Daniel G. Teivelis daniel.teivelis@consist.br

1. Semantic Web: Information & Services Integration Daniel G. Teivelis daniel.teivelis@consist.com.br

2. The Semantic Web

3. W3C‘s Semantic Web Architecture

4. Semantic Web: An Extension of the WWW

5. Semantic Web: Special Terminology • semantic – the meaning • metadata – data about data • ontology – giving context, vocabulary • taxonomy – classification • knowledge – the whole experience • artificial intelligence – examining and learning online, living systems

6. Semantic Web: Building Blocks

7. www evolves to semantic web

8. Explain the Semantic Web in Business Terms!

9. Web Aspects • The Good • Universally accepted • Improving performance and standardization • The Bad • Application integration over the Web • Vendor bickering over protocols and tools • The Ugly • Definition of meaning and semantics for knowledge representation • Automatic content transformation

10. The Key Challenge - Still • How do average users find the information they need amidst a flood of irrelevant matter? • Quickly, Easily, Consistently? • We need to build Publish & Find Engines • With a reasonable amount of effort / cost • Within a reasonable amount of time But how?

11. Approaches for Knowledge Representation • Centralized • Easier to manage on a small scale (one company) • Hard to get agreements between corporations • Cannot scale to the size of a global knowledge base • Decentralized • Distributed effort • Common denominator approach • Some fuzziness allowed to achieve versatility Semantic Web

12. The Semantic Web • „The Semantic Web is not a separate Web but an extension of the current one, in which information is given well-defined meaning, better enabling computers and people to work in cooperation“ Source: Scientific American: The Semantic WebTIM BERNERS-LEE, JAMES HENDLER and ORA LASSILA http://www.sciam.com/2001/0501issue/0501berners-lee.html

13. The Semantic Web • „The Semantic Web will enable machines to COMPREHEND semantic documents and data, not human speech and writings.“ Source: Scientific American: The Semantic WebTIM BERNERS-LEE, JAMES HENDLER and ORA LASSILA http://www.sciam.com/2001/0501issue/0501berners-lee.html

14. The Semantic Web • The Web • Initially built for humans • Scales from the Desktop to the World • Inherently weak when supporting machine to machine communication • Key enabler for further Web-Evolution to the Semantic Web • Structured Markup • Meta Data • Knowledge about Knowledge • Available Frameworks • XML (Extensible Markup Language) • Resource Description Framwork (RDF) • Ontologies (Taxonomies and Inference rules)

15. The Three Cornerstones of The Semantic Web ONTOLOGIES RDF XML

16. RDF (Resource Description Framework) • Scope: • A foundation for processing metadata • Mission: • To provide interoperability between applications that exchange machine-understandable information on the Web • Strategy: • To emphasize facilities to enable automated processing of Web resources

17. RDF Fundamentals A Thing Identified by UniqueResourceIdentifierseach has Properties have Values

18. Example Flower Describedin XMLDocumentsdriven by XMLSchemas Color Green

19. RDF Application Areas • Resource discovery • to provide better search engine capabilities, • Cataloging • for describing the content and content relationships available at a particular Web site, page, or digital library, • Intelligent software agents • to facilitate knowledge sharing and exchange • Content rating • describing collections of pages that represent a single logical "document"

20. RDF Application Areas • Other application areas: • Describing intellectual property rights of Web pages, • Expressing the privacy preferences of a user • Expressingprivacy policies of a Web site • In short • Wherever XML is being used or consdidered for use right now. • What you gain is S.P.E.E.D

21. The Result: Ontologies • „An ontology is a document or file that formally defines the relations among terms“ Validated by Schemas Source: Scientific American: The Semantic WebTIM BERNERS-LEE, JAMES HENDLER and ORA LASSILA http://www.sciam.com/2001/0501issue/0501berners-lee.html

22. So . . . Simple? Trivial even?

23. The Semantic Web – A Roadmap • What the Semantic Web is NOT ... • The Semantic Web is not Artificial Intelligence • The Semantic Web does not allow arbitrary complexity • The Semantic Web is not something that will ever be complete • What the Semantic Web IS ... • A great vision • Something that will be built over time • An emergent property of the global effort towards standardization around XML

24. The Story of the Frog Source: John Thackera: the design challenge of pervasive computing:http://www.doorsofperception.com/projects/chi/

25. The water we are in Rules Semantics Languages Model Theories World Complexity

26. The Semantic Web: Simple in concept , but massive in scale • We produce 1 ExaByte of Information per year • Source: Stanford University Study • 60% of programming time is wasted on extracting and moving data from point A to point B • Source: Gartner Group Study • 50% of world economy depends on Office Work manipulating data by hand • Source: MIT research

27. Semantic Web Awareness (Informal research among IT decision makers) 100% 50% XML Ontologies RDF 0%

28. Business Relevance of Semantic Web Components (personal opinion) 100% O n t o l o g i e s 50% RDF XML 0%

29. The Semantic Web Conundrum I can't find my ontology ! Ant Hill

30. The Key Question How to Start ?

31. Market Overview ERP B2B W3C BPM B2C ERM EAI XML J2E B2E TBI ECM B2N CRM WAP E2E

32. The breakthrough: „Shattering the 3-letter-barrier for acronyms!“ U.D.D.I. S.O.A.P W.S.D.L. XML XBRL XSLT

33. Bringing things into perspective „one to bind them & one to rule them all ...“ B2B BPM EAI B2C ERP SCM CRM ECM B2E UDDI X M L WAP SOAP J2E ERM .NET W3C

34. Infoworld Analysis • Integration costs consume an average of 24 percent of yearly IT budgets. • More than half of the InfoWorld readers polled believe that Web services will make integration cheaper, easier, and faster. • For at least the next couple of years, traditional integration technologies will evolve in parallel with Web services. • Defining XML vocabularies and business processes now, both for internal use and for connections to partners, will make the later transition to Web services much easier.

35. The story of The Elephant ...

36. A matter of perspective ... "a tree" "a fire truck" "a rope"

37. Corporate Elephants have ... "core systems" "front ends" "back ends"

38. Different Integration Angles ... "data" "application" "process" Enterprise Legacy Environments Purchasing Huge Amounts of New Technologies

39. B O G U S Quantum Integration Equation • Process = Application PLUS Data • Process MINUS Data = Application • Process MINUS Application = Data Applications MUST keep the process independent of data! Data MUST keep the processindependent of applications!

40. Fact is ... • You cannot cleanly separate Data, Applications and Process ... • They are forever intertwined by 4 decades of legacy application development • COBOL Applications (Process and Data) • Stored Procedures in RDBMS (Process and Data) • Proprietary workflow applications (Process descriptions) • This is creating a huge problem for any customer!

41. Market Status • Customers will maintain their transaction systems „forever“ • Must accept that data, application and process are interlinked • Customers are building / buying new applications • That are based on standards that keep data, applications and process separated • Customers are building up „Integration Centers“ • To integrate new and existing systems • To take advantage of commodity content and applications

42. Main Solution Ingredient XML is the common standard for independence and integration of • D a t a • A p p l i c a t i o n s • P r o c e s s e s

43. Scale Up 500 Million Servers 1 Billion Users 20 Billion Devices 200 Trillion transactions Scale Out Distributed Data Distributed Applications Distributed Processes Key Issues for IT: Scale Up and Scale Out Server-Centric Process-Centric

44. Old Server-CentricArchitectures Business process drives humans Humans drive applications Applications drive functions Functions drive data No human, no data, no transaction New Process-CentricArchitectures Data drives functions Functions drive applications Applications drive business processes Business processes drive transactions Humans review transactions How to scale out ... This is how to scale out! This can only scale up!

45. Aside: Big conceptual changes like this have happened before: Y.C.G.T.F.H.

46. Some implementaton are at risk Map X M L

47. You can‘t get there from here ... • To take full advantage of XML • It is not enough to „map“ existing data to XML! • It is not enough to have an XML interface to the application! • It is not enough to describe your process in XML documents! • You need a new concept • A concept that allows data to drive the business • Automatically • Based on Standards

48. A key component for Process-Centric Architectures: The XML Document

49. The XML Document is the foundation for process-centric architectures Meta Data Data Links Data The X M L Document Process & Rules Human Readable Instructions Machine Readable Instructions

50. So ..., XML is great for techies, but what do customers want ?