As a public school teacher, I frequently feel overwhelmed by the sheer amount of information I receive. I get data about student performance, about equity measures, about student’s lives and about parent’s aspirations. Yet at some point during my graduate coursework I started to rethink how I approached exactly what value I was getting from that data, and from my degree more generally. That was when this new term started popping in my mind: the macroscope.
A microscope takes an object and magnifies a single component. A (metaphorical) macroscope, on the other hand, takes the small pieces and takes a step back; it assembles them together and allows us to see a bigger picture. It lets us stop asking “what is this data?” and, “what are their implications?” and instead start asking, “why are we gathering and using this data in the first place?”
To me, this is fundamentally a feature of good data visualization, and an essential component of a New Data Epistemology.
Take, for example, Albert Munsell’s color scheme.
Munsell created a way of modeling our perception of color with an irregular orb. Colors run across the equator. The axis of the orb goes from white at the north pole to black as the south, while horizontally each value is a gradation that goes from no saturation to full saturation.
This could be used to describe virtually any perceptible color, and it was particularly revolutionary in the early 1900’s because earlier attempts at color spheres had used symmetric shapes, which did not capture the limitations of human perception.
Munsell was a researcher, taking measurements of visual responses methodically and with an eye for scientific rigor. This accounts for the irregularity in the shape of the orb: colors are as perceptually uniform as he could get, which reflected the inability of the human eye to discern every conceivable color perfectly.
As he noted:
Desire to fit a chosen contour, such as the pyramid, cone, cylinder or cube, coupled with a lack of proper tests, has led to many distorted statements of color relations, and it becomes evident, when physical measurement of pigment values and chromas is studied, that no regular contour will serve.
(From Munsell’s “A Pigment Color System and Notation”)
This is what is interesting about his work. What is particularly striking is that he did not try to fit his schema into preexisting limits. Prior attempts at 3-dimensional representations of color had tried to fit them into a regular sphere, which simply did not model reality. He instead let the science guide his visualization. In doing so, he was able to capture more information in a way that was more understandable. He began with diagrams like this:
But ended with this:
An adequate visualization begs the question of why it matters; a truly good visualization demonstrates its importance implicitly.
This may be a jump here, but this makes me think of a concept that appears from time to time in my graduate literature, called dysconsciousness (See for more information Ladson-Billings, 2009). This is the practice of uncritical settlement to the status quo. It is this idea that even if—or maybe precisely because—you understand that you have some privilege, if you don’t critical reflect on how you will act on it, you are contributing to a status quo—one that in my line of work means a system that is deeply unequal. In other words, without really thinking about how all the parts relate in a scientific and critical way, and without determining what that means about a system as a whole (whether it is a social system like schools or a scientific system like the perception of color), we simply keep doing the same thing over again. We need a macroscope in our lives in order to parse out exactly how we can act. Munsell used one; we need them desperately in data sciences today.
I think if were to have seen the term dysconsciousness a few years ago, I would have thought about my time at the University of Chicago. It implies, ultimately, an uncritical habit of mind, and if the University of Chicago taught me anything, it’s that an uncritical mind is a wasted mind.
Our perceptions, attitudes, assumptions, and beliefs that justify inequity and exploitation are fundamentally predicated on abdicating our intellectual capacities to critically analyze and challenge the structures and institutions in which we act. We only accept the existing order of things as given if we accept that order as right. This, I think, is a fundamental element of the New Data Epistemology: it is a macroscope for big data, and as such demands that people think, and think critically. I can only hope that what we create will serve to change the status quo, and challenge systems that we know are not right.
It is far easier, like Munsell suggested, to simply try to fit everything into a simple shape, even if we know it doesn’t work. But he didn’t. It only takes one person to make us rethink our assumptions, and it only takes one person to reshape how we think about the world.
Thanks for reading.
Ladson-Billings, G. (2009). The dreamkeepers: Successful teachers of African American children. San Francisco, Calif: Jossey-Bass Publishers.
Munsell, A.H. (1905). A Color Notation: A measured color system, based on the three qualities of Hue, Value, and Chroma, with Illustrative Models, Charts, and a Course of Study arranged for teachers. Boston: Geo. H. Ellis Co.