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Category Archives: FAIR data

Metrics for the evaluation of FAIRness

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A team of FAIR principles authors and drivers have published a core set of semi-quantitative metrics for the evaluation of FAIRness. You can read the preprint about these FAIR Metrics on bioRxiv. “One of the big questions around the FAIR principles has been how to measure what we call their ‘FAIRness’. This paper takes an important first step in that… Continue reading →

What does FAIR mean for agricultural science?

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Andrew Lyons, a researcher at the Division of Agriculture and Natural Resources (ANR) of the University of California, wrote a blogpost about the FAIR principles, the GO FAIR initiative and what it means for agricultural research. “ANR academics are impacted by the data tsunami in at least two ways (neither for good). Like all practicing scientists, we have to deal with the… Continue reading →

NIH awards to test ways to store, access, share, and compute on biomedical data in the cloud

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Twelve awards totaling $9 million in Fiscal Year 2017 will launch a National Institutes of Health Data Commons Pilot Phase. A data commons is a shared virtual space where scientists can work with the digital objects of biomedical research, such as data and analytical tools. The NIH Data Commons will be implemented in a four-year pilot phase to explore the… Continue reading →

European Open Science Cloud Declaration online

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On 26 October 2017, the European Commission made the EOSC Declaration available to all scientific stakeholders, for their endorsement and commitments to the realisation of the EOSC by 2020. The Declaration emerged from the EOSC Summit of 12 June, where more than 80 key scientific stakeholders showed a strong sense of commitment, dedication and intellectual rigour with respect to the implementation of the… Continue reading →

Science goes FAIR at Health-RI 2017

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What does FAIR Data mean in practice? How can you make your data FAIR? What novel science becomes possible when research data become more FAIR? Luiz Bonino and Michel Dumontier will answer these pressing questions at the Health-RI conference on 8 December 2017 in Utrecht. Register for Health-RI 2017. View the conference programme. FAIR Data is rapidly becoming the new standard… Continue reading →

Reuse of clinical data for research: overcoming the hurdles

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The systems of the eight Dutch UMCs contain a wealth of patient data, such as medical images, physical examination results, and treatment outcomes. “These data have been collected to diagnose and treat patients, but we can reuse them to answer important research questions. However, reusing clinical data is not as simple as you may think. In addition to concerns about… Continue reading →

The first Data4lifesciences symposium: a report

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On 11 September 2017, the Centraal Museum in Utrecht hosted the very first Data4lifesciences symposium. D4LS Programme Manager Dr Jan-Willem Boiten: “This symposium was an important milestone for the programme; we presented an overview of our first results.” The NFU programme Data4lifesciences (D4LS) aims to realise an integrated research data infrastructure for biomedical research at the Dutch UMCs. DTL is actively involved… Continue reading →

Watch the ELIXIR Webinar on the rare disease interoperability pilot

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On 18 October 2017, Marco Roos presented an ELIXIR webinar ‘Rare Disease test case for ELIXIR interoperability backbone’. “The ELIXIR rare disease pilot aims to make data machine readable and linkable, making it easier for researchers to combine data from multiple sources,” explains Roos in the webinar. You can watch the webinar here.

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

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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 →