FAIR Data Training

With the FAIR Data principles gaining momentum, many people want to learn more about FAIR Data. We frequently organise FAIR Data Trainings, ranging from general introductions to highly specialised trainings.

Our FAIR Data training may be generic (i.e., applicable in all research domains for all researchers) or tailored to specific domain experts and data (e.g., medical researchers with patient data). Training related to Data Management and Data Stewardship is also part of our portfolio. We offer 1-day and 2-day workshops in FAIR Data, as well as 1-week mini-schools.

Previous FAIR Data training events
Please find below an overview of FAIR Data Training events that we have organised so far.

From 10 to 15 July 2016, LERU, Leiden University and Leiden University Medical Center organised the 7th LERU Doctoral Summer School. DTL supported the event. The summer school’s theme was ‘Data Stewardship for Scientific Discovery and Innovation’ and it was received with enormous enthusiasm. The organisers have prepared a video with an impression of the summer school.

The LERU Doctoral Summer School is a yearly event organised by different LERU members. The aim is to provide PhD candidates with unique professional and personal development opportunities, beyond what they are usually exposed to in the course of their PhD training. By creating an exceptional and truly international, intercultural, and interdisciplinary meeting of bright young minds, the Summer School creates a highly stimulating learning experience which is of long lasting value to the participants’ future careers.

Data Stewardship
The 2016 theme was ‘Data Stewardship for Scientific Discovery and Innovation’. Existing methods of scholarship, scientific discovery and communication (publishing research articles) have been in place for hundreds of years. But as the amount of data being generated, either collectively or in any single study increases, methods that worked so well before, are now impeding the discovery potential latent within large and heterogeneous data. Out-dated methodologies for and incentives behind data generation, capture, processing, interlinking and analysis make data hard to find, hard to integrate and impossible to analyze. Without effective data management plans and data stewardship protocols, valuable data sets are increasingly at risk of being lost.

Essential skill
Robust data stewardship and data publication in machine-readable format is swiftly becoming an essential skill for participation in professional science, and are becoming more and more the responsibility of the data-generator whether they come from academic research or private companies and governmental organizations. Beyond technical challenges, there are also interdependent ethical, legal and societal issues at stake. The LERU Summer School prepared its participants for the future of complex, data-intensive, multi-stakeholder and multi-disciplinary scientific methods and collaborations.

More information

 

On 3-4 November 2016 DTL organised a workshop on FAIR Data stewardship for discovery and innovation. The first day of the workshop, dedicated to providing a high level overview of the issues at hand, and showing concrete examples of FAIR data tools, was attended by 51 participants. The second day focussed on the technical aspects and was joined by 36 people.

Your input
We invite you to share your thoughts on which data sets you’d like to see made FAIR (the FAIR Data game).

Presentations

Day 1:

Ruben Kok: Welcome & introduction
Jaap Heringa: (FAIR) Data Stewardship in Europe in 2017
Erik Schultes: (FAIR) Data Stewardship: Value to the researchers
Arie Baak: Euretos Knowledge platform
Jildau Bouwman: Phenotype DB
David van Enckevort: MOLGENIS
Derk Arts: Castor EDC
Andrew Stubbs: myFAIR
Rob Hooft: The Data stewardship plan
Luiz Bonino: The FAIR data ecosystem

Day 2:
Mark Thompson:

Mark Wilkinson:Interoperability and FAIRness through existing Web technologies