This week I’ve been relaxing in Montana. Two days of my visit here so far were dedicated to learning the basics of fly fishing. During my childhood, the only recreational activity that my family engaged in together was fishing — mostly at lakes using bait to catch catfish, bass, and perch. In recent years, I’ve wondered if fly fishing might reconnect me to the joy of fishing in my youth in a way that better suits the person that I’ve become: one who is nourished by intellectual challenges. Based on the recommendation of a friend from Montana, I engaged a fellow named Joel Thompson of Montana TroutAholics to serve as my guide and teacher in the ways of the tied fly. To my delight, Joel turned out to be more than an expert fisherman.
If I ever move to a place with an abundance of pristine rivers and streams like Montana, I suspect that I’ll take up fly fishing as a regular form of meditation. In the meantime, I’ll treasure the insights that Joel shared with me, especially those that, odd as it might seem, apply to my work in data visualization.
Joel has observed through many years of fishing that the flies that effectively appeal to trout, despite their endless variety, can be reduced to about 10 basic patterns. These patterns are limited in number because the senses and appetites of trout are finite. Flies mimic the appearances of insects that trout eat. The patterns that express the appearance of these insects (mayflies, grasshoppers, etc.) can be distilled to a few, but their expression can vary a little in specifics such as color.
I told Joel that my work in data visualization similarly revolved around a finite set of visual attributes that could be used to encode quantitative data. Just as trout have a limited set of visual patterns that appeal to their appetites, so humans have a limited set of visual attributes that can be used to represent data.
Joel went on to explain that flies come in endless variety in part because people tend to design them in ways that appeal to themselves, which considerably exceeds the interests of trout. People love to make them colorful, fanciful, and pretty. They overwork the design, adding more and more features that amount to pure decoration. He admitted that even he is naturally inclined to overdo it when designing a fly. When he visits a fly fishing shop or online fly store he’s automatically drawn to flies that look cool, but knows that the essential question is, do they look cool to trout? He has to rein himself in when wrapping his own flies — a pastime of many fly fisherman, especially during the cold and dark winter months — reducing his designs to clear expressions of the basic patterns.
While visiting a fly fishing shop in Missoulla, I noticed that the two clerks were occupied, giving every ounce of their attention to an attractive young female customer — apparently a rare cause for celebration in a the male-dominated world of fly fishing. After she departed, the guys enthusiastically shared their joy with me and another male customer by recounting the interaction. They told us that upon entering the store the young lady asked for assistance in selecting “a pretty fly.” In her naiveté she expressed what many a stoic male fisherman often feel but would never admit: a natural attraction to things that are pretty and cool.
Novice or avaricious makers of flies approach the task as the addition of features rather than the subtraction of all that goes beyond the essential pattern of mimicry. I suspect that expert fly makers appreciate the elegance of simplicity. The parallel to data visualization is obvious. Data visualization beginners and those with experience who are willing to do what appeals even if it doesn’t work, make eye-catching charts that attract parts of our brains that are not engaged in understanding data. We can forgive the naiveté of beginners if they’re open to learning. The avarice of vendors that make dysfunctional data visualization tools and of so-called data visualization experts who obscure and complicate simple data-based stories by dressing them up in bangles and glitter to earn the adoration of a naïve public, this we shouldn’t forgive.
Whether we’re trying to lure a trout to the end of our line or working to make better decisions based on data, we need to focus on the patterns that work. Overworking them might be a natural inclination, but so is over-eating. It’s time to behave like responsible adults.