1. Metadata Standards and Applications 6. Vocabularies: Attributes and Values

2. Goals of Session Understand how different vocabularies are used in metadata Understand how different vocabularies are used in metadata Learn about relationships in vocabularies Learn about relationships in vocabularies Understand methods of encoding vocabularies for various purposes Understand methods of encoding vocabularies for various purposes Learn about how registries are used to document vocabularies Learn about how registries are used to document vocabularies Metadata Standards & Applications 2

3. 3 Vocabulary Issues Where vocabularies occur in metadata Where vocabularies occur in metadata Establishment of formal relationships among terms (where appropriate) Establishment of formal relationships among terms (where appropriate) Testing and validation of terms Testing and validation of terms The role of Metadata Registries The role of Metadata Registries

4. Metadata Standards & Applications 4 Why bother? To improve retrieval, i.e., to get an optimum balance of precision and recall To improve retrieval, i.e., to get an optimum balance of precision and recall –Precision – How many of the retrieved records are relevant? –Recall – How many of the relevant records did you retrieve?

5. Metadata Standards & Applications 5 Improving recall and precision Controlled Vocabularies improve recall by addressing synonyms [attire vs. dress vs. clothing] Controlled Vocabularies improve recall by addressing synonyms [attire vs. dress vs. clothing] Controlled Vocabularies improve precision by addressing homographs [bridge (game) vs. bridge (structure) vs. bridge (dental device)] Controlled Vocabularies improve precision by addressing homographs [bridge (game) vs. bridge (structure) vs. bridge (dental device)]

6. Metadata Standards & Applications 6 Types of Controlled Vocabularies Lists Lists Synonym Rings Synonym Rings Taxonomy Taxonomy Thesaurus Thesaurus [Classification Schemes] [Classification Schemes] Ontology Ontology

7. Metadata Standards & Applications 7 Thesauri & Classification Some knowledge management researchers feel that these are essentially the same, with the primary difference being whether the preferred term is a notation Some knowledge management researchers feel that these are essentially the same, with the primary difference being whether the preferred term is a notation As the need to do machine readable encoding progresses, some additional differences are emerging As the need to do machine readable encoding progresses, some additional differences are emerging

8. Metadata Standards & Applications 8 Lists A list is a simple group of terms Example: Example:AlabamaAlaskaArkansasCaliforniaColorado.... Frequently used in Web site pick lists and pull down menus Frequently used in Web site pick lists and pull down menus

9. Metadata Standards & Applications 9 Synonym Rings Synonym rings are used to expand queries for content objects Synonym rings are used to expand queries for content objects –If a user enters any one of these terms as a query to the system, all items are retrieved that contain any of the terms in the cluster Synonym rings are often used in systems where the underlying content objects are left in their unstructured natural language format Synonym rings are often used in systems where the underlying content objects are left in their unstructured natural language format – the control is achieved through the interface by drawing together similar terms into these clusters Synonym rings are used in conjunction with search engines and provide a minimal amount of control of the diversity of the language found in the texts of the underlying documents Synonym rings are used in conjunction with search engines and provide a minimal amount of control of the diversity of the language found in the texts of the underlying documents

10. Metadata Standards & Applications 10 Taxonomies A taxonomy is a set of preferred terms, all connected by a hierarchy or polyhierarchy Example: Example:Chemistry Organic chemistry Polymer chemistry Nylon Frequently used in web navigation systems

11. Metadata Standards & Applications 11 Thesauri A thesaurus is a controlled vocabulary with multiple types of relationships Example: Example:Rice UF paddy UF paddy BT Cereals BT Plant products NT Brown rice RT Rice straw

12. Metadata Standards & Applications 12 Ontology A useful definition: An arrangement of concepts and relations based on an underlying model of reality. A useful definition: An arrangement of concepts and relations based on an underlying model of reality. –Ex.: Organs, symptoms, and diseases in medicine No real agreement on definition every community uses the term in a slightly different way No real agreement on definition every community uses the term in a slightly different way

13. Metadata Standards & Applications 13 Thesaural Relationships Relationship types: Use/Used For – indicates preferred term Use/Used For – indicates preferred term Hierarchy – indicates broader and narrower terms Hierarchy – indicates broader and narrower terms Associative – almost unlimited types of relationships may be used Associative – almost unlimited types of relationships may be used It is the most complex format for controlled vocabularies and widely used. It is the most complex format for controlled vocabularies and widely used.

14. Metadata Standards & Applications 14

15. Metadata Standards & Applications 15 Z39.19 Types of Concepts Things and their physical parts Things and their physical parts Materials Materials Activities or processes Activities or processes Events or occurrences Events or occurrences Properties or states of persons, things, materials or actions Properties or states of persons, things, materials or actions Disciplines or subject fields Disciplines or subject fields Units of measurement Units of measurement Unique entities Unique entities

16. Metadata Standards & Applications 16 Examples Birds (things) Birds (things) Ornithology (discipline) Ornithology (discipline) Feathers (materials) Feathers (materials) Flying (activity or process) Flying (activity or process) Bird counts (event) Bird counts (event) Barn Owl (unique entity) Barn Owl (unique entity)

17. Metadata Standards & Applications 17 Relationships Equivalence Equivalence Hierarchical Hierarchical Associative Associative

18. Metadata Standards & Applications 18 Equivalence Relationships Term A and Term B overlap completely A = B

19. Metadata Standards & Applications 19 Hierarchical Relationships Term A is included in Term B Term A is included in Term B B A

20. Metadata Standards & Applications 20 Associative Relationships Semantics of terms A and B overlap Semantics of terms A and B overlap AB

21. Metadata Standards & Applications 21 Expressing Relationship

22. Metadata Standards & Applications 22 Hierarchy rules Relationships must be independent of context Relationships must be independent of context Examples: Examples: –Mice (BT Rodents); Rodents (NT Mice) –NOT Mice (BT Pests); Pests (NT Mice)

23. Metadata Standards & Applications 23 Hierarchy rules Terms must represent the same type of entity Terms must represent the same type of entity Examples: Examples: –Shoes (BT Footwear); Footwear (NT Shoes) –NOT Shoes (BT Shoemaking); Shoemaking (NT Shoes)

24. Metadata Standards & Applications 24 Vocabulary Management The degree of control over a vocabulary is (mostly) independent of its type The degree of control over a vocabulary is (mostly) independent of its type –Uncontrolled – Anybody can add anything at any time and no effort is made to keep things consistent –Managed – Software makes sure there is a list that is consistent (no duplicates, no orphan nodes) at any one time. Almost anybody can add anything, subject to consistency rules –Controlled – A documented process is followed for the update of the vocabulary. Few people have authority to change the list. Software may help, but emphasis is on human processes and custodianship

25. Metadata Standards & Applications 25 Informal Vocabularies New movement towards bottom up classification goes by many names: New movement towards bottom up classification goes by many names: –Tagging –Social bookmarking –Folksonomies Many in this movement, seeing problems of scale, are moving towards more formalization Many in this movement, seeing problems of scale, are moving towards more formalization

26. Libraries/Museums and Tagging Penn Tags Penn Tags –Still experimental, primarily internal to Penn –http://tags.library.upenn.edu/help/ http://tags.library.upenn.edu/help/ Library of Congress Flickr project Library of Congress Flickr project –Open public tagging, still unclear how results will be used –http://www.flickr.com/photos/library_of_congress/ http://www.flickr.com/photos/library_of_congress/ The Art Museum Social Tagging Project The Art Museum Social Tagging Project –Research/software project focused on museum application –http://www.steve.museum/ http://www.steve.museum/ Metadata Standards & Applications 26

27. Metadata Standards & Applications 27 Current Encoding Standards: Authorities MARC 21 MARC 21 –Authority Format used for names, subjects, series; –Classification Format used for subject classification MADS (a derivative of MARC authorities) MADS (a derivative of MARC authorities) –Used primarily for names

28. Metadata Standards & Applications 28 MARC 21 Authority Name

29. Metadata Standards & Applications 29 MARC 21 Authority Subject

30. Metadata Standards & Applications 30 MARC 21 Classification LCC

31. Metadata Standards & Applications 31 MARC 21 Classification DDC

32. What is MADS? Metadata Authority Description Schema Metadata Authority Description Schema –A companion to MODS for authority data using XML –Defines a subset of MARC authority elements using language-based tags –Elements have same definitions as equivalent MODS MADS can be used for metadata about people, organizations, events, subjects, time periods, genres, geographics and occupations MADS can be used for metadata about people, organizations, events, subjects, time periods, genres, geographics and occupations Metadata Standards & Applications 32

33. MADS Elements Authority Authority –name –titleInfo –topic –temporal –genre –geographic –hierarchicalGeographic –occupation Related Related –same subelements Variant Variant –same subelements Note Note Affiliation Affiliation url url Identifier Identifier fieldOfActivity fieldOfActivity Extension Extension recordInfo recordInfo Metadata Standards & Applications 33

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35. New/Upcoming Standards:Authorities Functional Requirements for Authority Data (FRAD) Functional Requirements for Authority Data (FRAD) –A new model for authority information –Developed by the IFLA Working Group on Functional Requirements and Numbering of Authority Records (FRANAR) –VIAF (Virtual International Authority File) Prototype at: http://orlabs.oclc.org/viaf/ Prototype at: http://orlabs.oclc.org/viaf/http://orlabs.oclc.org/viaf/ A Review of the Feasibility of an International Authority Data Number (ISADN) A Review of the Feasibility of an International Authority Data Number (ISADN) Simple Knowledge Organization System (SKOS) a W3C standard Simple Knowledge Organization System (SKOS) a W3C standard Metadata Standards & Applications 35

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37. Functions of the Authority File Document decisions Document decisions Serve as reference tool Serve as reference tool Control forms of access points Control forms of access points Support access to bibliographic files Support access to bibliographic files Link bibliographic and authority files Link bibliographic and authority files (Slide from Glenn Patton)

38. Metadata Standards & Applications 38 FRANAR Concept Model, top

39. Metadata Standards & Applications 39 FRANAR Concept Model, bottom

40. FRAD person attributes From FRBR (AACR2 additions to names): Dates associated with the person Title of person Other designation associated with the person New: Gender Place of birth Place of death Country Place of residence Affiliation Address Language of person Field of activity Profession/occupation Biography/history (Slide from Ed Jones)

41. Metadata Standards & Applications 41 VIAF Search Result

42. Metadata Standards & Applications 42 VIAF DNB Display

43. SKOS Simple Knowledge Organisation System (SKOS) Simple Knowledge Organisation System (SKOS) –A World Wide Web Consortium (W3C) standard –Based on RDF and OWL –Currently resolving last call comments, will be finalized in early 2009 –http://www.w3.org/skos/ http://www.w3.org/skos/ Metadata Standards & Applications 43

44. Metadata Standards & Applications 44 The skos:Concept class allows you to assert that a resource is a conceptual resource. That is, the resource is itself a concept.skos:Concept

45. Metadata Standards & Applications 45 The RDF/XML Encoded Version

46. Metadata Standards & Applications 46 Preferred and Alternative Lexical Labels

47. Metadata Standards & Applications 47 The RDF/XML Encoded Version

48. Metadata Standards & Applications 48 Registries: the Big Picture (Adapted from Wagner & Weibel, The Dublin Core Metadata Registry: Requirements, Implementation, and Experience JoDI, 2005)

49. Metadata Standards & Applications 49 Why Registries? Support the interoperability cycle: Support the interoperability cycle: –Discovery of available schemes and schemas for description of resources –Promote reuse of extant schemes and schemas –Access to machine-readable and human- readable services –Support for crosswalking and translation Coping with a state of perpetual metadata heterogeneity (Bianchi and Petrone) Coping with a state of perpetual metadata heterogeneity (Bianchi and Petrone)

50. Metadata Standards & Applications 50 What Do Registries Register? Metadata Schemas (element sets, formats) Metadata Schemas (element sets, formats) –Crosswalks between metadata schemas Controlled Vocabularies Controlled Vocabularies –Mappings between vocabularies Application Profiles Application Profiles –Schema and vocabulary information in combination with specific usage instruction

51. Metadata Standards & Applications 51 Dublin Core RegistryTerm Level

52. Metadata Standards & Applications 52 NSDL RegistryProperty Vocabulary List

53. Metadata Standards & Applications 53 NSDL RegistryProperty Vocabulary Detail

54. Metadata Standards & Applications 54 Element Detail RDF

55. Metadata Standards & Applications 55 Concept Vocabulary Detail

56. Metadata Standards & Applications 56 Concept Vocabulary XML Schema

57. Please Play! The NSDL Registry has a sandbox where anyone can try out the registry software: The NSDL Registry has a sandbox where anyone can try out the registry software: –http://sandbox.metadataregistry.org http://sandbox.metadataregistry.org Please feel free to play in the Registry Sandbox! Please feel free to play in the Registry Sandbox! Note: The production registry is open as well, but not for play … Note: The production registry is open as well, but not for play … Metadata Standards & Applications 57

58. Metadata Standards & Applications 58 Acknowledgements Some slides used here are from presentations by Marcia Zeng and Alistair Miles Some slides used here are from presentations by Marcia Zeng and Alistair Miles