The need for standardisation in life science research - an approach to excellence and trust

. 2020 ; 9 () : 1398. [epub] 20201204

Jazyk angličtina Země Anglie, Velká Británie Médium electronic-ecollection

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/pmid33604028

Today, academic researchers benefit from the changes driven by digital technologies and the enormous growth of knowledge and data, on globalisation, enlargement of the scientific community, and the linkage between different scientific communities and the society. To fully benefit from this development, however, information needs to be shared openly and transparently. Digitalisation plays a major role here because it permeates all areas of business, science and society and is one of the key drivers for innovation and international cooperation. To address the resulting opportunities, the EU promotes the development and use of collaborative ways to produce and share knowledge and data as early as possible in the research process, but also to appropriately secure results with the European strategy for Open Science (OS). It is now widely recognised that making research results more accessible to all societal actors contributes to more effective and efficient science; it also serves as a boost for innovation in the public and private sectors. However for research data to be findable, accessible, interoperable and reusable the use of standards is essential. At the metadata level, considerable efforts in standardisation have already been made (e.g. Data Management Plan and FAIR Principle etc.), whereas in context with the raw data these fundamental efforts are still fragmented and in some cases completely missing. The CHARME consortium, funded by the European Cooperation in Science and Technology (COST) Agency, has identified needs and gaps in the field of standardisation in the life sciences and also discussed potential hurdles for implementation of standards in current practice. Here, the authors suggest four measures in response to current challenges to ensure a high quality of life science research data and their re-usability for research and innovation.

Department of Animal Breeding and Genetics Bioinformatics section University of Agricultural Sciences Uppsala 750 07 Sweden

Department of Bioinformatics BiGCaT Maastricht University Maastricht 6229 ER The Netherlands

Department of Biotechnology and Systems Biology National Institute of Biology Ljubljana 1000 Slovenia

Department of Computer Networks and Systems Silesian University of Technology Gliwice 44 100 Poland

Department of Systems Engineering Kharkiv National University of Radio Electronics Kharkiv Oblast 61000 Ukraine

Division Molecular Biotechnology and Functional Genomics Technical University of Applied Sciences Wildau Wildau Brandenburg 15745 Germany

Division of Bioinformatics and Biostatistics National Center for Toxicological Research US Food and Drug Administration Jefferson AR Jefferson USA

Faculty of Science University of Potsdam Potsdam Brandenburg 14476 Germany

Information Technology for Translational Medicine S A ITTM S A Esch sur Alzette Esch 4354 Luxembourg

Institute for Biomedical Technologies National Research Council Italy Bari 70126 Italy

Institute of Computer Science University of Białystok Białystok 15 328 Poland

Leibniz Institute of Vegetable and Ornamental Crops Großbeeren Brandenburg 14979 Germany

Luxembourg Centre for Systems Biomedicine University of Luxembourg Esch sur Alzette 4367 Luxembourg

Maastricht Centre for Systems Biology Maastricht University Maastricht 6229 ER The Netherlands

Masaryk University Brno 601 77 Czech Republic

SB Science Management UG Berlin Berlin 12163 Germany

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