1. Towards Semantic oriented Database
JTC1 SC32N1636
Towards Semantic oriented Database
Sung-Kook Han
Semantic Web Services Lab.
Won Kwang University

2. Agenda Ontology and Semantic Representation
The current issues in Database
Semantic-oriented database

3. Ontology and Semantic Representation

4. Knowledge-based Systems Information Resources Hierarchical Structure
The Age of Semantics
Relational
Modeling
Object-oriented
Metadata-based
Ontology-based
Knowledge-based Systems
Description of
Information Resources
Software Design
(Components, GUI,…)
Relational DB
Applications
OWL
XML, RDF/S
UML
SQL
Languages
Domain Ontology
Metadata
(Dublin Core…)
Class,
Hierarchical Structure
ERD,
Thesaurus
Information
Systems
Concept,
Semantics
Object
Entity-Relation
Core
Elements

5. Ontology Spectrum: One View
Is Disjoint Subclass of with transitivity property
Modal Logic
Logical Theory
Thesaurus
Has Narrower Meaning Than
Taxonomy
Is Sub-Classification of
Conceptual Model
Is Subclass of
DB Schemas, XML Schema
UML
First Order Logic
Relational
Model, XML ER
Extended ER
Description Logic
DAML+OIL, OWL
RDF/S
XTM
Syntactic Interoperability
Structural Interoperability
Semantic Interoperability
weak semantics
strong semantics
Technologies
has_experience_in
Programs
works
Personnel S1
Agent
Company
illusion
has
WISO
Department am AS
Leo
Paulnderleez
Intelligence
Navy
Brad
Ann
Howard
Assistant
Director
Reza
Technical
Management
Project
Telecommunication
Task
Program
EcDARPA
Request
Semantic
Interoperability
Knowledge
Representation
Natural
Language
Animal
Mammal
Reptile
Bird
Snake
Dog Cat
Cocker
Spaniel
Lady

6. What is an Ontology?
"An ontology is an explicit specification of a conceptualization." [Gruber 1993]
An ontology is a formal, explicit specification of a shared conceptualization. [Borst 1997]
"An ontology defines a common vocabulary for researchers who need to share information in a domain [Noy & McGuinness 2001]

7. What is an Ontology? ‘Conceptualization’ ‘Explicit’ ‘Formal’ ‘Shared’
refers to an abstract model of some phenomenon in the world by having identified the relevant concepts of that phenomenon.
‘Explicit’
means that the type of concepts used, and the constraints on their use are explicitly defined.
‘Formal’
refers to the fact that the ontology should be machine readable, which excludes natural language.
‘Shared’
reflects the notion that an ontology captures consensual knowledge, that is, it is not private to some individual, but accepted by a group. [Studer etc 1998]

8. Ontology in a nutshell Domain Knowledge Model
A vocabulary for representing knowledge about a domain and for describing specific situations in a domain
A domain-specific vocabulary of entities
classes, properties, predicates, and functions, and to be a set of relationships that necessarily hold among those vocabulary terms.
Shared formal conceptualizations of particular domains that provide a common interpretation of topics that can be communicated between people and applications.
Also allow definition of axioms and constraints on particular concepts and properties.
Ontological Commitment: General agreement to use a vocabulary
Ontology is social contracts.
Agreed, explicit semantics
Understandable to outsiders
(Often) derived in a community process
Quartermaster needs to represent simultaneously some CISCO Firewall/Switch
Relation
Concept
Instance
Axiom
Function

9. Ontology and Semantic Web

10. Core Technologies for Ontology
Metadata
Ontology Languages
Rule Languages
Ontology Tools
Inference Engines
Semantic Web Agents
Intelligent Search
Semantic Portal
e-Gov., e-Leaning,…
Standards
Ontology Enablers
Ontology Applications

11. W3C Semantic Web Activity
RDF Core Working Group
Advanced Development
Annotation (Annotea)
Access Control
Calendaring
Collaboration
Logic
Rules
Workflows
…………….
■ update RDF Model and Syntax Recommendation
■ revise RDF Schedule
Web Ontology Working Group
■ build upon RDF Core Work a language for
defining structured Web based ontology
Semantic Web Best Practices and
Deployment Working Group
■ provide hands-on support for developers of
Semantic Web Applications
RDF Data Access Working Group
■ evaluate the requirements for an Query Language
and network protocol for RDF and test cases for such requirement

12. W3C Semantic Web Activity Status
Final W3C Approval Two Key Semantic Web Standards
On February 10, 2004
Web Ontology Language (OWL) and Revised Resource Description Framework (RDF)
W3C Launches Phase 2 of Semantic Web Activity
: W3C announced the launch of phase 2 of Semantic Web Activity
Two new Working Groups have been formed.
Semantic Web Best Practices and Deployment WG
RDF Data Access WG

13. The current issues in DB

14. Schema Matching
Schema match plays a central role in numerous applications
web-oriented data integration, electronic commerce, schema integration, schema evolution and migration, application evolution, data warehousing, database design, web site creation and management, and component-based development.
Schema matching is typically performed manually, and many previous research papers have proposed many techniques to achieve a partial automation of the match operation for specific application domains.

15. Architecture of Generic Match
Portal Schema
E-Business
Schema
Data Warehouse
Database
Schema Import/Export
Generic Match
internal schema representation
Global Libraries
(dictionaries,
Schema,…)
by Erhard Rahm, Philip Bernstein (2001)

16. Schema Matching Approaches
by Erhard Rahm, Philip Bernstein (2001)

17. Data Integration
With the advent of the Internet and electronic commerce, most large organizations and companies are now seeking ways to maximize the power of their information assets stored across hundreds of databases and application programs by bringing them into open interoperable environments. Sometimes it is called multidatabase or federated database.
The main cause of this integration is heterogeneity. This includes different hardware, operating systems, data models, data semantics and data quality. Especially, semantic interoperability and semantic integration is crucial for system integration.
The semantics of diverse information resources are captured by ontologies — definitions of terms, i.e. concepts and the relationships between concepts.

18. Ontology-based integration
Ontology is seen as domain-oriented concepts. It includes abstract concepts and specifies domain-level constraints that can be used for knowledge-level reasoning.

19. Data Definition Person Publication Name Address Phone Title Date Pages
Pub-ID
Country
Publish
CREATE TABLE Person (
Name varchar (30) NOT NULL PRIMATY KEY,
Address varchar,
Phone varchar, )
CREATE TABLE Publication
Pub-ID number(7) PRIMARY KEY,
Title varchar (50),
Date date,
Country DEFAULT “USA”,
Page int,
CREATE TABLE Publish
Name varchar (30),
Pub-ID numebr(7)
Only defined structural properties
Application dependent
Hard to add the diverse domain vocabularies
Low-level description
Schema match and Data integration is difficult.

20. Data Modeling vs. Ontology
Ontology: An agreement about a shared, formal, explicit and partial account of
a conceptualization
Data Model: Representation of the structure and integrity of the data elements of
specific application
Data Modeling
Ontology
Partial account of conceptualization
Dependent on the specific needs and tasks
Application independent
Informal agreement between the developers and users
Generic knowledge
Not intended to be shared by other applications
Sharable and reusable for different kind of applications
Structure and integrity
Semantics
Application specific
Open environment

21. Semantic-oriented Database
Ontology Base
(Triple)
Triple-based
Difficult, still developing
storage methods
Different query language
(SPARQL)
Lack of physical properties
Ontology
(Concepts, Relations, Individuals)
Database Base
(Table)
Knowledge Base
Limited semantics
Data integration
use conventional RDB
technology
Efficient
Stable
Legacy RDB
(Columns, rows)

22. Semantic Sugar ontology definition structure definition Name Address
Person
Publication
Publish
Researcher
Manager
Papers
Books
Reports
JournalPaper
WorkshopPaper
Phone
Title
Country
Address
ontology definition
structure definition
Name
Address
Phone
ZIP
PUB-ID
Title
Date
Pages

23. Ontological Schema Description
Web Services
WSDL (Web Services Description Language) SOAP (Simple Object Access Protocol)
UDDI (Universal Description, Discovery, and Integration)
Ontology
OWL-S
SQL-S??
Database
S Q L - D D L
S Q L - D M L
Service Profile
Service Model
Service Grounding
DB Description
Table Description
Data Manipulation
Semantic Web Services
Semantic Database

24. Ontological Schema Description
OWL-S Upper Ontology
SQL-S Upper Ontology
Import ontology for DB
Definition of DB ontology
Specification of DB
Mapping to WSDL
communication protocol
marshalling/serialization
Control flow of the service
Protocol Specification
Abstract Messages
Capability specification
General features of the Service
Quality of Service
Classification in Service
taxonomies
DB Description
Database
Semantic query language
Structural query language
Data manipulation
Data Manipulation
Table Description
Field specification with ontology and
data type

25. SQL 2006
ISO/IEC :2006 defines ways in which SQL can be used in conjunction with XML.
It defines ways of importing and storing XML data in an SQL database, manipulating it within the database and publishing both XML and conventional SQL-data in XML form.
In addition, it provides facilities that permit applications to integrate into their SQL code the use of XQuery to concurrently access ordinary SQL-data and XML documents.
No semantic consideration.
No ontological representation of SQL vocabularies.

26. Thank You Very Much..