This webinar will focus on how the CINECA project is applying FAIR (Findable, Accessible, Interoperable, Reusable) principles in practice. Enabling federated data discovery, data access, and research and analysis, by using open standards across the federated network, is crucial in order to fully exploit the potential of human cohorts to drive personalised medicine. CINECA is working in collaboration with other GA4GH driver projects developing and implementing the methods and infrastructure which will allow effective use of widely-dispersed data to improve the size and quality of datasets available for disease research.

The FAIR principles – standing for Findability, Accessibility, Interoperability, and Reusability – have become the guiding principles for the wider sharing of research data in the life sciences. While FAIR provides guidance for the management of data as well as tools and workflows, the institutional conditions and organizational challenges associated with data sharing need to be taken into account to ensure responsible and fair data practices. This requires considering the context of legal requirements, for instance the principle of fairness and transparency in GDPR, expectations of research participants/data subjects, societal aspects and the “ethics work” that is an integral part of data flows, as well as fairness, equity and benefit sharing within transnational collaborations, which is of utmost importance. This webinar will, from the perspective of ethical, legal and societal implications (ELSI), discuss this broader context of responsible and fair data sharing associated with FAIR.

During this webinar, we will give you some tips and suggestions on how you can make more of the training materials you produce and encourage others to do the same. FAIR is not just for data - we can make our training materials FAIR too. Join us to find out the benefits of sharing your FAIR materials and some simple ways you can make it easy for others to use your materials in their teaching, or as aids for individuals to learn more.

This webinar will focus on practical applications of the FAIR data principles, particularly in the context of clinical bioinformatics. We will highlight several example projects that have put the FAIR principles in practice, and discuss the advantages and some of the challenges involved. ELIXIR Galaxy community (elixir-europe.org/communities/galaxy) promotes the use of Galaxy projects that enhance the FAIRness in data analysis. We will demonstrate the Galaxy services that deliver practical FAIR data analysis with “Single Sign-On” capability provided by ELIXIR-AAI. The aim is to provide (medical) researchers with the practicalities of implementing and using FAIR principles in the context of the CINECA project as applied to translational research at Erasmus University Medical Center.

In this talk, I will discuss the importance of the FAIR principles for the software tools we use to process data. Ranging from small analysis scripts to full fledged data processing pipelines, software needs to be FAIR to enable other researchers to reproduce our own experiments and reuse our software. However software and data are fundamentally different – software is executable in nature and may have intricate dependencies. FAIR principles apply differently to software than they do to data and we must be aware of these differences. Existing initiatives such as the RDA FAIR for Research Software (FAIR4RS) working group (https://www.rd-alliance.org/groups/fair-4-research-software-fair4rs-wg) and http://fair-software.eu/ are already focused on addressing these differences and raising awareness of the importance of FAIR for software.

In this presentation, we will explore several informatics techniques, such as the use of ontology, to make cohort data more FAIR. We will also consider the implications of making cohort data more open and the ethical and governance issues associated with open science benefit sharing.

CINECA starts a "How FAIR are you" webinar series with a presentation by Kees van Bochove, founder of The Hyve. In this webinar, we will dive into the basics of FAIR health data, but also take stock of the current situation in health data networks: after a year of frantic research and collaborations and many open datasets and hackathons on COVID-19, has the situation actually improved? Are we sharing health data on a global scale to improve medical practice, or is quality medical data still only accessible to researchers with the right credentials and deep pockets?