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Towards a Contextual Approach to Data Quality

Author

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  • Stefano Canali

    (Institute of Philosophy, Leibniz University Hannover, Im Moore 21, 30167 Hannover, Germany)

Abstract

In this commentary, I propose a framework for thinking about data quality in the context of scientific research. I start by analyzing conceptualizations of quality as a property of information, evidence and data and reviewing research in the philosophy of information, the philosophy of science and the philosophy of biomedicine. I identify a push for purpose dependency as one of the main results of this review. On this basis, I present a contextual approach to data quality in scientific research, whereby the quality of a dataset is dependent on the context of use of the dataset as much as the dataset itself. I exemplify the approach by discussing current critiques and debates of scientific quality, thus showcasing how data quality can be approached contextually.

Suggested Citation

  • Stefano Canali, 2020. "Towards a Contextual Approach to Data Quality," Data, MDPI, vol. 5(4), pages 1-10, September.
    • Handle: RePEc:gam:jdataj:v:5:y:2020:i:4:p:90-:d:419528
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    References listed on IDEAS

    as
    1. Sabina Leonelli, 2018. "Rethinking Reproducibility as a Criterion for Research Quality," Research in the History of Economic Thought and Methodology, in: Including a Symposium on Mary Morgan: Curiosity, Imagination, and Surprise, volume 36, pages 129-146, Emerald Group Publishing Limited.
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