Although FAIR Data is becoming norm across research domains, the issues of scale and privacy have so far impeded the development of reproducible infrastructures for large-scale bioinformatics research. The NIH Data Commons Project [1] is intended to explore solutions towards developing comprehensive, open-source data analysis ecosystems that enable accessible and reproducible data management workflows in the cloud.
Elsevier is participating in a multi-stakeholder consortium, funded by the Data Commons project, to develop components for open cloud-based research infrastructures together with SevenBridges in Cambridge, Repositive in the UK, and the Veteran’s Administration. Using FAIR principles, the project will make biomedical data more Collaborative, Usable, Reproducible, Extendable and Scalable (CURES), by employing a scalable infrastructure, using interoperable standards for the integration and analysis of diverse data types, and providing workspaces with secure and controlled access protocols [2].
In this presentation, I will present the current state of this project and discuss a Research Object [3] Authoring Tool which Mendeley Data [4]/Elsevier are developing, together with the University of Manchester.
[1]
https://commonfund.nih.gov/commons[2]
https://www.businesswire.com/news/home/20171106005807/en/Bridges-Leads-Public-Private-Partnership-Develop-New-Data[3]
http://www.researchobject.org/[4]
https://data.mendeley.com/
