Experiences Using Deliberation RuleML 1.01 as a Rule Interchange Language

Experiences Using
Deliberation RuleML 1.01 as
a Rule Interchange Language
Do Rulebases Need an External Vocabulary?
Matthias Tylkowski and Martin Müller
Binarypark, Erich-Weinertstr. 1, 03044 Cottbus, Germany
The 8th International Web Rule Symposium Prague, Czech Republic, August 18-20, 2014

RuleML Basics
• Individuals, Data, Atomic statements, logical
formulas, rules, quantifiers
• Hierarchical sub-languages – RuleML lattice
• Support for various semantics
• Schema configurability via MYNG 1.01
• Design based on Relax NG and XML Schema
The 8th International Web Rule Symposium Prague, Czech Republic, August 18-20, 2014 2

UServ Product Derby
• Describes a virtual car insurance company
• Business model based on business rules
• Traditional object-oriented data model
o classes (Car, Driver, ConvertibleCar, …),
o properties (price, eligibilityScore, potentialTheftRating )
o objects (car1, car2, …)
If all of the following are true, then the car’s potential theft rating is low:
- car’s price is less that $20,000
- car model is not on the list of “High Theft Probability Auto”
Any senior driver is not a young driver.
3

Individuals, Data and Variables (1)
RuleML Support:
• IRIs (@iri) to provide unique names for individuals. Typing
of individuals (@type)
• Declaration of property values for individuals.
<Atom>
<oid>
<Ind iri="http://userv.org/ontology/i/a9fccd3a-a851-4e80-de3a8c2e15ba"
type="http://userv.org/ontology/LuxuryCar">
</Ind>
</oid>
<slot>
<Rel iri="http://userv.org/ontology/price">price</Rel>
<Data xsi:type="xs:positiveInteger">39000</Data>
</slot>
</Atom>
4

RuleML Support:
• Best practice of declarative definition of instances (facts)
by atoms/formulas (푙푢푥푢푟푦퐶푎푟 becomes a type)
<Assert>
푙푢푥푢푟푦퐶푎푟 푐푎푟4 ∧ 푐푎푟푀표푑푒푙 푐푎푟4, ′Honda Odyssey′ ∧ 푝푟푖푐푒 푐푎푟4, 39000 .
<Atom>
<Rel iri="http://userv.org/ontology/carModel"/>
type="http://userv.org/ontology/LuxuryCar">car4</Ind>
<Data xsi:type="xs:string">Honda Odyssey</Data>
</Atom>
<Atom>
<Rel iri="http://userv.org/ontology/price">price</Rel>
</Atom>
</Assert>
5

RuleML Support:
• Beyond the logic programming tradition, allows typing of XML
data(@xsi:type). However, only RuleML supported XML
datatypes are permitted.
• Typed variables (@type).
<Var type="http://userv.org/ontology/ConvertibleCar">C</Var>
<Data type="us:Rating">
<us:ratingValue xsi:type="xs:positiveInteger">4</us:ratingValue>
<us:ratingVerbalization xml:lang="en">
high
</us:ratingVerbalization>
</Data>
6
• No typing of User-defined structured data

UServ - Design
• Object instances (such as specific cars) map to
RuleML individuals
• Classes map to RuleML unary relations.
• Type classification (aka classes) can also be
declared explicitly inside typed variables or typed
individuals
• Properties map to RuleML binary relations
• Rules are based on ontology models
• UServ rules are based on relations and properties
defined by an external ontology (accessible via
RuleML @type ) – the rule vocabulary .
7

Encoding Types/Classes
RuleML Support:
• Type/class encoding using variables or individuals
• Type/class encoding using atoms with unary relations
<Ind type="us:Car">car4</Ind>
<Var type="us:Car">C</Var>
<Atom>
<Rel iri="us:Car">car</Rel>
<Var>C</Var>
</Atom>
∀퐶 푐푎푟(퐶)
8
푐푎푟(푐푎푟4)

Multi-typing
RuleML Support:
• Explicit typing of individuals
<Assert>
푐푎푟 푐푎푟1 ∧ 푐표푛푣푒푟푡푖푏푙푒퐶푎푟(푐푎푟1)
<Atom>
<Rel iri="http://userv.org/ontology/Car">car</Rel>
<Ind iri="http://userv.org/ontology/i/a9fccd3a-a851-4e80">car1</Ind>
</Atom>
<Atom>
<Rel iri="http://userv.org/ontology/ConvertibleCar">car</Rel>
</Atom>
</Assert>
9

Inheritance (1)
RuleML Support:
• No internal subClassOf inheritance support
• Define inheritance externally (e.g. RDFS) or via of rules
<Implies>
<Atom>
∀퐶 푐표푛푣푒푟푡푖푏푙푒퐶푎푟 퐶 → 푐푎푟(퐶)
<Rel iri="us:ConvertibleCar">convertibleCar</Rel>
<Var>X</Var>
</Atom>
<Atom>
<Rel iri="us:Car">car</Rel>
<Var>X</Var>
</Atom>
</Implies>
10

Inheritance (2)
RuleML Support:
• Rule-based inheritance may introduce complexity in execution.
• Usually search (backtracking) used for multiple inheritance
• Keep inheritance in external vocabulary or use higher-order syntax
<owl:Class rdf:about="http://userv.org/ontology/ConvertibleCar">
<rdfs:subClassOf rdf:resource="http://userv.org/ontology/Car"/>
</owl:Class>
<Atom>
<Rel iri="rdfs:subClassOf">subClassOf</Rel>
<arg index="1">
<Rel iri="us:ConvertibleCar" type="owl:Class">convertibleCar</Rel>
</arg>
<arg index="2">
<Plex>
∀퐶 ([푐표푛푣푒푟푡푖푏푙푒퐶푎푟 퐶 → 푐푎푟 퐶 ] ∨ [푐표푛푣푒푟푡푖푏푙푒퐶푎푟 퐶 → 푙푢푥푢푟푦퐶푎푟 퐶 ]).
<Rel iri="us:Car" type="owl:Class">car</Rel>
<Rel iri="us:LuxuryCar" type="owl:Class">luxuryCar</Rel>
</Plex>
</arg>
</Atom>
퐶표푛푣푒푟푡푖푏푙푒퐶푎푟 ⊑ 퐶푎푟
11

Encoding Properties (1)
<Atom>
<Rel iri="us:price">price</Rel>


</Atom>
<Atom>
∀퐶 푐푎푟(퐶) ∧ 푝푟푖푐푒 퐶, 25000 .
luxuryCar (푐푎푟4) ∧ 푝푟푖푐푒 푐푎푟4, 39000 .
</Atom>
12

Encoding Properties(2)
<Atom>
<Rel iri="us:theftRating">theftRating</Rel>
<Var type="http://userv.org/ontology/LuxuryCar">C</Var>
<Data type="us:Rating" >
<us:ratingValue xsi:type="xs:positiveInteger">4</us:ratingValue>
<us:ratingVerbalization xsi:type="xs:string" xml:lang="en">
high
</us:ratingVerbalization>
</Data>
</Atom>
<Atom>
∀퐶 푙푢푥푢푟푦퐶푎푟 퐶 ∧ 푡ℎ푒푓푡푅푎푡푖푛푔 퐶, 푟푎푡푖푛푔(4, ′high′) .
<Rel iri="us:airbag">airbags</Rel>
<Var type="http://userv.org/ontology/Car">C</Var>
<Plex>
<Data xsi:type="xs:string">driverAirbag</Data>
<Data xsi:type="xs:string">frontAirbag</Data>
</Plex>
</Atom>
13
∀퐶 푐푎푟 퐶 ∧ 푎푖푟푏푎푔푠 퐶, [′driverAirbag′, ′푓푟표푛푡퐴푖푟푏푎푔′]

Encoding Properties (3)
• Definition of properties via external ontology
<Atom>
<Plex>
<Data xsi:type="xs:string">high</Data>
</Plex>
</Atom>
<owl:DatatypeProperty
rdf:about="http://userv.org/ontology/price">
<rdfs:domain rdf:resource=http://userv.org/ontology/Car/>
<rdfs:range>
<owl:Class>
<owl:unionOf rdf:parseType="Collection">
<owl:Class rdf:about="xs:positiveInteger"/>
<owl:Class rdf:about="xs:string"/>
</owl:unionOf>
</owl:Class>
</rdfs:range>
</owl:DatatypeProperty>
14

Built-ins
RuleML Support:
• Tests such as for numerical constraints and list memberships
• Operators with an @iri attribute refer to libraries of built-in
predicates such as one defined by RIF
<Atom>
푃 ≤ 45000.
<Rel iri="pred:numeric-less-than-or-equal">gt</Rel>
<Var type="xs:positiveInteger">P</Var>
<Data xsi:type="xs:integer">45000</Data>
</Atom>
15

Collection membership (1)
RuleML Support:
• List membership tests via use of collections (<Plex>) in atoms
<Atom>
<Rel iri="prolog:member">member</Rel>
<Var>M</Var>
<Plex>
<Ind iri="http://userv.org/ontology/i/5bff7cc6-72f7-4be3">car3</Ind>
<Ind iri="http://userv.org/ontology/i/5eb91389-f1f3-473c">car5</Ind>
</Plex>
</Atom>
16

Collection membership (2)
RuleML Support:
• Collections must be repeatedly given wherever needed
• Best practice to define collection constants via equality
<Equal oriented="yes">
<Ind>HighTheftProbabilityAutoList</Ind>
<Plex>
<Ind iri="http://userv.org/ontology/i/5bff7cc6-72f7-4be3">car3</Ind>
<Ind iri="http://userv.org/ontology/i/5eb91389-f1f3-473c">car5</Ind>
</Plex>
</Equal>
17

Rules and Rulebases (1)
RuleML Support:
• Rules are defined similarly with logical implications, but
many flavours are supported. A rulebase is a set of rules.
<Implies direction="backward">
<Naf>
<Atom>
If the car is a convertible and has no roll
bar, then the potential occupant injury is
extremely high.
<Rel iri="http://userv.org/ontology/hasRollBar">hasRollBar</Rel>
<Var type="http://userv.org/ontology/ConvertibleCar">C</Var>
</Atom>
</Naf>
<Atom>
<Rel iri="http://userv.org/ontology/injuryRating">injuryRating</Rel>
<Var>C</Var>
<Data><us:Value xsi:type="xs:positiveInteger">5</us:Value></Data>
</Atom>
</Implies>
18

Rules and Rulebases (2)
RuleML Support:
• Limited support for annotations of rulebases:
o Logic programming defines a relation by rules. All rules referring
that relation are grouped
o Production rules define a rulebase towards performing a
specific task
• No global identity for rulebases (@iri)
<Rulebase xml:id="theftRating">

<meta>
<Atom>
<Rel iri="http://userv.org/ontology/theftRating">theftRating</Rel>
</Atom>
</meta>
…
</Rulebase>
19

Rulebase Metrics
• This rulebase covers around 40% of the use case
• We encoded:
o 30 rules
o 32 predicates, 5 built-ins
o 11 compound facts, 5 descriptions of individuals
o 7 usages of Naf
o 2 usages of Neg

Conclusion
• RuleML 1.01 can be used as a rule interchange language
• Improvements on handling types, inheritance, collections
and global constants are possible
• UServ design used classes and properties, defined by the
UServ ontology
• Our knowledge base uses NafNegHornlogEq family
• However, except for collections we do not use functions
("Datalog with Plex")
• Equality is used only to define collections as individuals
• Strong negation is used twice because of an explicit
negative information
• NafDatalog+FiniteCollections would be great
21

Acknowledgments
We would like to thank to Tara Athan, Harold Boley,
Adrian Giurca and Adrian Paschke for their essential
feedback and insights.

Useful information sources
• Tutorial introduction (http://ruleml.org/papers/Primer)
• RuleML MediaWiki (http://wiki.ruleml.org)
• RuleML Blog & Social Mediazine
(http://blog.ruleml.org)
• Mailing lists
(http://wiki.ruleml.org/index.php/Mailing_Lists)
• Technical Groups
(http://wiki.ruleml.org/index.php/Technical_Groups)
• RuleML sources hosted on Github
(https://github.com/RuleML)

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