How to Identify Calculated Tags in Your PI System

In the world of industrial data management, distinguishing between direct (raw) and calculated tags is essential for accurate reporting, troubleshooting, and auditing. Within OSIsoft PI System, calculated tags—sometimes referred to as derived or composite tags—are created through aggregation, formulae, or analytics rather than being a direct interface to a sensor or field device. Here’s a concise guide on how to locate these tags and understand their origins.

1. Filtering by Point Source in PI SMT

The PI System Management Tools (SMT) provide an efficient starting point. Each PI tag has a Point Source attribute, commonly leveraged to categorize tags by their data origin:

• T: Totalizer subsystem (tags representing totals or sums over time)
• G / @: Alarm subsystems
• R: Random interfaces
• 9: RampSoak interfaces (often related to test or simulation data)
• C: Performance Equation subsystem (tags calculated via PI Performance Equations)
• L: Laboratory or Analytics (commonly used for outputs of AF Analyses)

How to use:
Navigate to SMT ➔ Points ➔ Point Builder, and filter/search tags by their Point Source. If your organization follows standard conventions, most calculated tags will cluster under the sources above, especially C, T, and L.

Limitations:

• Organizations may use custom or inconsistent point sources.
• Not all calculated tags (especially those written back from external applications or custom interfaces) fit neatly into these buckets.

2. Examining the exdesc Attribute

Many calculated tags have descriptive formulas or calculation logic stored in their exdesc (extended descriptor) attribute. This can be accessed via PI DataLink or directly in SMT.

• Clues in exdesc: Look for function names like tagavg(, tagnval(, etc.
• How to check: In PI DataLink, pull the tag attributes and inspect exdesc for identifying text.

3. Leveraging Tag Naming Conventions

A reliable practice is to use consistent naming conventions for calculated tags, such as:

• TAGNAME.CALC
• TAGNAME.TOT
• TAGNAME.ACE
• TAGNAME.AFCALC

While not foolproof, these conventions offer at-a-glance identification and support search-based discovery.

4. Identifying AF Analysis Outputs

Many modern PI Systems use Asset Framework (AF) Analyses to produce calculated values:

• AF Analysis Processors can write results directly to PI Points. These outputs may use a dedicated Point Source (like L) or take over existing tags.
• Within PI System Explorer, search for Analyses that output to PI Points. Documenting these mappings in your asset model helps with long-term traceability.

5. Remember External and Custom Calculations

Calculation logic may reside in:

• Custom applications (written in C#, Python, etc.) writing results to PI
• Third-party data integration platforms
• Supervisory control and data acquisition (SCADA) or historians upstream from PI

In these cases, neither point source nor exdesc will provide a full picture. Consult with system integrators or review application documentation as needed.

Conclusion

Finding calculated tags often begins with point source and attribute inspection, but for a comprehensive approach, combine multiple strategies: examine naming conventions, dig into exdesc, review AF Analyses, and involve your broader OT/IT teams. Good tag management practices, such as rigorous documentation and standardized naming, are the foundation for seamless calculated tag identification in the long run.

Further Reading:

• OSIsoft Knowledge Base: PI Points and Attributes
• Using PI DataLink for Tag Information

How does your organization identify and document calculated tags? Share your tips or challenges in the comments!