> ## Documentation Index
> Fetch the complete documentation index at: https://docs.speckle.systems/llms.txt
> Use this file to discover all available pages before exploring further.

# Validation Widgets in Dashboards

> Use Property Checker and Model Validation widgets inside Intelligence dashboards, and know when to use dedicated Data Validation.

Use this page when your validation work happens inside **Intelligence dashboards**
with widgets.

This is a focused sub-guide of [Common
workflows](/analytics/dashboards/common-workflows).

## Which path are you on?

* **Dashboard widget path**: Property Checker and Model Validation widgets inside
  dashboards.
* **Checks-and-standards path**: Validation Checks and Standards in the dedicated Data
  Validation area.

<Info>
  If you are trying to validate directly in dashboards, start here. If you are creating
  persistent checks and standards in the web app flow, use [Data Validation
  Overview](/analytics/data-validation/overview).
</Info>

## Dashboard widget path

In dashboards, use:

* **Property Checker** for quick single-property checks.
* **Model Validation** for reusable rulesets applied from widget context.

## Typical dashboard validation workflow

<Steps>
  <Step title="Open Intelligence dashboard">
    Create or open a dashboard with model data sources.
  </Step>

  <Step title="Add validation widget">
    Add Property Checker for quick checks or Model Validation for full rulesets.
  </Step>

  <Step title="Define rules">
    Configure `WHERE` / `AND` / `CHECK` conditions, then set severity and message.
  </Step>

  <Step title="Run and interpret">
    Review pass/fail outcomes in widget views and viewer colorization.
  </Step>
</Steps>

## Rule authoring in widgets

### Rule structure

| Component       | Description                       |
| --------------- | --------------------------------- |
| `WHERE`         | Filter objects in scope           |
| `AND`           | Additional filter clauses         |
| `CHECK`         | Final validation assertion        |
| Property Name   | Object property path to evaluate  |
| Predicate       | Comparison operation              |
| Value           | Reference value                   |
| Report Severity | `ERROR`, `WARNING`, or `INFO`     |
| Message         | User-facing text shown in results |

### Widget rule usage

* Property Checker supports quick rule creation in dashboard context.
* Model Validation supports multi-rule rulesets for a single model.
* Rulesets can be exported/imported for portability.
* Predicates cover existence, comparison, pattern matching, and numeric range checks.

### Migration to Data Validation

Exported Model Validation check rulesets can be imported into **Data Validation
(checks and standards)**, then used to create or update checks and standards in
the product workflow.

## Reading results in widgets

### Property Checker results

* Donut/chart views show pass/fail percentages.
* Validation steps show progression through `WHERE` / `AND` / `CHECK`.
* Viewer colorization helps locate affected elements quickly.

### Model Validation results

* Ruleset outcomes summarize pass/fail/not-applied behavior.
* Breakdown views group outcomes by property values.
* Rules tabs support rule-by-rule inspection.

### Interpreting outcomes

* **Pass**: compliant for evaluated scope.
* **Fail**: non-compliant objects detected.
* **Not Applied**: no matching objects or non-evaluable context.

## When to move to checks-and-standards Data Validation

Move to checks-and-standards Data Validation when you need:

* check-centric runs with explicit tracked model history
* standards-first authoring and reuse
* check detail views focused on latest vs historical outcomes