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Article | REF: SL1060 V1

Quality approach for robust research data

Authors: Frédérique ANDRIEU, Fanny BOURRÉE, Marie-Hélène GENTIL, Nathalie GRISE, Loïc KLINGER, Michael S. PRAVIKOFF, Bénédicte SALIN, Henri VALEINS

Publication date: November 10, 2019

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ABSTRACT

Researchers to be known and recognized must publish. However, we note that the number of retractions has been soaring. If the retractions due to malice are set aside, many errors on the search data are unintended. How to avoid these "honest mistakes"? The objective of this article is to show that the quality approach implemented in the research laboratories can improve the robustness of the research data published in scientific journals. For this, the contribution of quality procedures based on ISO 9001 at each stage of a scientific process is presented.

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AUTHORS

  • Frédérique ANDRIEU: Quality Manager - Délégation Aquitaine du CNRS, Esplanade des arts et métiers, Talence, France

  • Fanny BOURRÉE: QHSE Manager - LIRYC (L'Institut de rythmologie et de modélisation cardiaque), Hôpital Xavier Arnozan, CHU de Bordeaux, Avenue du Haut Lévêque, Pessac, France

  • Marie-Hélène GENTIL: Associate Professor UMR 5218 – IMS – Laboratoire de l'intégration du matériau au système, 351 Cours de la libération, Talence, France

  • Nathalie GRISE: Adjointe conseiller prévention de center INRA (Institut national de la recherche agronomique), Centre INRA Bordeaux-Aquitaine, 71, avenue Edouard Bourlaux, Villenave-d'Ornon, France

  • Loïc KLINGER: Quality Management Manager Université de Bordeaux – CNRS – INSERMì UMS 3033 IECB (European Institute of Chemistry and Biology), Pessac, France

  • Michael S. PRAVIKOFF: Chargé de recherche CNRS Université de Bordeaux – CNRS CENBG (Centre d'études nucléaires de Bordeaux-Gradignan) UMR 5797 Université de Bordeaux CNRS, Gradignan, France

  • Bénédicte SALIN: Quality Manager University of Bordeaux – CNRS IBGC (Institute of Biochemistry and Cellular Genetics), Bordeaux, France

  • Henri VALEINS: Head of information systems and quality Université de Bordeaux – CNRS CRMSB (Centre de résonance magnétique des systèmes biologiques), Bât. 4A – Zone Nord – case 93, Bordeaux, France

 INTRODUCTION

To obtain reliable and robust results in research, whether academic or industrial, we need to ensure that the data is sufficiently accurate and numerous to enable reproducibility. For scientific data, the conditions of acquisition, processing and storage must be fully traceable. According to the X05-501 (1994 Identification – Structuring principles and reference designations), reliability is the ability of a device to perform a required function, under given conditions of use and maintenance, for a given period of time.

The constant evolution of the research world, its constraints and complexity, sometimes lead to errors, honest or otherwise... It's time to take stock of best practices and to remind ourselves of the methodology to follow in order to minimize these "honest errors" and non-reproducible results.

This article shows that the quality approach, with its original and proven concepts, is clearly a response to this problem. The aim is to show that quality approaches, best practices and the implementation of quality standards can help improve the reliability of research data and the work of laboratory staff on a day-to-day basis.

The authors are members of the steering committee of the Quality in Research Aquitaine Limousin Regions (QRRAL) network, which is an offshoot of the national Quality in Research (QeR) network supported by the CNRS Mission for Transversal and Interdisciplinary Initiatives (MITI).

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KEYWORDS

ISO 9001   |   quality management system   |   robustness of research data

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