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Frequently asked questions

What is ArcGIS Data Reviewer?

ArcGIS Data Reviewer is an extension for ArcGIS Pro that offers a range of quality assurance and quality control tools. These tools identify errors related to the integrity, attribution, or spatial relationships of your features. Data Reviewer supports data management needs for both data production and analysis. It provides automated review, semi-automated review, and visual review capabilities to streamline your data review processes.

How can I use Data Reviewer in an ArcGIS Server environment?

To use Data Reviewer in a server environment, you must use branch versioned data. You can evaluate your data using the validation service capability. Starting at ArcGIS Enterprise 11.3, you can use visual review capabilities on feature services.

How can I expand Data Reviewer capabilities?

You can leverage Data Reviewer by creating custom web applications using capabilities in the Validation Service.

What has been deprecated in Data Reviewer?

The ArcMap runtime-based server object extension (SOE) has been deprecated.

Note:

Data Reviewer for ArcGIS Server is the equivalent to the SOE and requires a license for the Data Reviewer server extension.

What is the difference between Topology Rules and Data Reviewer?

Geodatabase topology and Data Reviewer are both capabilities that support the creation and management of high-quality data. There are advantages to using both capabilities in data management workflows. A key difference between these capabilities is the aspects of a feature's quality that can be assessed. Data Reviewer checks are used to assess multiple aspects of a feature's quality. This includes the ability to identify data quality issues related to a feature's integrity, attribution, as well as a feature's spatial relationship to other features. For a complete list of Data Reviewer checks, review the ArcGIS Data Reviewer Checks poster.

A geodatabase topology is used to enforce a spatial relationship between features in a geodatabase. This includes assessment of spatial relationships such as overlaps, intersections, and gaps. For a complete list of topology rules, review the ArcGIS Geodatabase Topology Rules poster.

Learn more about the components that define GIS data quality

Is there a limit to the number of features that can be validated using automated checks?

No, there is no limit to the number of features that can be validated using automated checks.

Note:

The more features and quality checks there are, the longer it may take to validate. In extreme cases, the resulting errors from the validation process could exceed the number of features in the database.

What is the difference between Attribute Rules and Data Reviewer?

Data Reviewer is an integrated capability in attribute rule-based workflows, that provides a library of no-code, ready-to-use checks that identify common errors found in GIS data. It also provides error lifecycle management to aid in keeping track of errors and the error review process. By comparison, Arcade-based attribute rules can provide more fine-grained control in identifying errors but require familiarity with ArcGIS Arcade.

Learn more about Data Reviewer checks

Can I run Data Reviewer validation rules using ArcGIS Server?

Yes, you can run Data Reviewer validation rules using ArcGIS Server. When you share web feature layers using ArcGIS Pro, you can enable the Validation capability. The Validation capability uses your federated ArcGIS Server to assess the quality of features referenced in your web feature layers using validation attribute rules that you have authored using ArcGIS Pro.

What types of features are supported by Data Reviewer checks?

Data Reviewer checks support the following data types:

  • Point Features
  • Line Features
  • Polygon Features
  • Standalone Tables

Data Reviewer supports these feature types in file geodatabases, mobile geodatabases, and branch versioned Enterprise geodatabases.

Why are some error features removed while others remain in the Error Inspector after I fix the errors in my data?

Data Reviewer attribute rule error features remain in the Error Inspector pane after they are fixed due to traceability and error lifecycle management. Traceability allows you to track and manage errors throughout the data validation process, ensuring that errors have been properly addressed. The error management process records which errors were identified and fixed, allowing you to track the history of data quality improvements.

The only error features that are removed are Arcade-based attribute validation rules. These errors only persist if the error condition they search for is still present. Once an error is fixed and the validation rules are re-evaluated, the Arcade-based validation errors are removed.

Learn more about Data Reviewer's error lifecycle management

Can I remove the Validation status field from my data?

No. Once a batch calculation or validation attribute rule has been authored on your dataset, the Validation status field is automatically generated and can no longer be deleted, even if you delete all other rules.

Learn more about the Validation Status field