Software and Data - the interplay for FAIR access to Data, and FAIR Software

[CaroleGoble]

[//]: # "==Do not write above this line== Instructions for posting issues: (1) Review what is already there. Perhaps a comment to an existing issue would be more appropriate than opening a new one? (2) Write your post below using Markdown (as per https://guides.github.com/features/mastering-markdown/ ) or just plain text. (3) Don't worry about these introductory lines - you can leave or delete them, as they won't display anyway (you can check this via Preview). (4) Hit the 'Submit new issue' button. ==Write below this line==" Data alone is not sufficient. Software is needed to access data and enable it to be FAIR and the software itself thus needs to be FAIR. In fact FAIR applies to aggregated and compound Research Objects (researchobject.org), their manifests and containers.

[CaroleGoble]

The Common Workflow Language http://www.commonwl.org is an important FAIR workflow initiative, grassroots and sponsored by NIH, ELIXIR and many other organisations.

[Lau1187]

I came across an article today about FAIR software, co-authored by Carole (reference below). The paper gives four recommendations:

1. Make source code publicly accessible from day one;
2. Make software easy to discover by providing software metadata via a popular community registry;
3. Adopt a licence and comply with the licence of third-party dependencies;
4. Define clear and transparent contribution, governance and communication processes

A paragraph on alignment with FAIR principles is included in the article. A very interesting read!

Jiménez RC, Kuzak M, Alhamdoosh M et al. Four simple recommendations to encourage best practices in research software [version 1; referees: 2 approved]. F1000Research 2017, 6:876 doi: 10.12688/f1000research.11407.1

[brucellino]

This is something close to my heart. In fact, even research objects (software packages etc), are dependent on the instrument/environment which they are expressed ; the same software package compiled against different dependencies and with different optimisations could yield different results.

So, :+1: for this issue. However, as someone who is trying to build citable platforms as well as citable applications, it's very confusing to know what to do, and how to make it easily usable to any researchers. I'm trying to follow the work that CodeMeta is doing with the crosswalk.

@CaroleGoble can you comment on which aspect of FAIR CWL best addresses ? To me it's the "R" bit... but since I'm not a big user of it, I don't have first-hand experience.

[npch]

At a workshop coorganised by DANS and the SSI, we had a session on FAIR for software.

A presentation motivating the discussion is here: https://dans.knaw.nl/nl/actueel/20170307_FAIRSoftwarePrinciplesPeterDoorn.pdf

The notes from that session are available here: https://docs.google.com/document/d/11usAKJsj6fYKwsu0WGqwb3jPy0dGxqulXlFz4KVG-2c/edit?usp=sharing

A brief summary of the discussion is:

• The aim of FAIR for software should be to support open science
  • Avoid confusion with criteria for software sustainability or software quality which are narrower than FAIR for software
• F and A in the FAIR principles apply to software in a similar way to data, I and R need to be interpreted differently
  • It may also be the case that there are additional principles required for software, i.e. FAIR+
• FAIR for software is different but linked to the role software has in ensuring data is FAIR

I'm still trying to write up these notes into something more structured.

[CaroleGoble]

In UK for the BBSRC funding council we are developing Software Sustainability Plans. One of the significant challenges is commercial and licensing issues and the complex provenances of software that challenges the A in FAIR. the SSI ran a workshop on this https://www.software.ac.uk/news/developing-software-licensing-guidance-bbsrc-workshop