10.5281/zenodo.6340732
https://zenodo.org/records/6340732
oai:zenodo.org:6340732
Katz, Daniel S.
Daniel S.
Katz
0000-0001-5934-7525
University of Illinois at Urbana-Champaign
Barker, Michelle
Michelle
Barker
0000-0002-3623-172X
Research Software Alliance
Chue Hong, Neil P.
Neil P.
Chue Hong
0000-0002-8876-7606
Software Sustainability Institute / University of Edinburgh
Garcia-Castro, Leyla Jael
Leyla Jael
Garcia-Castro
0000-0003-3986-0510
ZB MED
Gruenpeter, Morane
Morane
Gruenpeter
0000-0002-9777-5560
Software Heritage
Harrow, Jennifer
Jennifer
Harrow
0000-0003-0338-3070
ELIXIR-Europe
Martinez, Carlos
Carlos
Martinez
0000-0001-5565-7577
Netherlands eScience Center
Martinez, Paula Andrea
Paula Andrea
Martinez
0000-0002-8990-1985
National Imaging Facility
Psomopoulos, Fotis E.
Fotis E.
Psomopoulos
0000-0002-0222-4273
Centre for Research and Technology Hellas
The Overlap Between FAIR for Research Software and Open Science
Zenodo
2022
FAIR4RS
open source
research software
open science
2022-03-09
Presentation
10.5281/zenodo.6340731
https://zenodo.org/communities/fair4rs
https://zenodo.org/communities/osc2022
Creative Commons Attribution 4.0 International
Humanity has a mix of overlapping goals that relate to science (and more broadly, wissenschaft). We seek new knowledge for its own purpose as well as for its potential solution to both detailed and general problems, situations, and crises. And we want to be able to verify (or disprove) such knowledge (reproducibility), then build on it (reuse), as simply and as cost-effectively as possible. In this talk, I will focus on knowledge captured in research software, which can be both read, executed, and extended. Specifically, we have developed a new set of FAIR (findable, accessible, interoperable, and reusable) Principles for Research Software, which serve an overlapping purpose with open science. This talk will incude: the role of software in research, the FAIR for Research Software Principles, the community that developed them, the next steps in their implementation, and systematic challenges that need to be addressed for software to be more FAIR and for it to better help meet humanity's science goals.