Challenge #2: It’s Hard to Visualize Data When You Need to Correlate It

Contributed by Derrick Snyder | Austin, TX

This is the second installment of the blog series, “The Top Challenges of Visualizing Time-Based Measurement Data.”

Often, data is being collected about a number of different phenomena at the same time. Though visualizing one data set alone is certainly valuable, incredible results come from the ability to discover relationships between different types of data. For example, when engineers test the ability of an airplane’s wing to withstand the violent forces that could occur in times of turbulence, they may simultaneously measure the force being applied to the wing, the strain (flex) of the material in the wing, the vibration on the wing, the noises that the components make when they finally reach their breaking point, and high definition video of the entire test being performed. Looking at a simple graph of the strain data over time is beneficial, but the ideal goal for engineers performing this test is probably to characterize how the strain and vibration of the wing are affected when exposed to different levels of force over time for a given design (all while watching and listening to the event played back). To do this, simple static graphs or images are insufficient.

Today’s advanced data processing software must be dynamic. Not only should graphs be able to depend on or interact with one another (for example, to provide cursor visualization coordinating one graph’s data values in time as compared to others), but in fact, graphs alone are no longer adequate visualization tools. To properly visualize engineering measurement data, it needs to be able to be correlated with alternative information such as video, GPS positioning or timestamps, sound, and more – you never know when the interrelationship of information may be the key to the next breakthrough in understanding.

– Derrick Snyder


About Derick Snyder

Derrick Snyder is a product manager for NI DIAdem measurement data processing and visualization software at National Instruments. He received a bachelor’s degree in Computer Engineering from Vanderbilt University.


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