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The suite of DDI Alliance products has been formally recognized as an international standard through the publication of ISO/PAS 25955:2026 -- Learn more
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DDI-CDI v1.0

Published: 2025-01-31

XML Schema entry point (use in xsi:schemaLocation declaration if not using a local copy of the schema set):
http://www.ddialliance.org/Specification/DDI-CDI/1.0/XMLSchema/ddi-cdi.xsd 

RDF Namespace
http://www.ddialliance.org/Specification/DDI-CDI/1.0/RDF/
DDI-CDI URIs e.g. for classes and properties will resolve by default to field-level documentation. 

The following RDF serializations are available by specifying the content type type in the HTTP Accept header:  
application/ld+json and text/turtle.

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DDI-CDI is a new standard which is designed to be used with research data from any domain. While it minimally describes metadata for cataloguing and citation, its fundamental purpose is to describe data and process. The specification is domain-neutral and covers the majority of data structures in common use today: Wide, Long, Multi-Dimensional and Key-Value. It offers, for the first time, a mechanism to interoperate disparate data from multiple disciplines and domains at the lowest level of granularity i.e. the datum itself. While it is designed to complement its siblings in the DDI Alliance Product Suite - DDI-Codebook and DDI-Lifecycle, which operate in the Social, Behavioral and Economic domain - it is also intended to work with a wide variety of other domain-specific and generic metadata specifications. Integration is a first-order consideration in DDI-CDI and so it is designed from the ground up to work well with controlled vocabularies from any domain as well as with other standards.

DDI-CDI is a new kind of specification, aimed at both supplementing existing metadata models, and serving a unique purpose in its own right. Its key features include:

  • Model-driven
  • Domain-independence
  • Datum-oriented data description
  • Provenance-focused: process description down to a datapoint level if required

DDI-CDI has three main components. The first one supplies a rich set of foundational metadata for variables, classifications, and other concepts and representations. The second one describes data in rectangular (wide), long (event), multi-dimensional (cube), and no-SQL (big data) data formats. The third one describes process as the primary aspect of data provenance.

DDI-CDI goes back to first principles and abstracts the foundational characteristics of different data structures. On this basis, it uses a “model-based” approach using UML classes. For non-modelers, this simply means that DDI-CDI can be used in the format of your choice, whether you prefer XML, JSON, or other implementation syntaxes.