➔ Poster
AuthorsSaskia Hiltemann 1, Rick Jansen 1, David Van Zessen 1, John Hays 2, Andrew Stubbs 1*
1 : Bioinformatics Dept., Erasmus University Medical Center (Erasmus MC)
2 : MMIZ, Erasmus University Medical Center (Erasmus MC)
* : Corresponding author
AbstractIn recent publications, it has been proposed that approximately 50% of pre-clinical research data is not reproducible. Whilst we cannot address all the challenges associated with these findings we can work towards creating an ecosytem at Erasmus MC in which we enable researchers to comply with FAIR data (Findable, Accessible, Interoperable, Re-usable) principles. The correct ‘long-term care' of valuable digital assets means that data can be efficiently re-used for subsequent investigations, either alone, or in combination with newly generated data to create new knowledge. To address the challenges associate with un-FAIR data the European Union has initiated a plan for Open research data in H2020 which is a requirement for all grantees, whereby all research data complies with the FAIR data principles. Our aim was to implement a secure and an easy to use translational research application for clinical research scientists that uses existing informatics technology and services with FAIR data principles built into the design. We implement a generic “end to end” FAIR data point and analysis architecture, myFAIR Analysis, that is applicable for any type of translational or clinical research project. myFAIR was developed using FAIR Data compliant applications including B2DROP (EUDAT), an ownCloud, that provides end users with Dropbox like storage and sharing services which comply with FAIR data principles. myFAIR uses Galaxy to deliver reusable and “provenant” predefined workflows. myFAIR Analysis enables scientists to apply FAIR data principles to both their data and analysis within one single web application that will be freely available from
https://github.com/ErasmusMC-Bioinformatics/myFAIR.
