Over the past few weeks, I’ve been exploring different ways to deal with digital history methods of analyzing data to produce visualizations. I have also learned how to critique data visualizations and make analyses on the ways they are used.

My process when I engage with and analyze historical data visualizations has not changed much from the beginning. I still look at the information about the creators of the visualization and any possible legends, keys or how-to instructions before I examine the content of the visualization. I have known about this step in the process for a long time and understand how crucial it is to understand any kind of graphic. Getting the context of a visualization is arguably one of the most important things to do in order to understand it. Without knowledge of the circumstances with which a graphic was produced, the graphic loses its usefulness for answering or asking questions about the topic. In the case of historical data visualizations, the topic includes the place of whatever is being visualized in history and certain key historical events. After the preliminary look-over, I then would look at the actual content and try to understand the message that is being communicated. I would interpret how the quantitative and/or qualitative data relate to each other based on the legend, labels, etc. and the type of representation being used like bar chart, histogram, or scatter plot.

One way I can think of where my process changed is that near or at the end of the process, it can be useful to think about what the visualization is lacking and how it may have omitted things, whether this is done on purpose in an effort to mislead the viewer or due to an oversight by the creator. Before taking this class, I didn’t think of using this technique to comprehend a visualization thoroughly because it is difficult to think about what isn’t there as opposed to what is. I believe adding this step to my process of analyzing a historical visualization is a beneficial improvement. An essay by Frederick W. Gibbs about critiquing data-driven historical visualizations mentions some additional questions I could ask about visualizations to analyze them.

When creating representations of data largely done through software (and especially at large scales), must representations remain free of direct manipulation after an initial algorithmic rendering? Is it acceptable to alter a computed representation in order to highlight a particular feature? To what extent might that be considered subversive or misleading? To what extent is that simply better communication? Is the visualization more about the unadulterated output of the tool (even if unfortunately treated as a black box) or about communicating an interesting historical phenomenon?

Those questions relate to the larger question of whether or not the visualization needed to solely be developed with computational methods. This is another way to pick apart the context of a representation and think critically about what is being presented.


Gibbs, Frederick W. “New Forms of History: Critiquing Data and Its Representations.” The American Historian, 2016.http://tah.oah.org/february-2016/new-forms-of-history-critiquing-data-and-its-representations/.