Eytan Adar pointed me to a video, Reasoning Under Uncertainty, from the historical ACM SIGCHI (computer-human interaction) Video Project. Beyond fashionable hairstyles, it demos interfaces from a software curriculum to teach high school students statistical reasoning in 1989. They’ve got stretchy histograms, where you can adjust bars to see how the moments change (reminding me of more recent work on sketch-based and other graphical elicitation interfaces, including some of my own), and shifty lines, where you drag a line trying to find the best fit, as in more recent work on regression by eye. Ben Shneiderman’s interface design guidelines came up recently on the blog, and both are nice early examples of interacting with data through direct manipulation, one of the ideas he pioneered. They were also using hypothetical outcome plots years before we attempted to make them cool! 

Sometimes I suspect the majority of the good ideas for statistical software were already out there back in the 80s and 90s, at least in pedagogical form. I’m thinking about work like Andreas Buja and colleagues’ “Elements of a viewing pipeline for data analysis” (from 1988) and their early mentions of graphical inference techniques like the line-up in the 90s. There’s also the ASA Statistical Graphics video library which includes a lot of cool early work.

It’s too bad that many of the mainstream GUI-based interactive visualization systems we see today dropped many of the ideas related to sampling and uncertainty in favor of what we’ve called  “data exposure” (making it as immediate as possible for the user to see and interact with the data itself). Much of the research too, at least in the more computer-science oriented data visualization community, seems more interested in pursuing variants of an exposure philosophy like “behavior-driven optimization”, where the system is trying to learn what data or queries the user might want to see next so as to serve those up. The idea of GUI-based visualization tools that let you simulate processes, for example, has never really caught on (though we’re still trying, e.g., here). 

P.S. I  haven’t watched the video that follows it, but it promises to describe the ‘The Andrew System’, a computing system that can offer the benefits of many diverse and useful systems within a common environment.  Maybe they were on to something there too!