
Open Science As Public Art
It has been a bit more than a year since we installed open source simulations of swarm behavior (Flocking) in a public walkway at the University of Calgary’s Werklund School of Education. At that time, I published a story on Medium (Freecodecamp) on the big idea behind the effort: “Code” that helps us learn should be a public object and experience, not a private language. Digiplay was designed to be a space and a learning environment where the public — anyone — could walk in, play with the simulation, and hack the code.
In the year that passed, we have seen people of a variety of ages play and hack. This is the story of the most recent public hack — as of yesterday — when Jordan Kidney, a computer science instructor at Mount Royal University, came in and installed a “riff” of the same swarm algorithm that powers the simulations at Digiplay. Below is a video of Jordan explaining his installation.
Here is why I find Jordan’s work to be powerful: it shows us how open science can also become public art.
The idea of “public” is the least talked about / understood idea in current education research. The public realm is where conversations take place, dissent and consensus take shape. It is the space where ideas become knowledge, thoughts become (inter)actions. Digiplay was designed to reconceptualize computational science as the public realm.
Jordan’s work illustrates an interesting possibility of this new form of public realm. As he explains in the video, playing with scientific code can at once be science as well as art.
The work of science is modeling. Simply put, scientists make (build, design, develop, refine, test) models. Scientific models are powerful, as they can explain and predict events and phenomena that are otherwise unseen and difficult to understand.
In this sense, making science “public” and “open” should also mean that the public should be able to tinker with the models, and even make scientific models. But science is typically produced in restricted-access spaces, by a chosen few; so instead of making scientific models, the public, by and large, only “receives” scientific facts. The “experience” of science — modeling — is still inaccessible to the public.
In a recent white paper presented at an NSF/NIH sponsored conference on Open Science, my colleague Marie-Claire Shanahan and I argued that the idea of “public” in relation to science and technology
is colonized with images of passive or resistant recipients of finalized knowledge. It is this conception of public that we confront here, by challenging the image of academic knowledge as a private language — a secret code that can only be known by an individual or a chosen few.
and that
computational science can serve as a suitable mode of public engagement with the “private language” of science.
The power of open-source code is that it is free, open and publicly available. And Jordan also reminds us that the real power of code is that it is malleable — so, while making science, we can also make art. Open science can also be public art.
