 80000-1
Product Catalogues ISO/DIS 22014:2019
“Library objects for architecture, engineering and construction”
14
Catalogue product objects = specific
product with fixed properties, available
from a catalogue to be :
— downloaded and used directly
— associated to unique product identifiers.
Parametric series product objects = a
controlled range or series of generic or
product objects with variable properties, to
be :
— downloaded and configured to suit the
design and engineering requirements
— associated to unique series identifiers.
Engineered-to-order product objects =
specific product, either as a requirement
specification or a resolved solution that can be
manufactured, to be :
— downloaded and configured to document
design and engineering requirements
— used as the basis for requests for
engineered solutions from suppliers and
manufacturers
— upgraded to engineered solutions supplied
by a supplier/manufacturer.
ISO/DIS 22014:2019

15. Classifications
15
OmniClassOmniClass
MasterFormatMasterFormat
UniformatUniformat
ISO 12006-2:2015ISO 12006-2:2015

16. Industry
• Define and set use cases
• Define and help specifying expert rules in natural language
• Use standards & standard vocabularies
• Implement knowledge-based approaches
Research
• Listen, keep a close relation to industrial needs
• Design efficient and helpful knowledge management systems
• Define links between vocabularies
• Develop Proof-Of-Concept
As a conclusion…
16

17. Thank you for
your attention
Contact: ana-maria.roxin@ubfc.fr