Why Use DDI?

The aim of DDI

• To facilitate the creation of metadata by reducing the complexity of describing research data
• To structure metadata to make data documentation usable to people, software systems and computer networks
• To offer benefits for a wide range of users from different backgrounds who might also use DDI for different reasons

Flexibility and Usability

• Helps with harmonizing data and making it comparable
• Makes your (meta)data machine-actionable
  • this is crucial for data harmonization and exchange, and reduces time spent on describing data
• Is platform-agnostic, so there is no need for further configurations
• DDI is designed to work together with other standards (e.g. ISO 19115, ISO 8601, DCAT, PROV, etc.)

Discovery and Access

• Creates full context for your data
  • Describes the data accurately
  • Allows you to index your data
  • Allows discoverability of the many topics found within variable groups
• Creates standard documentation
  • Metadata to accompany your data (questionnaire, data dictionary, etc.)
  • Metadata that can also contribute to question banks and statistical classifications
• Creates the provenance of the data, how data was collected and what happens to it and where it moves over time.

Efficiency

• Consistency in metadata
• Controlled vocabularies
• Quality control
• Metadata reuse (questions, code lists, variables, classifications, etc.)
• Data sharing (interoperability)

Preservation

• Versioning is documented
• Data integrity is preserved
• Data encoding / encapsulation
• Standard, open documentation

DDI and FAIR

• Using DDI to structure your metadata makes it easier for your data to comply with the FAIR principles for scientific data management and stewardship. This helps to make your metadata Findable, Accessible, Interoperable, and Reusable.
  

  Findable

  • The first step in (re)using data is to find them
  • Metadata and data should be easy to find for both humans and computers.
  • Machine-readable metadata are essential for automatic discovery of datasets and services

  Accessible

  • Once the user finds the required data they can access them
    • Includes authentication and authorization, where necessary

  Interoperable

  • The data can be integrated with other data
  • Data are able to interoperate with applications or workflows for analysis, storage, and processing

  Reusable

  • The possibility to optimise the reuse of data
  • Metadata and data are well-described in DDI, they can be replicated and/or combined in different settings

Resources

• The DDI Training Group maintains a rich collection of training materials in different formats.
• The DDI Training Group is always ready to help you with any questions regarding the set-up, implementation and maintenance of the standard. Click here to request a training session!