FAIR-EASE : D6.5 - Guidelines for the improvement of the FAIRness of digital resources in the Earth Sciences communities

In this deliverable we report on the efforts made in FAIR-EASE in assessing and improving the 
FAIRness of the research data and software used in, or created by, the project. For the assessments 
we used a mix of automated and manual tools, this work being done in WP6 in collaboration with 
the FAIR-IMPACT project. For the improvements, WPs 3, 4 and 6 worked on tackling particular 
aspects of the metadata to improve the FAIRness gaps highlighted by the assessments.  

On the basis of the work reported here, we make specific recommendations for the data publishers 
providing the data used by the pilots (Sec. 2.1). We report on results using the F-UJI automated 
FAIRness assessment tool (Sec. 2.2), including our feedback to F-UJI and to the FAIR-EASE pilots on 
to how to best use this tool. We report on the improvements made to the FAIRness of the metadata 
from the data catalogues ingested into FAIR-EASE’s dataset discovery and access service (Sec. 2.3), 
and point out how those same improvements could impact efforts outside of FAIR-EASE.  

For research software, we assessed the FAIRness of a subset of the FAIR-EASE software components 
using a template (i.e. manual) approach (Sec. 3.1). We summarise the work done with FAIR-IMPACT 
to develop and refine assessment criteria for software, which could be included within automated 
assessment tools (Sec. 3.2). On the basis of these inputs, we develop recommendations for how to 
make research software FAIR, with a focus on the FAIR-EASE domain, i.e. the Earth and 
Environmental sciences (Sec. 3.3).  

Finally, summarising all of the work (Sec. 4.1), we make recommendations for making research data 
more FAIR, from the data creators (the scientists, research communities, research organisations) 
through the data publishers to data brokers (such as FAIR-EASE). Data moving along this pathway 
can be made technically more FAIR at any point – improving Interoperability and Accessiblity – but 
it is necessary that the source data creators provide the necessary data descriptions (metadata to 
provide Findability and Reusability) and provide Interoperable data: these aspects cannot be 
improved in a significant way subsequently. Data creators – whether they are individual scientists 
or larger organisations – are the key to having FAIR data. 

Summarising the work done on software FAIRness (Sec. 4.2): we offer some practical  
recommendations, guidelines, and a template that will help to make research software more FAIR.