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Workflow Detail & Editor

Workflows define how protocols are organized into complete experimental or operational pipelines.

A workflow represents the ordered progression of laboratory procedures over time.

While protocols define how individual procedures are performed, workflows define:

Workflows are the orchestration layer connecting laboratory procedures into reproducible operational systems.

Workflow Overview

Workflows act as reusable execution templates for:

Workflows themselves do not directly execute work.

Instead, workflows are instantiated during batch creation, where they generate the operational structure used for real laboratory execution.

Workflow Metadata

The top section of the workflow defines its operational identity and scope.

Workflow metadata controls:

Name

The workflow name identifies the experimental or operational pipeline.

Examples:

Clear workflow naming improves:

Domain

The domain defines the biological or operational category for the workflow.

Examples may include:

Domains help organize workflows and ensure compatibility with related protocols and operational resources.

Species (Optional)

Workflows may optionally target a specific species.

Species targeting allows organizations to:

If no species is specified, the workflow may be used more broadly.

Description

The description provides a human-readable summary of the workflow’s purpose and operational intent.

Descriptions may include:

Descriptions appear throughout the platform in workflow listings, execution views, and reports.

Workflow Lifecycle

Workflows typically evolve through operational lifecycle stages such as:

Organizations may use workflows as:

Workflow governance improves reproducibility and operational consistency across laboratories.

Cloning Workflows

Workflows may be cloned to create new workflow variants without modifying the original definition.

Cloning is useful for:

Workflow cloning helps laboratories evolve operational systems while preserving historical traceability.

Protocol Sequence

The Protocol Sequence section defines the ordered protocols that make up the workflow.

Each protocol represents a major operational stage within the overall experimental process.

Examples:

  1. Media Preparation
  2. Explant Sterilization
  3. Culture Initiation
  4. Expansion Phase
  5. Root Induction
  6. Hardening & Transfer

This sequence becomes the operational backbone for execution scheduling.

Adding Protocols

Protocols may be added to a workflow by:

Protocols are intentionally reusable across workflows.

This improves:

Protocol Ordering

Protocols execute sequentially according to their order within the workflow.

Ordering controls:

Protocols may be reordered using workflow controls.

Execution systems preserve this ordering when batches are instantiated.

Workflow Scheduling Logic

Workflow ordering directly affects operational scheduling.

When workflows are instantiated into batches:

Scheduling may incorporate:

This enables workflows to model real laboratory timelines rather than static checklists.

Removing Protocols

Protocols may be removed from workflows while editing.

Removing a protocol affects future workflow executions only.

Existing batches preserve the workflow structure that existed at the time of instantiation.

This ensures:

Workflow modifications never retroactively alter completed execution records.

Workflow Visualization & Procedure Preview

The Procedure Preview provides a read-only representation of the workflow as a continuous operational procedure.

This allows users to:

The preview dynamically reflects the current workflow configuration and linked protocol definitions.

Shared Workflow Resources

Some workflows may expose consolidated operational resources across all protocols.

Examples include:

This provides a high-level operational overview useful for:

Actual execution tracking remains protocol and step specific.

Workflow Execution Model

Workflows become operational when instantiated into batches.

During batch creation:

  1. A workflow is selected
  2. Samples are generated
  3. Protocol schedules are created
  4. Step execution timelines are initialized
  5. Operational tracking begins

Once execution starts:

Subsequent workflow edits only affect future batches.

Relationship to Protocols

Protocols and workflows serve different operational purposes.

Protocols Define Procedure Logic

Protocols define:

Protocols describe how individual procedures are performed.

Workflows Define Operational Progression

Workflows define:

Workflows describe how procedures connect together into a complete operational system.

Compliance Integration

Workflows may include compliance-aware operational structure.

Examples include:

Compliance integration ensures workflows remain operationally enforceable within regulated environments.

Automation & Operational Orchestration

Workflows integrate closely with Flask Track’s automation systems.

Automation capabilities may include:

This allows workflows to function as operational orchestration systems rather than static documentation.

Auditability & Traceability

Workflow definitions contribute directly to operational traceability.

Execution systems preserve:

This ensures laboratories can reconstruct:

even long after execution has completed.

Archival & Deletion

Workflows that have been:

may become protected from deletion.

In many cases, workflows are archived rather than permanently removed.

This preserves:

Who Uses This Page?

Scientists

Scientists use workflows to:

Technicians

Technicians use workflows to:

Administrators

Administrators use workflows to:

Auditors & Reviewers

Auditors review workflows to verify:

Workflows provide the authoritative definition of how laboratory procedures connect together operationally.

Summary

Workflows are the orchestration layer of Flask Track.

They transform individual protocols into structured, repeatable, and scalable laboratory pipelines capable of supporting:

By combining protocol sequencing, scheduling logic, compliance integration, and operational orchestration, workflows provide the framework for managing complex laboratory processes in a controlled and reproducible way.