Years ago, I remember being in a German history course and learning about the fall of the Berlin Wall on the 9th of November in 1989. Despite this, Der Tag der Deutschen Einheit, or Unity Day takes place on October 3rd. The reason for this difference in dates stems from a long-standing stigma with November 9th in German culture. This day represents historical events in Germany ranging from the founding of the Weimar Republic to the Beer Putsch and even the infamous Kristallnacht. For this reason, Germans found it distasteful to hold their holiday on a day with such sinister connotations. Now it’s not too difficult to be aware of such a stigma against a single day. But in our world of data, we can visualize larger trends. David McCandless pointed out how even things such as video games are not released during April due to a stigma associated with the Columbine shootings. Data visualization gives us the opportunity to conceptualize these trends and apply them to research in the humanities.
“Data is the new oil”
Water Levels of a building along the Danube in Passau, Germany
Though this trend towards data visualization often involves technology, the concept of data visualization isn’t necessarily new and doesn’t necessarily involve advanced technology. Maps as far back as the 18th-century chart things from the population of various European cities to mortality and crime rates. In a very low tech demonstration of data visualization, cities along the Danube often display water level charts on their historic buildings which show how high the water level reached in regards to its respective building.
Though data visualization has its low-tech roots, we now have the opportunity to apply modern technology to older methods. For example, Google maps now has a map of Stolpersteine (stepping stones) which commemorate the last known willfully chosen living space of victims of the holocaust. Data visualization becomes quite advanced when you apply text plots to large files such as with Henry Kissinger’s correspondences. Here, we see an attempted solution to a problem many 20th and 21st century historians face: Too much data. A blog on quantifying Kissinger sums up the situation with this quote.
“Scarcity of information is a common frustration for historians. This is especially true for researchers of antiquity, but not exclusively so. For students of twentieth- and twenty-first century history the opposite problem is also increasingly common — overwhelmed instead by a deluge of information and confronted by a vast field of haystacks within which they must locate the needles (and presumably, use them to knit together a valid historical interpretation), historians have already struggled with what is now understood as ‘big data’.”
Data visualization allows us to make meaning out of large troves of information that otherwise would be impossible to access. For instance, Joshua MacFadyen and Nolan Kressin created a temporal geospatial map of firewood transport on Canadian trains from 1876 to 1903. In their blog, they mention how Harold Innis published a book called the fur trade in Canada in 1930. They mentioned how his book involved deep archival research, to the point in which they referred to him as a “dirt researcher” in regards to the strenuous nature of his research. Juxtaposed to Innis’ book, MacFayden and Kressin created a 15 second video showing how firewood flowed through various railways in Eastern Canada. This certainly shows the power of data visualization. However, the authors maintained that the visualization raised just as many questions as it answered.
This coincides with a larger observation about data visualization as historians are pushed to create meaning out of larger and larger amounts of data. At this point, we must ask ourselves: “To what point should we rely on data to provide reliable historical interpretations and narratives?” To me, this is a complex issue. I think that geospatial data can be a great way to view historical figures that essentially speak for themselves. For instance, Charles Minard’s temporal geospatial map did an excellent job at depicting the casualties in Napoleon’s march to Russia. However once you get past raw facts such as casualty rates, visualization methods become more skewed.
John B. Sparks published a map on global power shifts over the past 4,000 years. Though it’s interesting to see the rise and fall of empires throughout time, the blog about the chart points out that much of its creation relied on guesswork, and that it had an apparent bias against China. Another issue with data visualization is the scarcity of certain information. For instance, much of Galileo’s correspondence was destroyed in the wake of his trial for supporting Copernican astronomy. This can be difficult when trying to visualize the data. However, when making an assessment, historians should know that sometimes the absence of information is in and of itself information. Florence Nightingale provided an example of this when she analyzed the death rates of British soldiers in the Crimean War. She found that soldiers weren’t dying as much from fighting, but rather from diseases. This realization caused the British government to increase sanitation standards.
Currently, data visualization and technology are regular aspects of our lives. Just by viewing the U.S. census website, I can access data that social scientists 50 years ago could only have dreamed of. Though this data is useful, we must not overlook the necessity to critique it. Frederick W. Gibbs mentions how methodology and data critique is now more important than ever in fostering valid historical narratives. As long as we can fulfill these critiques, data visualization will continue to be a useful medium for conveying history.
Routley, Nick. “Histomap: Visualizing the 4,000 Year History of Global Power.” Visual Capitalist. Last modified March 8, 2019. Accessed October 13, 2020. https://www.visualcapitalist.com/histomap/?utm_content=bufferdf855.
Thompson, Clive. “The Surprising History of the Infographic.” Smithsonian.com. Smithsonian Institution, July 1, 2016. Last modified July 1, 2016. Accessed October 13, 2020. https://www.smithsonianmag.com/history/surprising-history-infographic-180959563/.
“Data Visualization and the Modern Imagination.” Spotlight at Stanford. Accessed October 13, 2020. https://exhibits.stanford.edu/dataviz.
“New Forms of History: Critiquing Data and Its Representations.” New Forms of History: Critiquing Data and Its Representations | The American Historian. Accessed October 13, 2020. https://www.oah.org/tah/issues/2016/february/new-forms-of-history-critiquing-data-and-its-representations/.
Nicole Coleman, Stanford University. Mapping the Republic of Letters. Accessed October 13, 2020. http://republicofletters.stanford.edu/.
The Website Services & Coordination Staff, US Census Bureau. “Data Visualization Gallery.” Visualization Gallery. Last modified March 1, 1994. Accessed October 13, 2020. https://www.census.gov/dataviz/.
MacFadyen, Josh. “The Fir Trade in Canada: Mapping Commodity Flows on Railways.” NiCHE. Last modified October 8, 2020. Accessed October 13, 2020. https://niche-canada.org/2020/10/08/the-fir-trade-in-canada-mapping-commodity-flows-on-railways/.
Kaufman, Micki. “‘Everything on Paper Will Be Used Against Me:” Quantifying Kissinger.” Everything on Paper Will Be Used Against Me Quantifying Kissinger. Accessed October 13, 2020. https://blog.quantifyingkissinger.com/.
McCandless, David. “The Beauty of Data Visualization.” Last modified November 23, 2012. https://www.youtube.com/watch?v=5Zg-C8AAIGg&ab_channel=TED-Ed.
“Napoleon’s Ill-Fated March to Russia – Intro to Data Science.” Last modified February 15, 2015. https://www.youtube.com/watch?v=PYwwSHpPZdc&feature=youtu.be&ab_channel=Udacity.
“Stolpersteine in Berlin.” https://www.google.com/maps/d/viewer?ie=UTF8&oe=UTF8&msa=0&mid=1uIMsJp798Y2OBdQbdPMHjrqS8Hs&ll=52.488633317667805%2C13.353340000000022&z=13.