When a user starts an authoring action (creating, editing, importing, etc.) on one or more records, he uses a stepper.

A stepper defines the cluster of related records that is manipulated when authoring, as well as the wizard-like sequence of steps that guides the user through the authoring process.

For example, a CreateContact stepper defines that:

  • Authoring contacts consists in authoring Contacts and their related Addresses. The cluster of records contains several contacts and, for each of them, several address records.

  • Creating a contact consists of three steps: 1.General Info, 2.Addresses and 3.Comments. The second step (2.Addresses) is composed of two sub-steps, namely 1.Address Data and 2.Phone Numbers.

Collection and form steps

A stepper contains two types of steps:

  • Collection steps show a set of records. The user may select one or more records and edit these records.

  • Form steps show attributes of one record. A form step displays attributes using the layout and contents defined in a form. Multiple form steps are sequenced under a collection step, guiding users through the steps to create or modify a record.

When using a stepper to author master-record data on behalf of a publisher (for more information, see Data authoring patterns), only the first level of the stepper is used, and second-level collection steps are ignored.

Triggers and validations

As part of the data authoring flow, a stepper supports automated data transformations and data validations.

Automated transformations take place in the form of calls to enrichers defined in the entities, or to procedures declared in the model.

Data validations check that the data complies with data quality rules defined in the model, such as mandatory attributes, unique keys, SemQL validations, etc. When a data validation fails, it is raised to the user and may prevent that user from proceeding in the stepper.