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Why DDI?

For developers, adopting structured, machine-actionable DDI metadata simplifies integration, enhances interoperability, and enables automation across research data systems.

How DDI Helps Developers

  • Facilitates Integration: DDI's standardized metadata formats make it easier to integrate data across different repositories and discovery platforms.
  • Supports Interoperability: With DDI's shared schemas and vocabularies, developers can build systems that reliably exchange metadata with other platforms using common, well-defined structures.  
  • Automates Data Processing: Structured, consistent metadata supports automation of tasks like transformation, validation, ingestion, and export in metadata-driven pipelines.

How to Get Started

  1. Explore the DDI Schemas -- Review the product schemas to understand the data model, required elements, and available extensions.
  2. Experiment with Tools and APIs -- Leverage DDI tools to import, integrate, and export DDI-compliant metadata within your data system or repository.
  3. Implement DDI in Your Systems -- Incorporate DDI-compliant metadata into your data repository, catalog, ETL pipelines, or research applications.  This might involve: mapping existing metadata to DDI, creating metadata export/import functions, or validating against DDI schemas.
  4. Join the Developers Community and Stay Updated -- DDI is open and community-driven. Engage with other developers by joining the DDI Developers mailing list, contributing to GitHub DDI-Developers group projects, or joining DDI hackathons.