Post #5: Spatial History

The data charted for my spatial analysis maps out some of the major sites involved with the Manhattan Project.  The locations shown do not represent a comprehensive list of all the sites involved with the creation of the atomic bomb, only the most prominent areas.  This information is ideal for spatial analysis because it demonstrates how physical space played a major role in the Manhattan Project.  Looking at the map, it is easy to see that the Manhattan Project required civilian and military officials to utilize different regions throughout the US.  At its most basic level, this type of analysis raises questions about the infrastructure network connecting all of these locations.  How did raw materials move from Colorado to Washington and Tennessee for processing and then down to New Mexico?  Similarly, how did people move from site to site?  The map also points toward a sophisticated physical and organizational network to coordinate the operation.  What types of communication were used to facilitate the movement of information between locations?  How was the Manhattan Project organized to maximize efficiency? Or, conversely, did bureaucratic structures decrease productivity?  If the map is paired with census data, the types of work being done at different sites is more easily understood.  Washington D.C. and New York City – both major population centers and seats of government power – served administrative functions.  Rural areas in Washington and Tennessee were used for dangerous and classified activities like plutonium and uranium enrichment.  Finally, the comparably empty space around Alamogordo, New Mexico witnessed the first atomic test in human history.

The features of the map itself provide some information, but unfortunately Google Maps Engine Lite does not allow base maps to be imported.  If this feature were available, it would be possible to use  maps of the US’s road, rail, and telecommunications network during the 1940s.  This type of map might further explain the location choices of some of the rural sites supporting the Manhattan Project.  Lacking this ability, the next best option is to use a map that includes the current US roadway infrastructure and some terrain data.  Even though the modern interstate highway system did not exist in the 1940s, looking at a map of the current network and the locations of Manhattan Project sites allows historians to ask questions about the decisions that went into charting the paths of highways.  All of the sites on the map are directly connected to or very near major interstates.  Were the interstates built with the intention of reaching these locations or did the interstate designers simply expand pre-existing roadways already used to connect Manhattan Project sites?

As a footnote, symbols used for marking the locations of Manhattan Project sites can make it easier to process information (i.e. factory shaped icons where factories were built, shovel and pickaxe to denote a mine).  However,  the basic Google Maps Engine does not allow these types of icons to be customized.  Without the ability to change color, the unique icons were sparingly used to avoid color redundancy.



Post #4: Data Visualization and Organization

For my data visualization project, I analyzed two texts that are instrumental to my research area: George Kennan’s “Long Telegram” from 1946  and Kennan’s 1947 article “The Sources of Soviet Conduct.”  The purpose of  comparing these two texts is to evaluate the differences between the documents.  Kennan wrote the “Long Telegram” as a dispatch to Secretary of State James Byrnes intended only for use within the US government.  In 1947, Kennan penned “The Sources of Soviet Conduct” as an internal report for the State Department, but it was published later that same year under the pseudonym “X” in Foreign Affairs magazine.  The two documents are not identical – the “Long Telegram” is 5,336 words while “The Sources of Soviet Conduct” comes in at just over 6,850 – but their tone and purpose is similar enough that using a data visualization tool like Voyant helps reveal shifts in Kennan’s policy concerns.

After eliminating Stop Words, Voyant highlights, both in the word cloud and list of word frequencies throughout the corpus, the major continuities and discontinuities that exist across the two documents.  “Soviet” is the most frequently used unique word and occurs as an almost identical percentage of the total words used in both articles, slightly over 1%.  The words “power” and “world” are both in the top 5 unique words identified in the two articles, though they do not appear in similar percentages of total words.  However, beyond these three key words a greater variation in usage and percentage of words is visible.  Given the subject matter, comparing the words “communist” and “capitalist” demonstrates differences in the focus of each article.  In the “Long Telegram,” Kennan uses “capitalist” 16 times and “communist” only 9 times.  In “The Sources of Soviet Conduct,” however, this trend is reversed with “communist” appearing 18 times compared to only “12” uses of “capitalism.”

By itself, this type of data does not provide a definitive interpretations of Kennan’s writings, but it does provide a new method of accessing the material.  Voyant is particularly helpful in accomplishing this task because it creates multiple visualizations including a word cloud, frequency list, and trend graph.  While manipulating these tools is not an entirely straightforward process once the visualizations are generated they are pretty transparent and do not require a great deal of specialized knowledge to interpret, thereby avoiding one of the major pitfalls of statistical analysis noted by Theibault.

“Long Telegram” visualization.

“The Sources of Soviet Conduct” visualization.

Unfortunately, I could not figure out how to get the URL’s to link to the data set with the Stop Words already locked in place.  Individual tools (i.e. Word Cloud) were capable of providing URL’s for manipulated data sets, but I could not figure out how to do it as whole.