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Welcome. 1. K 1. Bruce Bargmeyer. Lawrence Berkeley National Laboratory University of California Tel: +1 510-495-2905, bebargmeyer@lbl.gov. Welcome Conference Logistics Internet connections – SSID and password in your packets. Meals Breakfast with room Lunch 90 minutes

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  1. Welcome 1 K 1 Bruce Bargmeyer Lawrence Berkeley National Laboratory University of California Tel: +1 510-495-2905, bebargmeyer@lbl.gov

  2. Welcome Conference Logistics Internet connections – SSID and password in your packets. Meals Breakfast with room Lunch 90 minutes Reception – Tonight at 19:30 in Emerald Room Agenda Prompt start and stop of presentations Some late breaking changes Thanks to Program Committee Professor Hajime Horiuchi, General Chairman Professor Doo-Kwon Baik, Vice Chair Program Committee Members ISO/IEC JTC 1/SC 32/WG 2 ISO TC 37 ISO TC 184 Thanks to Speakers Thanks to host and organizers Welcome

  3. Thanks Host: IPSJ / ITSCJ: Information Processing Society of Japan / Information Technology Standards Commission of Japan. Supporter: OGIS-RI Co. Ltd. (Osaka Gas Information Systems–Research Institute) Sponsors: Infoterm International Information Centre for Terminology TermNet The International Network for Terminology Information System Society of Japan UML based Modeling Technologies Promotion

  4. Introduction to the Open Forum on Metadata Registries 2006 1 K 1 Bruce Bargmeyer Lawrence Berkeley National Laboratory University of California Tel: +1 510-495-2905, bebargmeyer@lbl.gov

  5. Users Metadata Registry CONCEPT Concept SystemsThesauri Taxonomies Refers To Symbolizes Ontologies Common logic “Rose”, “ClipArt” Data Standards Structured Metadata Stands For Referent 11179 Metadata Registry 19763 Ontology Registry WG 2 Metadata TC 37 Terminology

  6. We have come to join … Terminology& Metadata

  7. Questions from friends, relatives, associates: TC 184, TC 154, ebXML Asia (Reg/Rep), ODM, practitioners, … Now: Who are WG 2/TC 37? How did WG 2/TC 37 earn a living? What skills and tools do they have? Future: Can they work together? Can they earn a living in a changing world? What skills and tools do they need? What are the most promising directions? We will discuss these and hear about new R&D, standards development, implementations, and new ideas from the speakers at OFMR2006. ???

  8. Area of Work: To develop and maintain standards that facilitate specification and management of metadata. Use of these standards will enhance the understanding and sharing of data, information and processes to support, for example, interoperability, electronic commerce and component-based development. The scope shall include: a framework for specifying and managing metadata; specification and management of data elements, structures and their associated semantics; specification and management of value domains, such as classification and code schemes; specification and management of data about processes and behaviour; facilities to manage metadata, for example: data dictionaries, repositories, information resource dictionary systems, registries and glossaries; facilities to exchange metadata, including its semantics, over the Internet, intranets and other media. Who is WG 1?Metadata

  9. Area of Work: Standardization of principles, methods and applications relating to terminology and other language and content resources in the contexts of multilingual communication and cultural diversity. Who is TC 37?Terminology and other language and content resources

  10. Specification of the “meaning” of data (what data is meant to represent). Documentation of the provenance of data. Standardization and harmonization of data Stewardship of data What has WG 2 Focused On in the Past?

  11. Provide a systemic description of the concepts in the field of terminology Clarify the use of the terms in this field Addressed to, not only standardizers and terminologists, but to anyone involved in terminology work, as well as to the users of terminologies. Exchange of Terminology … What has TC 37 Focused Onin the Past?

  12. ISO 704 Terminology work -- Principles and methods ISO 860 Terminology work -- Harmonization of concepts and terms ISO 1087 Terminology work -- Vocabulary -- Part 1: Theory and application ISO 1087 Terminology work -- Vocabulary -- Part 2: Computer applications ISO 12200 Computer applications in terminology -- Machine-readable terminology interchange format (MARTIF) -- Negotiated interchange ISO 12620 Computer applications in terminology -- Data categories ISO 16642 Computer applications in terminology -- Terminological markup framework Some Inspirational ISO TC 37 Standards

  13. Panhandle Public assistance (government leadership) Data Standards Data management Data administration Build and operate MDR Serve as MDR Registration Authority How Did WG 2 People Earn a Living in the Past?

  14. Crumbs off library tables Catalog library contents Developing terminologies for application areas Computational linguistics … How Did TC 37 People Earn a Living in the Past?

  15. 11179 E 1 Write data descriptions down in Text Used typewriters, word processors, or “editors” Started using DBMSs 11179 E 2 Record data descriptions in databases SQL based query facilities Designed the Metadata Registry schema with modeling tools (but wrote it in text also) Used 11179 E 1 and E 2 Data Standards techniques What Tools & Skills did WG 2Use to Earn a Living?

  16. Information science Write thesauri and taxonomies down in Text Used word processors, “editors”, or typewriters Started using DBMSs Software & database—Data Category Registry … What Tools & Skills did TC 37Use to Earn a Living?

  17. Data integration and harmonization is still a large challenge, but not exciting to large organizations. People like to make up new data and new words unfettered by the past. (It is fine for dictionaries and registries to record what they have done.) Metadata, thesauri and taxonomies are “so last year”. Now knowledge, semantics and ontologies are hot. They get increasing organizational mind share and funding. Knowledge bases Ontologies Triples (subject, verb, object) Inferencing Semantic Web There is recognition of the need for integration and harmonization. But, “If you can’t dance it, you can’t teach it.”–from the movie “Ballroom Dancing” The Future?

  18. Inference engines Reasoners Agents Triple stores Search engines … Have these rendered metadata registries and Data Category Registries obsolete? Have these rendered TC 37 and WG 2 skills, techniques and technologies obsolete? New Tools

  19. Semantics: Where have we been? Where are we planning to go? System manuals Semantic grids Data dictionaries Semantics services (SSOA) 11179 E1 Data + ontology lifecycle management Data Standards 11179 E2 Complex semantics management Data Management/ Data Administration ISO/IEC 11179 E3 19763 P 1-4 24707 Data engineering Terminologies Metadata Registries (MDR) Semantic Web & Ontologies XML & related standards

  20. Users Metadata Registry CONCEPT Concept SystemsThesauri Taxonomies Refers To Symbolizes Ontologies Common logic “Rose”, “ClipArt” Data Standards Structured Metadata Stands For Referent 11179 Metadata Registry 19763 Ontology Registry WG 2 Metadata TC 37 Terminology

  21. Ogden’s Semiotic Triangle Thought or Reference Refers to Symbolises Symbol Referent Stands for C.K Ogden and I. A. Richards. The Meaning of Meaning.

  22. Concept in Semiotic Triangle Thought or Reference (Concept) Refers to Symbolises Symbol Referent Stands for “Rose”, “ClipArt” C.K Ogden and I. A. Richards. The Meaning f Meaning.

  23. From 11179 E2 (2003) Concept : unit of knowledge created by a unique combination of characteristics [ISO1087-1:2000, 3.2.1] Designation: representation of a concept by a sign which denotes it [ISO1087-1:2000, 3.4.1] Definition: representation of a concept by a descriptive statement which serves to differentiate it from related concepts [ISO1087-1:2000, 3.3.1] Concept Relationship: a semantic link among two or more Concepts concept relationship type description: a description of the type of relationship among two or more Concepts WG 2 “Concept”

  24. WG 2 “Concept” Figure8 — Data Element Concept metamodel region ISO/IEC 11179 E2 (2003)

  25. WG 2 “Classification Scheme Item” Figure7 — Classification metamodel region ISO/IEC 11179 E2 (2003)

  26. TC 37 “Concept”

  27. CONCEPT Refers To Symbolizes “Rose”, “ClipArt” Stands For Referent ConceptEssence and Differentia TC 37: Definition Ogden: Symbol TC 37: Designation (Sign)

  28. CONCEPT Refers To Symbolizes “Rose”, “ClipArt” Stands For Referent ConceptEssence and Differentia Definition: Essence & Differentia Ogden: Symbol TC 37: Sign?

  29. 1. any of the wild or cultivated, usually prickly-stemmed, pinnate-leaved, showy-flowered shrubs of the genus Rosa. Cf. rose family. 2. any of various related or similar plants. 3. the flower of any such shrub, of a red, pink, white, or yellow color. --Random House Webster’s Unabridged Dictionary (2003) Rose:

  30. Is each a Rose? — as Defined by Essence and Differentia

  31. Concept: Described by Relationships to Other Concepts Love Romance Marriage CONCEPT Refers To Symbolizes “Rose”, “ClipArt” Stands For Referent

  32. SNOMED – Terms Defined by Relationships • Is this: • The thing that is defined as a procedure that involves an excision of a structure of lobe of lung? (Axiom) 2. A statement saying “All procedures that involve an excision of the structure of lobe of lung are pulmonary lobectomy? (Falsifiable proposition)

  33. Rose: Same Concept? Romance Love Marriage XXX Baby Family Romance Love Marriage XXX Baby Family

  34. Rose: Same Concept? Romance Love Marriage XXX Baby Family XXX Romance Love Marriage Baby Family

  35. Rose: Same Concept? XXX Romance Love Marriage XXX Baby Family

  36. The Communication Process CONCEPT CONCEPT Symbolises Refers To Refers To Symbolises “Rose”, “ClipArt” “Rose”, “ClipArt” Stands For Stands For Referent Symbol Symbol

  37. CommunicationConcept vs. Symbol Symbol Symbol CONCEPT CONCEPT Symbolises Refers To Refers To Symbolises “I see a ClipArt image of a rose” “Rose”, “ClipArt” “Rose”, “ClipArt” Stands For Stands For Referent Symbol Symbol “Rose” “Rose”

  38. RDF: Symbol and Reference Symbol Symbol CONCEPT CONCEPT Symbolises Refers To Refers To Symbolises “I see a ClipArt image of a rose” “Rose”, “ClipArt” “Rose”, “ClipArt” Stands For Stands For Referent Symbol Symbol

  39. RDF: Both Symbols and Reference (Definition) Edge Node Node Subject Predicate Object URI: ….. Rose URI: ….. URI: …..

  40. Edge Node Node Subject Predicate Object Address State Code AB Registry may be used to “ground” the Semantics of an RDF Statement. The address state code is “AB”. This can be expressed as a directed Graph e.g., an RDF statement:

  41. Grounding RDF nodes and relations –URIs Reference a Metadata Registry dbA:e0139 ai: MailingAddress dbA:ma344 ai: StateUSPSCode “AB”^^ai:StateCode @prefix dbA: “http:/www.epa.gov/databaseA” @prefix ai: “http://www.epa/gov/edr/sw/AdministeredItem#”

  42. URI Resolution– in a Metadata Registry Node and relationship meaning is established through a URI pointing to an ISO/IEC 11179 Metadata Registry Mailing Address: “http://www.epa/gov/edr/sw/AdministeredItem#MailingAddress” • The exact address where a mail piece is intended to be delivered, including urban-style address, rural route, and PO Box State USPS Code: “http://www.epa/gov/edr/sw/AdministeredItem#StateUSPSCode” • The U.S. Postal Service (USPS) abbreviation that represents a state or state equivalent for the U.S. or Canada Mailing Address State Name: “http://www.epa/gov/edr/sw/AdministeredItem#StateName” • The name of the state where mail is delivered Needed: Persistent URIs pointing to each item in a 11179 Metadata Registry (Not currently part of the standard).

  43. Independent development and autonomous evolution Multiple ways to specify the same thing within a language (formalism, notation) and between languages Precise specification so that software (agents, applications, systems) can process without human intervention Harmonization and vetting within a community of interest Life cycle management (data, concept systems, ....) Processing based on semantic reasoning, rather than procedure Major Issues in Semantics Management addressed by ISO/IEC 19763, 24707 and 11179

  44. Semantics management - creating, managing, harmonizing, using, exchanging, … : Data, Concepts & relationships (concept systems), Sentences/axioms, Created by diverse organizations, For diverse purposes Management approach: “coordinate and cultivate”, rather than top-down “command and control” Strong Commonality of Purpose19763 & 24707 & 11179

  45. Objective Promote interoperability based on ontologies. Obstacles to ontology-based interoperation Issue 1 Each ontology is developed independently and evolves autonomously. Issue 2 Ontologies are described in several languages, sometimes with different names for the same thing in a Universe of Discourse or with the same name for different things in a UoD. FMI is to solve these problems, providing a registration framework for ontologies. ISO/IEC 19763Framework for Metamodel Interoperability

  46. To avoid this difficulty, FMI Ontology Registration provides two types of ontologies, Reference Ontology and Local Ontology. Agent A Agent B Ontology for application system A Ontology for application system B Give me a ‘green card’. Green card??? I can give you a Christmas card. Christmas card??? Difficulty caused by independent development and autonomous evolution This ontology has a definition of ‘green card’ and does not have a definition of ‘Christmas card’. This ontology does not have a definition of ‘green card’ but has a definition of ‘Christmas card’.

  47. FMI Ontology Registration provides the registration framework where a local ontology is defined based on reference ontologies Card is … Certification is … Color is … Green is … Reference Ontology Agent A Agent B Local Ontology for application system A Local Ontology for application system B Give me a green card. What is a green card? Is it a Christmas card whose color is green? Christmas card is defined in terms of Reference Ontology. Green Card is defined in terms of Reference Ontology No. A green card is a certification of working in the U.S. OK. I understand. Then, I do not have a green card. Reference Ontology

  48. Two agents, A and B, each have a first-order formalization of some knowledge A and B wish to communicate their knowledge to each other so as to draw some conclusions. Any inferences which B draws from A's input should also be derivable by A using basic logical principles, and vice versa The goal of Common Logic is to provide a logic based framework which can support this kind of use and communication without requiring complex negotiations between the agents. Goal of Common Logic

  49. Support traditional data management and data administration in more powerful way. Go beyond traditional Data Standards and Data Administration. We want to support computer processing based on semantics--concepts and relationships. Motivation for ISO/IEC 11179Metadata Registry Extensions

  50. From unstructured natural language metadata (written as text) to structured metadata Explicit modeling and characterization of relationships Graph based metamodels to aid comprehension and searching Formal ontologies AND from human consumption to machine processing for Software agents Computing inferences Semantic applications (e.g., transitive search, subsumption testing, etc.), Semantic services, E.g., mapping – between equivalent value domains, units conversion, … With new key technologies Graph databases (e.g., RDF) facilitate visualization & machine processing Description logic (e.g., OWL DL) for more precise semantics & machine reasoning Software Reasoners (e.g., inference engines) Evolution of metadata technology

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