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How Statistical Agencies Use DDI

Why DDI?

Statistical agencies play a crucial role in collecting, processing, and disseminating high-quality data to inform public policy and research.  DDI provides a standardized approach to describing these data, ensuring consistency, interoperability, and long-term usability.

How DDI Helps Statistical Agencies

  • Standardizes Metadata: DDI helps agencies consistently document surveys, variables, methods, and classifications -- making data more transparent and easier to manage over time. 
  • Enables Data Interoperability and Integration: With machine-readable, standards-based metadata, DDI makes it easier to combine and share data from surveys, censuses, and administrative sources -- both nationally and internationally. 
  • Supports Longitudinal and Historical Comparisons: DDI tracks changes in variables and methods across time, helping agencies harmonize data and support reliable historical comparisons. 
  • Improves Data Access and Reuse: DDI powers search catalogs and detailed documentation, making data easier to find, understand, and reuse by researchers and the public.
  • Automates Workflows: By embedding metadata into processes, DDI reduces manual effort through automation of documentation, validation, and data release tasks. 

How to Get Started

  1. Assess Your Metadata needs -- Conduct an inventory of your current metadata structures and workflows.  Determine which parts of your data lifecycle (e.g., collection, processing, dissemination) would benefit most from DDI.
  2. Map Existing Metadata Practices -- Review how you currently handle metadata -- what's collected, how it's stored, and where gaps exist.  Compare this with the DDI lifecycle to identify areas where DDI can enhance your workflows.
  3. Leverage Tools and Resources -- Explore DDI-compliant tools.  Evaluate whether open-source or vendor-supplied tools best suite your infrastructure.
  4. Review Case Studies -- Review case studies of other statistical agencies using DDI.