Ontologies and semantic web
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Transcript of Ontologies and semantic web
Ontologies and Semantic Web
STANLEY WANG SOLUTION ARCHITECT, TECH LEAD @SWANG68 http://www.linkedin.com/in/stanley-wang-a2b143b
Ontologies and Semantic Web
• In general, an ontology describes formally a domain of discourse and consists of a finite list of terms and the relationships between the terms;
• The terms denote important concepts, classes of objects of the domain, e.g. in a University Model, staff members, students, courses, modules, lecture theatres, and schools are some important concepts;
In the context of the Web, ontologies provide a shared understanding of a domain,
which is necessary to overcome the difference in terminology.
Ontological Vision of Semantic Web
• An ontology is document or file that formally and in a standardized way defines the hierarchy of classes within the domain, semantic relations among terms and inference rules;
• Sharing semantics of your data across complex distributed applications: Gene Ontology, Glycomics, Pharmaceutical Drug, Treatment-Diagnosis, Repertoire Management, Equity Markets, Anti-Money Laundering, Suspicious Activity Monitoring, OFAC, Financial Risk, Terrorism, Customer Profile, etc;
Ontology model can be Public, Government, Limited Availability, Commercial.
Formal, explicit specification of a shared conceptualization
Machine readable
Concepts, properties, functions, axioms are explicitly defined
Consensual knowledge
Abstract model of some phenomena
in the world
What is an ontology?
What is an Ontology?
A model of (some aspect of) the world
• Introduces vocabulary
relevant to domain, e.g.:
o Anatomy
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What is an Ontology?
A model of (some aspect of) the world
• Introduces vocabulary
relevant to domain, e.g.:
o Anatomy
o Cellular biology
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What is an Ontology?
A model of (some aspect of) the world
• Introduces vocabulary
relevant to domain, e.g.:
o Anatomy
o Cellular biology
o Aerospace
What is an Ontology?
A model of (some aspect of) the world
• Introduces vocabulary
relevant to domain, e.g.:
o Anatomy
o Cellular biology
o Aerospace
o Dogs
What is an Ontology?
A model of (some aspect of) the world
• Introduces vocabulary
relevant to domain, e.g.:
o Anatomy
o Cellular biology
o Aerospace
o Dogs
o Hotdogs
o …
What is an Ontology?
A model of (some aspect of) the world
• Introduces vocabulary
relevant to domain
• Specifies meaning of terms
Heart is a muscular organ that
is part of the circulatory system
What is an Ontology?
A model of (some aspect of) the world
• Introduces vocabulary
relevant to domain
• Specifies meaning of terms
Heart is a muscular organ that
is part of the circulatory system
• Formalised using suitable logic
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PhD Student AssProf
AcademicStaff
rdfs:subClassOf rdfs:subClassOf
cooperate_with
rdfs:range rdfs:domain
<swrc:AssProf rdf:ID="sst">
<swrc:name>Steffen Staab
</swrc:name>
...
</swrc:AssProf>
http://www.aifb.uni-karlsruhe.de/WBS/sst
Anno-
tation
<swrc:PhD_Student rdf:ID="sha">
<swrc:name>Siegfried
Handschuh</swrc:name>
...
</swrc:PhD_Student>
Web
Page
http://www.aifb.uni-karlsruhe.de/WBS/sha URL
<swrc:cooperate_with rdf:resource =
"http://www.aifb.uni-
karlsruhe.de/WBS/sst#sst"/>
instance of instance
of
Cooperate_with
Ontology and Annotation
Links have explicit meanings!
Ontology
Personalization:
is mechanism, which
allows users to have
own conceptual view
and be able to use it for
semantic querying of
search facilities.
“Driver”
“Driver”
“Driver”
“Driver” “Driver”
Common ontology
Search
Ontology Model Example: Customer Profile
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Ontology F-Logic
similar
Ontology F-Logic
similar
PhD Student Doktoral Student
Object
Person Topic Document
Tel
PhD Student PhD Student
Semantics
knows described_in
writes
Affiliation described_in is_about
knows P writes D is_about T P T
D T T D
Rules
subTopicOf
Researcher Student
instance_of
is_a
is_a
is_a
Affiliation
Affiliation
Siggi
AIFB +49 721 608 6554
Ontology Model Example: University Research
A Typical Enterprise Semantic Application Lifecycle
Build Ontology • Build Schema(model level representation)
• Populate with Knowledgebase (people, location, organizations, events)
Automatic Semantic Annotation (Extract Semantic Metadata)
• Any type of document, multiple sources of documents
• Metadata can be stored with or sparely from documents
Applications: semantic search (ranked list of documents), portal integration, summarize & explain, analyze, make decisions;
• Reasoning Techniques: Graph Analysis, Logic Inference
Ontology
Semantic Query
Server
1. Ontology Model Creation (Description) 2. Knowledge Agent Creation
3. Automatic aggregation of Knowledge 4. Querying the Ontology
Ontology Creation and Maintenance
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Ontology Editors and Environments
• Protégé, SWOOP, GrOWL, TopBraid, Ontotrack, SemanticWorks, ..
JENA • Jena is a Java framework for building Semantic Web
applications. It provides a programmatic environment for RDF, RDFS and OWL, including a rule-based inference engine.
• Jena is open source and grown out of work with the HP Labs Semantic Web Program.
• The Jena Framework includes:
• A RDF API
• Reading and writing RDF in RDF/XML, N3 and N-Triples
• An OWL API
• In-memory and persistent storage
• RDQL – a query language for RDF
Jena is one of the most widely used Java APIs for RDF and OWL, providing services for model representation, parsing, database persistence, querying and some visualization tools. Protege-OWL always had a close relationship with Jena. The Jena ARP parser is still used in the Protege-OWL parser, and various other services such as species validation and datatype handling have been reused from Jena. It was furthermore possible to convert a Protege OWLModel into a Jena OntModel, to get a static snapshot of the model at run time. This model, however had to be rebuild after each change in the model.
As of August 2005, Protege-OWL is now much closer integrated with Jena. This integration allows programmers to user certain Jena functions at run-time, without having to go through the slow rebuild process each time. The architecture of this integration is illustrated on the next slide…
Jena Integration of Protégé-OWL
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Jena Integration of Protégé-OWL
The OWLModel API has a new method getJenaModel() to access a Jena view of the Protege model at run-time. This can be used by Protege plugin developers. Many other Jena services can be wrapped into Protege plugins this way, by providing them a pointer to the Model created by Protege.
The key to this integration is the fact that both systems operate on a low-level "triple" representation of the model. Protege has its native frame store mechanism, which has been wrapped in Protege-OWL with the TripleStore classes. In the Jena world, the corresponding interfaces are called Graph and Model. The Protege TripleStore has been wrapped into a Jena Graph, so that any read access from the Jena API in fact operates on the Protege triples. In order to modify these triples, the conventional Protege-OWL API must be used. However, this mechanisms allows to use Jena methods for querying while the ontology is edited inside Protege.
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Joseki - a SPARQL Server for Jena
Joseki: The Jena RDF Server. Joseki is a server for publishing RDF models on the web. Models have URLs and they can be access by HTTP GET. Joseki is part of the Jena RDF framework.
Joseki is an HTTP and SOAP engine supports the SPARQL Protocol and the SPARQL RDF Query language. SPARQL is developed by the W3C RDF Data Access Working Group.
Joseki Features:
RDF Data from files and databases
HTTP (GET and POST) implementation of the SPARQL protocol
SOAP implementation of the SPARQL protocol
Real Life Example: Semantic Application in a Global Bank
• Goal Legislation (PATRIOT ACT) requires banks to identify ‘who’ they are
doing business with;
• Problem Volume of internal and external data needed to be accessed Complex name matching and disambiguation criteria Requirement to ‘risk score’ certain attributes of this data
• Approach Creation of a ‘risk ontology’ populated from trusted sources OFAC ; Sophisticated entity disambiguation Semantic querying, Rules specification & processing
• Solution Rapid and accurate KYC checks Risk scoring of relationships allowing for prioritisation of results; Full visibility of sources and trustworthiness
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Watch List Organization
Company
Hamas
WorldCom
FBI Watch List
Ahmed Yaseer
appears on Watchlist
member of organization
works for Company
Ahmed Yaseer:
• Appears on
Watchlist ‘FBI’
• Works for Company
‘WorldCom’
• Member of
organization ‘Hamas’
Process from Business Perspective
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World Wide Web content
Public Records
BLOGS, RSS
Un-structure text, Semi-structured Data
Watch Lists Law
Enforcement Regulators
Semi-structured Government Data
Scores the entity based on the content and entity relationships
Establishing New Account
Fraud Prevention Application using Semantics
User will be able to navigate the ontology using a number
of different interfaces
Ontology Model
Semantic Technology in Summary
• Semantic Web is not only a technology as many used to name it;
• Semantic Web is not only an environment as many naming it now;
• Semantic Web it is a new context within which one should rethink and re-interpret the existing businesses, resources, services, technologies, processes, environments, products etc. to raise them to totally new level of performance…