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About expanding dataset records

Additional metadata beyond basic dataset information provides structural and contextual information that makes your datasets more comprehensive, discoverable, and valuable to Data Users. This additional information improves clarity, prevents misuse, enables integration, supports governance, and reduces support burden.

You can add the following components to expand your dataset records:

  • Distributions: Specify how users can access your dataset through downloadable files or web services. You must provide at least one distribution for each dataset record. This includes multiple access methods, formats, and technical specifications for different user needs.
  • Data services: Assign API endpoints to distributions when your dataset is accessed through web services rather than downloadable files.
  • Data dictionary: Document the structure and meaning of dataset fields. Define what each column represents, its data type, and any constraints—improving data understanding and reducing misuse.
  • Dataset relations: Connect datasets to related datasets or external resources. Establish meaningful links to show how datasets fit into larger data collections.
  • Qualified attributions: Provide detailed attribution information about contributors, sources, or responsible parties beyond basic publisher information.
  • Authentic source labels: (For published datasets) Indicate which organisation or entity is the authoritative source for specific data fields within a dataset, enhancing trust and accountability.

How it works:

  • Use these metadata components to align with DCAT-AP-LU standards for comprehensive metadata documentation and significantly improve your dataset's discoverability and usability.
  • You must be an Editor or have the permission to add or edit datasets to add these components.
  • You can only add these components to datasets in the Draft state.
  • When you publish the dataset record, these components become part of its metadata and are visible to Data Users.
  • By adding these components, you make your dataset records more valuable to Data Users through richer context and better accessibility.