Available with Data Reviewer license.
Summary
The Domain check finds features that contain attribute values that do not comply with domain constraints. This includes numeric values that are greater than or less than those specified in a range domain and attribute values that are not found in a coded value domain.
Overview
The purpose of the Domain check is to identify range or coded value domain values outside the domain constraints. Attribute field domains can either be coded values or ranges. When a value is entered, especially if the field is a range field, the value may be greater or less than the allowed values. This is especially true if validation was not performed when attributes were edited. In addition, if data has been loaded from an external source, features may exist that violate both range and coded value domains.
Industry scenarios
The following are scenarios in which you can use this check:
- In topographic mapping, elevation contours with invalid values in the domain-restricted Hypsography Portrayal Type (HQC) attribute impact cartographic production when symbolizing features.
- In water utility management, incorrect values in the diameter properties of features such as water mains and lateral lines may impact the results of hydraulic modeling of the utility network.
Supported workflows
ArcGIS Data Reviewer checks support multiple methods for implementing automated review of your data. The following table identifies the supported implementation methods for this check:
| Validation | Constraint | ||
|---|---|---|---|
Reviewer batch job | Reviewer map rule | Attribute (validation) rule | No |
Yes | Yes | Yes | |
Syntax
| Parameter | Required | Description | Workflows |
|---|---|---|---|
Input Layers/Standalone Tables | Yes | The input feature layers or stand-alone tables evaluated by the rule. Valid inputs for this rule type are feature
layers and stand-alone tables. Click the Forward button | Validation (map rules) |
Subtype | No | The subtype that the rule is applied to if the dataset has subtypes. | Validation (attribute rules) |
Attribute | No | A query that identifies the features to which the rule is applied. | Validation (attribute rules) |
Attributes to Ignore | No | The attribute values to ignore during evaluation. Only editable fields can be ignored. | Validation (attribute rules) |
Null Value Check/Search for Null Values | No | Attribute values that are <Null> (no value) are returned as an error. | Validation |
Title/Name | No | A unique title or name for the rule. This information is used to support data quality requirement traceability, automated reporting, and corrective workflows. | Validation |
Notes/Description | No | Descriptive text of the error condition when noncompliant features are found. This information is used to provide guidance to facilitate corrective workflows. | Validation |
Severity | No | Severity of the error created when noncompliant features are found. This value indicates the importance of the error relative to other errors. Values range from 1 to 5, with 1 being the highest priority and 5 being the lowest. | Validation |
Tags | No | Tag property of the rule. This information is used in rule authoring and management workflows to support traceability and reporting of data quality requirements. | Validation |
to apply filtering to specific features in the feature layer or specific rows in the stand-alone table.Notes
Keep the following in mind when using the check:
- Features or table records that are assigned to a subtype are evaluated based on the domains defined by the subtype.
- Features or table records assigned to an invalid subtype will not be evaluated by this check. It is recommended that you use the Subtype check to find features assigned to invalid subtypes and correct them before using this check.
- When this check is authored as an attribute (validation) rule, the Attribute filter parameter is limited to comparison (=, <>, >, <, >=, <=) and logical (AND/OR, IN/NOT IN, LIKE/NOT LIKE, IS NULL) operators.
- When this check is authored as a map-based rule, verify that filter parameters using database-specific SQL functions are the same as from those supported in your production environment.