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Overview of content related to 'digital archive'

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This page provides an overview of 1 article related to 'jacs'. Note that filters may be applied to display a sub-set of articles in this category (see FAQs on filtering for usage tips). Select this link to remove all filters.

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The Joint Academic Classification of Subjects (JACS) system is used by the Higher Education Statistics Agency (HESA) and the Universities and Colleges Admissions Service (UCAS) in the United Kingdom to classify academic subjects, especially for undergraduate degrees. A JACS code for a single subject consists of a letter and three numbers. The letter represents the broad subject classification and subsequent numbers represent further details, similar to the Dewey Decimal System. For example, F represents the Physical Sciences, F300 Physics, F330 Environmental Physics and F331 Atmospheric Physics. (Excerpt from Wikipedia article: Joint Academic Classification of Subjects (JACS))

Key statistics

Metadata related to 'jacs' (as derived from all content tagged with this term):

  • Number of articles referring to 'jacs': 2 (0.1% of published articles)
  • Total references to 'jacs' across all Ariadne articles: 4
  • Average number of references to 'jacs' per Ariadne article: 2.00
  • Earliest Ariadne article referring to 'jacs': 2004-04
  • Trending factor of 'jacs': 0 (see FAQs on monitoring of trends)

See our 'jacs' overview for more data and comparisons with other tags. For visualisations of metadata related to timelines, bands of recency, top authors, and and overall distribution of authors using this term, see our 'jacs' usage charts. Usage chart icon

Top authors

Ariadne contributors most frequently referring to 'jacs':

  1. phil barker (see articles on this topic by this author)
  2. neil jefferies (see articles on this topic by this author)
  3. andy powell (see articles on this topic by this author)
  4. sally rumsey (see articles on this topic by this author)

Note: Links to all articles by authors listed above set filters to display articles by each author in the overview below. Select this link to remove all filters.

Titlesort icon Article summary Date

RDN/LTSN Partnerships: Learning Resource Discovery Based on the LOM and the OAI-PMH

Andy Powell and Phil Barker explore the technical collaboration currently underway between the RDN and the LTSN and describe the RDN/LTSN LOM Application Profile and its use to support resource discovery.

April 2004, issue39, feature article

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by Dr. Radut
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