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Uncovering Hidden Insights for Information Management: Examination and Modeling of Change in Digital Collection Metadata

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Transforming Digital Worlds (iConference 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10766))

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Abstract

This paper reports the study which measured and categorized metadata change in the digital collection of patents. The descriptive metadata in this collection is based on the local version of Dublin Core. The moist frequently occurring categories and subcategories of change are identified, as well as metadata fields that are edited the most often. Comparative analysis between multiple editing events is conducted. Results and future/concurrent research are discussed.

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Author information

Authors and Affiliations

  1. Department of Information Science, University of North Texas, 1155 Union Circle 311068, Denton, TX, 76203-5017, USA

    Oksana L. Zavalina, Shadi Shakeri, Priya Kizhakkethil & Mark E. Phillips

Authors
  1. Oksana L. Zavalina
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  2. Shadi Shakeri
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  3. Priya Kizhakkethil
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  4. Mark E. Phillips
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Corresponding author

Correspondence to Oksana L. Zavalina .

Editor information

Editors and Affiliations

  1. Northumbria University, Newcastle upon Tyne, United Kingdom

    Gobinda Chowdhury

  2. Northumbria University, Newcastle upon Tyne, United Kingdom

    Julie McLeod

  3. University of Sheffield, Sheffield, United Kingdom

    Val Gillet

  4. University of Sheffield, Sheffield, United Kingdom

    Peter Willett

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Zavalina, O.L., Shakeri, S., Kizhakkethil, P., Phillips, M.E. (2018). Uncovering Hidden Insights for Information Management: Examination and Modeling of Change in Digital Collection Metadata. In: Chowdhury, G., McLeod, J., Gillet, V., Willett, P. (eds) Transforming Digital Worlds. iConference 2018. Lecture Notes in Computer Science(), vol 10766. Springer, Cham. https://doi.org/10.1007/978-3-319-78105-1_74

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  • DOI: https://doi.org/10.1007/978-3-319-78105-1_74

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-78104-4

  • Online ISBN: 978-3-319-78105-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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