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Labels and Use Cases -- Organizing What Matters

Learning Goals

By the end of this section, you will be able to:

  • Understand what labels and use cases are, and how they differ
  • Use them to filter dashboards, drive workflows, and communicate impact
  • Create and apply labels and use cases correctly
  • Explain how this structure improves visibility and governance across domains

Overview

Osprey collects thousands of assets, displays, and tags from the PI System. Without organization, this volume of information can quickly become overwhelming. Labels and use cases are how Osprey turns that noise into signal.

They help you focus on what matters most -- whether that's environmental compliance, production uptime, or safety reporting. By categorizing data with business and operational context, you gain clarity across all layers of your PI environment.

Understanding Labels

A label is a flexible tag that you can attach to any asset, display, or issue within Osprey. Think of labels as universal filters you can use anywhere -- in dashboards, searches, and reports.

Common examples include:

  • Mission-Critical
  • Environmental
  • Production
  • Test or Sandbox

Labels serve three main purposes:

Prioritization -- Separate what truly matters from background noise.

Filtering -- Narrow dashboards and views to what's relevant for your role.

Collaboration -- Align teams around shared terminology across departments.

You can apply multiple labels to the same asset. For example, a tag might be both Mission-Critical and Environmental. This flexibility allows different teams to view the same data through lenses that reflect their own priorities.

Understanding Use Cases

While labels describe what an asset is, use cases describe why it exists. A use case groups assets by purpose, initiative, or workflow, giving structure to how data supports the business.

Common examples include:

  • Environmental Reporting: Tracking emissions and compliance KPIs
  • OEE: Improving overall equipment effectiveness
  • Data Science: Ensuring clean, reliable data pipelines
  • Energy Management: Monitoring energy consumption and efficiency

Each use case provides a business lens -- helping domain owners and managers understand how data quality, lineage, and governance affect their initiatives.

When configured, Osprey dashboards can roll up data quality scores by use case, making it clear which programs are at risk because of poor data.

How Labels and Use Cases Work Together

Labels and use cases complement one another to connect operational data with business priorities.

Labels provide granularity -- defining risk categories, functions, or system attributes.

Use cases define intent -- the outcomes or initiatives that data supports.

For example: A pump tag might be labeled Mission-Critical, but also belong to the OEE use case. Together, these relationships enable precise, contextual questions such as:

  • "Which mission-critical assets in our OEE program are failing checks?"
  • "Which environmental tags have stale data?"

This structure creates smarter dashboards, faster insights, and clearer communication between engineering, operations, and leadership.

Creating and Applying Labels and Use Cases

To create a new label or use case:

  1. Navigate to Labels in the Osprey sidebar
  2. Click New Label or New Use Case
  3. Define a name, description, and color
  4. Apply it to assets or displays directly from the asset page, or through bulk selection on the dashboard

Once applied, these filters appear instantly across dashboards, lineage views, and data quality reports -- giving you an organized way to interpret data at scale.

Propagation

Osprey automatically propagates labels and use cases downstream, ensuring consistency across your data hierarchy.

For example:

  • Labeling a tag as Mission-Critical automatically extends that label to any AF references, calculations, and PI Vision displays that use it
  • Tagging an AF database with the OEE use case applies that classification to all child elements, analyses, and related assets

This automation prevents manual tagging overload and keeps governance consistent throughout your system.

Viewing Data Quality Reports

Once labels and use cases are in place, Osprey integrates them directly into dashboards and reports. You can view data quality summaries, heatmaps, and trend charts filtered by label or use case -- revealing where poor data quality has the greatest operational or business impact.

For example:

  • View all Mission-Critical assets with stale data
  • Identify Environmental tags failing compliance checks
  • See how data quality trends differ between OEE and Reporting initiatives

These insights allow leaders to allocate resources and attention where it matters most.

Your Turn

  1. Navigate to Labels in Osprey
  2. Create a new label named Mission-Critical, assign a color, and add a description
  3. Navigate to Use Cases in Osprey
  4. Create a new use case named OEE and describe its purpose
  5. Apply both to a PI tag or display of your choice
  6. Open the Dashboards >> Business Impact section and use your new label and use case as filters to verify visibility

Key Takeaways

Labels and use cases bring structure and context to your operational data.

Labels classify what an asset represents.

Use cases define why it matters.

Together, they enable a consistent language for governance, better filtering in dashboards, and targeted workflows that connect data quality with business outcomes.

In the next section, we'll explore Views -- how to turn these filters into reusable perspectives for specific teams and roles.

Knowledge Check

Question 1

What is the main difference between a label and a use case?

A. Labels describe what an asset is; use cases describe why it exists
B. Use cases describe what an asset is; labels describe why it exists
C. They are interchangeable terms
D. Labels are for PI Vision only

Question 2

If a tag is labeled Mission-Critical and part of the OEE use case, what benefit does this give you?

A. It improves PI tag scan rate
B. It allows targeted dashboards showing high-impact issues
C. It automatically adds that tag to reports
D. It hides the tag from dashboards

Question 3

How do labels and use cases improve governance?

A. By defining ownership and making issues traceable to business objectives
B. By limiting who can view dashboards
C. By storing data externally
D. By replacing the AF hierarchy