Guidance for Datasets

Requirements for data submission are defined and managed by the regulatory authorities to whom data are submitted. This section describes general requirements for datasets which may be part of a submission. However, additional conventions may be defined by regulatory bodies or negotiated with regulatory reviewers. In such cases, additional requirements must be followed.

Tabulation Datasets

Observations about tobacco products and study subjects generated to support a submission are represented in a series of datasets aligned with logical groupings of data per domains. Domains described in this guide are generally aligned with implementation of a single dataset in which to represent data in scope for a domain. All datasets are structured as flat files with rows representing observations and columns representing variables. In some cases, a dataset implemented for a domain may be split into physically separate datasets to support submission when needed and as allowable by the regulatory authority. 

The following guidance will be adhered to when implementing tabulation datasets: 

Generally, a domain is represented by a single dataset. 

A domain dataset may be split into physically separate datasets to support submission when needed and as allowable by the regulatory authority. The following conventions must be adhered to when splitting domains into separate datasets:

• A domain based on a general observation class may be split according to values in --CAT. When a domain is split on --CAT, --CAT must not be null.
• The Findings About (FA) domain may alternatively be split based on the domain of the value in --OBJ.

To ensure split datasets can be appended back into one domain dataset:

Dataset names will reflect the following conventions:

• Names will be a unique 2 to 4 letter character code.
• This code, which is stored in the SDTM variable named DOMAIN, is used in 4 ways: as the dataset name, as the value of the DOMAIN variable in that dataset, as a prefix for most variable names in that dataset, and as a value in the RDOMAIN variable in relationship tables (see Section 8, Representing Relationships and Data).

A domain dataset may be split into physically separate datasets to support submission when needed and as allowable by the regulatory authority. The following conventions must be adhered to when splitting domains into separate datasets:

• A domain based on a general observation class may be split according to values in --CAT. When a domain is split on --CAT, --CAT must not be null.
• The Findings About (FA) domain may alternatively be split based on the domain of the value in --OBJ.

To ensure split datasets can be appended back into one domain dataset:

1. 1. The value of DOMAIN must be consistent across the separate datasets as it would have been if they had not been split (e.g., LB, FA).
   2. All variables that require a domain prefix (e.g., --TESTCD, --LOC) must use the value of DOMAIN as the prefix value (e.g., LB, FA).
   3. --SEQ must be unique within USUBJID for all records across all the split datasets. If there are 1000 records for a USUBJID across the separate datasets, all 1000 records need unique values for --SEQ.
   4. When relationship datasets (e.g., SUPPxx, FAxx, CO, RELREC) relate back to split parent domains, the value of IDVAR would generally be --SEQ. When IDVAR is a value other than --SEQ (e.g., --GRPID, --REFID, --SPID), care should be used to ensure that the parent records across the split datasets have unique values for the variable specified in IDVAR, so that related children records do not accidentally join back to incorrect parent records.
   5. Permissible variables included in one split dataset need not be included in all split datasets.
   6. For domains with 2-letter domain codes, split dataset names can be up to 4 characters in length. For example, if splitting by --CAT, dataset names would be the domain name plus up to 2 additional characters (e.g., QS36 for SF-36). If splitting Findings About by parent domain, then the dataset name would be the domain code, "FA", plus the 2-character domain code for parent domain code (e.g., "FACM"). The 4-character dataset-name limitation allows the use of a Supplemental Qualifier dataset associated with the split dataset.
   7. Supplemental Qualifier datasets for split domains would also be split. The nomenclature would include the additional 1 to 2 characters used to identify the split dataset (e.g., SUPPQS36, SUPPFACM). The value of RDOMAIN in the SUPP-- datasets would be the 2-character domain code (e.g., QS, FA).
   8. In RELREC, if a dataset-level relationship is defined for a split Findings About domain, then RDOMAIN may contain the 4-character dataset name, rather than the domain name "FA", as shown in the following example. 

      relrec.xpt

      Row	STUDYID	RDOMAIN	USUBJID	IDVAR	IDVARVAL	RELTYPE	RELID
      1	ABC	CM		CMSPID		ONE	1
      2	ABC	FACM		FASPID		MANY	1

Standards for tabulation represent data in groupings of related data called domains. Datasets are the dataset structure associated with those groupings.

 a domain is a grouping of observations that are related while a dataset 

The terms domain and dataset 

The terms “domain” and “dataset” are commonly used in CDISC’s nomenclature and found frequently in the Study Data Tabulation Model (SDTM). For example, the SDTM v1.8 includes 134 instances of "domain" and says "A collection of observations on a particular topic is considered a domain." The Model includes 78 instances of dataset and certain structures in the model are called "datasets" rather than "domains." Is there a difference between a domain and a dataset?

The CDISC Glossary defines these terms as follows:

• Domain: A collection of logically related observations with a common, specific topic that are normally collected for all subjects in a clinical investigation. NOTE: The logic of the relationship may pertain to the scientific subject matter of the data or to its role in the trial. Example domains include laboratory test results (LB), adverse events (AE), concomitant medications (CM). [After SDTM Implementation Guide version 3.2, CDISC.org] See also general observation class.
• Dataset: A collection of structured data in a single file. [CDISC, ODM, and SDS] Compare to analysis dataset, tabulation dataset.

In plainer terms, a domain is a grouping of observations that are related while a dataset is the data structure associated with that grouping of observations. Both domains and datasets use the same nomenclature, which is why they are often confused.

The distinction between domain and dataset is most clearly seen in cases where a general observation class domain is split into multiple datasets in a submission. Common examples are splitting the Laboratory Test Results (LB) domain due to size, splitting the Questionnaires (QS) domain by questionnaire, and splitting the Findings About Events or Interventions (FA) domain by parent domain.

However, since in most cases there is a one-to-one relationships between a conceptual domain and a dataset based on that conceptual domain, the words are used interchangeably in the standards and, therefore, by most users. The structures called “relationship datasets” were given that name because they are mechanisms for connecting information represented in different datasets rather than observations about study subjects. Note that none of the relationship datasets includes the variable DOMAIN. However, in a submission, these datasets need dataset names, and character strings used in those names are included in the CDISC Codelist called "SDTM Domain Abbreviations."

In conclusion, there is a clear distinction between the meaning of "domain" and "dataset" but given that the naming conventions are the same across both terms, in many cases they can be considered interchangeable.

Tabulation Datasets

langauge from here https://www.cdisc.org/kb/articles/domain-vs-dataset-whats-difference

The terms “domain” and “dataset” are commonly used in CDISC’s nomenclature and found frequently in the Study Data Tabulation Model (SDTM). For example, the SDTM v1.8 includes 134 instances of "domain" and says "A collection of observations on a particular topic is considered a domain." The Model includes 78 instances of dataset and certain structures in the model are called "datasets" rather than "domains." Is there a difference between a domain and a dataset?

The CDISC Glossary defines these terms as follows:

• Domain: A collection of logically related observations with a common, specific topic that are normally collected for all subjects in a clinical investigation. NOTE: The logic of the relationship may pertain to the scientific subject matter of the data or to its role in the trial. Example domains include laboratory test results (LB), adverse events (AE), concomitant medications (CM). [After SDTM Implementation Guide version 3.2, CDISC.org] See also general observation class.
• Dataset: A collection of structured data in a single file. [CDISC, ODM, and SDS] Compare to analysis dataset, tabulation dataset.

In plainer terms, a domain is a grouping of observations that are related while a dataset is the data structure associated with that grouping of observations. Both domains and datasets use the same nomenclature, which is why they are often confused.

The distinction between domain and dataset is most clearly seen in cases where a general observation class domain is split into multiple datasets in a submission. Common examples are splitting the Laboratory Test Results (LB) domain due to size, splitting the Questionnaires (QS) domain by questionnaire, and splitting the Findings About Events or Interventions (FA) domain by parent domain.

However, since in most cases there is a one-to-one relationships between a conceptual domain and a dataset based on that conceptual domain, the words are used interchangeably in the standards and, therefore, by most users. The structures called “relationship datasets” were given that name because they are mechanisms for connecting information represented in different datasets rather than observations about study subjects. Note that none of the relationship datasets includes the variable DOMAIN. However, in a submission, these datasets need dataset names, and character strings used in those names are included in the CDISC Codelist called "SDTM Domain Abbreviations."

In conclusion, there is a clear distinction between the meaning of "domain" and "dataset" but given that the naming conventions are the same across both terms, in many cases they can be considered interchangeable.

Analysis Datasets