Open Data is no longer enough. Digital data must be provided in a 'fair' manner, findable, accessible, interoperable and reusable.
The FAIR Data principles are a globally recognised standard for the sustainable creation and provision of digital data. And if you want to get a project funded, you are increasingly being asked for a concept of how to implement the principles concretely.
But in many areas, there is still a lack of technologies and tools to prepare digital data in compliance with fair- principles. In particular, there is a lack of solutions for efficient metadata management. The basis on which all 4 principles rest.
This makes it difficult to truly comply with the principles.
Metadata, the alpha and omega
The FAIR Data principles are based on the detailed exploration of digital knowledge resources with metadata. They must precisely describe the contents and thus make them better understandable, for humans and machines. This ensures that the data can be used and processed in a versatile manner.
The principles in brief:
Findability:
Knowledge resources must be reliably findable, through unique and permanent addresses (Persistent Identifiers), and the granular description of all contents with qualified metadata.
Accessibility:
Knowledge resources must be provided in such a way that all contents can be used without specialised technologies or tools. Contents that cannot be made accessible must be described by metadata. Ideally, they are made accessible through an authentication and authorisation procedure.
Interoperability:
Knowledge resources must be provided in formats and standards that can be interconnected system-independently, cross-system and system-linking.
Reusability:
Knowledge resources must be designed from the outset to be reused in a versatile way, not only for the original purpose, but also in other unforeseen contexts.
We develop solutions for efficient metadata management. With user-generated keywords, a controlled vocabulary, through automated metadata extraction – or a mixture of everything. Guided authoring services support working with domain-specific vocabularies, ontologies and taxonomies. They can be directly embedded into the authoring tools.