The aims of the CHARTED project include “making HPC training content more FAIR (findable, accessible, interoperable and reusable);”. This terminology may not be familiar to everyone involved in the development of the training ecosystem for digital Research Technical Professionals. Even where the terminology may be familiar, different people will have different interpretations of the terms.

The FAIR Principles are a set of fifteen principles first defined in the context of research data, but broadly applicable to any digital resource.They include guidance for addressing each of the four aspects of making data findable, accessible, interoperable and reusable by people and machines. Due to their broad applicability, there are areas where the guidance is non-specific, and more specific guidance can be useful for specific use cases. For example, Principle I1.3 states that “(meta)data [should] meet domain-relevant community standards”, but deliberately does not attempt to specify the domain, communities or standards.

Separate initiatives have sought to define FAIR more specifically for different domains and different types of data. The most relevant to CHARTED is the definition of FAIR for learning materials. In this context, a learning material (often used interchangeably with learning resource, training material, training resource) is any piece of material that supports learning, including printed material, online tutorials, instructor notes etc. As digital objects, the FAIR Principles and guidance could be applied to them as-is, but more specific definitions are useful to guide creators. The application of FAIR principles to learning materials can be summarised as follows (taken from Skills4EOSC FAIR-by-design):

  • Findable: The editable learning material has a unique and persistent identifier (PID) and is described with sufficiently detailed metadata.
  • Accessible: The human and machine readable metadata and object are stored in a trusted repository with clear authentication and authorization procedures.
  • Interoperable: The metadata describing the learning material follows the RDA [Research Data Alliance] minimum metadata schema combined with agreed-upon controlled vocabularies. Formal, accessible, shared, and broadly applicable language(s) and format(s) are used to develop the material.
  • Reusable: The learning material has a clear usage license (CC-BY-4.0 recommended) and accurate information on provenance.

This definition only covers the four main terms of FAIR however, and is not a complete re-interpretation of the fifteen principles in the context of learning objects. This type of re-interpretation has been carried out for other types of data, particularly software, and a similar exercise could be valuable for learning material. These definitions are still intended to cover learning materials in any domain or community.

There have been attempts to focus these principles on specific communities and domains, most prominently within the life sciences, for example through the ELIXIR FAIR training handbook. In the CHARTED project, we are specifically interested in exploring how these definitions could be tailored to the dRTP community and relevant domains. For example, this could include identifying specific controlled vocabularies and metadata standards to make training material for dRTP skills more interoperable.

Through the discussions we’ve had with learners and trainers, it’s clear that these terms don’t always match the perspectives of many people: for example, when asked about findability, they may be more interested in the appearance of training in repositories or search tools; for accessibility, they are likely to consider aspects of access or usability by different user groups; for interoperability, they may consider how concepts from one piece of training may be applied to another; and for reusability they may clearly distinguish between a learner making use of training and a trainer using material developed by another, both of which are considered reuse for data. Additionally, training is not exactly equivalent to learning material, often including significant non-digital components, e.g. verbal instruction (although ideally this should be supported by digital learning material such as instructor notes).

As such, for CHARTED’s funds and tools, we are taking a relatively broad approach to the definition of FAIR. Funding applications that focus on either of the formal definitions of FAIR given above are welcome. However, we also welcome applications that will address broader aspects of these terms, improving training in ways that benefit trainers and help to meet CHARTED’s aims of improving the dRTP training landscape.

We are inviting owners of different training resources to make use of our FAIR Training evaluation service. This can be used to assess training, particularly with regards to making training FAIR. This evaluation service offers you guidance about actions you can take in order to assess and improve the findability, accessibility, interoperability and reusability of your training. To access the service, please visit the service description page.

A portion of CHARTED’s flexible fund is also dedicated to improving FAIRness of the existing training materials and creating more guidance and resources to support the FAIRification process. For more information please visit Fund 1 description page.