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Protocol Step Forms & Data Collection

Protocol Step Forms allow researchers and operators to capture structured execution data while performing protocol, workflow, batch, and sample activities.

FlaskTrack supports both predefined system-generated forms and fully customizable data collection forms, enabling organizations to standardize data capture while maintaining flexibility for specialized workflows.

All submitted form data becomes part of the permanent execution record and is automatically available for reporting, analytics, compliance review, and audit traceability.

Overview

Every protocol step can optionally collect data from the user during execution.

When configuring a protocol step, administrators may choose one of three data collection modes:

Mode Description
No Form Defined step data and environmental information is recorded as listed
System Form FlaskTrack automatically generates a form based on the selected step action.
Custom Form Administrators build a fully customized data collection form.

Data entered during step execution becomes part of the execution history for the associated workflow, batch, sample, or protocol run.

No Form

The simplest execution mode.

Users complete the step without entering structured data. The information from the protocol step is copied to the event. If the steps min/max temperatures are 15 and 16 - this will be copied verbatim into the event.

Typical use cases:

The execution event itself is still recorded.

Recorded information includes:

System Forms

System Forms are automatically generated by FlaskTrack.

When a protocol step is assigned a specific action type, FlaskTrack can present a standardized form designed for that action. This allows users to update default step information as well as common additional fields based on the action of the step.

Examples include:

System Forms help organizations enforce consistent data collection across procedures.

Benefits include:

System Forms may automatically collect:

Custom Forms

Custom Forms allow protocol authors to design their own structured data collection experience.

Custom Forms can contain:

Custom forms can be tailored to:

Validation Rules

Custom Forms support validation requirements to ensure collected data meets organizational standards.

Examples include:

Validation occurs before a step can be completed.

This helps improve data quality and reduces reporting errors while being able to build complex protocol data entry forms to capture anything you need for reporting.

Completing a Step

When a user executes a protocol step:

  1. FlaskTrack evaluates step requirements.
  2. Required forms are displayed.
  3. The user enters requested data.
  4. Validation rules are evaluated.
  5. The step is submitted.
  6. An execution event is created.
  7. Collected form data is attached to the execution record.

Once completed, the information becomes part of the permanent execution history.

Execution Records

Every completed step generates a structured execution event.

Execution records contain:

Execution records provide complete traceability for laboratory and operational activities.

Environmental Data

Protocol steps may define environmental requirements that operators are expected to follow during execution.

Examples include:

Temperature

Lighting

Agitation

Additional notes can be recorded for each environmental condition.

Environmental requirements become part of the execution record and can be reported later.

Timing & Scheduling Data

Protocol steps may also define timing constraints.

Supported timing modes include:

Additional scheduling controls include:

These values are recorded alongside execution events and may be analyzed through reports.

From Execution to Reporting

Every step completion creates structured events inside the FlaskTrack operational database.

These execution events include:

FlaskTrack continuously transforms these execution records into reporting datasets.

Data Lake Architecture

Execution events are automatically synchronized into the FlaskTrack reporting data lake.

The data lake serves as the analytical layer used by:

The data lake preserves execution history while optimizing analytical performance.

This separation allows transactional workflow execution and reporting workloads to scale independently.

System Reports

System Reports provide prebuilt operational visibility into collected protocol data.

Examples include:

System Reports automatically incorporate submitted form data.

Custom Reports

Organizations may build custom reports using Data Explorer or SQL-based reporting.

Custom reports can combine:

This allows organizations to generate highly specialized operational and scientific reporting.

Audit & Compliance Benefits

All protocol form submissions are permanently associated with:

This provides:

Every recorded value can be traced back to the exact execution event that generated it.

Best Practices