Automatic Metadata Generation Charles Duncan
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Automatic Metadata Generation Charles Duncan

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Slides by Charles Duncan summarising the findings of the automatic metadata generation use cases project, see http://www.intrallect.com/wiki/index.php/AMG-UC

Slides by Charles Duncan summarising the findings of the automatic metadata generation use cases project, see http://www.intrallect.com/wiki/index.php/AMG-UC

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Automatic Metadata Generation Charles Duncan Automatic Metadata Generation Charles Duncan Presentation Transcript

  • Findings of the Automatic Metadata Generation Use Cases project
      • Charles Duncan
      • [email_address]
  • Find and Seek
    • Hide and Seek?
  • What is metadata?
    • Anything that aids the discovery and discrimination of resources
    known unknowns unknown unknowns too many results ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?
  • Purposes of metadata
    • Discovery (known unknowns)
    • Discrimination (too many results)
    • Recommendation (unknown unknowns)
  • Simplistic View
  • Closer to reality Just-in-case Metadata Generation Other Information Archives Other Information Arc hives Other Information Archives Metadata Use Information Archive Deposit Discovery Metadata Generation Discrimination Recommendation Metadata Generation Just-in-time
  • In-case v. In-time
    • Could require unreasonable processing times for a real-time service
    • Allows great flexibility for new applications
    Just-in-time
    • May create and store metadata which might never be used
    • Efficient if metadata is created once and used many times
    Just-in-case Against For
  • Use case - student
    • Student on history course gets reading list from VLE. Selects an article and is offered, additional information about geographic locations and historical characters mention in the article, list of other articles by same author that have the same highly ranked keywords, other articles that commonly appear on reading lists with this article and books borrowed by students of similar profile with matched keywords.
  • Use case - depositor
    • Researcher submits a paper for deposit in a repository. The PDF is analysed and keywords and classification suggested. File type and size are detected. Author and journal names are detected and checked and disambiguated against authoritative source. Page numbers and date of publication extracted. All these metadata fields completed automatically. Depositor puts paper into two “collections”. All references are identified and related to this paper.
  • Types of automatic metadata gen
    • Automatic recognition and extraction services
      • Key word extraction
      • Automatic classification
      • Basic facts (date, depositor, file type, file size, etc)
    • Authoritative source services
      • Name authority
      • Journal title authority
    • Translation services
      • Conversion between metadata schemas
      • Conversion between languages
    • Metadata quality validation services
      • Harvesting and validating metadata
    • Activity aggregation services
      • Usage (reading lists, library borrowing, search terms)
    • Relationship services
      • User-created collections
      • Automatic term relation mapping (with “strength”)
  • Types of automatic metadata gen  Relationship services  Activity aggregation services  Metadata quality validation services   Translation services   Authoritative source services   Automatic recognition and extraction services Just-in-time Just-in-case
  • Reports
    • Synthesis Report (Use Cases)
    • Guidance Report (Tools)
    • Recommendations Report (JISC only)
    • Specialist reports
      • Subject metadata
      • Name metadata
      • Geospatial metadata
      • Factual metadata
      • Bibliographic metadata
      • Usage metadata
      • File format metadata
      • Integrating automatic metadata services
    http://www.intrallect.com/index.php/intrallect/knowledge_base/research_projects/automatic_metadata_generation_use_cases