Abstract
Open Science describes the ongoing transitions in the way research is performed, i.e. researchers collaborate, knowledge is shared, and science is organized. It is driven by digital technologies and by the enormous growth of data, globalization, enlargement of the scientific community and the need to address societal challenges [23]. It has now widely been recognized that making research results more accessible to all societal actors contributes to better and more efficient science, as well as to innovation in the public and private sectors [1, 17]. However, the reuse of research results can only be achieved reliably and efficiently, if these data are valorized in a specific manner. Data are to be generated, formatted and stored according to Standard Operating Procedures (SOPs) and according to sophisticated Data Management Plans [23]. Hence, to generate accurate and reproducible data sets, to allow interlaboratory comparisons as well as further and future use of research data it is mandatory to work in line with good laboratory practices and well-defined and validated methodologies. Within this article, members of the Cost Action CHARME [10] will discuss aspects of quality management and standardization in context with Open Access (OA) efforts. We will address the question: Are Standardization and Quality Management measures in life-science research crucially needed or introduce further unwanted means of regulation?
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Editorial: Benefits of sharing. Nature 530(7589), 129 (2016). https://doi.org/10.1038/530129a
Berman, H., Henrick, K., Nakamura, H.: Announcing the worldwide protein data bank. Nat. Struct. Mol. Biol. 10(12), 980 (2003). https://doi.org/10.1038/nsb1203-980
Directorate-General for Research and Innovation. ISBN 978-92-79-65567-8, https://doi.org/10.2777/380389
Understanding Science. University of California, Museum of Paleontology, 3 January 2018. http://www.understandingscience.org
Ellingsen, G., Monteiro, E.: Seamless integration: standardisation across multiple local settings. Comput. Support. Coop. Work CSCW 15(5–6), 443–466 (2006). https://doi.org/10.1007/s10606-006-9033-0
Endrullat, C., Glöckler, J., Franke, P., Frohme, M.: Standardization and quality management in next-generation sequencing. Appl. Transl. Genom. 10, 2–9 (2016). https://doi.org/10.1016/j.atg.2016.06.001
European Commission EUR 22836 - Improving knowledge transfer between research institutions and industry across Europe: embracing open innovation (2007). ISBN 978-92-79-05521, http://ec.europa.eu/invest-in-research/pdf/download_en/knowledge_transfe_07.pdf
Freedman, L.P., Venugopalan, G., Wisman, R.: Reproducibility 2020: progress and priorities. F1000Research 6, 604 (2017). https://doi.org/10.12688/f1000research.11334.1. [version 1; referees: 2 approved]
Gargis, A.S., et al.: Assuring the quality of next-generation sequencing in clinical laboratory practice. Nat. Biotechnol. 30(11), 1033–1036 (2012). https://doi.org/10.1038/nbt.2403
Harmonising standardisation strategies to increase efficiency and competitiveness of European life-science research (CHARME) Cost Action CA15110. https://www.cost-charme.eu/the-action/about-charme
Impact of Emerging Technologies on the Biological Sciences, Report of a Workshop, 26–27 June 1995. https://nsf.gov/bio/pubs/reports/stctechn/stcmain.htm
Monya, B.: How quality control could save your science. Nat. News 529, 456–458 (2016)
Wilkinson, M.D., et al.: The FAIR guiding principles for scientific data management and stewardship. Sci. Data 3, Article no. 160018 (2016). Winkler-News. http://www.ariadne.ac.uk/issue64/datacite-2010-rpt
Nickerson, D., et al.: The Human Physiome: how standards, software and innovative service infrastructures are providing the building blocks to make it achievable. Interface Focus 6(2), 20150103 (2016). https://doi.org/10.1098/rsfs.2015.0103
OECD: Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development. The Measurement of Scientific, Technological and Innovation Activities. OECD Publishing, Paris (2015). Accessed 27 Oct 2017
OECD Principles and guidelines for access to research data from public funding – OECD (2007). http://www.oecd.org/sti/sci-tech/38500813.pdf
Open Access in Deutschland. https://www.bmbf.de/pub/Open_Access_in_Deutschland.pdf
Rehm, H.L., et al.: ACMG clinical laboratory standards for next-generation sequencing. Genet. Med. 15(11), 733–747 (2013). https://doi.org/10.1038/gim.2013.92. Working Group of the American College of Medical Genetics and Genomics Laboratory Quality Assurance Committee
Sansone, S., et al.: FAIRsharing: working with and for the community to describe and link data standards, repositories and policies. bioRxiv No. 1, 0–9 (2018)
Smalter Hall, A., Shan, Y., Lushington, G., Visvanathan, M.: An overview of computational life science databases & exchange formats of relevance to chemical biology research. Comb. Chem. High Throughput Screen. 16(3), 189–198 (2013)
Source: Definition of ‘science’. https://www.collinsdictionary.com/dictionary/english/science
Stuart, D., et al.: Practical challenges for researchers in data sharing. Springer Nature (2018). https://doi.org/10.6084/m9.figshare.5975011.v1
The transition towards an Open Science system - Council conclusions, 8791/16 RECH 133 TELECOM 74. http://data.consilium.europa.eu/doc/document/ST-9526-2016-INIT/en/pdf. Accessed 27 May 2016
Acknowledgement
This publication is based upon work from COST Action CHARME (CA15110) supported by COST (European Cooperation in Science and Technology). www.cost.eu.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Hollmann, S. et al. (2018). Standardization and Quality Assurance in Life-Science Research - Crucially Needed or Unnecessary and Annoying Regulation?. In: Kalajdziski, S., Ackovska, N. (eds) ICT Innovations 2018. Engineering and Life Sciences. ICT 2018. Communications in Computer and Information Science, vol 940. Springer, Cham. https://doi.org/10.1007/978-3-030-00825-3_2
Download citation
DOI: https://doi.org/10.1007/978-3-030-00825-3_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-00824-6
Online ISBN: 978-3-030-00825-3
eBook Packages: Computer ScienceComputer Science (R0)