Adi Alter, Ex Libris
A growing number of research institutions are adopting the FAIR Guiding Data Principles for making research data findable, accessible, interoperable, and reusable.
When research data is easily discoverable and reusable by others, knowledge advances more rapidly. Scholars are able to build on each others’ work, and the entire research community benefits as a result.
FAIR Data Guidelines
But what do FAIR data principles actually require? Here’s a summary of what the FAIR data guidelines call for according to this description from LIBER (the Association of European Research Libraries):
- To make research data findable, data and all supplementary materials should have sufficiently rich metadata and a unique and persistent identifier.
- To make data accessible, the data and its associated metadata should be understandable to humans and machines. Data should be deposited in a trusted, accessible repository.
- To ensure that data are interoperable, metadata should use a formal, accessible, shared, and broadly applicable language for knowledge representation.
- For data to be reusable, all data and collections should have clear usage licenses and should provide accurate source information.
For research data and output to be discoverable, metadata must be applied to these assets consistently across the institution, and they must be stored in a repository that is open and accessible. 
Adopting FAIR Data Principles
Adopting the FAIR data principles requires institutions to strengthen their policies around the sharing and management of research data. For the most part, these efforts are being led by research librarians, who have the unique skills and expertise needed to help their institutions become FAIR compliant. For instance, librarians are already familiar with applying metadata to make research outputs more discoverable, as well as managing the data in institutional repositories and making this information available to external knowledge systems.
However, ensuring that FAIR data guidelines are adopted institution-wide can be challenging. For research data and output to be discoverable, metadata must be applied to these assets consistently across the institution, and they must be stored in a repository that is open and accessible. An additional challenge is the need to link between research publications, the underlying datasets, and related assets (such as conference posters, patents, blog posts, and social media posts). Without connecting all research assets, valuable research work can be harder to find and reuse.
Relying on faculty to change their practices by applying the correct metadata and depositing all research data and output in an open repository can be problematic. Library staff can help with these tasks, but this responsibility is time-consuming and detracts from the time they could be spending on more strategic work instead, which would allow them to support more research initiatives.
Research institutions need high-quality research data management tools and workflows that will make it easy for them to follow the FAIR guidelines. To be effective, these tools and workflows should be designed to avoid or minimize change in researchers’ habits. Any approach that institutions take should not depend on researchers to do anything differently. But adopting the FAIR guidelines should also not create a lot of additional work for librarians, who need to support numerous research projects.
Ex Libris has partnered with several leading universities to develop a new service that simplifies research management and supports the adoption of FAIR data principles in a sustainable way. Esploro is a cloud-based research service solution that automates data capture from internal and external sources, enables libraries to enrich metadata systematically, connects research assets, and facilitates showcasing institutional research work.
To learn more about how Esploro can help research institutions implement the FAIR data principles, read our paper on “The Need for a Next-Generation Research Repository.”
4月 29, 2019
