This small timeline on the history of data visualization highlights important data visualizations that were named and inspired by natural elements. Throughout history, art has thematically been inspired by nature that stands still against time. In 2020, we can look back on a Leonardo Da Vinci red chalk sketch of a tree, and recognize the subjects of the drawing 520 years later in our own yards. If this is true for pieces of art, it might also be true for data visuals. Data sets can be easily understood if it is presented in a way that is familiar to viewers, for example the depiction of a family tree. The branches of a tree grow long and spit off as a growing family does through generations. This data visualization is inspired by nature, which makes it simple and easy to understand, and easy to utilize. If the way in which a tree grows can inspire the way a set of data is depicted, then what other elements of nature have inspired data visualizations?
This project used the software Timeline.js to form the dataset into a timeline. The data set was first written into a google document while in the research collection phase, and was then transferred into a google spreadsheet. From there, the Timeline.js software analyzed the spreadsheet and created the timeline you see below. Additional photos added as examples of each data visual were taken from WikiCommons, as well as background photos intended to show the nature the data visual was inspired by.
Process and Discussion
Before creating my data set, I analyzed a timeline on datavis.ca to find data visualization inventions to inspire my own timeline. I ended up noticing both the “Evolutionary Tree” and the “Tree Map” and wondering how they were differential to each other. While further investigating, I wondered how many other data visuals might have been inspired by nature. This led me to sunspots, star plots, and the tag cloud. I found the name Sparkline in my research, and though it was inspired by line graphs more than it was a spark, I felt it important to add in my timeline. Sparkline fits in with its name, and its simplicity, but also because its representation is very elemental, which I think looks more like a wave than a spark. Throughout the timeline, you can see how the data visuals began as simple representations, like the sunspots, and became slightly more abstract, like the Tree Map. My theory on this evolution is that the datasets became less about explaining how the data interacts, to understanding the overall impact of the data.
Overall, Timeline.js was a simple product to use. It has clear instructions and simple ordered steps. This can also be its downfall because its simplicity leads to little versatility. The timeline shows in slides, with a representation of the data as well as a background. There is little else that can be changed with it. In addition to this, the software only recommends about 20 data entries. That said, the background element was a nice touch that I thought really brought my timeline together visually. In the future, I would love to be able to add even more events, and be able to change things like the font color or the overall timeline aesthetics.