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Maastricht University’s Institute of Data Science lands two major research projects on FAIR data

The Institute of Data Science (IDS) at Maastricht University is the only European research group invited to take part in an international research project led by the National Center for Advancing Translational Sciences (NCATS) in the USA. “This will allow us to collaborate with the world leaders in translational research”, says Michel Dumontier, distinguished university professor of Data Science and… Continue reading

FAIR: Putting machine readability first

Barend Mons recently gave an interview about the FAIR principles and the GO FAIR initiative in the journal e-Data & Research. “The way science currently deals with the huge amounts of research data has to change. If you receive tax money for your research, you should take care of the data that you produce and facilitate reuse by others. The FAIR… Continue reading

ePlan workshop on FAIR Facts and Implementations: a report

On 14 September 2017, ePLAN (the national Platform of eScience/Data Research organisations in the Netherlands) organised a workshop ‘FAIR: Facts and Implementations’ at the Netherlands eScience Centre in Amsterdam. Close to 30 people from different Dutch universities, research support services, research institutions, and ventures followed the workshop. Wilco Hazeleger (ePlan), Barend Mons (GO FAIR), Peter Doorn (DANS), and Gareth O’Neill… Continue reading

18 October: ELIXIR webinar on FAIR tools and training materials

On Wednesday 18 October 2017 14:00 BST, ELIXIR-NL’s Marco Roos will present an ELIXIR webinar ‘Overview of a suite of tools and training materials for implementing FAIR data principles’. Join the webinar. There is global endorsement of principles to make data findable, accessible, interoperable and reusable (FAIR) by humans and computers. Marco Roos (ELIXIR-NL), will present standards-based tools, architecture, and training material that help… Continue reading

Find FAIR Data tools

The DTL FAIR Data team has developed tools that compose the so-called ‘Data FAIRport’: FAIRifier and Metadata Editor (to create) FAIR Data Point (to publish) FAIR Search Engine (to find) ORKA (to annotate) Disclaimer: the tools on this page are for the demonstration purposes only. They are still under development and are deployed at SURFsara. We are susceptible to SURFsara’s maintenance… Continue reading

ELIXIR publishes position paper on FAIR data management in life sciences

On 7 September 2017, ELIXIR stated how its infrastructure will help researchers to make published life science data FAIR (Findable, Accessible, Interoperable, and Reusable). This statement also voices ELIXIR’s commitment to enabling the availability of FAIR data within the framework of the European Open Science Cloud (EOSC), an initiative of the European Commission and Member States to connect big data across… Continue reading

DTL-SURF Focus meeting: FAIR tooling

This Focus meeting is a first attempt at coordinating between the different efforts and aligning on the practical implementation of the FAIR principles. The presenters at the Focus meeting will cover several aspects of FAIR in the tools they develop and in the discussion we aim to achieve alignment on common standards and architecture. Continue reading

FAIR workshop on 14 September

On 14 September 2017, the Netherlands eScience Center organises a workshop for researchers and policy makers on FAIR data in Amsterdam. FAIR data refers to data being Findable, Accessible, Interoperable and Reusable, with the goal to make science more transparent, efficient and accessible. It is expected that the FAIR principles will increasingly be used by funding agencies and institutes in the… Continue reading

Nature Genetics editorial: Data models to GO FAIR

On 28 June 2017, the scientific journal Nature Genetics published an editorial calling for submissions containing linked open data models that embody and extend the FAIR principles: “This journal and Scientific Data are calling for submissions containing linked open data models that embody and extend the FAIR principles: that data should be findable, accessible, interoperable and reusable by both humans and machines.… Continue reading
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