Semantic Web Layers. How Semantic Languages Work. Why Go Beyond XML? Bring information together Draw inferences for further processing RDF OWL RDFS

(1)

Franz Inc

Module XIII: Extending OWL with Rules

Executive Overview of Semantic languages

Franz Inc

Semantic Web Layers

Franz Inc

Why Go Beyond XML?

Issue Solution

Same word has two meanings XML

Namespaces

Describe what tags to use, how to use them (syntax) XML Schema

Manage distributed definitions and content RDF

Express relationships between elements RDFS

Express semantics for concepts, instances and relationships OWL

Manage evolution of schema and content OWL

Suppliers and Consumers agree on what tags to use (maybe) Suppliers and Consumers agree on what tags mean (less likely) Each item is described by only one supplier (sure!)

“A small amount of RDF goes a long way” – Jim Hendler

“subclass”, “domain”, “range”

“sameAs”, “differentFrom”, “equivalentClass”, “intersectionOf”, “unionOf”, “complementOf”, “disjointWith”

“cardinality”, “transitive”, “inverseOf”, “symmetricProperty”, “restriction”, “subPropertyOf”, “FunctionalProperty”, “InverseFunctionalProperty” “allValuesFrom”, “someValuesFrom”, “hasValue”, “oneOf” “DeprecatedClass”, “DeprecatedProperty”,” versionInfo”, “priorVersion, “backwardCompatibleWith”, “inCompatibleWith”

Franz Inc

How Semantic Languages Work Bring information together

Draw inferencesfor further processing

RDF

RDFS

OWL

Franz Inc

What is RDF?

RDF (Resource Description Framework) is an infrastructure for:

Encoding,

Exchange and

Distributing metadata

RDF Triple: Subject

Safety Harbor Object

Massage Predicate

offers

Franz Inc

RDF – A Distributed Network of Data!

offeredBy

Safety Harbor _Facial

offers Massage Safety Harbor offers Massage Facial offeredBy Safety Harbor RDF Files: “bags of triples” … …

(2)

Franz Inc

RDFS – A Schema Language for RDF RDFS allows us to create vocabularies

offers Spa Resort rdfs:subClassOf Safety Harbor Massage Treatment Activity rdfs:subClassOf offers rdfs:domain rdf:type Franz Inc RDFS is RDF, Too!

SafetyHarbor offers Massage offers rdfs:domain Safety Harbor rdfs:subClassOf Resort Spa Spa rdf:type Spa rdf:type Resort rdfs:subClassOf Safety Harbor Massage offers Treatment Activity rdfs:subClassOf rdf:type offers rdfs:domain rdfs:range If the bags contain RDFS key symbols, then RDFS can infer

certain conclusions …

…

Franz Inc

OWL – Specify Rich Relationships

SafetyHarbor

Facial offers

offeredBy

Massage

offers owl:inverseOf offeredBy

offeredBy

offers

Franz Inc

The Kennedy Family

Joseph Rose

Rosemary Kathleen Eunice Patricia Jean

Joseph Jr. John Robert Edward hasDaughter hasDaughter hasSon hasSon rdfs:domain Person Person rdfs:range FemalePerson FemalePerson rdfs:domain Person Person MalePerson MalePerson rdfs:range subPropertyOf hasDaughter

hasDaughter hasSonhasSon

Has Has--childchild

Franz Inc

OWL vs. RDF vs. RDFS

OWL and RDFS add no syntax to RDF RDF allows symbols from any package

RDFS uses symbols from the RDFS package OWL uses symbols from the OWL package

Syntactically, RDF = RDFS = OWL

“The difference is in the inference”

Franz Inc

OWL vs. Other Schema (Data Model) Languages

XML schema is used to Validate Database schema is used to interpret RDF schema is used for inference Object Models define behavior OWL Model

Can have multiple uses

(3)

Franz Inc

Limitations of RDF, RDFS & OWL

Class definition and reasoning requiring

numerical computation

For example, VIP customers are those that spent over $1,000 across all purchases in the last 3 months For example, a young man is a MalePerson who is less than

20 years old.

Classification of an individual depends on examining specific relationships between 2 or more other individuals:

For example, city’s first lady is a wife of city’s mayor. Mr. Bloomberg is New York’s mayor. Mrs. Bloomberg is his wife. Is Mrs. Bloomberg New York’s first lady?

Franz Inc

Rules Complement RDF/RDFS/OWL

(4)

Franz Inc.

Module XII – Extending OWL with Rules

Allegro RDF Prolog

Franz Inc.

Limitations of RDF, RDFS & OWL

Class definition and reasoning requiring

numerical computation

For example, VIP customers are those that spent over $1,000 across all purchases in the last 3 months For example, a young man is a MalePerson who is less than

20 years old.

Classification of an individual depends on

examining specific relationships between 2 or more other individuals:

For example, city’s first lady is a wife of city’s mayor. Mr. Bloomberg is New York’s mayor. Mrs. Bloomberg is his wife. Is Mrs. Bloomberg New York’s first lady?

Franz Inc.

Rules Complement RDF/RDFS/OWL

Franz Inc.

Rules Technology

Venerable tradition

Expert Systems (1970’s and 1980’s)

Rules embedded in application code

Not scalable, extendable, maintainable, …

Business Rules

Datalog (DATAbase LOGic)

Sophisticated algorithms (RETE, Magic Sets)

SWRL – a rule exchange language in RDF

Franz Inc.

Rules and RDF – SWRL

Rules can be distributed just like anything

else

Therefore, rules can be expressed in RDF

SWRL (Semantic Web Rule Language) is a

representation of rules in RDF

Franz Inc.

SWRL Rules for Semantic Technology “IFa person has been CEO of a big, Fortune 500 company THENthis person is an important person”

Major:

(?company rdf:type BigCompany) (Fortune500 lists ?company) (?company hasCEO ?person) -> (?person rdf:type ImportantPerson)

Body

Head Rule name

(5)

2

Franz Inc.

OWL vs. SWRL

OWL SWRL

W3C Recommendation Not yet a standard Recent implementations >20 years technology Formal decidability Possibility of Spaghetti _code Restriction language

highly constrained Powerful pattern language

Franz Inc.

SPARQL vs. SWRL

SPARQL SWRL

Complex patterns with

?variables Complex patterns with ?variables Defaults, options, boolean

operations AND only

Filters with math SWRL built-ins for math Run under user/program

control chaining opportunistically Optimized for a single

query Optimized for groups of rules

Franz Inc.

Requirements for Rule Languages

Well-defined language semantics

Formal decidability

Expressive syntax

Standard based

Small set of composable logical operators

Flexibility, reusability …

Extensible syntax

Scalablility

Apply rules to very large data set (e.g., > 1 billion RDF triples)

Franz Inc.

Well-defined

language semantics Yes

Small set of composable

logical operators Yes

Extensible syntax No

Scalablility No

Requirement

Requirement OWL scoreOWL score

The last two no’s deserve more discussion ...

OWL vs. Rule Requirements

Franz Inc.

SPARQL vs. Rule Requirements

Well-defined language semantics

Procedural semantics for access language

logical operators Kitchen sink

Extensible syntax Unfortunate choice of syntax

Scalablility Yes, SPARQL scales

Requirement

Requirement SPARQL hasSPARQL has

Franz Inc.

Well-defined

language semantics Yes

logical operators Yes

Extensible syntax Yes

Scalablility For subsets

Requirement

Requirement CL (Prolog) scoreCL (Prolog) score

CL / Prolog vs. Rule Requirements

(6)

Franz Inc.

Semantic RDF Database Needs …

A Simple QUERY language

An efficient and easy to understand

mechanism for RULES

A server based PROGRAMMING

LANGUAGE

Franz Inc.

Does SPARQL Qualify?

SPARQL is an access language, no rules, no

programming.

No defined way to deal with rules

2+ arity is hell, needs ‘magic predicates’ to help

Negation is hard

Filters should go, replaced by magic predicates Datatype handling is bizarre

No way to deal with unpredictable path lengths (yes, they are working on this)

Franz Inc.

Prolog Almost Qualify

Query language + Rules + Full programming

language + a Standard language

And very fast:

AllegroGraph RDFS++ reasoner is implemented

in Prolog

For 1.1 Billion triples for the Leheigh University Benchmark: 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 12 34 5678 910 11 12 13 14 S e c o n d s Queries

LUBM(8000) with long queries zeroed

A lleg roGraph 3.2 Othe r

Franz Inc.

PROLOG

AllegroGraph Rule Language

Franz Inc.

Prolog Rule – Based On Unification

A function call returns an output value

based on the input supplied

(+ 1 (* 2 3) 4) => 11 (append ‘(1 3) ‘(5)) => (1 3 5) (member 3 '(1 3 5)) => (3 5)

+, appendand memberare functions

A Prolog functorwill try to unify the

“input” and “output” arguments

Franz Inc.

Prolog Functor: append

(?- (append ?x ?y (1 3 5))) ?x = () ?y = (1 3 5); ?x = (1) ?y = (3 5); ?x = (1 3) ?y = (5); ?x = (1 3 5) ?y = (); No. (?- (append (1 3) (5) ?z)) ?z = (1 3 5); No. (?- (append (1) ?y (?x 3 5))) ?y = (3 5) ?x = 1; No.

(7)

4

Franz Inc.

Prolog Functor: member

(?- (member ?x (1 3 5))) ?x = 1; ?x = 3; ?x = 5; No. (?- (member 1 (?x 3 5))) ?x = 1; No. (?- (member (1 ?x) ((?y 3) 5))) ?x = 3 ?y = 1; No.

Franz Inc.

Allegro Prolog as Query Language

Unify over RDF database with q functor

(q ?person rdf:type :Patriarch)

A much more powerful query language for

RDF triples, more versatile than SPARQL

An industrial strength Prolog embedded in

Allegro CL, geared to RDF query

Conform to Clocksin & Mellishs Prolog and

ISO kernel specification

Prolog clauses are compiled to Lisp then to machine code, running at processor speed

Franz Inc.

Basic Allegro Prolog Syntax for RDF

The functor q-&qtells RDF Prolog to look

for data for variable unification in the AllegroGraph triple database

q- only search the original triples q include inferred triples in the search

By convention, all Prolog variables start

with a “?”, e.g., ?company, ?person, to separate them from Lisp variables

Franz Inc.

Encapsulated / Federated Encapsulated / Federated

RDF Database RDF Database

Allegro Prolog Query Language

A very expressive query language, finding

semantic relations in RDF database automatically Query can be applied to inferred RDF triples,

combining with semantic reasoning

Asserted RDF Triples Inferred RDF Triples RDFS++ Reasoning Prolog Query Engine

Semantic Applications

Franz Inc.

selectWrapper in Lisp

(select… ) returns the values of unified variables in a list, for further processing by application code (select(?x ?y) (append ?x ?y (1 3 5))) (("nil" (1 3 5)) ((1) (3 5)) ((1 3) (5)) ((1 3 5) "nil")) (select (?person)

(q- ?person rdf:type :Patriarch)) (({person1}))

Franz Inc.

Allegro Prolog as Rule Language

Assert a fact or rule

<-- clause : (<--(ImportantPerson ?person) … ) starts a new rule

<- clause : (<-(ImportantPerson ?person) … ) add to the rule

Iteratively prove the concatenation of

clauses

(select ?person (ImportantPerson ?person) ) Allegro Prolog will look for data (maybe in RDF

database) that unifies the variables and satisfies ALL the clauses

(8)

Franz Inc.

Rule in SWRL and Allegro Prolog

Rule in SWRL

Major:

(?company rdf:type BigCompany) (Fortune500 lists ?company) (?company hasCEO ?person) -> (?person rdf:type ImportantPerson)

Rule in Prolog (1) Rule in Prolog (1)

(<-- (ImportantPerson ?person) (q ?company rdf:type BigCompany) (q Fortune500 lists ?company) (q ?company hasCEO ?person) )

Rule in Prolog (2) Rule in Prolog (2)

(<-- (MajorCompany ?company) (q ?company rdf:type BigCompany) (q Fortune500 lists ?company) ) (<-- (ImportantPerson ?person)

(MajorCompany ?company) (q ?company hasCEO ?person) )

Franz Inc.

The Kennedy Family

Joseph Rose

Rosemary Kathleen Eunice Patricia Jean

Joseph Jr. John Robert Edward

hasDaughter hasDaughter hasSon hasSon rdfs:domain Person Person rdfs:range FemalePerson FemalePerson rdfs:domain Person Person MalePerson MalePerson rdfs:range subPropertyOf hasDaughter

hasDaughter hasSonhasSon Has Has--childchild

Franz Inc.

© Copyright 2011 Franz Inc. slide 27 (<-- (male ?x) (q- ?x !ex:sex !ex:male)) (<-- (female ?x) (q- ?x !ex:sex !ex:female)) (<-- (father ?x ?y) (male ?x) (q ?x !ex:has-child ?y)) (<-- (mother ?x ?y) (female ?x) (q ?x !ex:has-child ?y)) (<-- (parent ?x ?y) (father ?x ?y)) (<- (parent ?x ?y) (mother ?x ?y)) (<-- (grandparent ?x ?y) (parent ?x ?z) (parent ?z ?y)) (<-- (grandchild ?x ?y) (grandparent ?y ?x)) (<-- (ancestor ?x ?y) (parent ?x ?y)) (<- (ancestor ?x ?y) (parent ?x ?z) (ancestor ?z ?y)) (<-- (descendent ?x ?y) (ancestor ?y ?x)) Building Semantic Relations with RDF Prolog on RDF Database

Franz Inc.

Building Complex Semantic Relations (<-- (aunt ?x ?y) (parent ?z ?x) (female ?x) (parent ?z ?w) (not(=?x ?w)) (parent ?w ?y)) (<-- (niece ?x ?y) (aunt ?y ?x) (female ?x)) (<- (niece ?x ?y) (uncle ?y ?x) (female ?x)) ?Z ?Y ?X ?W parent parent parent aunt (<-- (uncle ?x ?y) (parent ?z ?x) (male ?x) (parent ?z ?w) (not (= ?x ?w)) (parent ?w ?y)) (<-- (nephew ?x ?y) (aunt ?y ?x) (male ?x)) (<- (nephew ?x ?y) (uncle ?y ?x) (male ?x)) Franz Inc.

“Semantic” Rule Inference

Allegro Prolog rules can be applied to inferred RDF triples, combining rule inference and

semantic reasoning Encapsulated / Federated Encapsulated / Federated RDF Database RDF Database Asserted RDF Triples Inferred RDF Triples RDFS++ Reasoning Prolog Rule Engine

Semantic Applications

Prolog Rules

Franz Inc.

Interact with AllegroGraph Database

All “data” values stored in the DB as UPI’s;

convert to its original value with lisp function upi->value, e.g.,

(upi->value ?birth-year)

Data need to be converted to UPI before

it can be compared with db values, e.g.,

(literal “Maria Shriver“)

Use (read-from-string …) to convert a string (come out of DB) to its native type

(9)

6

Franz Inc.

Execute Lisp Code inside Prolog

(lisparg form) : Execute Lisp form(code) inside Prolog, the result of executing the

formis returned to Prolog variable, arg

(lispform) : For side effect only

(lisppform): unified if formreturns “true”

(select (?name ?birth-year) (q- ?person rdfs:label ?name) (q- ?person :birth-year ?birth-year) (lispp (>= (read-from-string

(upi->value ?birth-year)) 1965) ) )

Franz Inc.

Execute Prolog Rules Inside Lisp

(prolog…) : invoke prolog inside Lisp code

(lisparg form) : Execute Lisp code inside

Prolog, the result is returned to arg

(lispform) : For side effect only

(defun animal-friends-of (person) (let ((list-friends nil))

(prolog

(lisp?person person) (q ?person :likes ?x) (q ?x rdf:type :animal) (lisp(pushnew ?x list-friends))) list-friends))

Franz Inc.

RDF Prolog Exercise

Using Allegro Prolog in AllegroGraph

Using Prolog query and rules on Kennedy

database

Franz Inc.

Use Prolog to Find Maria Shriver & Her Birth Year

(select (?p ?year)

(lisp ?name (literal "Maria Shriver ")) (q- ?p !rdfs:label ?name)

(q- ?p !ex:birth-year ?year))

Assuming that the data has NOT been normalize Use lispfunctor to bind a value from Lisp to Prolog

Franz Inc.

Find All Ancestors of Maria Shriver (select (?name)

(lisp ?y !ex:person26) (ancestor ?x ?y)

(q- ?x !rdfs:label ?name))

(select (?name) (:distinct t) (lisp ?y !ex:person26) (ancestor ?x ?y) (q- ?x !rdfs:label ?name)) Franz Inc.

Find All Ancestors of Maria Shriver (let ((anc nil)

(anc-list nil)) (setq anc (select (?name)

(lisp ?y !ex:person26) (ancestor ?x ?y)

(q- ?x !rdfs:label ?name))) (dolist (e anc)

(pushnew (first e) anc-list)) anc-list)

(10)

Franz Inc.

Find Nieces of Edward Kennedy (select (?niece ?name)

(lisp ?edward (literal "Edward Kennedy ")) (q- ?p !rdfs:label ?edward)

(niece ?niece ?p)

(q- ?niece !rdfs:label ?name))

Franz Inc.

Find Old Men (borne before 1950) in Kennedy Family (<-- (old-kennedy ?x) (male ?x) (q- ?x !ex:birth-year ?year) (lispp (< (read-from-string (upi->value ?year)) 1950))) (select (?name) (old-kennedy ?x) (q- ?x !rdfs:label ?name)) © Copyright 2011 Franz Inc. slide 38

Franz Inc.

Old Living Men in Kennedy Family

(<-- (OldMan ?person)

(q- ?person !ex:birth-year ?birth-year) (q ?person !rdf:type !ex:MalePerson) (not(q ?person !ex:death-year ?death-year))

(lispp (< (read-from-string (upi->value ?birth-year)) 1950)) )

(select (?name) (OldMan ?x)

(q- ?x !rdfs:label ?name) )

<- Negation

Franz Inc.

Young Men (borne after 1965) in Kennedy Family

(<-- (YoungMan ?person)

(q- ?person !ex:birth-year ?birth-year) (q ?person !rdf:type !ex:MalePerson) (lispp (>= (read-from-string (upi->value ?birth-year)) 1965)) ) (select (?name) (YoungMan ?x) (q- ?x !rdfs:label ?name) )

Franz Inc.

Expressive Logics are Coming to RDF

SPARQL OWL

First Order Logic Logic Programs Common Logic, Prolog

SILK RIF

RDF

No Semantics

Franz Inc.

Franz Rule Language

Rule language for AllegroGraph RDF store

Has expressive syntax – CLIF (Common

Logic Interchange Format)

Has a well-defined, constructive semantics

Aligns as much as possible with an existing

(11)

8

Franz Inc. Prefix CLIF Infix CLIF SPARQL ACL Prolog Translator CLIF Translator Franz Inc. Events Container Container Actions Decision Engine “Sesame” AllegroGraph Triple Store DB Event Ingestion Scheduled Events Inference Engine Business Business Rules Rules Bayesian Belief Network Events Events CRM Operational Systems Operational Systems

Event Data Sources Event Data Sources

Amdocs Event Collector Work Bench CRM RM Amdocs Integration Framework OMS NW Web 2.0

Amdocs Intelligent Decision Automation

Trillion Triples

Franz Inc.

Copyright Franz Inc. 45

Franz Inc.

Dr. Sheng-Chuan Wu

[email protected] Thank You