Available with Data Reviewer license.
Summary
The Valency check validates relationships between point and polyline features or polylines within the same feature class, to ensure specific patterns of polylines are connected at a point.
Supported workflows
ArcGIS Data Reviewer checks support multiple methods for implementing automated review of data. The following table identifies the supported implementation methods for this check:
Workflow | Supported | Licensing |
---|---|---|
Validation attribute rule | Yes (ArcGIS Pro 3.5 and ArcGIS Enterprise 11.5 or later) | Available with ArcGIS Pro Standard and Data Reviewer license |
Constraint attribute rule | No | N/A |
Run Data Checks | No | N/A |
Overview
When features are included in a network dataset, such as roads, powerlines, and pipelines, there may be requirements for how these features relate to the points that connect them. For example, the product specification may require that all major intersections have four roads at a junction or that a T-fitting on a water main connects to three pipelines. This relationship is known as valency.
The Valency check can also be configured to find relationships based on the digitized direction of polyline features, specified patterns or values of polyline attributes, and the location of missing point features.
Industry scenarios
This check can be used in the following scenarios:
- In the electric utilities industry, you may need to validate that the operating voltage on the conductors are different when they are connected to a step transformer.
- In pipeline referencing, you may need to identify errors with points designated as reducer fittings that are either not connected to two pipes or are connected to two pipes with the same diameter.
- In the water/wastewater utility industry, you may need to identify two adjacent sewage lines that both digitize their direction (flow) into the same manhole.
Attribute Rule syntax
The following table describes the validation attribute rule parameters:
Parameter | Required | Description | Workflow |
---|---|---|---|
Subtype | No | The subtype(s) to which the rule is applied. | Validation |
Attribute | No | A query that identifies the features to which the rule is applied. | Validation |
Features to Compare | Yes | Input features are returned as errors based on their relationship to the features from this data source. Only polyline features are valid inputs. This parameter is only displayed when the rule is configured on a point feature class. | Validation |
Filter | No | A query that identifies the features to include in the rule, from the data source specified in the Features to Compare parameter. | Validation |
Search Goal | Yes | Specifies the number of polyline features connecting at a point or the number of lines meeting at endpoints. The query returns all connections that meet the defined search goal condition as errors.
| Validation |
Search Only for Missing Point Locations | No | Identifies the location of missing point features based on the number of connecting polylines determined by the Search Goal parameter. This parameter is displayed when the rule is configured on a point feature class. Note:When you enable this parameter, the rule only returns errors for missing points. Caution:If Subtype, Attribute Filters, or Attribute Relationships are used with this parameter, false positive errors may occur. | Validation |
Attribute Relationship | No | The attribute value comparison between features or rows from the input data source and the data source of the Features to Compare parameter. This parameter is displayed when the rule is configured on a point feature class. Note:An error will be generated if any feature from the Features to Compare data source matches the feature attribute from the input data source. | Validation |
Use Digitized Direction | No | Considers the expected direction or pattern in which polyline features are digitized.
| Validation |
Attribute Comparison Rules | No | Compares attribute values of polyline features that meet a specific pattern or values.
Note:Descriptions for coded values and range domain values are not supported by this parameter. Use the domain code instead. Null attribute values will cause the Attribute Comparison Rules parameter to be ignored. When multiple Attribute Comparison Rules are configured, they will use AND logic and will all need to be satisfied to produce an error. | Validation |
Name | Yes | A unique name for the rule. This information is used to support data quality requirement traceability, automated reporting, and corrective workflows. | Validation |
Description | No | A description of the error you define when a noncompliant feature is found. This information is used to provide guidance for corrective workflows. | Validation |
Severity | No | The severity of the error assigned when a noncompliant feature is 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 | The 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 |
Notes
Keep the following in mind when using the check:
- The Specify Values option is only available when Is equal to is selected as the Search Goal parameter.
- The Valency check is not available for use in the Composite check.
- When you create maps, project packages, or share web layers with the Validation capability enabled, include the data source for the Features to Compare parameter.
- The Attribute and Filter parameters are limited to comparison (=, <>, >, <, >=, and <=) and logical (AND/OR, IN/NOT IN, LIKE/NOT LIKE, and IS NULL) operators.
- The Attribute and the Features to Compare filter parameters do not support the following field types: Big Integer, Date Only, Time Only, and Timestamp Offset. If selected, the row header is marked in red and does not allow the rule to be saved.
- The Input Features and the Features to Compare parameters must share a common datum in their data sources.