ontologies? semantic web? owl? – making sense of it all
DESCRIPTION
Ontologies? Semantic Web? OWL? – Making sense of it all. Presenters [email protected] [email protected] [email protected] www.ibcn.intec.ugent.be INTEC Broadband Communication Networks (IBCN) Department of Information Technology (INTEC) - PowerPoint PPT PresentationTRANSCRIPT
Ontologies? Semantic Web? OWL? – Making sense of it all
[email protected]@intec.ugent.beStijn.Verstichel@intec.ugent.bewww.ibcn.intec.ugent.beINTEC Broadband Communication Networks (IBCN)Department of Information Technology (INTEC)Ghent University - IBBT
2
The ontology cloud
Semantic Web
Ontology
OWL
Formal logic
Reasoning
RDF
SWRL
SPARQL
3
The evolution of the Web
Connections between people
Con
nect
ions
bet
wee
n In
form
atio
n
Social Networking
Groupware
JavascriptWeblogs
Databases
File Systems
HTTPKeyword Search
USENET
Wikis
Websites
Directory Portals
2010 - 2020
Web 1.0
2000 - 2010
1990 - 2000
PC Era1980 - 1990
RSSWidgets
PC’s
2020 - 2030
Office 2.0
XML
RDF
SPARQLAJAX
FTP IRC
SOAP
Mashups
File Servers
Social Media Sharing
Lightweight Collaboration
ATOM
Web 3.0
Web 4.0
Semantic SearchSemantic Databases
Distributed Search
Intelligent personal agents
JavaSaaS
Web 2.0 Flash
OWL
HTML
SGML
SQLGopher
P2P
The Web
The PC
Windows
MacOS
SWRL
OpenID
BBS
MMO’s
VR
Semantic Web
Intelligent Web
The Internet
Social Web
Web OS
4
The limitations of keyword search
Amount of data
Pro
duct
ivity
of S
earc
h
Databases
2010 - 2020
Web 1.0 2000 - 2010
1990 - 2000
PC Era1980 - 1990
2020 - 2030
Web 3.0
Web 4.0
Web 2.0 The World Wide Web
The DesktopKeyword search
Natural language search
Reasoning
Tagging
Semantic SearchThe Semantic Web
The Intelligent Web
Directories
The Social Web
Files & Folders
5
Semantic Web – Adding meaning to data
Different methods to add semantics to data: Tagging Statistics Linguistics Ontology – Semantic Web AI
Semantic Web: Set of open standards by the W3C to add semantics (meaning) to data
6
Ontology - OWL
“An ontology is a specification of a conceptualization in the context of knowledge description”
Pizza Meathas_topping *
Is a
SalamiSpiciness
Vegetarian PizzaPizzaNot(has_topping some Meat)
7
Ontology - OWL
Structured knowledge representation
Domain Application
Sharing – Reuse
Support communication
Capture knowledge formally Reasoning Extract new knowledge
8
RDF – Store data as “triples”
the subject, which is an RDF URI reference or a blank node
the predicate, which is an RDF URI reference
the object, which is an RDF URI reference , a literal or a blank node
Femke IBCNWorks_at
Subject
Predicate
Object
The Semantic Web
9
The semantic graph connects everything…
EmailsCompanies
Products
Services
Web Pages
Multimedia
Documents
Events
Projects
Activities
Interests
Places
People
Groups
The social graph just connects people
Better search
More targeted ads
Smarter collaboration
Deeper integration
Richer content
Better personalization
10
SWRL - SPARQL
SWRL Define rules by using domain concepts Add more expressivity then pure OWL
Person(?p) ^ hasSalaryInPounds(?p, ?pounds) ^ swrlb:multiply(1.9, ?pounds, ?dollars) -> hasSalaryInDollars(?p, ?dollars)
SPARQL Query data Similar to SQL but optimized for RDF data
PREFIX foaf: <http://xmlns.com/foaf/0.1/> SELECT ?name WHERE { ?person foaf:mbox <mailto:[email protected]> . ?person foaf:name ?name . }
11
Layered cake of the Semantic Web
OWL
SWRL & SPARQL
Reasoning
Data triples
Tutorial: Building an OWL Ontology
Department of Information Technology – Broadband Communication Networks (IBCN) 12
Named & Disjoint Classes
Department of Information Technology – Broadband Communication Networks (IBCN) 13
Class Hierarchy
Department of Information Technology – Broadband Communication Networks (IBCN) 14
Object Properties
Department of Information Technology – Broadband Communication Networks (IBCN) 15
Object Property Characteristics
Department of Information Technology – Broadband Communication Networks (IBCN) 16
Property Domains & Ranges
Department of Information Technology – Broadband Communication Networks (IBCN) 17
Property Restrictions
A restriction describes an anonymous class of individuals based on the relationships that members of the class participate in.
3 main categories: Quantifier Restrictions
Existential restrictions Universal restrictions
Cardinality Restrictions hasValue Restrictions
Department of Information Technology – Broadband Communication Networks (IBCN) 18
Existential Restriction
Department of Information Technology – Broadband Communication Networks (IBCN) 19
Reasoning
Key Features Classification:
Test whether or not one class is a subclass of another class
Consistency checking Check whether or not it is possible for a class to
have any instances
Department of Information Technology – Broadband Communication Networks (IBCN) 20
Consistency Checking
Department of Information Technology – Broadband Communication Networks (IBCN) 21
Necessary & Sufficient Conditions
Primitive Class Class that only has
‘necessary’ conditions Defined Class
Class that has at least one set of ‘necessary and sufficient’ conditions
Department of Information Technology – Broadband Communication Networks (IBCN) 22
Automated Classification
Computing subclass- superclass relationships vital to keep large ontologies in logically correct state
Department of Information Technology – Broadband Communication Networks (IBCN) 23
Universal Restrictions
Constrain the relationships along a given property to individuals that are members of a specific class
They don’t specify the existence of a relationship
Department of Information Technology – Broadband Communication Networks (IBCN) 24
Open World Assumption
It cannot be assumed that something does not exist until it is explicitly stated that it does not exist!
Closed World Assumption (programming languages, databases, …)
Department of Information Technology – Broadband Communication Networks (IBCN) 25
Closure Axiom
Department of Information Technology – Broadband Communication Networks (IBCN) 26
Value Partition
Restricting the possible values for a property to an exhaustive list
Design Pattern
Department of Information Technology – Broadband Communication Networks (IBCN) 27
Value Partition
Department of Information Technology – Broadband Communication Networks (IBCN) 28
Cardinality Restrictions
For property P, cardinality restrictions describe the minimum, maximum or exact number of P relationships that an individual can participate in
Department of Information Technology – Broadband Communication Networks (IBCN) 29
Qualified Cardinality Restriction
Department of Information Technology – Broadband Communication Networks (IBCN) 30
Datatype Properties
Department of Information Technology – Broadband Communication Networks (IBCN) 31
Data Properties
Department of Information Technology – Broadband Communication Networks (IBCN) 32
Open World Reasoning bis
Department of Information Technology – Broadband Communication Networks (IBCN) 33
Open World Reasoning bis
Department of Information Technology – Broadband Communication Networks (IBCN) 34
hasValue Restriction
Department of Information Technology – Broadband Communication Networks (IBCN) 35
Enumerated Classes
Department of Information Technology – Broadband Communication Networks (IBCN) 36
Multiple Sets of Necessary & Sufficient Conditions
Department of Information Technology – Broadband Communication Networks (IBCN) 37
Ontologies – more than just a datamodel … but !
39
Important Consideration
ONTOLOGY≠
DATA-MODEL
ONTOLOGY=
DOMAIN-MODEL
40
Three common layers
LOGIC
Ontology
Rules
Application
+/- STATIC
DYNAMIC
REUSE
41
What do you need in an ontology-based application?
Data
Sources• Legacy• Ontology
A-Box• ….
Persistency• Relational DB• Files• Triple Store
Reasoning• Pellet• Fact++• …• None
Rules• Jess• Bossam• …• None
Appl’on Support• Jena• Sesame• Redland• …
SHARED ONTOLOGY MODEL
42
Typical Ontology Service
MySQL
JENA D2RQ
JOSEKI
SPARQL
PopulatorA
PopulatorB
PopulatorC
PopulatorD
SPARQL
SDB
TDB
Spreadsheet
RDF123
SPARQL
PopulatorE
43
D2R-Server: Treating Non-RDF Databases as Virtual RDF Graphs
44
RDF123 is an application and web service to generate RDF data from spreadsheets
45
Recent commercial initiatives
Ontology.com Thinking Service Models
Metatomix Semantic web-based solutions for Enterprise Resource
Interoperability TopQuadrant
Making Information Work for the Enterprise Semantic Discovery Systems
Beyond Business Intelligence, from Analytics to Discovery Oracle 11g
Open, scalable, secure and reliable RDF management
46
Every feature at a certain cost
Genericness Performance
SWRL Rules
First-Order Logic Concepts
A-Box Size
Domain Modeling
Application Reuse
Questions [email protected]@intec.ugent.beStijn.Verstichel@intec.ugent.bewww.ibcn.intec.ugent.beINTEC Broadband Communication Networks (IBCN)Department of Information Technology (INTEC)Ghent University - IBBT
Some slides and graphs borrowed from the presentation “Making sense of the Semantic Web” by Nova Spivackhttp://www.mindingtheplanet.net