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Metadata Registry Standards: A Key to Information Integration

Metadata Registry Standards: A Key to Information Integration. Judith Newton NIST. DAMA NCR May, 1999. Agenda. Specification and Standardization of Data Elements: ISO 11179, Parts 1-6 Metamodel for Management of Shareable Data, ANS X3.285

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Metadata Registry Standards: A Key to Information Integration

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  1. Metadata Registry Standards: A Key to Information Integration Judith Newton NIST DAMA NCR May, 1999

  2. Agenda • Specification and Standardization of Data Elements: • ISO 11179, Parts 1-6 • Metamodel for Management of Shareable Data, • ANS X3.285 • Specification of Data Value Domains, • ISO TR 15452 • NWI for Content Issues

  3. Parts of 11179Status • Part1: Framework DIS • Part2: Classification DIS • Part 3: Basic Attributes IS • Part 4: Formulation of Definitions IS • Part 5: Naming and Identification IS • Part 6: Registration IS

  4. Part 1 - FrameworkOrganization of FrameworkDocument • Definitions • Fundamental Concepts • Other parts • Informative Annexes

  5. Definition: Data Element • A unit of data for which the definition, identification, representation, and permissible values are specified by means of a set of attributes.

  6. Database, File, Etc. Database, File, Etc. Transaction, Exchange Unit, Etc. Data Element Record, Segment, Class, Tuple, Etc. Identifier Definition Name Value Domain Etc. Data Element Identifier Definition Name Value Domain Etc. Data Element Identifier Definition Name Value Domain Etc. Field, Column, Etc. Character, Image, Sound, Etc.

  7. Fundamental Model • Taken From Data Modeling • 3 Components • object class • property • representation

  8. Definition: Object Class • Things for which to Store Data • Entities in E-R Models • Classes in O-O Models • Employers, Persons, Automobiles, Orders, etc.

  9. Definition: Property • A peculiarity common to all members of an object class. • Distinguishes or Describes Objects • Attributes or Data Members in Models • Identifier, Age, Address, etc.

  10. Definition: Representation • The combination of a representation class, value domain, datatype, and, if necessary, a unit of measure or a character set.

  11. Part 2 - ClassificationClassification Structures • What forms can classification take? • Keywords • Controlled word lists • Terms from models • Thesaurus • Taxonomy • Ontology • Acyclic directed graph, lattice • Multiple inheritance

  12. Classification -Fundamental Notions • Each node in a classification structure is a taxon (plural: taxa). • Given a classification structure, any taxa relating to a data element can be recorded • The taxa can be recorded in a separate “classification” attribute • With adequate software, users could access and navigate the classification structure • A nonintelligent identifier for each taxon helps to deal with change

  13. Status • ISO • Draft International Standard • Continuing R&D • Concept is evolving • Search engines • Middleware - agents, mediators, request brokers • XML tags • New project - terminology for registries

  14. Part 3 - Basic AttributesScope of Part 3 • Specifies set of “basic attributes” of data elements • independent of their usage in application systems, data bases, data interchange messages. • Recognizes need for additional attributes. • No logical or physical structure of the data implied.

  15. Categories of Basic Attributes • Identifying • identification of a data element • Definitional • description of semantic aspects of data element • Relational • associations among and/or between data elements • Representational • representational aspects • Administrative • management and control

  16. Example Data Element

  17. Summary • Part 3 is a good start to establishing an unambiguous set of specifics documenting data elements. • However, • Further work on the other 11179 parts and beyond has resulted in many refinements and advances addressing a variety of data-related concepts. • A new work item involves replacing Part 3 with X3.285.

  18. Part 4 - Data DefinitionsData Definition Rules • A data definition shall: • Be unique (within a data dictionary) • Be stated in the singular • State what the concept is, rather than what it is not • Be stated as a descriptive phrase or sentence(s) • Contain only commonly understood abbreviations • Be expressed without embedding definitions of other data elements or underlying concepts

  19. Data Definition Guidelines • A data definition should: • State the essential meaning of the concept • Be precise and unambiguous • Be concise • Be able to stand alone • Be expressed without embedding rationale, functional usage, domain information or procedural information • Avoid circular reasoning • Use consistent terminology and structure for related definitions

  20. Part 5 - Naming and Identification • Identification of Data Elements • Five attributes serve to identify a data element. • name • context • registration authority identifier • data identifier • version identifier • Name and context always occur in pairs. • The other three attributes compose the • International Registration Data Identifier.

  21. Principles for Registration Identification of Data • Each data element has a unique identifier within the register of a • Registration Authority. • The combination of: • Registration authority identifier • Data identifier and • Version identifier • uniquely identify a data element. • To be assigned an identifier, the element must be derived, attributed, defined, named, • and registered according to ISO/IEC 11179. • A data element shall have at least one name within a context.

  22. Rule Derivation for Data Elements: Naming principles are described in general terms with examples furnished. Rules are derived from the principles by which standard names are developed. These rules form a naming convention. Because syntax, semantic and lexical rules vary by organization, such as corporations or standards-setting bodies for business areas, no specific naming convention rules are prescribed in the International Standard. The naming principles described in the standard can be applied to other entities, such as attributes and objects.

  23. Rule Types Data element names are formed of components. Each is assigned meaning (semantics) and relative or absolute position (syntax) within a name. They are subject to lexical rules. The components are: object class terms, property terms, representation terms, and qualifier terms. The first three components have counterparts in the Metamodel.

  24. Naming Component Example OBJECT CLASS TERM: REPRESENTATION TERM: Country Name PROPERTY TERM: Identifier QUALIFIER TERMS: Trading partner NAME: Trading partner country name

  25. Part 6 - RegistrationMeta Data Registration Principles • Non exclusive registration: Every organization may be a Registration Authority. • Data sharing registration: Data may be shared intra- or inter-organizationally. • Economically enforced registration: Utility determines longevity and usefulness. • Flexible Registration: Meta data may be registered at different levels of quality.

  26. Retired Standardized Certified Recorded Incomplete Registration Status

  27. X3.285 - MetamodelMetamodel Purpose • Promote sharing of metadata for • understanding (meaning, representation, identification) • discovery • harmonization • reuse • analysis • Provide a common base for metadata registries • management structure • components for interchange

  28. Stewardship Data ElementAdministration Data Element Concept Administration Conceptual &Value DomainAdministration Naming &Identification Classification Metamodel Regions

  29. DATA ELEMENT DataElementConcept Object Class Property Conceptual Domain Value Meaning PermissibleValues Data ValueDomain Representation Class Data Element Representation Data Element Model

  30. Data Element Concept Representation Class Representation class name 1 0..* 0..* 0..* 1 1 Data Value Domain Conceptual Domain value domain name conceptual domain identifier value domain character set name value domain minimum character quantity value domain maximum character quantity 1 1 1..* 1..* value domain dependency description value domain format 1 1 +contains +contains 1 1 enumerated value domain enumerated conceptual domain 2..n 2..n 2..n 2..n +contained in +contained in Permissible Value Value Meaning +means +represents permissible value label value meaning identifier (VMID) permissible value begin date value meaning descriptor permissible value end date value meaning begin date 1 1 1 1 value meaning end date

  31. Future Extensions & Work • Promotion of X3.285 to an ISO standard • Completion of TR 15452 - Data Value Domains • XML Tags • Content consistency • Extended classification/terminology support • Object extensions

  32. DTR 15452 - Specification of Data Value DomainsDefinition: Value Domain • A set of permissible values. • Enumerated: • Countries of the world • Non-Enumerated: • All Real Numbers Between 0 & 1,17 Char Alpha-Num, YYYYMMDD

  33. Value Domains -Examples • Geographic Codes • Chemical Names • Biological Classification

  34. TheProblem How can data values be mapped among representations so that the equivalent semantic meaning is determined, even if the language, format or character set of the representations differ? The Benefits The sharing and reuse of data through equivalent data values will allow information to be exchanged faster and more efficiently. Sets of reusable domain values, with unique identifiers assigned, eliminate the need for exact representation matches.

  35. Scope of the TR Attributes for identification, specification, development and reuse of data value domains for data elements. Assigning a unique identifier to each value within a domain. Defining a data element conceptual domain and describing mappings between the values of a conceptual domain and the values of each representational data value domain. Defining reuse of value domains among data elements.

  36. Data Element Concept Representation Class Representation class name 1 0..* 0..* 0..* 1 1 Data Value Domain Conceptual Domain value domain name conceptual domain identifier value domain character set name value domain minimum character quantity value domain maximum character quantity 1 1 1..* 1..* value domain dependency description value domain format 1 1 +contains +contains 1 1 enumerated value domain enumerated conceptual domain 2..n 2..n 2..n 2..n +contained in +contained in Permissible Value Value Meaning +means +represents permissible value label value meaning identifier (VMID) permissible value begin date value meaning descriptor permissible value end date value meaning begin date 1 1 1 1 value meaning end date

  37. Data Element Concept Representation Class Representation class name 1 0..* 0..* 0..* 1 1 Data Value Domain Conceptual Domain value domain name conceptual domain identifier value domain character set name value domain minimum character quantity value domain maximum character quantity 1 1 1..* 1..* value domain dependency description value domain format 1 1 +contains +contains 1 1 enumerated value domain enumerated conceptual domain 2..n 2..n 2..n 2..n +contained in +contained in Permissible Value Value Meaning +means +represents permissible value label value meaning identifier (VMID) permissible value begin date value meaning descriptor permissible value end date value meaning begin date 1 1 1 1 value meaning end date Conceptual Level: Object class and Property Logical Level: Representation with addition of qualifier, Application Level

  38. Conclusions Application of all principles of the ISO 11179 family to the development of meta data registries allows easy and effective exchange of data and meta data nationally and internationally.

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