language (formalisms) for ontology building
DESCRIPTION
Language (Formalisms) For Ontology Building. Neda Alipanah 22 October 2012. Content. Why Ontologies ? Machine Process able Knowledge Knowledge Exchange Big Data Relevant Technologies Layered Architecture Building Tools and Visualization Ontology Application Information Integration - PowerPoint PPT PresentationTRANSCRIPT
Language (Formalisms) For Ontology Building
Neda Alipanah22 October 2012
ContentWhy Ontologies?
Machine Process able Knowledge Knowledge Exchange Big Data
Relevant Technologies Layered Architecture Building Tools and Visualization
Ontology Application Information Integration Web Database Management Web Services
Why Ontologies? 1. Machine readable and understandable
process of data
2. Consistent Knowledge Presentation for Enterprise application integration (Knowledge Exchange)
3. Nodes and links that essentially form a very large database with specific rules
Why Ontologies? 1. Machine readable and understandable process of
data
John Smith is Assistant
Professor of Computer Science in University of X.
He is teaching several courses including Course
A, B, C.
Assistant
Professor
John Smith
University X
Why Ontologies? 2. Consistent Knowledge Presentation for
Enterprise application integration (Knowledge Exchange)
Disease
PatientSymptom
s
Address
Why Ontologies? 3. Nodes and links that essentially form a very
large database with specific rules. Database capture the data and relations (Entity Relations) but not the semantic and rules
Concept 1 is reverse of Concept 2. Concept 2 is subclass of Concept 3. Concept 100 has isA relation with Concept 2000 and is reverse of Concept 500.
Disease
PatientSymptom
s
Address
ContentWhy Ontologies?
Machine Process able Knowledge Knowledge Exchange Big Data
Relevant Technologies Layered Architecture Building Tools and Visualization
Ontology Application Information Integration Web Database Management Web Services
Technologies- Layered Architecture
Tim Berners Lee Architecture
XML/XML Schemas
RDF/Ontologies
Rules/Query
Logic, Proof and TrustTRUST
OtherServices
URI/UNICODE
PRIVACY
Technologies- Layered Architecture
URI (Uniform Resource Identifiers): ◦ Simple and Extensible means for Identifying a Resource◦ Universal Resource Identifiers in WWW◦ Example http://www.nih.gov/
http://www.ncbi.nlm.nih.gov/gap
http://www.ucsd.edu
http://www.semanticwe
b/JohnSmith
What is XML about?XML= eXtensible Markup Language by
the W3C (World Wide Web Consortium)Transport and Store Data (Structured
Knowledge)Key to XML is Document Type
Definitions (DTDs)◦Defines the role of each element of text in a
formal modelCompound Documents(Multiple files)
XML Example
Patents
Funds
Year: 2002
Name: U. Of X
ExpensesName:BioInformatics titleAuthorID
Asset report
Assets
Dept
Equipment
news
Patent
Other assets
Grants
Contracts
XML File Example<Professor credID=“9” subID = “16: CIssuer = “2”>
<name> Alice Brown </name><university> University of X <university/><department> CS </department><research-group> BioInformatics</research-
group></Professor>
<Secretary credID=“12” subID = “4: CIssuer = “2”><name> John James </name><university> University of X <university/><department> BioInformatics </department><level> Senior </level>
</Secretary>
Technologies- Layered Architecture
Tim Berners Lee Architecture
XML/XML Schemas
RDF/OWL Ontologies
Rules/Query
Logic, Proof and TrustTRUST
OtherServices
URI/UNICODE
PRIVACY
RDFRDF = Resource Description FrameworkAdds semantics with the use of ontologies,
XML syntax
RDF Concepts◦ Basic Model
Resources, Properties and Statements
◦ Container Model Bag, Sequence and Alternative
RDFRDF/RDFS Elements
◦ Class (School, Department, Person) Rdfs:SubClassOf
◦ Properties (Works) Rdfs:SubPropertiesOf
◦ Domain and Range of Property Rdfs: domain (School) Rdfs: range (Person)
School
Department
SubClass
Person
Works
RDF vs. XML Views
<product><title>iPhone</title><price>$200</price>
</product>
<product title=”iPhone”>
<price>$200</price></product>
An iPhone is a Product that has a price of $200″
XML Views<owl:Class rdf:about="&OntTeaching;Product"/><owl:NamedIndividual
rdf:about="&OntTeaching;Product1"> <rdf:type rdf:resource="&OntTeaching;Product"/>
<rdfs:label
rdf:datatype="&xsd;Name">iPhone</rdfs:label> <price rdf:datatype="&xsd;decimal">200</price>
</owl:NamedIndividual>
OntTeaching:product1 rdf:type OntTeaching:Product OntTeaching:product1 OntTeaching:title “iPhone”
OntTeaching:product1 price “200″RDF View
OWL Web Ontology LanguageOWL: Semantic Markup Language for
Publishing/Sharing Ontologies Enumeration on Classes<owl:Class> <owl:oneOf rdf:parseType="Collection"> <owl:Thing rdf:about="#Europe"/> <owl:Thing rdf:about="#Africa"/> <owl:Thing rdf:about="#NorthAmerica"/> <owl:Thing rdf:about="#SouthAmerica"/> <owl:Thing rdf:about="#Australia"/> <owl:Thing rdf:about="#Antarctica"/> </owl:oneOf> </owl:Class>
OWL Web Ontology LanguageOWL
◦Value Constraints OWL:ALLVALUESFROM OWL:SOMEVALUESFROM OWL:HASVALUE
<owl:Restriction> <owl:onProperty rdf:resource="#hasParent" /> <owl:someValuesFrom rdf:resource="#Physician" /> </owl:Restriction>
<owl:Restriction> <owl:onProperty rdf:resource="#hasParent" /><owl:hasValue rdf:resource="#Clinton" /></owl:Restriction>
OWL Web Ontology Language
OWL: Cardinality constraints OWL:MAXCARDINALITY OWL:MINCARDINALITY OWL:CARDINALITY
<owl:Restriction> <owl:onProperty rdf:resource="#hasParent" /> <owl:cardinality rdf:datatype="&xsd;nonNegativeInteger">2</owl:cardinality> </owl:Restriction>
OWL Web Ontology Language
OWL: Intersection, union and complement OWL:INTERSECTIONOF OWL:UNIONOF OWL:COMPLEMENTOF
Not Meat
<owl:Class> <owl:complementOf> <owl:Class rdf:about="#Meat"/> </owl:complementOf> </owl:Class>
<owl:Class><owl:unionOf rdf:parseType="Collection"> <owl:Class> <owl:oneOf rdf:parseType="Collection"> <owl:Thing rdf:about="#Tosca" /> <owl:Thing rdf:about="#Salome" /> </owl:oneOf> </owl:Class> <owl:Class> <owl:oneOf rdf:parseType="Collection"> <owl:Thing rdf:about="#Turandot" /> <owl:Thing rdf:about="#Tosca" /> </owl:oneOf> </owl:Class> </owl:unionOf> </owl:Class>
OWL Web Ontology Language
OWL: Equivalent Class, Disjoint Class
<owl:Class rdf:about="#Man"> <owl:disjointWith rdf:resource="#Woman"/> </owl:Class>
<owl:Class rdf:about="#DaPonteOperaOfMozart"> <owl:equivalentClass> <owl:Class> <owl:intersectionOf rdf:parseType="Collection"> <owl:Restriction> <owl:onProperty rdf:resource="#hasComposer"/> <owl:hasValue rdf:resource="#Wolfgang_Amadeus_Mozart"/></owl:Restriction> <owl:Restriction> <owl:onProperty rdf:resource="#hasLibrettist"/> <owl:hasValue rdf:resource="#Lorenzo_Da_Ponte"/> </owl:Restriction> </owl:intersectionOf></owl:Class> </owl:equivalentClass> </owl:Class>
How to Build OWL/RDF files?Do we need to remember all the
OWL language syntax?How to do it easy to use and
remember?
ContentWhy Ontologies?
Machine Process able Knowledge Knowledge Exchange Big Data
Relevant Technologies Layered Architecture Building Tools and Visualization
Ontology Application Information Integration Web Database Management Web Services
How to Build RDF/OWL files?Different Building and
Visualization Tools◦Protégé, http://protege.stanford.edu/◦Gruff,
http://www.franz.com/agraph/gruff/(Download version 3.3)
Using Programming Languages◦Java and Jena API◦http://jena.apache.org/ ◦http://jena.sourceforge.net/tutorial/RD
F_API/
Protégé Tool- Open Source Ontology Editor Class Creation
Protégé Tool- Open Source Ontology Editor Property (Object/Data properties)
Protégé Tool- Open Source Ontology Editor Individual Creation
Gruff Tool- A Grapher-Based Triple-Store Browser for AllegroGraph1.What is triple Store?
<owl:Class rdf:about="&OntTeaching;Product"/><owl:NamedIndividual
rdf:about="&OntTeaching;Product1"> <rdf:type rdf:resource="&OntTeaching;Product"/>
<rdfs:label
rdf:datatype="&xsd;Name">iPhone</rdfs:label> <price rdf:datatype="&xsd;decimal">200</price>
</owl:NamedIndividual>
Subject Predicate ObjectOntTeaching:product1 rdf:type OntTeaching:Product
OntTeaching:product1 OntTeaching:title “iPhone” OntTeaching:product1 price “200″
Product
Product1
iPhone
200type
title price
Gruff Tool- A Grapher-Based Triple-Store Browser for AllegroGraph
1.Create a New Triple Store2.Choose a Path for the
Ontology3.Load Ontology4.Present the Ontology Triples5.Query the Triples
Gruff Tool- A Grapher-Based Triple-Store Browser for AllegroGraph
Gruff Tool- A Grapher-Based Triple-Store Browser for AllegroGraph
Gruff Tool- A Grapher-Based Triple-Store Browser for AllegroGraph
Programming with OntologiesJava + Jena APICollection of Tools and Java Libraries For Developing Linked-data Apps, Tools and
ServersStore Information in RDF Triples in Directed
GraphsAn Ontology API for Handling OWL and
RDFS OntologiesA Rule-based Inference Engine for
Reasoning with RDF and OWL data sourcesEfficient Storage of Triples on DiskA query engine compliant with the latest
SPARQL
Ontology Building using Jena
http://www.semanticweb.org/ontologies/2012/9/OntTeaching.owl#Product1 http://www.w3.org/1999/02/22-rdf-
syntax-ns#type http://www.semanticweb.org/ontologies/2012/9/OntTeaching.owl#
Product
Product1 http://www.semanticweb.org/ontologies/2012/9/OntTeaching.owl#title
“iPhone”Product1 http://www.semanticweb.org/ontologies/iPhone.Owl#
price “200”
Triples
Ontology: iPhone.owl
Subject Predicate Object
Product
Product1
iPhone
200
typetitle
price
Ontology Building using JenaThe code to create this graph, or model, is simple:// some definitions static String productURI =
"http://www.semanticweb.org/ontologies/Product";
// create an empty Model Model model = ModelFactory.createDefaultModel();
// create the resource Resource product = model.createResource(productURI);
// add the property product.addProperty(title, ”iPhone”); product.addProperty(price, ”200”);
Jena How to read Ontology?
// list the statements in the ModelStmtIterator iter = model.listStatements();
// print out the predicate, subject and object of each statementwhile (iter.hasNext()) { Statement stmt = iter.nextStatement(); // get next statement Resource subject = stmt.getSubject(); // get the subject Property predicate = stmt.getPredicate(); // get the predicate RDFNode object = stmt.getObject(); // get the object
System.out.print(subject.toString()); System.out.print(" " + predicate.toString() + " "); if (object instanceof Resource) { System.out.print(object.toString()); } else { // object is a literal System.out.print(" \"" + object.toString() + "\""); }System.out.println(" .");}
SPARQL QueryQuery on Triples with Exact
Pattern Matching (Subject of query is Product1)
SELECT ?b ?c Where {
<http://www.semanticweb.org/ontologies/2012/9/OntTeaching.owl#Product1> ?b ?c
} Result
ContentWhy Ontologies?
Machine Process able Knowledge Knowledge Exchange Big Data
Relevant Technologies Layered Architecture Building Tools and Visualization
Ontology Application Information Integration Web Database Management Web Services
Ontology ApplicationsThe database of Genotypes and Phenotypes (dbGaP) is
archiving
the results of different Genome Wide Association Studies (GWAS).
• Phenotype variables are not harmonized across studies.
• Redundent phenotype identifiers for the same phenotype.
• dbGaP lacks semantic relations among its variables.• Search on phenotypes is inefficient and inaccurate .• Goal is to standardize dbGaP information to allow
accurate, reusable and quick retrieval of information
Ontology ApplicationsSeveral Available dbGAP Studies
id=”phv00122015”,
Description=”Age at time of Study”,
name=”age”,version=“1”,
Logical Max=”65”,
Logical Minimum=”18”,
unit=”Years”, type=”decimal”
id=”phv00122058”,
Description=”Age of patient at the time of Study”, name=”age”,version=“1”,
Logical Max=”90”,
Logical Minimum=”20”,
unit=”Years”, type=”decimal”
phs000284.v1.pht001901.v1.CFS_CARe_Sample.data_dict_2011_02_07
phs000284.v1.pht001903.v1.CFS_CARe_ECG.data_dict_2011_02_07
Ontology ApplicationsBuilding Information Model
(Ontology)
Individual
Age
id=”phv00122058”
id=”phv00122015”
Ontology ApplicationsInformation Retrieval and
Ranking PhenotypesQuery={Age of Subject}
Study Phenotype Variable
phs000284.v1.pht001901.v1.CFS_CARe_Sample.data_dict_2011_02_07
id=”phv00122058
phs000284.v1.pht001903.v1.CFS_CARe_ECG.data_dict_2011_02_07
id=”phv00122015”
ConclusionBenefits of Structured Data (XML,
OWL)Tools to Create and Visualize
OntologiesJena API for Building Ontologies Sparql Queries on OntologiesApplications uses Ontologies
ContactsNeda AlipanahDivision of Biomedical
Informatics9500 Gilman Dr., Bldg 2 #0203E
Email: [email protected]