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PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
Pieter Pauwels
pipauwel.pauwels@ugent.be
Ana Roxin
ana-maria.roxin@u-bourgogne.fr
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
Agenda
Scenario
EYE/N3
approach
STARDOG
approach
Results
Further
generalisation
2
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
SCENARIO
3
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
Input files
◼ 2 IFC files converted into ifcOWL (Turtle format)
facts1.ttl
facts2.ttl
◼ Additional statements
@prefix add: <http://www.additionalelements.org/> .
inst:IfcSpace_1021 add:isConnectedToStair inst:IfcStair_593 .
inst:IfcSpace_983 add:isConnectedToStair inst:IfcStair_593 .
inst:IfcSpace_1021 add:isConnectedToStair inst:IfcStair_613 .
inst:IfcSpace_983 add:isConnectedToStair inst:IfcStair_613 .
◼ An ensemble of 8 rules (IF -> THEN)
4
But, this can
also be
handled
through the
proper
elements in
IFC
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
Example Rule – R#7
• A stair is connected to an object having an exit to ground floor
• The distance from the stair to the exit is not greater than 30000IF
• The stair is a valid exitTHEN
5
PREFIX kba: <http://koreanbuildingcode.org/KR-BA-34-01/>
PREFIX math: <http://www.w3.org/2000/10/swap/math#>
PREFIX add: <http://www.additionalelements.org/>
IF {
?s add:isConnectedToStair ?obj .
?obj kba:hasExitOnGroundFloor "true" .
?s kba:hasEscapeDistanceToStaircase ?value .
?value math:notGreaterThan 30000 .
}
THEN {
?s kba:isValid "true" .
}
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
THE EYE/N3 APPROACH
6
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
The N3/EYE Approach
7
inference engine
OWL ontologies
query
User
RDF Repository
interface
IF-THEN rule repository
response in
RDF graph
EYE reasoning
engine
N3 OWLRDF
SPARQL
RDF / CSV
English
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
Rules in EYE/N3
8
RDF graph
Log:implies
(IF THEN)
N3Logic
@prefix kba: <http://koreanbuildingcode.org/KR-BA-34-01/> .
@prefix add: <http://www.additionalelements.org/> .
@prefix math: <http://www.w3.org/2000/10/swap/math#> .
{
?s add:isConnectedToStair ?obj .
?obj kba:hasExitOnGroundFloor "true" .
?s kba:hasEscapeDistanceToStaircase ?value .
?value math:notGreaterThan 30000 .
}
=>
{
?s kba:isValid "true" .
} .
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
Serialisation formats for the RDF data model
9
Source: https://www.w3.org/DesignIssues/diagrams/n3/venn
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
THE STARDOG APPROACH
10
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
Stardog
11
Source: http://stardog.com/
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
Scenario implementation on Stardog
Adapting
rules
• Stardog Rule
Syntax
Creating the
repositories
• 1 per IFC file
• Rules are added
on top of each
repository
Querying
the data
• Inferences
are made
on query
execution
12
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
Stardog Rule Syntax
13
SPARQL
"basic graph
patterns"
(BGPs)
explicit new
bits (IF-
THEN)
Stardog Rule
Syntax
PREFIX rule: <tag:stardog:api:rule:>
[] a rule:SPARQLRule ;
rule:content """
PREFIX kba: <http://koreanbuildingcode.org/KR-BA-34-01/>
PREFIX add: <http://www.additionalelements.org/>
IF {
?s add:isConnectedToStair ?obj .
?obj kba:hasExitOnGroundFloor "true" .
?s kba:hasEscapeDistanceToStaircase ?value .
FILTER (?value <= 30000) .
}
THEN {
?s kba:isValid "true" .
}""" .
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
Scenario
◼ 2 repositories
Facts1.ttl + rs1.ttl
Facts2.ttl + rs1.ttl
◼ SPARQL queries addressing the properties being
impacted by the rules in the rule set (rs1.ttl)
As Stardog performs reasoning at query time
◼ Web interface for
Uploading files
Addressing SPARQL queries
14
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
RESULTS
15
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
Inferences – validating R#1
◼ Query 1
◼ Output Facts1.ttl
◼ Output Facts2.ttl
16
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
Inferences – Validating R#2
◼ Query 2
◼ Output (same for Facts1.ttl & Facts2.ttl)
17
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
Inferences – Validating R#3
◼ Query 3
◼ Output Facts1.ttl
◼ Output Facts2.ttl
18
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
Inferences – Validating R#4
◼ Query 4
◼ Output Facts1.ttl
◼ Output Facts2.ttl
19
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
Inferences – Validating R#5
◼ Query 5
◼ Output (same for Facts1.ttl & Facts2.ttl)
20
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
Inferences – Validating R#6
◼ Query 6
◼ Output Facts1.ttl
◼ Output Facts2.ttl
21
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
R#7 and R#8 – Facts1.ttl
◼
◼
◼
22
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
R#7 and R#8 – Facts2.ttl
◼
◼
23
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
FURTHER GENERALISATION
24
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
Candidate languages
RASE
Ifc Constraint
Model
Procedural
Coding
SWRL
SPARQL and
SPIN
DROOLS
Legal Doc ML
and Legal Rule
ML
BIMRL
Rule Tables JenaRules
NLP and
Prolog
Commercial
Rule Engines
(e.g. Stardog)
BERA N3logic
25
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
Structure ????
26
SWRL
N3Logic
StarDog
Prolog
SPARQL/SPIN
BERA
RASE
IfcConstraint
Procedural
coding
DROOLS
RuleML
BIMRL
Rule
Tables
Jena
Rules
RIF
Natural Language
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
Language ‘families’
27
SWRLN3Logic StarDog
Prolog SPARQL/SPIN
BERA
RASE
IfcConstraint
Procedural
coding
DROOLS
LegalRuleML
BIMRL
Rule
Tables
Jena RIF
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
Cascading the families
28
SWRLN3Logic StarDog
Prolog SPARQL/SPIN
BERA
RASE IfcConstraint
Procedural
coding
DROOLS
LegalRuleML
BIMRL
Jena RIF
Natural Language
IMPLEMENTATION
MARKUP
STANDARD
PieterPAUWELS–pipauwels@ugent.be
AnaROXIN–ana-maria.roxin@u-bourgogne.fr
Pieter Pauwels
pipauwel.pauwels@ugent.be
Ana Roxin
ana-maria.roxin@u-bourgogne.fr
Thank you for your attention !

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