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The FAIR Guiding Principles, published in 2016, aim to improve the findability, accessibility, interoperability and reusability of digital research objects for both humans and machines. The FAIR principles are also directly relevant to research software. In this position paper “Towards FAIR principles for research software”, we summarised and developed a basis for community discussion. At the start, we discussed what makes software different from data concerning the application of the FAIR principles, and which desired characteristics of research software go beyond FAIR. Then, we presented an analysis of where the existing principles can directly apply to software, and where they need to be adapted or reinterpreted. Our next step after the position paper is to prompt for community-agreed identifiers for FAIR research software.Acknowledgments To all the authors of Towards FAIR principles for research software https://doi.org/10.3233/DS-190026, and the numerous people who contributed to the discussions around FAIR research software at different occasions preceding the work on this paper. References Lamprecht, Anna-Lena, et al. (2019) Towards FAIR principles for research software. Data Science. https://doi.org/10.3233/DS-190026 ABOUT THE AUTHOR(S) Dr Paula Andrea Martinez is leading the National Training Program for the Characterisation Community in Australia since 2019. She works for the National Image Facility (NIF). Last year she worked at ELIXIR Europe coordinating the Bioinformatics and Data Science training program in Belgium and collaborated with multiple ELIXIR nodes in the development of Software best practices. Her career, spanning Sweden, Australia and Belgium nurtured her experience in Bioinformatics and Research Software development for complex and dataintensive science. She started a career in Computer Science, later on, interested in research methods development and now outreach and advocacy in data and software best practices

ELIXIR is an intergovernmental organization that brings together life science resources across Europe. These resources include databases, software tools, training events and materials, cloud storage, and supercomputers. ELIXIR's activities are divided into the following five areas Data, Tools, Interoperability, Compute and Training known as “platforms”. The ELIXIR Training Platform coordinates training activities, trains life-science researchers, and helps scientists and developers to find the training they need. One of the goals of ELIXIR is to coordinate these resources so that they form a single interconnected infrastructure. This infrastructure makes it easier for scientists to find and share data, exchange expertise, and agree on best practices, such as best practices for developing and sharing training materials. The FAIR Training Working Group was first informally formed after the “How to make training FAIR” workshop held at the ELIXIR All Hands Meeting in Berlin in 2018. During the workshop, it became clear that there are two different but interdependent topics (1) availability and findability of training materials about FAIR Data Stewardship, (2) making training resources FAIR. Within the Working Group, two Task Forces have been established, and their activities will be highlighted in this talk.&nbsp

The objective of the EOSCpilot data interoperability task (6.2) is to demonstrate how to ensure availability of scientific data to services and users through an open cloud infrastructure. To do so, this task has produced a set of recommendations driving a coherent strategy, as well as a set of technical solutions to help users and programmatic services to find and access datasets across several scientific disciplines, enabling the EOSC to be built around a more coordinated and aligned data ecosystem.