Abstract
This practice paper describes an ongoing research project to test the effectiveness and relevance of the FAIR Data Principles. Simultaneously, it will analyse how easy it is for data archives to adhere to the principles. The research took place from November 2016 to January 2017, and will be underpinned with feedback from the repositories.
 The FAIR Data Principles feature 15 facets corresponding to the four letters of FAIR - Findable, Accessible, Interoperable, Reusable. These principles have already gained traction within the research world. The European Commission has recently expanded its demand for research to produce open data. The relevant guidelines1are explicitly written in the context of the FAIR Data Principles. Given an increasing number of researchers will have exposure to the guidelines, understanding their viability and suggesting where there may be room for modification and adjustment is of vital importance.
 This practice paper is connected to a dataset(Dunning et al.,2017) containing the original overview of the sample group statistics and graphs, in an Excel spreadsheet. Over the course of two months, the web-interfaces, help-pages and metadata-records of over 40 data repositories have been examined, to score the individual data repository against the FAIR principles and facets. The traffic-light rating system enables colour-coding according to compliance and vagueness. The statistical analysis provides overall, categorised, on the principles focussing, and on the facet focussing results.
 The analysis includes the statistical and descriptive evaluation, followed by elaborations on Elements of the FAIR Data Principles, the subject specific or repository specific differences, and subsequently what repositories can do to improve their information architecture.
 
 (1) H2020 Guidelines on FAIR Data Management:http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020-hi-oa-data-mgt_en.pdf
Highlights
The 4TU.Centre for Research Data2 (4TU.Research Data) is hosted by the Research Data Services team (RDS) of the Library of the Technical University of Delft
Our conclusions are divided into two sections, one on issues with the FAIR principles themselves, and a second on what repositories can do to respond to the FAIR principles. Within these sections this practice paper examines how closely existing archives are to meeting the FAIR principles. It looks at how much effort is needed to adjust existing data repository structures to adhere to the FAIR principles, and what can realistically be achieved in current set-ups
The type of technical infrastructure required to make datasets compliant to the FAIR principles is very different from making data FAIR compliant
Summary
The 4TU.Centre for Research Data (4TU.Research Data) is hosted by the Research Data Services team (RDS) of the Library of the Technical University of Delft. The FAIR principles intend to give “a minimal set of community-agreed guiding principles and practices” and was created in 2014 (FORCE 11, 2014b). Both machines and humans should be enabled to find (F), access (A), interoperate (I) and re-use (R) research data and metadata in an effortless but confined fashion. Within these sections this practice paper examines how closely existing archives are to meeting the FAIR principles It looks at how much effort is needed to adjust existing data repository structures to adhere to the FAIR principles, and what can realistically be achieved in current set-ups. The type of technical infrastructure required to make datasets compliant to the FAIR principles is very different from making data FAIR compliant
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