"Old-school computing: when your lab PC is ancient"

This Nature Technology Features has a lot of fun stories of ancient computers at the heart of research labs.

“The Hollywood depiction of cutting-edge science is always super fancy,” says James Mason, now a solar physicist at the University of Colorado Boulder, whose team built one of the Solar Dynamics Observatory instruments.

But the first time Mason visited the White Sands Test Facility, a laboratory in New Mexico that launches rockets to calibrate his team’s instrument, he was shocked to find data streaming to a boxy, custom-built 1980s-era desktop computer, spitting out lines of pixelated, greenish-yellow text. “It’s so old I can’t find any information about it on the Internet,” Mason says.

Now I want to make a film with a super-exaggerated version of this—Matthew McConaughey has to fly into a black hole in a spacecraft controlled by ENIAC.

Sometimes it’s the software upgrade itself that’s too expensive. In 2008, [Kristin] Low’s undergraduate lab at McGill University in Montreal used an Intel 386-based system running Microsoft’s then-16-year-old Windows 3.1 software to connect to their liquid chromatography system. Updating the chromatography software to support an upgraded operating system would have cost $10,000, Low says — a prohibitive amount.

Seriously though, I always think about these ongoing costs whenever new hardware (and software) might enter my workflow. There’s always a cost in the long-term.

And yes, open source can prevent some problems, like a vendor charging too much for an upgrade or even going out of business, but open source brings problems of its own. For one, there can be a heavy time commitment to keeping the software up-to-date 1. Maybe an ambitious grad student can help you, and you’ll avoid either doing the upkeep yourself or hiring it out to a technician, but then that grad student is not devoting their time to what really matters: cutting-edge research. And at the same time, a niche research area may not have enough popularity, or may be too technically challenging, to generate a groundswell of enthusiastic developers.

One way or the other, it’s money or time.


  1. I’ve got an interesting corollary to this, but that’s for another post. ↩︎

Jim Bagrow
Jim Bagrow
Associate Professor of Mathematics & Statistics

My research interests include complex networks, computational social science, and data science.