A data dictionary is a collection of names, definitions, and attributes about data elements that are being used or captured in a database, information system, or part of a research project. It describes the meanings and purposes of data elements within the context of a project and provides guidance on interpretation, accepted meanings, and representation. A data dictionary also provides metadata about data elements, which can assist in defining the scope and characteristics of data elements, as well as the rules for their usage and application.

There are two types of data dictionaries: active and passive. An active data dictionary is automatically updated by the database management system when any changes are made in the database. On the other hand, a passive data dictionary is maintained separately from the database, and its contents are stored in the dictionary. If the database is modified, the passive data dictionary must be updated manually.

Data dictionaries are useful for a number of reasons:

• They assist in avoiding data inconsistencies across a project.
• They help define conventions that are to be used across a project.
• They provide consistency in the collection and use of data across multiple members of a research team.
• They make data easier to analyze.
• They enforce the use of data standards.

Data dictionaries can be valuable tools for the organization and management of large data listings. They provide organized, comprehensive information about data elements, which can help increase the usability of research data and ensure that data will be recognizable and usable beyond the immediate research team.