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Research Data Reusability: Conceptual Foundations, Barriers and Enabling Technologies

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  • Costantino Thanos

    (Institute of Information Science and Technologies, National Research Council of Italy, 56124 Pisa, Italy)

Abstract

High-throughput scientific instruments are generating massive amounts of data. Today, one of the main challenges faced by researchers is to make the best use of the world’s growing wealth of data. Data (re)usability is becoming a distinct characteristic of modern scientific practice. By data (re)usability, we mean the ease of using data for legitimate scientific research by one or more communities of research (consumer communities) that is produced by other communities of research (producer communities). Data (re)usability allows the reanalysis of evidence, reproduction and verification of results, minimizing duplication of effort, and building on the work of others. It has four main dimensions: policy, legal, economic and technological. The paper addresses the technological dimension of data reusability. The conceptual foundations of data reuse as well as the barriers that hamper data reuse are presented and discussed. The data publication process is proposed as a bridge between the data author and user and the relevant technologies enabling this process are presented.

Suggested Citation

  • Costantino Thanos, 2017. "Research Data Reusability: Conceptual Foundations, Barriers and Enabling Technologies," Publications, MDPI, vol. 5(1), pages 1-19, January.
    • Handle: RePEc:gam:jpubli:v:5:y:2017:i:1:p:2-:d:87230
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    References listed on IDEAS

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    1. Alaina G. Kanfer & Caroline Haythornthwaite & Bertram C. Bruce & Geoffrey C. Bowker & Nicholas C. Burbules & Joseph F. Porac & James Wade, 2000. "Modeling Distributed Knowledge Processes in Next Generation Multidisciplinary Alliances," Information Systems Frontiers, Springer, vol. 2(3), pages 317-331, October.
    2. Christian Bizer & Tom Heath & Tim Berners-Lee, 2009. "Linked Data - The Story So Far," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 5(3), pages 1-22, July.
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    Cited by:

    1. Sirio Cividino & Gianluca Egidi & Ilaria Zambon & Andrea Colantoni, 2019. "Evaluating the Degree of Uncertainty of Research Activities in Industry 4.0," Future Internet, MDPI, vol. 11(9), pages 1-21, September.

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