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  • Modelling the Cost of Open Data

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    FaichneyPUB3058.pdf (6.549Mb)
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    Version of Record (VoR)
    Author(s)
    Faichney, Jolon
    Stantic, Bela
    Moaven, Yasaman
    Hiremath, Sanjeev
    Galvin, John
    Griffith University Author(s)
    Stantic, Bela
    Faichney, Jolon B.
    Hiremath, Sanjeev M.
    Moaven, Yasaman
    Year published
    2016
    Metadata
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    Abstract
    The basic principle of Open Data is that data should be freely available to the public to use it without restrictions from copyright or other mechanisms of control. Open Data has benefits including improvements in transparency, productivity, integrity, and accountability. However, at what cost do these benefits come? Relatively little work has been done in quantifying the costs of Open Data in comparison to quantifying the benefits. In this paper we provide a case study on the Open Data initiatives within the City of Gold Coast council. We provide a detailed analysis and description of the processes and people involved in ...
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    The basic principle of Open Data is that data should be freely available to the public to use it without restrictions from copyright or other mechanisms of control. Open Data has benefits including improvements in transparency, productivity, integrity, and accountability. However, at what cost do these benefits come? Relatively little work has been done in quantifying the costs of Open Data in comparison to quantifying the benefits. In this paper we provide a case study on the Open Data initiatives within the City of Gold Coast council. We provide a detailed analysis and description of the processes and people involved in opening data sets and provide estimates for the time involved for each participant in the process. We also explore methods to reduce the time and costs involved through the use of automation. By providing cost models for the Open Data process, organisations will be better equipped to formulate and budget for Open Data strategies
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    Conference Title
    ALLDATA 2016: The Second International Conference on Big Data, Small Data, Linked Data and Open Data
    Publisher URI
    http://www.iaria.org/conferences2016/ALLDATA16.html
    Copyright Statement
    © 2016 IARIA. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the conference's website for access to the definitive, published version.
    Subject
    Information and Computing Sciences not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/374591
    Collection
    • Conference outputs

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