For the first time in almost 55 years, humans are traveling beyond low Earth orbit. NASA's Artemis II mission launched on April 1, carrying four astronauts aboard the Orion spacecraft on a 10-day journey around the Moon and back. On April 6, the crew broke Apollo 13's record for the farthest distance humans have ever traveled from Earth.

The world is watching. And thanks to NASA publishing Orion's telemetry data and trajectory projections, you don't have to just watch. You can follow the data.

We couldn't help ourselves. We pulled NASA's public data into Sift.

Visualizing Orion’s telemetry with Sift’s Explore

Using Sift's Explore visualization engine, we mapped Orion's position and velocity from NASA's published telemetry data. No Python scripts, no math. The result is a queryable picture of the spacecraft's journey – not a dot on a map, but a dataset where every spike, dip, and inflection point is something you can explore.

Take the lunar flyby. As Orion swings around the far side of the Moon, the spacecraft decelerates at its farthest point from Earth. In a news broadcast, that's a sentence. In the telemetry, it's a story: velocity dropping, altitude shifting, trajectory bending under the Moon's gravity. Our annotations in Sift mark exactly when and where these transitions happen.

That's the difference between knowing Orion slowed down and seeing it.

From spacecraft telemetry to your hardware

Orion generates a tremendous amount of data: distance from Earth, distance from the Moon, speed, orientation, system health, and more. NASA has made headline metrics accessible to the public. But for anyone who's worked with complex mission data, the interesting questions aren’t "where is it?" They're "what changed, when did it change, and what else was happening at the same time?" That's the kind of analysis engineers do every day with Sift, whether the hardware is a spacecraft, a satellite, a turbine, or an autonomous vehicle.

Visualizing Orion's telemetry in Sift is a demonstration of something much bigger: the ability to take high-volume, time-series data from any complex machine and make it legible.

See what your data looks like in Sift

The machines we build are only as understandable as the tools we use to observe them. If publicly available NASA telemetry looks this clear in Sift, imagine what your own data would look like. Get in touch.