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?
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This publication is based upon work from COST Action CHARME (CA15110) supported by COST (European Cooperation in Science and Technology). www.cost.eu.
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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
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