Guiding questions

Purpose: Define the key concepts and relationships that must be standardised to ensure semantic alignment across use cases.

Which data products require semantic expression through a shared data model?
Which concepts, entities, and relationships must be standardised for your use case?

Purpose: Decide whether to reuse, extend, or develop new data models based on adoption, compatibility, and domain standards.

Can existing data models be reused directly? If not, can they be extended rather than replaced?
Which standards organisations or communities maintain the most relevant models for your domain?
What factors (adoption level, integration compatibility, constraints) influence model selection?

Purpose: Choose meta-standards and reference vocabularies to ensure consistent, machine-readable representation of data models.

Which meta-standards will be used to represent data models? (e.g., RDF/OWL, SKOS, JSON Schema, XML Schema, CSVW)?
What reference datasets or controlled vocabularies (e.g., EU vocabularies, ISO codes) will be linked?
Does your dataspace use W3C as a recognized standards for Identity Management?
Does Dataspace use JSON-LD type as a recognized standard of Identity & Access Management?
Are vocabularies in RDF (Resource Description Framework OWL complaint?

Purpose: Establish processes for managing ownership, versioning, and stakeholder engagement around data models.

Who will act as the data model provider for each model (e.g., Standards Development Organisation, The governance team, sectoral community)?
How will versioning, change approval, and stakeholder engagement be managed?
What processes will be in place for resolving conflicts or inconsistencies between models?

Purpose: Provide accessible platforms and services to host, discover, and link data models with exchange schemas and APIs.

Last updated 17 days ago