Logic Foundation and Services for Semantic Web

1. Logic Foundation and Services for Semantic Web Zhongzhi Shi shizz@ics.ict.ac.cn Institute of Computing Technology Chinese Academy of Sciences Logic Foundation Zhongzhi Shi

2. Outline • Introduction • Description Logic • Dynamic Description Logic • Agent-based Services • Ontology-based Knowledge Management KMSphere • Conclusions Logic Foundation Zhongzhi Shi

3. Semantic Web • Web was “invented” by Tim Berners-Lee (amongst others), a physicist working at CERN • His vision of the Web was much more ambitious than the reality of the existing (syntactic) Web: “… a plan for achieving a set of connected applications for data on the Web in such a way as to form a consistent logical web of data …” “… an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation …” This vision of the Web has become known as the Semantic Web Logic Foundation Zhongzhi Shi

4. Semantics Is Important • Avoid transformation code between data sets • Unambiguously capture service profiles • Enable dynamic discovery of services • Use reasoners to locate services in “yellow pages” • Enable dynamic collaboration of services • Use reasoners to infer service descriptions and capabilities • Enable rich, automatic, service orchestration • Process layer will be far more automated with semantics Logic Foundation Zhongzhi Shi

5. Adding “Semantic Markup” • Extend existing rendering markup with semantic markup • Metadata annotations that describe content/function of web accessible resources • Using Ontologies to provide vocabulary for annotations • “Formal specification” is accessible to machines • “Semantics” given by ontologies Make web resources more accessible to automated processes Logic Foundation Zhongzhi Shi

6. Ontology • In philosophy, an ontology is a theory about the nature of existence. • An ontology is a document or file that formally defines the relations among terms. • An ontology is a formal, explicit specification of a shared conceptualization. • The most typical kind of ontology for the Web has a taxonomy and a set of inference rules. Logic Foundation Zhongzhi Shi

7. The Semantic Web layer cakeby Tim Berners-Lee Logic Foundation Zhongzhi Shi

8. Web Ontology Language OWL • W3C Recommendation 10 Feb 2004. Deborah L. McGuinness and Frank van Harmelen eds. formerly Feature Synopsis for OWL Lite and OWL • OWL facilitates greater machine interpretability of Web content than that supported by XML, RDF, and RDF Schema (RDF-S) by providing additional vocabulary along with a formal semantics. • OWL has three increasingly-expressive sublanguages: OWL Lite, OWL DL, and OWL Full. Logic Foundation Zhongzhi Shi

9. The Ontology Language Stack OWL DAML-S DAML-R DAML+OIL DAML-Ont OIL DC PICS RDF Schema RDF XOL HTML XML + Name Space + XML Schema Unicode URI Logic Foundation Zhongzhi Shi

10. OWL • Ability to be distributed across many systems • Scalability to Web needs • Compatibility with Web standards for accessibility and internationalization • Openess and extensiblility Logic Foundation Zhongzhi Shi

11. OWL Reasoners • KAON2 is a reasoner for OWL extended with the DL-safe subset of SWRL; it also provides an OWL API. • FaCT -- a DL reasoner. see WonderWeb project, Bechhofer 15 Sep. • Racer -- a DL reasoner. see Horrocks 12Sep • Cerebra from Network Inference - owl syntax checker, nearly complete OWL DL Horrocks 12Sep • cwm -- useful but incomplete OWL Full • Euler -- useful but incomplete OWL Full,see De Roo 11 Jul: 51 / 234 tests • surnia -- OWL full reasoner based on otter. Hawke 26Aug • Jena/HP ( Reynolds/HP 7 May)will support OWL reasoning. • Vampire Horrocks 17 Jul - uses a first-order theorem prover to do OWL DL • Pellet is a reasoner built in Java that was designed specifically for OWL reasoning. Hendler/Sirin/Parsia 15Sep). • SWI-Prolog Semantic Web Library contains owl.pl - an OWL reasoning package. • F-OWL is an f-logic based Owl tool from UMBC. • E-wallet is an e-commerce and mobile computing tool based on a rule-based OWL reasoner. Logic Foundation Zhongzhi Shi

12. Outline • Introduction • Description Logic • Dynamic Description Logic • Agent-based Services • Ontology-based Knowledge Management KMSphere • Conclusions Logic Foundation Zhongzhi Shi

13. Description Logics • Consistency – query results, across vendor implementations and instances, should be consistent • Performance – Although performance metrics depend on model constructs, OWL-DL supports highly optimized inference algorithms • Predictable – semantics are mathematically decidable within the model, reasoning is finite • Foundational – provides a baseline inside applications for layered semantic models • Reliability – if the answer to a query is implied by any of the model data, it will be found – guaranteed. Logic Foundation Zhongzhi Shi

14. Description Logic • Frame-based system • Semantic Network • Object-oriented representation • Semantic data models • Ontology language Logic Foundation Zhongzhi Shi

15. Description Logic • Concepts and Role • Tbox——Assertions • Abox——Instance • Reasoning mechanism in terms of Tbox and Abox Logic Foundation Zhongzhi Shi

16. TBox TBox Language Set of axioms Definition: Concept name A = C, A⊑C Father = Man ⊓∃has-child.Human Human ⊑Animal ⊓Biped Logic Foundation Zhongzhi Shi

17. TBox Instance ◆ Concept ——entity (one unit predicate，class) Example：Student, Married {x | Student(x) } ，{x | Married(x) } Bird⊑Animal, Man ⊑ Human ◆Roles ——Property (two unit predicate，role) Examples：Friend，Loves {<x,y> | Friend(x,y) } ，{<x,y> | Loves(x,y) } Logic Foundation Zhongzhi Shi

18. ABox Language（Assertion） Set of concrete axioms ◆ Concept assertion a:C Examples：Tom is a student: Tom: Student Or Student(Tom) John: Man ⊓∃has-child.Female ◆ Role assertion ——Indicate the role between two objects <a,b>:R Example：John has a child called Mary <John,Mary>: has-child Logic Foundation Zhongzhi Shi

19. Syntax and Semantics Logic Foundation Zhongzhi Shi

20. Reasoning in DL 1) Subsumption 2) consistency 3) satisfiability 4) instance checking Logic Foundation Zhongzhi Shi

21. K B TBox(Scheme) Man = Human ⊓ Male Happy-father = Human ⊓∃ Has-child.Female⊓… Abox(Data) John: Happy-father <John,Mary> : Has-child Reasoning Interface Logic Foundation Zhongzhi Shi

22. Outline • Introduction • Description Logic • Dynamic Description Logic • Agent-based Services • Ontology-based Knowledge Management KMSphere • Conclusions Logic Foundation Zhongzhi Shi

23. Dynamic Description Logic The primitive symbols • Concept name：C1, C2, …； • Role name：R1, R2, …； • Individual constant：a, b, c, …； • Individual variable：x, y, z, …； • Concept operation：, ⊓, ⊔, , ； • Axiom operation：, ∧, ； • Action：A1, A2, …； • Action constraction：；(composition)，⋃ (alternation)，* (repeat)，？(test)； • Action variable：α,β, …； • Axiom variable：, , π, …； • State variable：u, v, w, …； Logic Foundation Zhongzhi Shi

24. Concepts in DDL are defined as the following: (1) Primitive concept P, top ⊤ and bottom ⊥ are concepts. (2) C, C⊓D, C⊔D are concepts. (3) ∃R.C, ∀R.C are concepts. Dynamic Description Logic Logic Foundation Zhongzhi Shi

25. Dynamic Description Logic An action description is the form of where (1) A is the action name. (2) x1, …, xnare individual variables, which denote the objects the action operate on. (3) PAis the set of preconditions, which must be satisfied before the action is executed. (4) EAis the set of results, which denote the effects of the action. Logic Foundation Zhongzhi Shi

26. DDL Semantics • Actions in DDL are defined as the following: • Atom actionA(a1, …, an) is action. • If α and β are actions, then α;β, α⋃β, α* are actions; • Ifis an assertion formula, then ? is action. Logic Foundation Zhongzhi Shi

27. Outline • Introduction • Description Logic • Dynamic Description Logic • Agent-based Services • Ontology-based Knowledge Management KMSphere • Conclusions Logic Foundation Zhongzhi Shi

28. Semantic Web Services • Define exhaustive description frameworks for describing Web Services and related aspects (Web Service Description Ontologies) • Support ontologies as underlying data model to allow machine supported data interpretation (Semantic Web aspect) • Define semantically driven technologies for automation of the Web Service usage process (Web Service aspect) Logic Foundation Zhongzhi Shi

29. ServiceProfile Presents (What it does) Support Service ServiceGrounding How to access it Described by How it works ServiceModel OWL-S Logic Foundation Zhongzhi Shi

30. OWL-S Context Logic Foundation Zhongzhi Shi

31. Service Description Language SDLSIN <asdl-descr>::=(ctype :service-name name :context context-name+ :types (type-name = <modifier> type)+ :isa name+ :inputs (variable: <modifier> put-type-name)+ :outputs (variable: <modifier> put-type-name)+ :input-constraints (constraint)+ :output-constrains (constraint)+ :io-constrains (constraint)+ :concept-description (ontology-name = ontology-body)+ :state-language name :concept-language name :attributes (attributes-name : attributes-value)+ :text-description name ) Logic Foundation Zhongzhi Shi

32. OWL-S OWL-S Interpreter DDL Incidences matrix+DDL OWL-S Petri Net Generator Petri Net Analysor Services Logic Foundation Zhongzhi Shi

33. Agent-based Services Logic Foundation Zhongzhi Shi

34. Agent Architecture Agent kernel Function Module Interface Function Component Sensor Engine Plug-INs Plug-in Manager Reasoning Communicator Negotiation Scheduling coOperation Resource Database Task Database others Logic Foundation Zhongzhi Shi

35. Metal State Model Mental State: <K, A, G, P, I >， Where • K belief； • A action； • G goal； • P plan； • I intention。 Logic Foundation Zhongzhi Shi

36. Multiagent Environment MAGE Requirement Analysis System Development System Deployment System Design Behaviour Library Agent Society Agent Library AUMP VAStudio MAGE Running Support Logic Foundation Zhongzhi Shi

37. Outline • Introduction • Description Logic • Dynamic Description Logic • Agent-based Services • Ontology-based Knowledge Management KMSphere • Conclusions Logic Foundation Zhongzhi Shi

38. Users Users Users Users Interface Application Level Concept Level groundinglevel Text Ontology Database Ontology Development Logic Foundation Zhongzhi Shi

39. Interface agent Knowledge Space Semantic link (Multi-lingual) Information Space KMSphere Logic Foundation Zhongzhi Shi

40. KMSphere Logic Foundation Zhongzhi Shi

41. Knowledge Application Knowledge Distribution Knowledge organization Ontology Acquisition Email Document File Image Video Web KMSphere Logic Foundation Zhongzhi Shi

42. KMSphere Logic Foundation Zhongzhi Shi

43. KMSphere Demo 通过可视化的人机交互界面手工创建本体 Logic Foundation Zhongzhi Shi

44. KMSphere Demo 从数据库中学习本体 Logic Foundation Zhongzhi Shi

45. KMSphere Demo 从文本中学习本体 Logic Foundation Zhongzhi Shi

46. KMSphere Demo 编辑、修改本体 Logic Foundation Zhongzhi Shi

47. KMSphere Demo 本体一致性检测 Logic Foundation Zhongzhi Shi

48. KMSphere Demo RDQL (RDF Data Query Language)查询 Logic Foundation Zhongzhi Shi

49. Agent Grid Intelligence Platform AGrIP E-B E-G IE Diag. DSS IB Simul Corl Information Sourses Applications Web Middelware CBR GIS Databases GHunt OKPS CAD KMSphere MSMiner MIRES Stream Media MAGE Logic Foundation Zhongzhi Shi

50. Emergency Center Emergency Signal Case Base Decision Making in Terms of Reasoning Retrival Emergency Case Base Solutions Emergency Execution Emergency Interactive Systsem GEIS Logic Foundation Zhongzhi Shi