Semantic Web Examples Semantic Web Examples Semantic Web

Semantic. Web Examples

Semantic. Web Examples

Semantic. Web Examples • 두 코드는 네임스페이스와 클래스와 속성의 정의에 따라 의미가 달라진다. 구분 리스트 1 Galloper 리스트 2 Galloper namespace www. ontology. or. kr/car# www. ontology. or. kr/toy# class Subclass of Passenger. Vehicle class Subclass of Car class property Model. Name, Car_Model, Maker, Speed, engine Model. Name, Material, Maker, Age, Color

Application for Sematic. Web • 텍스트기반: 프로티지2000, Onto. Edit, Oil. Ed • 그래픽기반: -Semtalk(www. semtalk. com) -Isa. Viz(www. w 3. org/2001/11/Isa. Viz): 소스공개 중 • 검색Application: -스탠포드 대학의 Knowledge Systems Laboratory(ksl. stanford. edu) -IBM Almaden의 Knowledge Management Group(www. almaden. ibm. com/software/km/index. shtml) 과 W 3 C Semantic Web Advanced Development. Initiatives (www. w 3. org/2001/sw/)의 공동 프로젝트 : 소스공개 중

Toppic Map • ISO standard. (ISO/ICE 13250: 2000 , 2002 includes XTM 1. 0) • Provide the way to model exchange information over the internet or intranet. • Topic maps provide a simple, yet powerful model for bridging the gap between information and knowledge.

Topic map based on INDEX • Back-of-book index example – Singers, 39 -52, See also individual names Baritone, 46 Bass, 46 -47 soprano, 41 -42 tenor, 44 -45 • T opics - the names by which they are known • A ssociations (between topics) - in the form of "see also" references • O ccurrences - the page numbers or locators

The Difference between TM and INDEX • Topic map generalized in order to be able to deal with the vastly more demanding requirements of digital information. • This generalization allows them to incorporate the key features into a single unified model.

Role of TM • reflects the associative mode typical of the way humans think. • Thus, it becomes possible to navigate around a multidimensional topic space to find the precise pieces of information. • Topic map can be used to answer queries of far greater complexity than any of today’s web search engines would be able to tackle.

Graphical Notation topic with id "chopin" topic with declared topic type "person"

Graphical Notation association with id "as 243" association with declared association type "born-in" topic "chopin" plays a unspecified role in association which type is "born-in" topic "chopin" plays a role of type "who" in association which type is "born-in"

What’s XTM? • Topic maps superimpose an external layer that describes the nature of the knowledge represented in the information resources. • The purpose of the extensible Markup language topic maps (XTM) initiative is to apply the topic maps paradigm in the context of the World Wide Web.

Why XTM? • XTM allow us to model and represent knowledge in an interchangeable form. • XTM provide a unifying frame work for knowledge and information management. • XTM promise to revolutionize the ways in which we search for and navigate information.

Element of XTM 1 • TAO – Topic – Associations – Occurrences

Element of XTM 2

Element of XTM 3

Element of XTM 4

Element of XTM 5

Introduction to XTM Syntax 1 • <topic. Ref>: Reference to a Topic element • <subject. Indicator. Ref>: Reference to a Subject Indicator • <scope>: Reference to Topic(s) that comprise the Scope • <instance. Of>: Points to a Topic representing a class • <topic. Map>: Topic Map document element • <topic>: Topic element • <subject. Identity>: Subject reified by Topic

Introduction to XTM Syntax 2 • <base. Name>: Base Name of a Topic • <base. Name. String>: Base Name String container • <variant>: Alternate forms of Base Name • <variant. Name>: Container for Variant Name • <parameters>: Processing context for Variant • <association>: Topic Association • <member>: Member in Topic Association

Introduction to XTM Syntax 3 • <role. Spec>: Points to a Topic serving as an Association Role • <occurrence>: Resources regarded as an Occurrence • <resource. Ref>: Reference to a Resource • <resource. Data>: Container for Resource data • <merge. Map>: Merge with another Topic Map

Topic. Map Problems • The model was good, but the syntax had three main problems: - it was SGML, no XML support at all - it used Hy. Time for all linking, so no URIs -it used architectural forms, so no fixed syntax

Topic maps and RDF -topic maps workshop, 2002 • The heart of both models is the same: things, and statements about things • The RDF model has nothing more(simpler) • Topic maps add several features to this • RDF is lower-level than topic maps

Usage areas • Topic maps are better at -findability -complex information models -information integration • RDF is better at -logical inferencing -simple metadata applications

Reference(Semantic. Web) • “The Semantic Web” Tim Berners-Lee, 2002, (www. w 3. org/2002/Talks/04 -sweb) • Semantic Web Home. Page : http: //www. w 3. org/2002/sw/ • Semantic. Web Advanced Development Home. Page: (www. w 3. org/2000/01/sw)

Reference(Topic. Map) • Topic maps Workshop, Lars Marius Garshol, 2002 • Topic map, Snu. OOP lab세미나 자료, 2000