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Ten simple rules on how to write a standard operating procedure

Authors :
Babette Regierer
Christoph Endrullat
Marcus Frohme
Domenica D'Elia
Andreas Kremer
Alina Nechyporenko
Susanne Hollmann
RS: NUTRIM - R1 - Obesity, diabetes and cardiovascular health
RS: FHML MaCSBio
Bioinformatica
Source :
PLoS Computational Biology, 16(9):1008095. Public Library of Science, PLoS Computational Biology, PLoS computational biology 16 (2020). doi:10.1371/journal.pcbi.1008095, info:cnr-pdr/source/autori:Hollmann, Susanne(1); Frohme, Marcus(2); Endrullat, Christoph(3); Kremer, Andreas(4); D'Elia, Domenica(5); Regierer, Babette(6); Nechyporenko, Alina(6)/titolo:Ten simple rules on how to write a standard operating procedure/doi:10.1371%2Fjournal.pcbi.1008095/rivista:PLoS computational biology/anno:2020/pagina_da:/pagina_a:/intervallo_pagine:/volume:16, PLoS Computational Biology, Vol 16, Iss 9, p e1008095 (2020), PLoS Computational Biology, 16, 9, S. e1008095
Publication Year :
2020
Publisher :
Public Library of Science (PLoS), 2020.

Abstract

Research publications and data nowadays should be publicly available on the internet and, theoretically, usable for everyone to develop further research, products, or services. The long-term accessibility of research data is, therefore, fundamental in the economy of the research production process. However, the availability of data is not sufficient by itself, but also their quality must be verifiable. Measures to ensure reuse and reproducibility need to include the entire research life cycle, from the experimental design to the generation of data, quality control, statistical analysis, interpretation, and validation of the results. Hence, high-quality records, particularly for providing a string of documents for the verifiable origin of data, are essential elements that can act as a certificate for potential users (customers). These records also improve the traceability and transparency of data and processes, therefore, improving the reliability of results. Standards for data acquisition, analysis, and documentation have been fostered in the last decade driven by grassroot initiatives of researchers and organizations such as the Research Data Alliance (RDA). Nevertheless, what is still largely missing in the life science academic research are agreed procedures for complex routine research workflows. Here, well-crafted documentation like standard operating procedures (SOPs) offer clear direction and instructions specifically designed to avoid deviations as an absolute necessity for reproducibility. Therefore, this paper provides a standardized workflow that explains step by step how to write an SOP to be used as a starting point for appropriate research documentation.<br />Zweitver��ffentlichungen der Universit��t Potsdam : Mathematisch-Naturwissenschaftliche Reihe; 1201

Details

ISSN :
15537358 and 1553734X
Volume :
16
Database :
OpenAIRE
Journal :
PLOS Computational Biology
Accession number :
edsair.doi.dedup.....bcd29999b4ffbb7526051ab7e6ff190d