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Ontologies and why they are useful

Ontologies provide agreed vocabularies to describe data in a uniform, machine‑readable way. In a data space, this eases integration across heterogeneous sources, advanced querying, and algorithm reuse.

Benefits

  • Flexibility: you can add new classes/properties without breaking integrations.
  • Machine readability: enables reasoning, validation, and automatic discoverability by AI agents.
  • Reuse: standard models speed up onboarding of new actors and use cases.

Example: Smart Data Models (https://smartdatamodels.org) offers open schemas for domains like agri, energy, or mobility. In our environment, we combine SAREF/ETSI with Smart Data Models to represent sensors, observations, and soil properties.

Rapid extensibility

  • Versioned repository of mappings and models.
  • Agile inclusion of new ontologies (e.g., RML to go from CSV/JSON to RDF) and validation with SHACL.