Towards the Semantic Web (Ontology-driven Knowledge Management) Chapter 1. Introduction Chapter 2. OIL and DAML OIL : Ontology Languages for the Semantic Web - PowerPoint PPT Presentation

Loading...

PPT – Towards the Semantic Web (Ontology-driven Knowledge Management) Chapter 1. Introduction Chapter 2. OIL and DAML OIL : Ontology Languages for the Semantic Web PowerPoint presentation | free to download - id: 704b9c-NjM1N



Loading


The Adobe Flash plugin is needed to view this content

Get the plugin now

View by Category
About This Presentation
Title:

Towards the Semantic Web (Ontology-driven Knowledge Management) Chapter 1. Introduction Chapter 2. OIL and DAML OIL : Ontology Languages for the Semantic Web

Description:

Towards the Semantic Web (Ontology-driven Knowledge Management) Chapter 1. Introduction Chapter 2. OIL and DAML+OIL : Ontology Languages for the Semantic Web – PowerPoint PPT presentation

Number of Views:115
Avg rating:3.0/5.0
Slides: 21
Provided by: kbj7
Category:

less

Write a Comment
User Comments (0)
Transcript and Presenter's Notes

Title: Towards the Semantic Web (Ontology-driven Knowledge Management) Chapter 1. Introduction Chapter 2. OIL and DAML OIL : Ontology Languages for the Semantic Web


1
Towards the Semantic Web (Ontology-driven
Knowledge Management) Chapter 1. Introduction
Chapter 2. OIL and DAMLOIL
Ontology Languages for the Semantic Web
Hyun-Jun Kim
2
Contents
  • Chapter 1
  • Introduction
  • The Semantic Web and Knowledge Management
  • The Role of Ontologies
  • An Architecture for Semantic Web-based Knowledge
    Management
  • Tools for Semantic Web-based Knowledge Management

3
1. Introduction
  • Semantic Web
  • It provides enhanced information access based on
    the exploitation of machine-processable
    meta-data.

4
1.1 The Semantic Web and Knowledge Management
  • How to get the right information to the right
    people
  • at the right time
  • Current weaknesses
  • Searching information irrelevant information
    that include certain terms in different meanings.
  • Extracting information human browsing and
    reading is required automatic agents do not
    posses the common sense knowledge.
  • Maintaining difficult and time-consuming
    activity when such sources become large.
  • Automatic document generation this needed to
    enable adaptive websites that are dynamically
    reconfigured according to user profile or other
    aspects of relevance.

5
1.2 The Role of Ontologies
  • It is a key technology for the Semantic Web.
  • It interweave human understanding of symbols with
    their machine processability.
  • Their promise
  • a shared and common understanding of a domain
    that can
  • be communicated between people and application
    systems.

6
1.3 An Architecture for Semantic Web-based
Knowledge Management
  • Knowledge Acquisition
  • Automatic knowledge extraction from unstructured
    and semi-structured data in external data
    repositories.
  • (Ontology editing tools)
  • Knowledge Representation
  • The knowledge is represented in an ontology
    language.
  • (Ontology repository)
  • Knowledge Maintenance
  • Development, management, maintenance, use of KB
  • (Ontology middleware)
  • Knowledge Use
  • Finding, sharing, summarizing, visualizing,
    browsing
  • (information access tools)

7
1.4 Tools for Semantic Web-based
Knowledge Management
  • Knowledge Acquisition
  • OntoWrapper, OntoExtract
  • Knowledge Representation
  • RDF (the SESAME system)
  • Knowledge Maintenance
  • OMM(Ontology Middleware Module) Chapter 11.
  • Knowledge Use
  • QuizRDF (Chapter 8) Semantic search engine.
  • Spectacle (Chapter 9) visualization and
    browsing tool.
  • OntoShare (Chapter 10) RDF-based knowledge
    sharing system.

8
Contents
  • Chapter 2 (DAML, DAMLOIL)
  • Introduction
  • The Semantic Web Pyramid of Languages
  • Design Rationale for OIL
  • OIL Language Constructs
  • Different Syntactic Forms
  • Language Layering
  • Semantics
  • From OIL to DAML OIL
  • Experiences and Future Developments

9
1. Introduction
  • OIL Ontology Inference Layer
  • DAML DARPA Agent Markup Language
  • DAML OIL
  • currently the most prominent ontology
    languages for the semantic web.
  • OWL Ontology Web Language (W3C)

10
2. The Semantic Web Pyramid of Languages
11
2. The Semantic Web Pyramid of Language
  • HTML
  • DTD (Document Type Definition)
  • Well-formed XML (Extensible markup Language)
  • XML Schema
  • RDF (Resource Description Framework)
  • RDFS (RDF Schema)
  • XML Schema prescribe the order and combination of
    tags in an XML document
  • RDFS only provides information about the
    interpretation of the statements given in an RDF
    data model, but it does not constrain the
    syntactical appearance of an RDF description.
  • RDFS lets developers define a particular
    vocabulary for RDF

12
3. Design Rationale for OIL
  • Limitation of RDFS for many types of knowledge.
  • Stating that every book has exactly one price,
    but at least one author
  • Stating that titles of books are strings and
    prices of books are numbers
  • Stating that no book can be both hardcover and
    softcover
  • Stating that every book is either hardcover or
    softcover

13
3. Design Rationale for OIL
  • Design goals for OIL
  • Maximizing compatibility with existing W3C
    standards.
  • Maximizing partial interpretability by less
    semantically aware processors.
  • Providing modelling primitives.
  • Maximizing expressiveness to enable modelling of
    a wide variety of ontologies.
  • Providing a formal semantics.
  • Enabling sound, complete and efficient reasoning
    services.







14
3. Design Rationale for OIL
  • These design goals lead to the following three
    requirements.
  • It must be highly intuitive to the human user.
  • It must have a well-defined formal semantics with
    established reasoning properties to ensure
    completeness, correctness, and efficiency.
  • It must have a proper link with existing web
    languages such as XML and RDF to ensure
    interoperability.

15
4. OIL Language Constructs
  • A Simple Example in OIL

16
5. Different Syntactic Forms
  • OILs XML serialization
  • OIL is human readable serialization
  • But it is not suitable for publishing ontologies
    on the web.
  • It is easier to parse than the more
    human-readable form
  • shown above.

17
6. Language Layering
  • Single ontology language can not fulfill all the
    needs of the large range of users and
    applications of the Semantic Web.

Heavy OIL (possible future extensions)
Instance OIL (standard OIL instances)
Standard OIL
Core OIL (Standard OIL RDFS)
18
6. Language Layering
  • The layered architecture of OIL has three main
    advantages.
  • An application is not forced to work with a
    language that offers significantly more
    expressiveness and complexity than is actually
    needed.
  • Applications that can only process a lower level
    of complexity are still able to catch same of the
    aspects of an ontology.
  • An application that is aware of a higher level of
    complexity can still also understand ontologies
    expressed in a simpler ontology language.

Instance OIL (standard OIL instances)
19
7. From OIL to DAML OIL
  • It is more tightly integrated with RDFS.
  • Re-use of existing RDFS infrastructure.
  • There is no way in RDFS to state that a
    restriction should consist of exactly one
    property and one class.
  • DAMLOIL is to define the semantics of the
    language in such a way that they give a meaning
    to any ontologies that conform to the RDFS
    specification

20
8. Experiences and Future Developments
  • First release in December 2000.(DAMLOIL)
  • A large number of tools have been written for US
    DAML and European IST.
  • Web Ontology Working Group (DAMLOIL)
  • The most important impact of OIL and DAML OIL
    may well not be the actual usage these languages
    get, but rather the fact that they form the basis
    of new languages, which will get widespread usage.
About PowerShow.com