Abstract
Research in various scientific disciplines shows an increasing data orientation. However, researchers are not usually interested in all-encompassing standardisation but in a narrow subject area for which they need well-prepared datasets.
Technical tools can provide a high degree of automation both for data integration and for reporting. However, there is a gap between what researchers want from a dataset and what even well-ordered data structures can offer. This gap is closed by research data centres: they offer suitable linking of data from different sources, technical preparation and good documentation of the data content. Most often, they also have to ensure confidentiality.
The existence of high-potential data sources, good preparation and accessibility of data may influence the direction of the research activity: namely, research goes where good data are available.
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Reference
Rendtel U (2011) Fernrechnen, die neue Dimension des Datenzugangs? FU Berlin. 20. Wissenschaftliches Kolloquium: Micro Data Access—Internationale und nationale Perspektiven Stat. Bundesamt, 11 November 2011. https://www.destatis.de/DE/Methoden/Kolloquien/2011/Rendtel.pdf?__blob=publicationFile. Accessed 20 Feb 2017
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Stahl, R., Staab, P. (2018). Standardisation and Research. In: Measuring the Data Universe. Springer, Cham. https://doi.org/10.1007/978-3-319-76989-9_6
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DOI: https://doi.org/10.1007/978-3-319-76989-9_6
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