Data Rule (Node Type)

This article is about the current version of Grooper. Note that some content may still need to be updated.
2025	2023	2021

flowsheet Data Rules are used to normalize or otherwise prepare data collected in a data_table Data Model for downstream processes. Data Rules apply conditional logic to data extracted from documents (folder Batch Folders).

• Each Data Rule executes a "Data Action" which do things like computing a field's value, parse a field into other fields, perform lookups, and more.
• Data Actions can be conditionally executed based on a Data Rule's "Trigger" expression.
• A hierarchy of Data Rules can be created to execute multiple Data Actions and perform complex data transformation tasks.

WIP	This article is a work-in-progress or created as a placeholder for testing purposes. This article is subject to change and/or expansion. It may be incomplete, inaccurate, or stop abruptly. This tag will be removed upon draft completion.

Introduction

A Data Rule is a configurable rule that applies conditional logic to extracted data. Data Rules are typically used after extraction to transform values into the format your downstream systems require, or to enforce business requirements that are easier to express as a rule than as extraction logic.

Unlike extractors (which focus on finding data on the document), Data Rules focus on fixing, moving, combining, and validating the data once it has been captured into a Data Model.

What a Data Rule runs against (scope)

A Data Rule runs against instances of a selected container. The container is chosen using the rule's "Scope" property:

• If the "Scope" is set to a Data Model, the rule executes once on the root document instance.
• If the "Scope" is set to a Data Section (and the section is multi-instance), the rule executes for each section record (each Section Instance).
• If the "Scope" is set to a Data Table, the rule executes for each row (each Table Row Instance).

This is important because many Data Actions operate on fields within the current record/row, and the meaning of “source” and “target” depends on what the rule is scoped to.

Conditional execution (Trigger, True Action, False Action)

A Data Rule can optionally use conditional logic to decide what should happen:

• The "Trigger" property must be configured with a Boolean expression.
• When "Trigger" evaluates to True:
  • The "True Action" runs.
  • Any child Data Rules (nested under the current rule) also run.
• When "Trigger" evaluates to False:
  • The "False Action" runs (if configured).
  • Child Data Rules are skipped.
  • If no "False Action" is configured, the Data Rule just does not run.

If the Trigger property is blank, the Data Rule will always run.

How Data Rules differ from other conditional components

Data Rules are purpose-built for manipulating and validating extracted values inside the Data Model hierarchy (document, section record, or table row). There are other Grooper components that also use conditional logic (for example, conditional paths in a Batch Process), but those typically control workflow routing or when a step runs. Data Rules control how extracted data is modified within the document's data structure.