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If data are in scope for a domain defined in this guide, but not all data can be collected using the domain's collection fields, then fields may be added from the CDASH Model or created using guidance below. Prior to adding fields from the CDASH Model or considering a new field, confirm that none of the fields in the domain will fit the need. Fields may be added from the CDASH Model or created only when data are different in nature and are not in scope for existing domain fields. 

Once confirmed, determine whether adding a field from the CDASH Model will fit the need. If adding a field from the CDASH Model meets the need, then a new field will not be created. New fields will only be created when data are not in scope for a field defined in the CDASH Model. 

The overall process for extending metadata is as follows:

  1. Using the root variables and other CDASH metadata in the CDASH Model, add any additional variables that are needed to meet the requirements of data collection.

    1. Refer to both the CDASH Model and Appendix x, CDASH Model Metadata Tables.

    2. Follow CDASH root variable-naming conventions where they exist (e.g., --DAT for dates, --TIM for times, --YN for prompts, as described in the CDASH Model) and Appendix x, CDISC Variable-naming Fragments, conventions, and 


Creating New Fields

When creating a new data collection field, determine whether the data will be used for an operational use case, such as data cleaning, or are actual data to be represented in a tabulation dataset. In general, new data collection fields (not already defined in the CDASH Model) will fall in one of following categories:

  • A field used for operational, Data Cleaning purposes only.
  • A field used to collect data that have Direct Mapping to a target variable in the tabulation dataset.
  • A field used to collect data that have No Direct Mapping to a target variable in the tabulation dataset.

The table below provides implementation guidance aligned with both the category of the field and target variable.

NumField CategoryTarget Tabulation VariableImplementation
1Data CleaningNAThe field --YN with Question Text "Were there any [interventions/events/findings]?" can be used for this purpose. Replace the two dashes (--) with the two-character domain code and create the Question Text or Prompt using generic Question Text or Prompt from the CDASH Model as a base. Always create custom data-cleaning/operational variables using consistent naming conventions.
2Direct MappingYesIf a value can be collected exactly as it will be reported in the tabulation dataset (i.e., same value, same data type, same meaning, same controlled terminology), the tabulation variable name will be used as the data collection variable name in the operational database to streamline the mapping process. Extensions may be appended if needed to create a unique variable name in the collection database. Any collection variable whose meaning is the same as tabulation variable will align with tabulation variable and the meaning will not be modified for data collection.
3

No Direct Mapping


Yes

If a value cannot be collected in alignment with the tabulation dataset variable (e.g., collected data type is different from the data type in the corresponding tabulation variable) or if the tabulation variable is derived from the collected value, then the operational database should use a collection variable with a different name from tabulation variable into which it will be mapped.

No

If a field does not align with a tabulation variable, a unique name should be assigned based on applicant business rules using CDASH naming fragments (e.g., --DAT, --TIM) as appropriate and CDISC variable naming fragments, found in Appendix x, CDISC Variable-naming Fragments, where possible. 

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