- What is ArcGIS Data Reviewer?
- Can Data Reviewer detect errors in web layers shared from Enterprise?
- Does Data Reviewer for Enterprise have additional software requirements?
- What Data Reviewer capabilities are deprecated?
- What is the difference between geodatabase topology rules and Data Reviewer?
- Is there a limit to the number of features that can be validated using automated checks?
- What is the difference between attribute rules and Data Reviewer?
- Can I run Data Reviewer validation rules using ArcGIS Server?
- What types of features are supported by Data Reviewer checks?
- Why are some error features removed while others remain in the Error Inspector after I fix the errors in my data?
- Can I remove the Validation status field from my data?
ArcGIS Data Reviewer is an extension to ArcGIS Pro and ArcGIS Enterprise that automates, simplifies, standardizes, and improves quality control workflows to enable delivery of geospatial data you can trust. Lower data management costs reduce risk in decision-making through this unified set of capabilities that support detection, management, and reporting of errors in your data.
To use Data Reviewer in a server environment, you must use branch-versioned data. You can evaluate the data using the Validation Service.
Services published from ArcMap are not supported after Enterprise 10.9. For Data Reviewer users, this change impacts capabilities delivered by the extension's ArcMap runtime-based server object extension (SOE) and associated geoprocessing service. Starting at Data Reviewer 3.0, these capabilities will not be supported after an upgrade to an existing deployment or in new deployments.
Learn more about the deprecation of the ArcMap runtime-based SOE
Remarque :
It is recommended that you begin migrating your quality control workflows to the Data Reviewers attribute rule-based workflows in ArcGIS Pro. The workflows in ArcGIS Pro are equivalent to those of the ArcMap runtime-based SOE.
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 them 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 identifying data quality issues related to a feature's integrity and attribution, as well as a feature's spatial relationship to other features. For a complete list of Data Reviewer checks, review the Data Reviewer checks help topic.
A geodatabase topology rule 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
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 in GIS data. It also provides error life cycle management to aid in error tracking and the error review process. By comparison, ArcGIS Arcade-based attribute rules can provide more fine-grained control in identifying errors but require familiarity with Arcade.
Yes. When you share web feature layers that contain validation attribute rules, you can enable the Validation capability to use the Validation Service. You can use the Validation Service to assess the quality of features using validation attribute rules authored in ArcGIS Pro.
Data Reviewer checks support the following data types:
- Point Features
- Line Features
- Polygon Features
- Standalone Tables
Data Reviewer-based constraint and validation rules support these feature types in file, mobile, and feature services published from branch-versioned enterprise geodatabases. Constraint attribute rules support these feature types in traditional-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 for traceability and error life cycle 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 error life cycle management in Data Reviewer
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