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Open AccessEssay

Towards a Contextual Approach to Data Quality

Institute of Philosophy, Leibniz University Hannover, Im Moore 21, 30167 Hannover, Germany
Received: 31 July 2020 / Revised: 18 September 2020 / Accepted: 21 September 2020 / Published: 25 September 2020
(This article belongs to the Special Issue Data Quality and Data Access for Research)
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. View Full-Text
Keywords: research data management; scientific epistemology; data quality; FAIR; reproducibility crisis research data management; scientific epistemology; data quality; FAIR; reproducibility crisis
MDPI and ACS Style

Canali, S. Towards a Contextual Approach to Data Quality. Data 2020, 5, 90. https://doi.org/10.3390/data5040090

AMA Style

Canali S. Towards a Contextual Approach to Data Quality. Data. 2020; 5(4):90. https://doi.org/10.3390/data5040090

Chicago/Turabian Style

Canali, Stefano. 2020. "Towards a Contextual Approach to Data Quality" Data 5, no. 4: 90. https://doi.org/10.3390/data5040090

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