A semantic mapping or linking is a relationship between two objects in the configuration.
It consists of one or more mapping elements, which are relationships defined between a destination element and one or more source elements.In general, a semantic mapping describes how elements in a source model (more conceptual) define elements in a destination model (closer to an implementation or representation). Elements in the destination model are representations or implementations of the associated element in the source model.
- Semantic usage: From the more general or design to the more specific or implemented (down).
- Semantic definition: From an implementation or specific object to its design or defining term (up).
| Type of semantic linking | Description | Implementation |
|---|---|---|
| Term classification | Links from a term to another object. You define a business name by creating a term in a glossary, such as Email address. You reuse the term to apply the business name to related elements, such as to any columns or fields with email addresses. |
System-managed links |
| Mapping |
Semantic links can be used for the following use cases:
|
User-defined links |
Term classification method
Term classification is the primary and recommended method as it is system-managed.
It takes precedence over semantic mapping for lineage (definition lookup and usage).
Classification works only with glossaries at the more abstract end of the link, using the Is defined by relationship from the Semantic Flow tab.
As it is managed by the system, you do not need to create mapping contents between the glossary and the target model. You do not need to manage the semantic lineage lines in the architecture diagram.
For more information on term classification, see Classifying a metadata element with a term.
Semantic mapping method
Semantic mapping is the secondary method as it is more user-managed.
Semantic mapping can be defined between any two contents such as glossary and/or model/PDM.
You must explicitly create and manage a content for each mapping content between two models/glossaries. Once created, you can map to individual data elements as much as you want within the scope of those two models.
As there is existing content in the repository, it can be managed using the semantic mapper, be exported and re-imported using the CSV format or be "embedded" to be migrated from semantic mapping to term classification from a glossary.