Minard Map
Earlier this term we learned about types of data and the ways it can be organized and used in the digital space. This week we expanded upon this by discussing the tools and ways that we can visualize data to both gain understanding and create stories. One example we looked at was the Minard Map. This map is an example of how data visualization can be used to convey an argument by compiling a variety of information formats into one visual. The Minard Map is famous for being a shining star in the world of data visualization, it offers a historical argument told through a visual composite of a variety of data types. Despite its five star review I must admit that I initially struggled to understand what the map was showing me. In order to grasp the importance and information being presented in this map it requires a fair amount of decoding. I don’t think this is necessarily a bad thing, rather it is a product of the sheer amount of information that it presents. Plus, after interacting with the map with a basic understanding of the argument and data points it suddenly becomes quite straightforward, a point complemented by the design choices.
I explored an interactive version of the map (linked here and shown in above screenshot) that lets you move a slider along the time axis and get a summary of the data (temperature, event and number of men alive) for that specific date. These stats are highlighted by the red box in the image above. The slider also colors in the black bar representing the French troop return march, indicated by the red arrow in the image above. I think this interactive version successfully improved upon the original. I liked being able to see the actual numbers change as I moved the slider back and forth, even though this is all information conveyed by the width of the black bar it helped to drive home the extent of the disaster.
The Lie Factor
One of my key takeaways from Lin’s lecture was on the importance of accuracy and honesty when creating data visualizations. She talked about the incredible potential visualization has to tell stories that are otherwise not represented by the raw data alone, but this only works when there is a commitment to honest manipulation of data. Lin showed us a few examples of what happens when visualizations are manipulated to illustrate the story the author wants to show instead of what the data is actually showing. One mistake that I had not thought much of before was conflating data representation in graphics. When showing a change in scale the graphic should correspond with the changes in data that is being represented.
Data visualization and DH
Connecting what we talked about with Lin and after exploring these examples it is clear that digital visualization should be an integral component of the digital humanities. I would argue that in many ways you could not have digital humanities without data visualization. The core of many DH projects is presenting data in a visual way that is accurate and communicates an argument. In order to accomplish this we need to be aware of the potential mistakes one can fall suspect to in order to avoid them so our projects can be accurate and descriptive.
