JURIX talk on representing and reasoning on the deontic aspects of normative rules relying only on standard Semantic Web languages. The corresponding paper is at https://hal.inria.fr/hal-01643769v1

1. NORMATIVE REQUIREMENTS
AS LINKED DATA
Fabien GANDON
Guido GOVERNATORI
Serena VILLATA

2. MIREL
MIning and REasoning with
Legal texts
http://www.mirelproject.eu/

3. MIREL
MIning and REasoning with
Legal texts
http://www.mirelproject.eu/
 International and inter-sectorial network to define a formal
framework and to develop tools
 European Union's 2020 research and innovation programme
Marie Skłodowska-Curie grant agreement No 690974.
 Conceptual challenges e.g. legal interpretation in mining and
reasoning
 Computational challenges e.g. handling of big legal data, and
the complexity of regulatory compliance

4. MIREL
MIning and REasoning with
Legal texts
http://www.mirelproject.eu/
 International and inter-sectorial network to define a formal
framework and to develop tools
 European Union's 2020 research and innovation programme
Marie Skłodowska-Curie grant agreement No 690974.
 Conceptual challenges e.g. legal interpretation in mining and
reasoning
 Computational challenges e.g. handling of big legal data, and
the complexity of regulatory compliance
 Bridge: legal ontologies and NLP parsers  reasoning methods
and formal logic
 promotes mobility and staff exchange, here:
 bridge normative requirements and linked data

5. RESEARCH IN

7. 7
HTTP
URI
reference address
communication
WEB
RDF
the giant global graph of data
HTTP
URI
HTML
reference address
communication
WEB

8. 8
"Music"
RDFis a model for directed labeled multigraphs
http://inria.fr/rr/doc.html
http://ns.inria.fr/fabien.gandon#me
http://inria.fr/schema#author
http://inria.fr/schema#topic
http://inria.fr/rr/doc.html
http://inria.fr/schema#keyword

9. 9
linked open data(sets) cloud on the Web
0
200
400
600
800
1000
1200
1400
01/05/2007 08/10/2007 07/11/2007 10/11/2007 28/02/2008 31/03/2008 18/09/2008 05/03/2009 27/03/2009 14/07/2009 22/09/2010 19/09/2011 30/08/2014 26/01/2017
number of linked open datasets on the Web

10. 10
Query data vs. search for documents
ex. DBpedia

11. 11
infer, reason, with semantics
URI
reference address
communication
WEB
RDF
URI
reference address
communication
WEB
RDF
RDFS
OWL

12. 12
RDFS to declare classes of resources,
properties, and organize their hierarchy
Document
Report
creator
author
Document Person

13. 13
OWL in one…
algebraic properties
disjoint properties
qualified cardinality
1..1
!
individual prop. neg
chained prop.


enumeration
intersection
union
complement
 disjunction
restriction!
cardinality
1..1
equivalence
[>18]
disjoint union
value restriction
keys
…

14. back to the topic

15. MOTIVATIONS
 rely on Web standard to represent, exchange and foster
interoperability between deontic rule bases
 rely on existing standards (e.g. SPARQL) and
infrastructures
(e.g. triple stores) to implement deontic systems
 combine linked data and semantic Web reasoning and
formalisms (e.g. OWL) with deontic reasoning to
support more inferences

16. QUESTIONS
Can we represent and
reason on the deontic
aspects of normative rules
with standard Semantic
Web languages?

17. QUESTIONS
Can we represent and
reason on the deontic
aspects of normative rules
with standard Semantic
Web languages?
 useful ontology-based reasoning
For which aspects schema-based reasoning (RDFS, OWL)
is relevant?

18. QUESTIONS
Can we represent and
reason on the deontic
aspects of normative rules
with standard Semantic
Web languages?
 useful ontology-based reasoning
For which aspects schema-based reasoning (RDFS, OWL)
is relevant?
 beyond classical ontology-based reasoning
Can we operationally formalize other deontic reasoning rules
with RDF and SPARQL?

19. identifying, classifying

20. ONTOLOGY
Ontological extension of the
LegalRuleML Meta Model focusing
on the deontic aspects
 LegalRuleML Meta Model [9] : primitives for deontic
rule and normative requirement representation
(Permission, Obligation, Prohibition).
 Integrate abstract formal framework for normative
requirements of regulatory compliance [10]
 Consider results on modal defeasible reasoning for
deontic logic on the Semantic Web [11]

21. MOTIVATING SCENARIOS
Step 1 to specify problems that
are not adequately addressed by
existing solutions [13].
e.g.
 support the annotation, detection and retrieval of
normative requirements and rules.
 support users in information retrieval with the ability
to identify and reason on the different types of
normative requirements and their statuses.

22. COMPETENCY QUESTIONS
Step 2 to place demands on the
targeted ontology, and they
provide expressiveness
requirements [13].
e.g.
 What are the instances of a given requirement and
its sub-types, e.g. obligation?
 Is a requirement violated by one or more states of
affairs, and if so, which ones?
 Which rules, documents and states of affairs are
linked to a requirement and how?

23. and… « voilà ! »
Normative Requirement Vocabulary (NRV) http://ns.inria.fr/nrv#

24. Compensable Requirement,
Non Compensable
Requirement, Compensated
Requirement : classes of
requirements with different
compensation statuses.
top classes (1/2)

25. Violable requirement, Non
Violable Requirement,
Violated Requirement and
Compliant Requirement: relation
to a Compliance or a Violation
top classes (2/2)

26. and… « voilà ! »
Normative Requirement Vocabulary (NRV) http://ns.inria.fr/nrv#

27. FORMALIZED ONTOLOGY
reuse & extend
lrmlmm: http://docs.oasis-open.org/legalruleml/ns/v1.0/metamodel#
owl: http://www.w3.org/2002/07/owl#
rdf: http://www.w3.org/1999/02/22-rdf-syntax-ns#
rdfs: http://www.w3.org/2000/01/rdf-schema#
rulemm: http://docs.oasis-open.org/legalruleml/ns/v1.0/rule-metamodel#
xml: http://www.w3.org/XML/1998/namespace
xsd: http://www.w3.org/2001/XMLSchema#
nrv: http://ns.inria.fr/nrv#
nru: http://ns.inria.fr/nrv-inst#

28. FORMALIZED ONTOLOGY
extract 1: normative requirements
disjoint characteristics
:NormativeRequirement a rdfs:Class;
owl:disjointUnionOf
( :CompensableRequirement :NonCompensableRequirement );
owl:disjointUnionOf
( :ViolableRequirement :NonViolableRequirement );
owl:disjointUnionOf
( :PersistentRequirement :NonPersistentRequirement ).

29. FORMALIZED ONTOLOGY
extract 2: disjointness of violation
relations
:hasCompliance
a owl:ObjectProperty ;
rdfs:label "has for compliance"@en ;
rdfs:domain :ViolableRequirement ;
rdfs:range lrmlmm:Compliance ;
owl:propertyDisjointWith :hasViolation .

30. EXPRESSIVITY
OWL fragment
 disjoint unions means OWL DL, i.e.,
 more precisely
 remove cardinality restrictions, unions and
disjointedness: OWL EL and OWL RL

31. missing part

32. LIMITS
a motivation case: compliance and
violation are disjoint locally to a
state of affair
:CompliantRequirement a rdfs:Class ;
rdfs:subClassOf :ViolableRequirement ;
owl:equivalentClass [ a owl:Restriction ;
owl:onProperty :hasCompliance ;
owl:minCardinality 1 ] .
owl:equivalentClass [ a owl:Restriction ;
owl:onProperty :hasViolation ;
owl:maxCardinality 0 ] .

33. THE GRAPH AS A RESOURCE
“name that graph”, Gandon,
Corby, 2010, W3C Workshop on
RDF 1.1
http://www-sop.inria.fr/edelweiss/fabien/docs/w3c/rdfsource/rdfsource.html
http://ns.inria.fr/fabien.gandon/foaf#me RDF Source
http://purl.org/dc/elements/1.1/title
mailto:fgandon@inria.fr Fabien Gandon
http://purl.org/dc/elements/1.1/creator
http://xmlns.com/foaf/0.1/mbox
http://xmlns.com/foaf/0.1/Person
http://www.w3.org/1999/02/22-rdf-syntax-ns#type
http://xmlns.com/foaf/0.1/name

34. NAMED GRAPHS
encapsulate state of affairs inside
RDF 1.1 named graphs to bound
the scope of some statements
GRAPH :StateOfAffairs1 {
:Tom :activity [ a :Driving ;
:speed "100"^^xsd:integer ;
rdfs:label "driving at 100km/h"@en ] . }
:StateOfAffairs1 a lrmlmm:FactualStatement .

35. METADATA
represent and
document legal
sources,
requirements, etc.
<http://gov.au/driving-rule> a lrmlmm:Source ;
rdfs:label "driving rules in Australia"@en .
nru:LSS1 a lrmlmm:Sources ;
lrmlmm:hasLegalSource <http://gov.au/driving-rule> .
nru:LRD1 a lrmlmm:LegalRuleMLDocument ;
lrmlmm:hasLegalSources nru:LSS1 ;
lrmlmm:hasAlternatives [ lrmlmm:fromLegalSources nru:LSS1 ;
lrmlmm:hasAlternative nru:PS1 ] ;
lrmlmm:hasStatements nru:SS1 .
nru:SS1 a lrmlmm:Statements ;
lrmlmm:hasStatement nru:PS1 .
nru:PS1 a lrmlmm:PrescriptiveStatement, lrmlmm:Prohibition ;
rdfs:label "can't drive over 90km/h"@en .

36. SPARQL RULES
implement some of the deontic
reasoning using SPARQL
operations on named graphs
DELETE { graph ?g { nru:PS1 nrv:hasCompliance ?g } }
INSERT { graph ?g { nru:PS1 a nrv:ViolatedRequirement ;
nrv:hasViolation ?g } }
WHERE { graph ?g { ?a a :Driving ; :speed ?s . }
FILTER (?s>90) } ;
DELETE { graph ?g { nru:PS1 a nrv:ViolatedRequirement ;
nrv:hasViolation ?g } }
INSERT { graph ?g { nru:PS1 nrv:hasCompliance ?g } }
WHERE { graph ?g { ?a a :Driving ; :speed ?s . }
FILTER (?s<=90) }

37. crash testing
formalization

38. PROOF OF CONCEPT
with two established tools
 Protégé [17] and its reasoners to check the NRV
OWL ontology : coherent and consistent.
 CORESE [18] to experiment named graph and
SPARQL based reasoning.

39. QUERY & INFER
e.g. CORESE/KGRAM [18]

40. FO  R  GF  GR
mapping modulo an ontology
car
vehicle
car(x)vehicle(x)
GF
GR
vehicle
car
O
RIF-BLD SPARQL RIFSPARQL
?x ?x
C C
List(T1. . . Tn) (T1’. . . Tn’)
OpenList(T1. . . Tn T)
External(op((T1. . . Tn))) Filter(op’ (T1’. . . Tn’))
T1 = T2 Filter(T1’ =T2’)
X # C X’ rdf:type C’
T1 ## T2 T1’ rdfs:subClassOf T2’
C(A1 ->V1 . . .An ->Vn)
C(T1 . . . Tn)
AND(A1. . . An) A1’. . . An’
Or(A1. . . An) {A1’} …UNION {An’}
OPTIONAL{B}
Exists ?x1 . . . ?xn (A) A’
Forall ?x1 . . . ?xn (H)
Forall ?x1 . . . ?xn (H:- B) CONSTRUCT { H’}
WHERE{ B’}
restrictions
equivalence no equivalence
extensions

41. demo:

42. INSIDE THE NAMED GRAPHS
state of affairs 1
state of affairs 2

43. CONCLUSION
Named Graph (state of affair) Subject Predicate Object
http://ns.inria.fr/nrv-inst#StateOfAffairs1 Tom http://ns.inria.fr/nrv-inst#activity driving at 100km/h
http://ns.inria.fr/nrv-inst#StateOfAffairs1 Tom http://www.w3.org/2000/01/rdf-schema#label Tom
http://ns.inria.fr/nrv-inst#StateOfAffairs1 can't drive over 90km http://www.w3.org/1999/02/22-rdf-syntax-ns#type violated requirement
http://ns.inria.fr/nrv-inst#StateOfAffairs1 can't drive over 90km has for violation http://ns.inria.fr/nrv-inst#StateOfAffairs1
http://ns.inria.fr/nrv-inst#StateOfAffairs1 driving at 100km/h http://ns.inria.fr/nrv-inst#speed 100
http://ns.inria.fr/nrv-inst#StateOfAffairs1 driving at 100km/h http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://ns.inria.fr/nrv-inst#Driving
http://ns.inria.fr/nrv-inst#StateOfAffairs1 driving at 100km/h http://www.w3.org/2000/01/rdf-schema#label "driving at 100km/h"@en
Named Graph (state of affair) Subject Predicate Object
http://ns.inria.fr/nrv-inst#StateOfAffairs2 Jim http://ns.inria.fr/nrv-inst#activity driving at 90km/h
http://ns.inria.fr/nrv-inst#StateOfAffairs2 Jim http://www.w3.org/2000/01/rdf-schema#label Jim
http://ns.inria.fr/nrv-inst#StateOfAffairs2 can't drive over 90km http://www.w3.org/1999/02/22-rdf-syntax-ns#type compliant requirement
http://ns.inria.fr/nrv-inst#StateOfAffairs2 can't drive over 90km has for compliance http://ns.inria.fr/nrv-inst#StateOfAffairs2
http://ns.inria.fr/nrv-inst#StateOfAffairs2 driving at 90km/h http://ns.inria.fr/nrv-inst#speed 90
http://ns.inria.fr/nrv-inst#StateOfAffairs2 driving at 90km/h http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://ns.inria.fr/nrv-inst#Driving
http://ns.inria.fr/nrv-inst#StateOfAffairs2 driving at 90km/h http://www.w3.org/2000/01/rdf-schema#label "driving at 90km/h"@en
Legal Rules on the Semantic Web
OWL + Named Graphs + SPARQL Rules
Future: differentiated classes of validity, non-binary modes,…

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