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The Open Ontology Repository

The Open Ontology Repository. Bart Gajderowicz Ryerson University Based on notes by Ken Baclawski Northeastern University. Agenda. Motivation OOR Added Value Requirements Research Challenges Design & Implementation. Why?.

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The Open Ontology Repository

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  1. The Open Ontology Repository Bart Gajderowicz Ryerson University Based on notes by Ken Baclawski Northeastern University

  2. Agenda • Motivation • OOR • Added Value • Requirements • Research Challenges • Design & Implementation

  3. Why? • Isn’t the Semantic Web notion of distributed islands of semantics sufficient as a de facto repository? • If you put it out there, will they come? • If you build it better and put it out there, will they prefer yours? • History does not show this laissez faire “field of dreams” is good reality.

  4. Okay, but why a new infrastructure? The Clickable Web • The “clickable” web has been very successful in employing a “lazy strategy” for HTML documents. • However the use and content of the Semantic Web has different characteristics that make it far less tolerant of: • change • frequent errors which are commonplace on the clickable web.

  5. Okay, but why a new infrastructure? The Clickable Web • The “clickable” web has been very successful in employing a “lazy strategy” for HTML documents. • However the use and content of the Semantic Web has different characteristics that make it far less tolerant of: • change • frequent errors which are commonplace on the clickable web.

  6. Okay, but why a new infrastructure? Distributed Data Sets • This is also true for increasingly large and complex data sets. • Generally impossible to judge integrity of data without access to metadata. • Increasingly important over time. • Metadata standards are important.

  7. Okay, but why a new infrastructure? Distributed Data Sets • This is also true for increasingly large and complex data sets. • Generally impossible to judge integrity of data without access to metadata. • Increasingly important over time. • Metadata standards are important.

  8. Okay, but why a new infrastructure? Distributed Data Sets • This is also true for increasingly large and complex data sets. • Generally impossible to judge integrity of data without access to metadata. • Increasingly important over time. • Metadata standards are important.

  9. SemWeb Distinguishing Characteristics • Machines, NOT humans, are the primary consumers of content. • Errors that a human may be able to diagnose and fix (such as a change in location of a document) are likely fatal for machine processing. • The use of owl:imports creates a strong transitive dependency between ontology documents. • Import closure can become: • inconsistent • change its meaning • change computational characteristics.

  10. SemWeb Distinguishing Characteristics • Machines, NOT humans, are the primary consumers of content. • Errors that a human may be able to diagnose and fix (such as a change in location of a document) are likely fatal for machine processing. • The use of owl:imports creates a strong transitive dependency between ontology documents. • Import closure can become: • inconsistent • change its meaning • change computational characteristics.

  11. SemWeb Distinguishing Characteristics • Machines, NOT humans, are the primary consumers of content. • Errors that a human may be able to diagnose and fix (such as a change in location of a document) are likely fatal for machine processing. • The use of owl:imports creates a strong transitive dependency between ontology documents. • Import closure can become: • inconsistent • change its meaning • change computational characteristics.

  12. SemWeb Distinguishing Characteristics • Machines, NOT humans, are the primary consumers of content. • Errors that a human may be able to diagnose and fix (such as a change in location of a document) are likely fatal for machine processing. • The use of owl:imports creates a strong transitive dependency between ontology documents. • Imported closures can become: • inconsistent • change its meaning • change computational characteristics.

  13. SemWeb Distinguishing Characteristics • Ontologies convey a precise meaning with an unambiguous machine interpretation. • When using this content, careful selection and precise reference is critical.

  14. OOR Charter Promote the global use and sharing of ontologies by: • establishing a hosted registry-repository • enabling and facilitating open, federated, collaborative ontology repositories • establishing best practices for expressing interoperable ontologies and taxonomy work in registry-repositories. http://openontologyrepository.org

  15. Open Ontology Repository "An ontology repository is a facility where ontologies and related information artefacts can be stored, retrieved and managed” • The persistent store. • The registry. • Value-added services: • Ontology sharing, searching, management, etc. • Linkage to databases, XML Schemas, documents, etc. • Reasoning capabilities.

  16. Open Ontology Repository "An ontology repository is a facility where ontologies and related information artefacts can be stored, retrieved and managed” • The persistent store. • The registry. • Value-added services: • Ontology sharing, searching, management, etc. • Linkage to databases, XML Schemas, documents, etc. • Reasoning capabilities.

  17. Folksonomies Terminologies Controlled vocabularies Taxonomies Thesauri Data schemata Data models OWL ontologies Logical theories Shared understanding Ontological commitments Open Ontology Repository All types of artefacts on the ontology spectrum:

  18. Open Ontology Repository Open Access • compliance with open standards • open technology (open source) • open knowledge (open content) • open collaboration (transparent community process) • open to integration with “non-open” repositories via an open interface

  19. Purpose and Scope of the OOR Initiative • Limited to providing an infrastructure that enables ontology and metadata management. • Formal architecture: • Interfaces • Required services • Enable interoperability among OOR instances. • Reference implementation: • Basic services • Basic metadata lifecycle.

  20. Purpose and Scope of the OOR Initiative • Limited to providing an infrastructure that enables ontology and metadata management. • Formal architecture: • Interfaces • Required services • Enable interoperability among OOR instances. • Reference implementation: • Basic services • Basic metadata lifecycle.

  21. Purpose and Scope of the OOR Initiative • Limited to providing an infrastructure that enables ontology and metadata management. • Formal architecture: • Interfaces • Required services • Enable interoperability among OOR instances. • Reference implementation: • Basic services • Basic metadata lifecycle.

  22. Example Architecture • Repository for ontologies and metadata annotations: • Data being annotated is usually outside the OOR • Knowledge-intensive data can be inside the OOR. • Main relationships: • Provides semantics • Annotates • Inter-ontology relationships (not shown in diagram).

  23. Example Architecture • Repository for ontologies and metadata annotations: • Data being annotated is usually outside the OOR • Knowledge-intensive data can be inside the OOR. • Main relationships: • Provides semantics • Annotates • Inter-ontology relationships (not shown in diagram).

  24. Semantics of OOR Ontology Annotates Repository Metadata Repository Metadata Repository Metadata Domain Specific Ontology Domain Specific Ontology Domain Specific Ontology Metadata Metadata Metadata Metadata Metadata Metadata Knowledge base Image data set Sensor data set Image data set Sensor data set Knowledge base

  25. OOR Value Added: Part 1.1 • The OOR is reliably available. • The OOR is persistent and sustainable, so you can be confident when committing to its use. • The OOR has information about when, why, and how an ontology has changed, so you can be aware of changes that may effect its usability.

  26. OOR Value Added: Part 1.1 • The OOR is reliably available. • The OOR is persistent and sustainable, so you can be confident when committing to its use. • The OOR has information about when, why, and how an ontology has changed, so you can be aware of changes that may effect its usability.

  27. OOR Value Added: Part 1.1 • The OOR is reliably available. • The OOR is persistent and sustainable, so you can be confident when committing to its use. • The OOR has information about when, why, and how an ontology has changed, so you can be aware of changes that may effect its usability.

  28. OOR Value Added: Part 1.2 • You can find ontologies and metadata easily. • Ontologies and metadata are registered, so you know who built them. • Metadata provides the ontology purpose, KR language, user group, content subject area, etc.

  29. OOR Value Added: Part 1.2 • You can find ontologies and metadata easily. • Ontologies and metadata are registered, so you know who built them. • Metadata provides the ontology purpose, KR language, user group, content subject area, etc.

  30. OOR Value Added: Part 1.2 • You can find ontologies and metadata easily. • Ontologies and metadata are registered, so you know who built them. • Metadata provides the ontology purpose, KR language, user group, content subject area, etc.

  31. OOR Value Added: Part 2.1 • The OOR enables services such as: • Ontology search capability • Mappings for connecting ontologies to each other • Content review and certification, and gauge quality and value by some recognized criteria. • OOR services allow users to: • Use services that others have developed, or • Plug in your own services.

  32. OOR Value Added: Part 2.1 • The OOR enables services such as: • Ontology search capability • Mappings for connecting ontologies to each other • Content review and certification, and gauge quality and value by some recognized criteria. • OOR services allow users to: • Use services that others have developed, or • Plug in your own services.

  33. OOR Value Added: Part 2.2 • Ontologies can reuse or extend other ontologies, including common middle and upper ontologies. • The OOR codebase can be extended to: • Domain specific architecture • Enterprise specific architecture.

  34. OOR Value Added: Part 2.2 • Ontologies can reuse or extend other ontologies, including common middle and upper ontologies. • The OOR codebase can be extended to: • Domain specific architecture • Enterprise specific architecture.

  35. Top Requirements • Scalable Repository Architecture. • Optimized for sharing, collaboration, and reuse. • Support for multiple formats, languages and levels of formalisms. • Distributed repositories. • Explicit machine usable formal semantics. • Support for IPR and related legal issues. • Allow for extensions and domain specific services. • Community involvement and engagement of the ontology lifecycle.

  36. Top Requirements • Scalable Repository Architecture. • Optimized for sharing, collaboration, and reuse. • Support for multiple formats, languages and levels of formalisms. • Distributed repositories. • Explicit machine usable formal semantics. • Support for IPR and related legal issues. • Allow for extensions and domain specific services. • Community involvement and engagement of the ontology lifecycle.

  37. Top Requirements • Scalable Repository Architecture. • Optimized for sharing, collaboration, and reuse. • Support for multiple formats, languages and levels of formalisms. • Distributed repositories. • Explicit machine usable formal semantics. • Support for IPR and related legal issues. • Allow for extensions and domain specific services. • Community involvement and engagement of the ontology lifecycle.

  38. Top Requirements • Scalable Repository Architecture. • Optimized for sharing, collaboration, and reuse. • Support for multiple formats, languages and levels of formalisms. • Distributed repositories. • Explicit machine usable formal semantics. • Support for IPR and related legal issues. • Allow for extensions and domain specific services. • Community involvement and engagement of the ontology lifecycle.

  39. Top Requirements • Scalable Repository Architecture. • Optimized for sharing, collaboration, and reuse. • Support for multiple formats, languages and levels of formalisms. • Distributed repositories. • Explicit machine usable formal semantics. • Support for IPR and related legal issues. • Allow for extensions and domain specific services. • Community involvement and engagement of the ontology lifecycle.

  40. Top Requirements • Scalable Repository Architecture. • Optimized for sharing, collaboration, and reuse. • Support for multiple formats, languages and levels of formalisms. • Distributed repositories. • Explicit machine usable formal semantics. • Support for IPR and related legal issues. • Allow for extensions and domain specific services. • Community involvement and engagement of the ontology lifecycle.

  41. Top Requirements • Scalable Repository Architecture. • Optimized for sharing, collaboration, and reuse. • Support for multiple formats, languages and levels of formalisms. • Distributed repositories. • Explicit machine usable formal semantics. • Support for IPR and related legal issues. • Allow for extensions and domain specific services. • Community involvement and engagement of the ontology lifecycle.

  42. Top Requirements • Scalable Repository Architecture. • Optimized for sharing, collaboration, and reuse. • Support for multiple formats, languages and levels of formalisms. • Distributed repositories. • Explicit machine usable formal semantics. • Support for IPR and related legal issues. • Allow for extensions and domain specific services. • Community involvement and engagement of the ontology lifecycle.

  43. Research Challenges: Overview Ontology Summit Topics • 2006 : Upper Ontologies. • 2007: Distinctions between Ontology, Taxonomy, Folksonomy. • 2008 : Repository Architecture. • 2009 : Toward Ontology-based Standards.

  44. Research Challenges: Part 1 • Inadequacies of the “clickable web” as a basis for the Semantic Web: • Need long-term maintenance rather than ontologies maintained in author’s web site. • Varying levels of coverage • Intellectual property concerns. • Best practices: • Policies and procedures • Provenance to enable trust.

  45. Research Challenges: Part 1 • Inadequacies of the “clickable web” as a basis for the Semantic Web: • Need long-term maintenance rather than ontologies maintained in author’s web site. • Varying levels of coverage • Intellectual property concerns. • Best practices: • Policies and procedures • Provenance to enable trust.

  46. Research Challenges: Part 2 • Ontology Metadata: • Dimensions: Expressiveness, Structure, Granularity, Intended Use, Automated Reasoning, Prescriptive vs. Descriptive, Governance • Ontology Metadata Vocabulary (omv.ontoware.org) • eXtended Metadata Registry (xmdr.org). • Interface ontologies: • Internal APIs for core modules and plug-ins • External APIs, especially web services • Federation APIs, among OORs.

  47. Research Challenges: Part 2 • Ontology Metadata: • Dimensions: Expressiveness, Structure, Granularity, Intended Use, Automated Reasoning, Prescriptive vs. Descriptive, Governance • Ontology Metadata Vocabulary (omv.ontoware.org) • eXtended Metadata Registry (xmdr.org). • Interface ontologies: • Internal APIs for core modules and plug-ins • External APIs, especially web services • Federation APIs, among OORs.

  48. Design and Implementation • OOR Sandbox based on BioPortal. • OOR meetings every other Friday at 12:00 EST: • Joint Ontolog-OOR conference calls on: • November 13 • November 27. • See Ontology Summit 2008 Presentation. • ISWC 2009 Paper and Poster. • Home page: openontologyrepository.org

  49. References • OOR Home Page: • http://openontologyrepository.org • OOR Instance • http://oor-01.cim3.net/ • Ontolog Forum • http://ontolog.cim3.net/ • Ontology Summit 2009 • http://ontolog.cim3.net/cgi-bin/wiki.pl?OntologySummit2009 • BioPortal • http://bioportal.bioontology.org/

  50. Open Ontology Repository The End Bart Gajderowicz http://www.scs.ryerson.ca/~bgajdero

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