Title: Logic Foundation and Services for Semantic Web
1Logic Foundation and Services for Semantic Web
Zhongzhi Shi shizz_at_ics.ict.ac.cn Institute of
Computing Technology Chinese Academy of Scicence
2Outline
- Introduction
- Description Logic
- Dynamic Description Logic
- Agent-based Services
- Ontology-based Knowledge Management KMSphere
- Conclusions
3Semantic Web
- Web was invented by Tim Berners-Lee (amongst
others), a physicist working at CERN - His vision of the Web was much more ambitious
than the reality of the existing (syntactic) Web
a plan for achieving a set of connected
applications for data on the Web in such a way as
to form a consistent logical web of data
an extension of the current web in which
information is given well-defined meaning, better
enabling computers and people to work in
cooperation
This vision of the Web has become known as the
Semantic Web
4Semantics Is Important
- Avoid transformation code between data sets
- Unambiguously capture service profiles
- Enable dynamic discovery of services
- Use reasoners to locate services in yellow
pages - Enable dynamic collaboration of services
- Use reasoners to infer service descriptions and
capabilities - Enable rich, automatic, service orchestration
- Process layer will be far more automated with
semantics
5Adding Semantic Markup
Make web resources more accessible to automated
processes by
- Extend existing rendering markup with semantic
markup - Metadata annotations that describe
content/function of web accessible resources - Useing Ontologies to provide vocabulary for
annotations - Formal specification is accessible to machines
- Semantics given by ontologies
6Ontology
- In philosophy, an ontology is a theory about the
nature of existence. - An ontology is a document or file that formally
defines the relations among terms. - An ontology is a formal, explicit specification
of a shared conceptualization. - The most typical kind of ontology for the Web has
a taxonomy and a set of inference rules.
7Ontologies
- XML DTDs
- Document Type Definition
- Define structure Car application contains a
price (integer), description and colour
- XML Schemas
- Allows richer definitions
- Define structure Car application contains a
price (ve integer between 1 and 20,000),
description and colour (taken from fixed
vocabulary)
- Ontologies
- Define relationships relationship between, say,
a postcode, a town, a suburb, etc - Builds on AI techniques
8The Semantic Web layer cake by Tim Berners-Lee
9Web Ontology Language
- The W3C Web Ontology Working Group (WebOnt) is
tasked with producing a web ontology language
extending the reach of XML, RDF, and RDF Schema.
This language, called OWL, is based on the
DAMLOIL web ontology language.
10The Ontology Language Stack
OWL
DAML-S
DAML-R
DAMLOIL
OIL
DAML-Ont
DC
PICS
RDF Schema
RDF
XOL
HTML
XML Name Space XML Schema
Unicode
URI
11OWL
- Loose-coupling semantics may be decoupled from
the application code (or parsing algorithms) - Machine-actionable automated decisions can be
made from interpretable inferences - Highly expressive can capture core elements of
EER, UML, and frame-based systems - Precision language checking available to
prevent inconsistent/contradictory model
semantics
12Outline
- Introduction
- Description Logic
- Dynamic Description Logic
- Agent-based Services
- Ontology-based Knowledge Management KMSphere
- Conclusions
13Description Logics
- Consistency query results, across vendor
implementations and instances, should be
consistent - Performance Although performance metrics depend
on model constructs, OWL-DL supports highly
optimized inference algorithms - Predictable semantics are mathematically
decidable within the model, reasoning is finite - Foundational provides a baseline inside
applications for layered semantic models - Reliability if the answer to a query is implied
by any of the model data, it will be found
guaranteed.
14Description Logic
- Frame-based system
- Semantic Network
- Object-oriented representation
- Semantic data models
- Ontology language
15Description Logic
- Concepts and Role
- TboxAssertions
- AboxInstance
- Reasoning mechanism in terms of Tbox and Abox
16TBox
TBox Language Set of axioms
Definition Concept name A C, A ? C Father
Man ? ? has-child.Human Human ? Animal ? Biped
17TBox Instance
? Concept entity (one unit predicate,class) Exam
pleStudent, Married x Student(x)
,x Married(x) Bird ? Animal, Man ? Human
? Roles Property (two unit predicate,role) Examp
lesFriend,Loves ltx,ygt Friend(x,y) ,ltx,ygt
Loves(x,y)
18ABox Language(Assertion)
Set of concrete axioms
? Concept assertion aC ExamplesTom is a
student Tom Student Or Student(Tom) John
Man ? ? has-child.Female
? Role assertion Indicate the role between two
objects lta,bgtR ExampleJohn has a child called
Mary ltJohn, Marygt has-child
19Syntax and Semantics
20OWL Class Constructors
21OWL Axioms
22Reasoning in DL
- 1) Subsumption
- 2) consistency
- 3) satisfiability
- 4) instance checking
23 K B
TBox(Scheme) Man Human ? Male Happy-father
Human ? ? Has-child.Female?
Abox(Data) John Happy-father ltJohn,Marygt
Has-child
Reasoning
Interface
24Outline
- Introduction
- Description Logic
- Dynamic Description Logic
- Agent-based Services
- Ontology-based Knowledge Management KMSphere
- Conclusions
25Dynamic Description Logic
- The primitive symbols
- Concept nameC1, C2,
- Role nameR1, R2,
- Individual constanta, b, c,
- Individual variablex, y, z,
- Concept operation?, ?, ?, ?, ?
- Axiom operation?, ?, ??
- ActionA1, A2,
- Action constraction(composition),?
(alternation), (repeat),?(test) - Action variablea,ß,
- Axiom variable?, ?, p,
- State variableu, v, w,
26Dynamic Description Logic
- Concepts in DDL are defined as the following
- (1) Primitive concept P, top ? and bottom ? are
concepts. - (2) ?C, C?D, C?D are concepts.
- (3) ?R.C, ?R.C are concepts.
27Dynamic Description Logic
An action description is the form of
where (1) A is the action name. (2) x1, , xn
are individual variables, which denote the
objects the action operate on. (3) PA is the set
of preconditions, which must be satisfied before
the action is executed. (4) EA is the set of
results, which denote the effects of the action.
28DDL Semantics
- Actions in DDL are defined as the following
- Atom action A(a1, , an) is action.
- If a and ß are actions, then aß, a?ß, a are
actions - If ? is an assertion formula, then ? ? is
action.
29Outline
- Introduction
- Description Logic
- Dynamic Description Logic
- Agent-based Services
- Ontology-based Knowledge Management KMSphere
- Conclusions
30What is a Semantic WS
An ontology to describe Web-services
OWL-S
What a service does? (Discovery)
How the service works? (Composition)
How the service is implemented? (Invocation)
31Composition of Services
- Planning based approaches
- construct a plan from elementary services to
obtain a required functionality. - reasoning based only on component specifications
- plan built every time from scratch
- Knowledge based approaches
- re-use preconfigured templates
- reasoning with specialised knowledge in a narrow
domain - sophisticated domain knowledge is needed
32Web Services Composition
OWL-S
semantics
Commitment Protocols
CTR-S
?-Calc
WSCL
Mealy
BPML
Complexity of glue language
Roman
CSP
WSDL
Complexity of component services
33OWL-S
34OWL-S Context
35Service Description Language SDLSIN
- ltasdl-descrgt(ctype
- service-name name
- context context-name
- types (type-name ltmodifiergt
type) - isa name
- inputs (variable ltmodifiergt
put-type-name) - outputs (variable ltmodifiergt
put-type-name) - input-constraints
(constraint) - output-constrains
(constraint) - io-constrains (constraint)
- concept-description
(ontology-name ontology-body) - state-language name
- concept-language name
- attributes (attributes-name
attributes-value) - text-description name
- )
36OWL-S
OWL-S Interpreter
DDL
Incidences matrixDDL
OWL-S
Petri Net Generator
Petri Net Analysor
Services
37Agent-based Services
38Architecture of Agent
Components
Belief Update
Knowledge base
Action Descriptions
Axioms
Current Belief
Belief Update
Planner
Scheduler
Sensor
Decision Maker
Goal rules
Plan rules
39Metal State Model
- Mental State ltK, A, G, P, I gt,
- Where
- K belief
- A action
- G goal
- P plan
- I intention?
40Outline
- Introduction
- Description Logic
- Dynamic Description Logic
- Agent-based Services
- Ontology-based Knowledge Management KMSphere
- Conclusions
41Ontology Development
42KMSphere
43KMSphere
44KMSphere
45KMSphere
46KMSphere Demo
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47KMSphere Demo
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48KMSphere Demo
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49KMSphere Demo
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50KMSphere Demo
???????
51KMSphere Demo
RDQL (RDF Data Query Language)??
52Agent Grid Intelligence Platform AGrIP
E-B
E-G
IE
DSS
IB
Simul
Corl
Diag.
Information Sourses
Applications
Web
Middelware
GIS
CBR
Databases
GHunt
OKPS
CAD
MSMiner
MIRES
KMSphere
Stream Media
MAGE
53Emergency Interactive Systsem GEIS
54Distributed Data Mining
55Conclusions
- The dynamic description logic is a good logic
foundation for Semantic Web. - Semantic Web services in terms of agents
- Ontology-based knowledge management system
KMSphere provides knowledge sharing to users.
56THANK YOU!
Question!
 Intelligence Science
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