The term substrate crops up in several places in Duke’s scientific labs, and as I was doing the rounds in my new role as Director of Research Computing, I found myself using the term to contain a concept: “Research computing is like a substrate,” I found myself saying in conversations. “It is a common base that supports and nurtures research work and scholarly endeavor all over the university.” Of course, in my previous role in genomics and bioinformatics, my tours through labs exposed me to substrates that lined the bottom of Petri dishes — nice nutritious goo for yeasts and bacteria to grow on or in. That’s a biological version of substrate (one of several in biology, actually).

But substrates are everywhere, and are not only used to grow things that normally we seek to wash off. In building construction and, I suppose, in some areas of engineering or geology, a substrate is what lies below topsoil and is the grounding for sound building foundations. In neuroscience, a “neural substrate” makes up the underlying substance and system for a certain behaviors or psychological states. Some substrates are consumed in reactions that they enable, as in “enzyme substrate” (biochemistry). And, of course, some substrates are paint primers — they form a stable base for colored paints that ornament our lives.

Substrates underlie, ground, sustain, or nurture some activity or state.


Research computing hasn’t been understood as a substrate for long. Indeed, research computing usually conjures up notions of large computer installations, massive air conditioning units, and people who type mysterious incantations on command lines. That older notion located “research computing” in fields like mathematics, physics, computer science (of course!) and statistics — fairly neatly bounded and “computationally intensive” disciplines. But, true to their early conception as a “universal machine,” the devices of information technology have been configured for other, more wide ranging applications, even in places like … classical studies departments.

Over time, good tools earn broad application and are adapted to fit new circumstances. That’s what’s happened in research computing, which has found a place everywhere in the university. Computing devices are everywhere, and ingenuity and curiosity transform them into new instruments of research computing.

Over the course of Duke’s 2014 Spring semester, this blog will present examples and perspectives of research computing — and not necessarily consistent views or complete ones. Every week, contributors will explore in blog-fashion things like

  • a depiction of how someone did something interesting with the Open Science Grid
  • announcements of and reasoning behind changes on Duke’s cluster computing resources
  • posts on why visualization is essential and … fun
  • maybe a “manifesto” for research computing from a faculty member
  • a professional perspective from the inside of the data center, too.

The point, I hope, will be to help us gather practices and uses of computing in research activities, and maybe we’ll enrich the agenda for research computing. I’m interested in a range of responses to the question “What is research computing?” for research computing is no longer limited to those with access to a specialized computer — though such devices play essential roles in research computing. Research computing has changed from a thing to an activity. We want to learn what research computing is by seeing it at work in science and scholarship, underlying and nurturing those core activities of the university.

If research computing is a substrate for scholarship, what are its features and qualities?

— Mark R. DeLong, PhD (