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A taxonomy of functional units for information use of scholarly journal articles

Published: 22 October 2010 Publication History
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  • Abstract

    Today's readers of scholarly literature want to read more in less time. With this in mind, this study applies the idea of the functional unit to the use of digital documents. A functional unit is the smallest information unit with a distinct function within the Introduction, Methods, Results and Discussion components of scholarly journal articles. Through a review and analysis of the literature and validation through user surveys, this study identifies a set of common functional units and examines how they are related to different tasks requiring use of information in journal articles and how they are related to each other for a particular information use task. The findings, presented in the form of a taxonomy, suggest a close relationship between functional units and information use tasks, and furthermore among a set of functional units for a particular information use task. This taxonomy can be used in the design of an electronic journal reading system to support effective and efficient information use.

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    1. A taxonomy of functional units for information use of scholarly journal articles

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          cover image DL Hosted proceedings
          ASIS&T '10: Proceedings of the 73rd ASIS&T Annual Meeting on Navigating Streams in an Information Ecosystem - Volume 47
          October 2010
          824 pages

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          American Society for Information Science

          United States

          Publication History

          Published: 22 October 2010

          Author Tags

          1. document components
          2. functional units
          3. genre analysis
          4. information use tasks
          5. relevance theory

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          ASIS&T '10
          ASIS&T '10: Navigating Streams in an Information Ecosystem
          October 22 - 27, 2010
          Pennsylvania, Pittsburgh

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          ASIS&T '10 Paper Acceptance Rate 52 of 149 submissions, 35%;
          Overall Acceptance Rate 135 of 277 submissions, 49%

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