Be FAIR to your data
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FEATURE ARTICLE
Be FAIR to your data Dörte Solle 1 Received: 11 June 2019 / Revised: 31 December 2019 / Accepted: 17 February 2020 # The Author(s) 2020
Abstract Wouldn’t it be great, if experimental data were findable wherever they were? If experimental data were accessible‚ regardless of the storage place and format? If experimental data were interoperable independent of the author or its origin? If experimental data were reusable for further analysis without experimental repetition? The current state of the art of data acquisition in the laboratory is very diverse. A lot of different devices are used, analogue as well as digital ones. Usually all experimental setups and observations are summarized in a handwritten lab notebook, independently from digital or analogue sources. To change the actual and common way of laboratory data acquisition into a digital and modern one, electronic lab notebooks can be used. A challenge of science is to facilitate knowledge discovery by assisting humans and machines in their discovery of scientific data and their associated algorithms and workflows. FAIR describes a set of guiding principles to make data Findable, Accessible, Interoperable, and Reusable. Keywords Scientific data management . Lab notebooks . FAIR principles . Open access
Introduction Wouldn’t it be great, if experimental data were findable wherever they were? Some years ago, data were stored on floppy discs or CDs. These data could get lost. Today, experimental data are distributed on various computer systems, mainly in personally defined folder structures. These data are hard to find for others who are not familiar with the folder structure. Are your data recoverable by yourself in some years or by others who might be interested in? Wouldn’t it be great, if experimental data were accessible‚ regardless of the storage place and format? Older storage media cannot be read any more in default of the necessary devices. Some software is not used any more, or downward compatible and sometimes different programmes are used for the same purpose. Are your data still accessible in some years or by others who have not the same computer setup or software? Wouldn’t it be great, if experimental data were interoperable independently of the author or its origin? Individual data
* Dörte Solle [email protected] 1
Leibniz Universität Hannover, Callinstr.5, 30167 Hannover, Germany
structure and annotation make it difficult to understand and interpret foreign data. Hardly any information is given to understand the experiment or to interpret the results. The context of the data is normally not obvious. Are your data interpretable by others without any explanation? Wouldn’t it be great, if experimental data were reusable for further analysis without experimental repetition? Without findable, accessible and interoperable experimental data, the experiment must be done again for modern data evaluation or comparison between different experiments and their results. Are your data reusable for further issues, questions or interp
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