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The scientific subject matter of the data and related activities such as data collection, data tabulation, data analysis, and data exchange drive which standards to implement. Implementation of standards starts with determining which standards are appropriate to use based on the nature of the data and activities to be supported. After standards are selected, it is then possible to determine how the data are collected, represented, or exchanged using the standards.

Standards in this guide are aligned with both use cases and activities. Given this, determining which standards to use may begin with by selecting standards appropriate for both in this guide by the use case and activity . The to be supported. For ease of use, the table below shows presents use cases and activities aligned with sections of , activities, and corresponding sections in this guide in which provide detailed instructions for implementation. It 

It It is recommended that all sections are read before the sections below  Sections referenced in this table are:

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he CDASH Model aligns with and is structured similarly to the SDTM. The CDASH Model organizes data into classes, which represent meaningful groupings of data in clinical research. It defines CDASH metadata for identifier variables, timing variables, general observation class variables (Events, Interventions, and Findings), domain-specific variables, and special-purpose domain variables.

The current CDASH Model represents Identifier, Timing, and Domain-specific variables in the metadata as an Observation Class. This does not align with the SDTM. This will be revised in a future version of the CDASH Model.

Standards for collection, tabulation, and analysis collect and represent data by common topics with standards for collection and tabulation grouping logically related data in domains and the design of analysis datasets customizable per analysis requirements. The scientific subject matter of the data further drives the selection of collection and tabulation standards, where the nature of the data must be within the scope of a domain for the domain to be used. Analysis needs drive the selection of analysis standards, where analysis requirements are supported by both the structure and the contents of the resulting dataset. Standards for data exchange are applicable to all use cases and support sharing of standard CRFs, tabulation datasets, and analysis datasets.

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