FAIR: Facts and Implementations - A workshop on the new requirements for Data in Open Science

"On 14 September 2017 ePLAN organizes a workshop for researchers and policy makers on FAIR data. FAIR data refers to data being Findable, Accessible, Interoperable and Reusable, with the goal to make science more transparent, efficient and accessible. It is to be expected that FAIR principles will be increasingly more often used by funding agencies and institutes in the academic domain as a minimum standard for added value creation for data that are created in academia. It is therefore important, both for the development of good academic practice as for future funding of research to learn master the terms and ideas the constitute FAIR. So, for example, is the implementation of the term Interoperable no trivial matter and generally different depending on discipline. At the same time one of the goals is to share and reuse data across disciplines. Which aspects of FAIR form the greatest challenge, which matters are discipline specific and which matters can be dealt with nationally and which need to be addressed internationally. Is FAIR concerned with data only, or are workflows, software and algorithms equally important?"