Towards a Contextual Approach to Data Quality

Stefano Canali
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Stefano Canali: Institute of Philosophy, Leibniz University Hannover, Im Moore 21, 30167 Hannover, Germany

Data, 2020, vol. 5, issue 4, 1-10

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.

Keywords: research data management; scientific epistemology; data quality; FAIR; reproducibility crisis (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2020
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