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 in this guide will be used based on the nature of the data and activities to be supported. After an applicable set or sets of standards have been identified, it is then possible to determine how the data are collected, represented, or exchanged using the standards.
Sets of standards in this guide are aligned with both use cases and activities. Given this, determining which standards to use may begin by selecting standards for the use case and activity to be supported. It is recommended that all TIG guidance is reviewed, both general and detailed, prior to implementing standards. For ease of use, the table below presents use cases, activities, and corresponding sections in this guide which provide detailed instructions for implementation. Detailed instructions referenced are:
- Section x.x, Standards for Collection, which guides development and use of case report forms (CRFs) by implementing the CDISC CDASH Model.
- Section x.x, Standards for Tabulation, which guides organization of data collected, assigned, or derived for a study by implementing SDTM.
- Section x.x, Standards for Analysis, which specify the principles to follow in the creation of analysis datasets and associated metadata by implementing the ADaM.
- Section x.x, Standards for Data Exchange, which support sharing of structured data between parties and across different information systems by implementing specified standards and resources.
Once standards are identified based on the use case and activity, the scientific subject matter of the data, its role, and analysis needs will determine where data belong, i.e., how the data are collected, represented, or exchanged using the standards. Standards for collection and tabulation in this guide collect and represent data using groupings of logically related data called domains. Domains are aligned between collection and tabulation standards to facilitate the transition of collected observations to their representation in tabulation datasets. Standards for analysis are organized in relation to analysis requirements with the structure of tabulation datasets facilitating the generation of analysis datasets.
To use standards for collection and tabulation, compare the nature or role of the data to the scope of a domain. Domain names provide short descriptions of intended scope and may be used to narrow down which domains to consider. A domain standard may be used when the nature of the data and the domain scope are aligned. Observations will be collected using standardized collection fields when applicable and represented as rows in tabulation datasets. Each observation is described by a series of data points which correspond to applicable data collection fields and variables in a tabulation dataset. A data collection field and/or tabulation variable may be used when the subject matter of a data point and the scope of a field and/or variable are aligned. The majority of data for a submission will be in scope for domains based on the three General Observation Classes described in the SDTM with data also in scope for additional domains and datasets based on other SDTM classes and defined datasets. Given this, referring to both the CDASH Model when applicable and the SDTM is highly recommended when using domains to support understanding of the intended domain scope and to inform extensions to domains and creation of custom domains when needed.
To use standards for analysis... add text here.
Standards for data exchange are applicable to all use cases and support sharing of standard CRFs developed using collection standards, tabulation datasets generated using tabulation standards, and analysis datasets designed using analysis standards.
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