Managing Time Zone Discrepancies in PI DataLink: A Guide

Time zones can often introduce complexity into data analytics and this is particularly true when dealing with international data systems such as OSISoft's PI System. A common issue faced by PI System users is ensuring consistent time zone usage across various modules, such as PI DataLink.

When using PI DataLink, you might encounter discrepancies in time when dealing with events across different geographical regions. PI DataLink has a setting to display time based on the Archive Server's timezone, which works well for data items that contain a PI point or a particular Asset Framework (AF) attribute with a PI point data reference. However, this becomes challenging when you're working with events and elements not directly tied to a PI point. In these cases, the time displayed defaults to the client workstation's timezone.

Understanding PI DataLink Time Zones

The key to managing time zones in PI DataLink effectively is understanding the under-the-hood data references. If your data involves a PI AF attribute unrelated to a PI point data reference, DataLink falls back on the client workstation's timezone settings. This is why users might see inconsistencies in time displays — particularly when they're in a timezone different from the Archive Server.

Why the Discrepancy Happens

When events are loaded, particularly using PI DataLink's Explore feature, the start and end times get calculated dynamically. Hence, they are influenced by the client machine's timezone rather than the Archive server. This results in time differences, such as the 7-hour shift noted when observing event data for a plant in Germany from a location in the USA.

How to Resolve Time Zone Issues in PI DataLink

1. Data Reference Review: Ensure that the data items used are PI points or have a PI point data reference. Any deviation means PI DataLink will interpret timestamps in the client's timezone.

2. Using PI Points for Event Start Times: To ensure consistent use of server time zones, consider using a PI Point to store event start times. This ensures the displayed time aligns with the Archive server settings.

3. Awareness and Communication: Make sure that all relevant stakeholders understand how time zones are managed within PI DataLink. Clear communication can help reduce confusion and ensure everyone interprets data correctly.

Conclusion

Dealing with time zones in distributed systems isn't always straightforward. However, understanding how PI DataLink interprets timestamps and adjusting your data practices accordingly can significantly reduce complications. Where possible, storing data in a standardized format directly associated with a PI point can help maintain consistent time zone management, facilitating accurate and consistent data analytics across geographical boundaries.

By being mindful of these aspects, you can optimize your use of PI DataLink across different time zones, enhancing the reliability and consistency of your data representations.