Software has an important place in academia and therefore in the FAIR ecosystem. It may be used as a tool throughout the research process to serve the data and it can also be the primary outcome of a research process or the object of study. Distinguishing between these different roles is essential for any assessment of the `FAIRness of software’.
This webinar is offered by FAIRsFAIR Work Package 2 - FAIR Practices: Semantics, Interoperability, and Services.
Our objectives for the webinar are:
After the presentations there will be time for Q&A and discussion.
Feedback on the underlying report Assessment report on 'FAIRness of software which is now available for comment from the community, will also be welcomed.
She is an active member of several working groups for Open Science and digital preservation, including: the Research Data Alliance’s Software Source Code Interest Group (SSC IG), the FORCE11’s Software Citation Implementation Working Group (SCI WG), the joint RDA & FORCE11 Software Identification Working Group (SCID WG) and the WikiData for Digital Preservation initiative (WikiDigi). Morane contributes to FAIRsFAIR’s task 2.4 and leads the activities about FAIR software.
Dr Hylke Koers heads up the SURFsara Data Management Services group, which develops and operates services to help research institutes manage their research data in a robust, safe, easy and cost-effective way. Hylke joined SURF in 2018, prior to which he was a Product Director at Elsevier, working on innovations to the scholarly article such as interactive plots and the Virtual Microscope. He co-founded the ICSU-WDS/RDA Working Group that created the Scholix framework, an emerging industry standard for linking research data and literature. He currently leads FAIRsFAIR task 2.4 on ‘FAIRness’ of data services & software, and contributes to the EOSC architecture WG and EOSC-hub WP12. Hylke holds a PhD in theoretical astrophysics from the University of Amsterdam.WEBINAR VIDEO
The FAIR guiding principles (Wilkinson et al. 2016) identified the difficulties of discovering and reusing data, and called for infrastructures to enhance the machine-actionability of their services. This first publication, which was specifically targeted to data, also states that FAIRness should be reached for all research objects including algorithms, tools and workflows. Since the publication of the FAIR principles, different academics and working groups have published articles suggesting that the FAIR principles as written do not automatically apply to software, and that when assessing the FAIRness of software, some adjustments and expansions are needed. It is imperative to consider software as a first class citizen in a FAIR ecosystem and provide guidelines, recommendations, metrics, solutions and infrastructures that acknowledge the importance of software while adequately respecting the differences between software and other digital objects.
| Attachment | Size |
|---|---|
 Webinar intro slides.pdf | 22.31 MB |
| FAIR + software.pdf | 2.58 MB |