Semantic Web Technologies and Applications in e-biz. Hong-Gee Kim Dankook University
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1 Semantic Web Technologies and Applications in e-biz Hong-Gee Kim Dankook University
2 Agenda pintroduction ð What & Why the Semantic Web? psemantic Web Applications in e-biz ð Weaknesses of the Current Web Technologies ð Potentials of Semantic Web Technologies psemantic Web Technologies ð Ontology Representation ð Languages & Tools pfuture of the Semantic Web 2
3 The Vision of the Web p collaboration between people p collaborations extend to computers Everything is connected to the Information Space. 3
4 The Bottleneck p The amount of information accessible from the Web is rapidly increasing. p The information sources are increasingly complicated. p The types of information source becomes diverse. 4
5 The Semantic Web q A Vision Of Possibilities The Semantic Web is an extension of the current web in which information is given welldefined meaning, better enabling computers and people to work in cooperation. - Tim Berners-Lee, James Hendler and Ora Lassila, The Semantic Web, Scientific American, May 2001 The Relationship between the Semantic Web and WWW 5
6 The Semantic Web p enable intelligent services - information broker,search agents, and information filters p further levels of interoperability have been established p standard must be defined not only for the syntactic form of documents, but also for their semantic content 6
7 The Evolving Web p The Semantic Web is a web of data, in some ways like a global database. by Tim Berners-Lee Resource Software href href href generated dependson dependson Resource Resource Resource Resource Document Software Document Software href href href isversionof href Resource href href href href Document href subject creator Resource Resource Resource Document Subject Person href locatedin Resource Very little information available More information available Place More Intelligent Knowledge Exchange 7
8 Agenda pintroduction ð What & Why the Semantic Web? psemantic Web Applications in e-biz ð Weaknesses of the Current Web Technologies ð Potentials of Semantic Web Technologies psemantic Web Technologies ð Ontology Representation ð Languages & Tools pfuture of the Semantic Web 8
9 Interoperability Problem in e-biz p The lack of proper standards in the e-biz world ð HTML does not neither provide syntax and semantics of information ð Lack of integration of data exchanges between online market participants ð Existing standards like EDIFACT are isolated and costly to manage p XML provides some solutions for B2B ð Human Understandable for Data Description ð Easy and cheap to maintain ð ebxml provides a comprehensive set of standardized XML document formats (Syntactic Interoperability) ð Good tool support for all document processes in e-biz 9
10 Too Many Standards p There are more standards than you would like to have ð UNSPSC, UCES, ecl@ss, RossettaNet, and much more vertical and horizontal standards ð Serious translation problem p All of the standards are based on semi-structured descriptions ð XML based descriptions of products, services, and business processes 10
11 Why Semantic Web? p Mapping and Integration between different standards ð Semantic Interoperability p Automization of business processes in terms of the formal semantics of descriptions ð Machine Understandability p So, buying decisions can be based on the whole of the relevant information ð Finding all relevant information sources and online stores for a specific product ð Integrating all information available on the Web, for comparing products and vendors 11
12 Potentials of Semantic Web Technologies p Automatic vendor recognition p Automatic product and service recognition p Price and quality comparison p Automatic negotiation protocols p Automatic coalition forming of vendor groups 12
13 IS Evolution Path Transactional Collaborative Knowledge Management ERP Systems Internal K-Commerce E-Commerce External 13
14 K-Commerce Knowledge Products/Services E-commerce (transactions) K-Commerce Marketing / Distribution Internet 14
15 Knowledge Packaging Create Convert Commercialize Customized Products/ Services Codified Diffused Uncodified E.g. processes, databases documents, drawings 15
16 The Semantic Web Architecture for e-biz p The use of URIs ð A global identification mechanism for products and traders p The RDF data model ð The direct publication of data on the Web using XML serialization ð Rich metadata for contents p The Web Ontology Language (OWL) ð The definition of common terms and concepts needed to understand RDF data 16
17 Agenda pintroduction ð What & Why the Semantic Web? psemantic Web Applications in e-biz ð Weaknesses of the Current Web Technologies ð Potentials of Semantic Web Technologies psemantic Web Technologies ð Ontology Representation ð Languages & Tools pfuture of the Semantic Web 17
18 Semantic Web Technology Tree 18
19 How the Semantic Web Will Be Possible p Languages ð Formal Syntax and Formal Semantics ð Real world semantics à Ontologies p Tools ð Ontology builders and browsers ð Ontology integration tools ð Semantic annotators ð Reasoners p Applications ð Knowledge management systems ð Natural language search engines ð e-biz 19
20 Ontology p Shared understanding within a community of people p Declarative specification of entities and their relationships with each other p Syntactically and semantically richer than common approaches for databases p Providing a domain theory and not the structure of a data container 20
21 Relational Database Schemas p Well established technique for specifying the structure of shared data, not for communication between people or agents p Declarative specification but of tables, not of entities and relationships p Some constraints are expressible but no significant rules (such as inheritance) p No explicit behavior p Standard language is SQL. 21
22 Logic p Very expressive but very difficult to use. Not designed for communication. p Most logical languages are not based on entities and relationships. p Very powerful reasoning capabilities. p Do not usually have any associated behavior. p Many examples: Prolog, KIF, Slang,... 22
23 Meaning and Human Communication Concept? Concept evokes refers to evokes Symbol Thing Symbol Concorde stands for stands for Concorde 23
24 Kinds of Ontologies ad hoc Hierarchies (Yahoo!) Structured Glossaries XML Schema Description Logics (DAML+OIL) Terms Thesauri DB Schema Formal Taxonomies Expressivity ordinary Glossaries Data Dictionaries (EDI) Principled, informal hierarchies XML DTDs Frames (OKBC) General Logic 24
25 Information Retrieval Using Ontologies Resource qafmd301.html Metadata FMD(Foot and Mouth Disease), Animal Welfare Information Center Kanghwado, South Korea Ontology FMD is caused by an RNA virus.kanghwado is located in Gyeonggi, South Korea. Neither this particular resource nor its metadata explicitly mention the recent occur of a RNA related virus in Gyeonggi, South Korea. Only an assisted search that maps metadata to underlying ontologies could retrieve this resour in response to the query the recent occur of a RNA related virus in Gyeonggi, South Korea. 25
26 Knowledge Representation on the Web p Universal expressive power - A Web based exchange format must be able to express any form of data. p Syntactic interoperability - Applications must be able to read the data and get a representation that can be exploited. p Semantic interoperability - Semantic interoperability is about defining mappings between terms within data, which requires content analysis. 26
27 Limits of XML p How do I know that you mean the same thing by <price> that I do? ð Does that include tax? shipping? surcharges? p That is, if the computers of two companies are negotiating, they need to know that they truly understand each other. p XML provides syntactic interoperability. There is a need for semantic interoperability. p The semantic web provides this added layer of interoperability through the use of shared ontologies. 27
28 Using XML p In semantic interoperability - has disadvantages 28
29 Using RDF p Expressive power - RDF s nested objected-attribute-value structure satisfies our universal expressive power requirement for an exchange format. p Syntactic interoperability - Application-independent RDF parsers are also available. p Semantic interoperability RDF has significant advantages over XML. 29
30 Three Layered Architecture of the Semantic Web Logical Layer - Formal Semantics - Reasoning support - Heavyweight ontologies Higher Semantics DAML+OIL, OWL Schema Layer - Definition of Vocabulary - Lightweight ontologies Semantics RDF Schema Data Layer - Simple data model and syntax For metadata - RDF : Instances Structure & Syntax RDF XML Schema 30
31 OWL Language p Three species of OWL ð OWL full is union of OWL syntax and RDF ð OWL DL restricted to FOL fragment (¼ DAML+OIL) ð OWL Lite is easier to implement subset of OWL DL p Semantic layering ð OWL DL ¼ OWL full within DL fragment ð DL semantics officially definitive p OWL DL based on SHIQ Description Logic ð In fact it is equivalent to SHOIN(D n ) DL p OWL DL Benefits from many years of DL research ð Well defined semantics ð Formal properties well understood (complexity, decidability) ð Known reasoning algorithms ð Implemented systems (highly optimised) OWL RDF Schema XML/DTD/XML Schemas Semantics Syntax 31
32 OWL Example (Classes Description) p owl:intersectionof ð links a class to a list of class description ð represent the AND <owl:class rdf:id="adult"> <owl:intersectionof rdf:parsetype="collection"> <owl:class rdf:about="#person"/> <owl:restriction> <owl:onproperty rdf:resource="#age"/> <owl:somevaluesfrom df:resource=" </owl:restriction> </owl:intersectionof> </owl:class> Adult = Person $ age.over17 32
33 OWL Example (Classes Description) p WhiteWine hassugar.(dry OffDry) <owl:class rdf:id="whitenonsweetwine"> <owl:intersectionof rdf:parsetype="collection"> <owl:class rdf:about="#whitewine" /> <owl:restriction> <owl:onproperty rdf:resource="#hassugar" /> <owl:allvaluesfrom> <owl:class> <owl:oneof rdf:parsetype="collection"> <owl:item rdf:resource="#dry" /> <owl:item rdf:resource="#offdry" /> </owl:oneof> </owl:class> </owl:allvaluesfrom> </owl:restriction>... 33
34 Ontology Tool Architecture Ontology Editor Query & Browser O ntology M iddleware Ontology Repository Creati on I ntegr ation Annotated Data Repository RDF Constraint Checking O ntology M iddleware Reasoning Engine Domain Ontology.... O ntology R epository(external) Task Ontology 34
35 Editor : Protégé
36 Modeling Tool: SemTalk 36
37 Tools Feature OILEd OntoEdit Ontolingua OpenKnoME Protégé Developers Uni. of Manchester Ontoprise KSL(Stanfor d Uni.) Availiability Open source Freeware Free Web Access Architecture standalone Standalone Client/Serve r Uni. of Manchester SMI(Stanfor d) WebODE Ontology Group(UPM) Freeware Open source Free Web Access Client/Server Standalone 3-tier Extensibility no Plug-ins None None Plug-ins Plug-ins Import for Language Export to Language KR paradigm Graphical taxonomy Collaborativ e working XML RDFS(S) Flogic DAML+OIL OIL RDF(S) DAML+OIL SHIQ DL(DAML+O IL) XML RDFS(S) Flogic DAML+OIL XML RDF(S) Flogic DAML+OIL Frames+FO L Ontolingua IDL KIF KIF3.0 CLIPS LOOM OKBC PROLOG Frames+FO L GRAIL GALEN IR GRAIL CLIPS GALEN IR HTML DL(GRAIL) XML RDF(S) XML Schema XML RDF(S) XML(S) Flogic JAVA Frames+FO L XML RDF(S) CARIN XML RDF(S) OIL DAML Prolog No No Yes No Yes Yes No No Yes Yes No Yes Frames+FO L 37
38 Simple Ontology Merger 38
39 Knowledge Modeling Tool for Pathological Gross Description 39
40 Ontology-Based Document Management System 40
41 Agenda pintroduction ð What & Why the Semantic Web? psemantic Web Applications in e-biz ð Weaknesses of the Current Web Technologies ð Potentials of Semantic Web Technologies psemantic Web Technologies ð Ontology Representation ð Languages & Tools pfuture of the Semantic Web 41
42 The Evolution of Information Technology Locative ( 공간적연결성 ) Mobile Computing Ubiquitous Computing Dynamic ( 프로세스적연결성 ) Web Services (UDDI, WSDL, SOAP) Intelligent Web Services (Ontology -Enhanced) Intelligent Ubiquitous Web Services Static ( 컨텐츠의의미적연결성 ) WWW (URI, HTML, HTTP) Semantic Web Ontology Computing 42
43 Web Services : current technologies 43
44 The Web Services Stack Wire Protocols Description Automated Discovery W3C WS Choreograph Group Invocation BPEL4WS (Microsoft, IBM, BEA) Interoperation WSCL (HP)BPML (Most but Microsoft) Composition WSCI (Sun, BEA, Yahoo, ) Monitoring XLANG (Microsoft), WSFL (IBM), Verification SOAP Blocks SOAP/XMLP XML HTTP/SMTP/BEEP TCP/IP Agreements Process WSDL Extensions WSDL XML D A M L S Registry (UDDI) Inspection Modification of slide by James Snell (IBM) 44
45 Semantic Web Services (DAML-S Upper Ontology). input types. output types. preconditions. postconditions. communication protocol (RPC, HTTP, ). port number. marshalling/serialization process flow composition hierarchy process definitions 45
46 Relevant dimensions between technologies Web Services Collaboration Intelligent Web Services Interoperability Autonomy Semantic Web Intelligence Agent Tech. 46
47 CoBrA Architecture 47
48 Future of the Semantic Web Technology Phase 1 Phase 2 Phase 3 시장채택단계 기존의분류체계를온톨로지화하고선도적사용자들이조직내의특수용도로온톨로지를구축하는초기단계 시맨틱웹기술의성숙기로서각산업별다양한온톨로지가구축되고온톨로지사용이확산되는단계 애플리케이션 / 프로세스통합을위한온톨로지기반기술이광범위하게사용되는보편화단계 설명 / 예 과학 - NIH 의게놈데이터온톨로지 의학 - SNOMED, GALEN ISO 표준분류체계 SIC 산업분류체계 경량급온톨로지 - 상품카달로그 - 사이트디렉토리 온톨로지저작및관리도구개발자들이활약 EC 애플리케이션에온톨로지사용이보편화 - EIP, CRM, SCM, ERP First Horizontal apps - proof and trust 서비스 RDF, 웹기반온톨로지언어사용이보편화됨 각산업별중량급온톨로지개발이보편화 온톨로지기반수평적애플리케이션통합 지능형웹서비스, 시맨틱애플리케이션, 에이전트기술, 유비쿼터스컴퓨팅 Source: Christian Ohms,
49 Conclusion p What the Semantic Web is NOT... ð The Semantic Web is not Artificial Intelligence ð The Semantic Web does not allow arbitrary complexity ð The Semantic Web is not something that will ever be complete p What the Semantic Web IS... ð A great vision ð Something that will be built over time ð An emergent property of the global effort towards standardization around XML 49
50 Final Words Ask not what the Semantic Web can do for you, ask what you can do for the Semantic Web Hans-Georg Stork 50
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