I am an assistant professor in the Department of History and Art History at George Mason University, working on digital history and the history of American religions. You can find a link to just about anything I've worked on in my CV or in the blog archives. Some of my work is described in more detail on the research page, and my syllabi are on the teaching page along with workshop materials. You can write to me at lincoln@lincolnmullen.com.


Syllabus for Programming for Historians

This fall I will be teaching a grad class called “Programming in History/New Media.” It is the third (optional) course in a three-part sequence of digital history classes taken by PhD students, hence the shorthand name #clio3. My aim in this course is to get students familiar with basic computer programming, then show them how to apply a number of the most useful technique for historical research, such as mapping, text mining, and network analysis. We will start out with JavaScript (in part because it is an obligatory language for web programming, but also because Marijn Haverbeke has written an excellent and free introduction to programming with JavaScript). Then we will move on to R for most of the applied section, circling back to JavaScript and D3.js at the end. The main student work for the course is a programming project of their choice, which I’m asking them to think of as the rough equivalent of a seminar research paper. I have some ideas about what form those projects might take, but I think I’ll be surprised at the ingenuity of the people taking the course.

Here is the syllabus for the course.

Visualizing Presbyterian Statistics Through One Hundred Years

The title Presbyterian Statistics through One Hundred Years, 1826–1926: Tabulated, Visualized, and Interpreted sounds like contemporary digital history project. Click the link, and if you’re an optimist about digital methods you might expect a revolutionary new methodology for doing history that overturns old models; if you are a pessimist you might expect to find some “Big Data” hubris. But what you’ll find is a book from 1927, compiled the Presbyterian minister and employee of the General Council of the Presbyterian Church U.S.A., Herman Carl Weber.1 Weber compiled the data at the behest of the PCUSA, laboriously compiling the statistics because the General Council wanted to know what insights could be gathered from its record.

The first part of Weber’s work included dozens of tables like the one below.2 Denominations often maintained records and published them in yearbooks and annual reports.3 What is especially useful with Weber’s figures are that he compiled the numbers longitudinally—apparently over a period of three years of work—so that it is possible to see change over time.

A table of membership figures from Weber, p.  12.
Figure 1: A table of membership figures from Weber, p. 12. [PNG]

Having gathered the numbers, Weber turned them into a series of visualizations and accompanying interpretations aimed at improving both the national church and individual congregations. In turning records into tables, and tables into graphs, Weber had some confidence that “the circle of those who can understand visualizations readily is very large,” though he also deemed it wise to use prose to “suggest what some of the visualizations mean” (3–4). In 1927 the idea of visualizations was not particularly innovative. Beginning in the 1780s the Scottish political economist William Playfair invented some of the foundational visualizations, including line charts, bar charts, and time series. As Susan Schulten has shown, maps and other kinds of data-driven visualizations were important techniques for nineteenth-century American science, engineering, and statecraft. Nor is it any coincidence that visualization was a technique for interpretation in the same period that the historians in America were turning themselves into professionals.

Weber’s charts told a story. In the first visualization in the book, reproduced below, notice the rise in Presbyterian membership over a hundred years. (The vertical orientation of the chart exaggerates growth, but from what I can tell Weber chose that orientation because of the constraints of printing and not out of any intention to distort.) Weber called this a “bird’s-eye view of the membership” (46).

A chart of membership from Weber, p.  46.
Figure 2: A chart of membership from Weber, p. 46. [PNG]

That first chart with its steep curve made the Presbyterians look good, but Weber was not so naive. He knew that in the nineteenth century United States everything was growing, and that some denominations were growing faster than the Presbyterians and had a larger share of the population. Weber included the “ratio chart” below, derived from the Yale economist and statistician Irving Fisher, that used a logarithmic scale to show “the same relative increases” with “the same slope” (203). The short explanation is that Weber found a way to show that the Presbyterians were only growing at the same rate as the population, and that the Baptists and Methodists were growing faster.

Weber
Figure 3: Weber’s ratio chart comparing denominations, p. 49. [PNG]

Weber’s most intriguing work was a pair of charts about people who joined the Presbyterian church. Weber was quite interested in whether or not the Presbyterians were fulfilling their mission to win converts. The chart below of “Accessions on Confession” was “the line of response from the young, adolescent life of the Church to the call of the Kingdom.” Weber annotated the chart to show the underlying causes in the fluctuations: the peaks for the revivals of Finney, Moody, and Sunday; the falling off in conversions caused by denominational splits, heresy trials, and the controversy with science.

Weber
Figure 4: Weber’s chart of ‘Accessions on Confession,’ p. 51. [PNG]

The chart of total new members showed a positive picture of Presbyterians’ growth, but again, Weber knew enough to normalize the data to account for growth in population. In the chart below, he created an “Evangelistic Index,” the “proportion of new members in the total membership.” This was “the most significant of all the visualizations submitted in this volume” because it “portrays the actual record of the Church in the primary functional responsibility which has been committed to it” (57).

Weber
Figure 5: Weber’s ‘Evangelistic Index,’ p. 56. [PNG]

My point in showing Weber’s visualizations is two-fold. First, visualization as a method for history is much older than current debates would sometimes lead one to believe. Such methods are deeply rooted in the nineteenth and early twentieth century. The corollary is that the history of American religion, insofar as it makes use of quantitative methods, must depend on data collected, aggregated, visualized, and interpreted by the very people whom historians wish to study.


  1. The book is Herman C. Weber, Presbyterian Statistics Through One Hundred Year, 1826–1926: Tabulated, Visualized, and Interpreted (Philadelphia: The General Council, Presbyterian Church in the U.S.A., 1927), http://catalog.hathitrust.org/Record/007109885.

  2. For use in my dissertation, and for a future project on the demography of American religion, I’ve turned some of Weber’s data tables into a useable format. If you want to see what I’ve started to do with the data—though this is very much a work in progress—you can see this repository.

  3. See for example this run of Congregationalist yearbooks from 1854 to 1960 compiled by the fine folks at the Congregational Library.

Map Projections and the Historical Imagination

At the New Republic, Susan Schulten has a fascinating article about maps made by Richard Edes Harrison during World War II. Schulten writes that Harrison, an artist and not a cartographer, changed the American public’s perception of the war and world by refusing to use the Mercator projection. Instead, he drew maps from various perspectives above the earth, evoking “the perspective of a pilot, but one placed at an infinite distance.”

Richard Edes Harrison,
Figure 1: Richard Edes Harrison, ‘Europe as Viewed from the U.S.S.R.’ (1944). Courtesy of David Rumsey. [JPG]

Schulten writes:

Most professional cartographers celebrated his provocative style for its ability to foster a more dynamic understanding of geographical relationships … . [H]is goal was to wrench Americans out of a two-dimensional sense of geography, and embrace an understanding of perspective and direction.

Much of maps that historians make on the web is also limited by the Mercator projection. Google Maps, Stamen, and Map Box all use a “Web Mercator” projection for the tiles they provide. If you’ve used a web map that pans and zooms, it was almost certainly created in the Mercator projection. Even if there are good technical reasons for Google to use that projection, historians have their own purposes that could be better served by alternative perspectives on the earth.

The world seen from Google.
Figure 2: The world seen from Google. [PNG]

According to Schulten, Harrison never thought of himself as a cartographer, and “cartographers were quick to point out that no such perspective existed in nature.” But thanks to the work of Mike Bostock and Jason Davies, the kinds of perspectives that Harrison used are available to web mapmakers.1 As part of the geographic projections available in D3, Bostock has created a satellite projection, with which the mapmaker can control the view of the earth as from a camera mounted on satellite. Such a map could be combined with any of the visualization techniques—choropleth shading, bubble maps, place names—for which D3 is known.

An example of Bostock
Figure 3: An example of Bostock’s satellite projection. [PNG]

Jason Davies has gone a step further and figured out how to reproject Mercator map tiles into any map projection.2

Davies
Figure 4: Davies’s reprojected map tiles for a satellite projection. [PNG]

This means that historians have the tools they need to re-imagine their historical maps outside of the constraints of any particular map projection.3 Just as Harrison changed the public view of the geopolitical situation with his perspective maps, so historians would have a powerful imaginative and rhetorical tool at their disposal if they could choose the perspective of their maps. One can imagine, for example, a map that redraws the Atlantic slave trade from the perspective of West Africa, or a map that literally faces east from Indian country. As is often the case when I read Schulten’s work, the historical maps she studies provide a useful suggestion for how historians could make their own maps to imagine the past.

Looking east over the Chesapeake.
Figure 5: Looking east over the Chesapeake. [PNG]

  1. There are many other artistic elements to Harrison’s work, such as the exaggerated topography, that it would be difficult to reproduce in a programmatic map.

  2. An example showing how Davies’s method for re-projecting tiles works.

  3. Such perspectives have been available in Google Earth for many years, but asking viewers to drop into a proprietary application prevents the integration of web maps with prose narrative and argument.

Mapping the Spread of American Slavery

[A revised version of this post was published at Smithsonian.com.]

In September of 1861, the U.S. Coast Survey published a large map, just under three feet square, titled a “Map showing the distribution of the slave population of the southern states of the United States.” Based on the population statistics gathered in the 1860 census, and certified by the superintendent of the Census Office, the map depicted the percentage of the population enslaved in each county.

U.S. Coast Survey, *Map showing the distribution of the slave population of the southern states of the United States* (Washington, DC: Henry S. Graham, 1861). Image from the [Library of Congress][large map].
Figure 1: U.S. Coast Survey, Map showing the distribution of the slave population of the southern states of the United States (Washington, DC: Henry S. Graham, 1861). Image from the Library of Congress. [PNG]

The map showed at a glance the large-scale patterns of slavery in the American South: the concentrations of slavery in eastern Virginia, in South Carolina, and most of all along the Mississippi. It also repaid closer examination, since each county was labeled with the exact percentage enslaved. The map of slavery was one of many thematic maps produced in the nineteenth century United States. As Susan Schulten has shown, this particular map was used by the federal government during the Civil War, and it was a favorite of Abraham Lincoln’s.1

A detail from the U.S.  Coast Survey map of slavery, showing the Mississippi River and delta.
Figure 2: A detail from the U.S. Coast Survey map of slavery, showing the Mississippi River and delta. [PNG]

Though such thematic maps, in particular of slavery, have their origins in the nineteenth century, the technique is useful for historians. As I see it, one of the main problems for the historians’ method today is the problem of scale. How can we understand the past at different chronological and geographical scales? How can we move intelligibly between looking at individuals and looking at the Atlantic World, between studying a moment and studying several centuries?2 Maps can help, especially interactive web maps that make it possible to zoom in and out, to represent more than one subject of interest, and to set representations of the past in motion in order to show change over time.

I have created an interactive map of the spread of slavery in the United States from 1790 to 1860.3 Using Census data available from the NHGIS, the visualization shows the population of slaves, of free African Americans, of all free people, and of the entire United States. It also shows those subjects as population densities and percentages of the population.4 For any given variable, the scales are held constant from year to year so that the user can see change over time. You can use the map for yourself, and I’ve also written briefly about what the map shows below.5 Historians have of course often made use of maps of slavery, in particular maps based on the Census, in support of their arguments. What I’ve tried to do in this interactive map is make it possible for users (including me) to explore the census data in support of making historical arguments.6

Screenshot 
of the interactive map of slavery
Screen shot of the interactive map of U.S. slavery.

The first thing to observe is that slavery spread more than it grew. The population of slaves in 1790 or 1800 was already very high compared the maximum population levels.7 In fact, in Charleston County, South Carolina (one of the counties with the highest populations of slaves) the number of enslaved people in 1860 was only 63% of what it had been in 1840. This is not to say that the total number of slaves in the eastern seaboard states did not go up over time. But the number of enslaved people in a particular place did not grow at anything like the rate of free people in the north. The free population in the north both grew in the same place and spread to the west. The slave population had a different dynamic. It grew in intensity in places around the Chesapeake bay, even as slavery was gradually abolished in the North. But primarily the slave population spread to the fertile crescent of lands in Georgia, Alabama, and Mississippi, and most of all to the Mississippi River valley. Below you can see two animations of the density of the slave population and the density of the total population (keep in mind that the scales are different). What you see in these maps is the spread of slavery through the domestic slave trade.8 You also see the origins of the sectional crisis in the continual expansion of slavery.

An animation of the density of slave population from 1790 to 1860. Notice that slavery spreads more than it grows. Taken from the [interactive map][].
Figure 3: An animation of the density of slave population from 1790 to 1860. Notice that slavery spreads more than it grows. Taken from the interactive map. [GIF]
An animation of density of the total population from 1790 to 1860. Notice that population in the north both grows in place and spreads westward. Taken from the [interactive map][].
Figure 4: An animation of density of the total population from 1790 to 1860. Notice that population in the north both grows in place and spreads westward. Taken from the interactive map. [GIF]

Another observation to make about slavery in the United States is what an extraordinarily high percentage of the population was enslaved. The majority slave populations of the Chesapeake, the South Carolina and Georgia coast were soon duplicated in the majority slave populations of the Mississippi River valley.

An animation of the percentage of the population enslaved from 1790 to 1860. Taken from the [interactive map][].
Figure 5: An animation of the percentage of the population enslaved from 1790 to 1860. Taken from the interactive map. [GIF]

A striking way to see the importance of slavery is to look at a map of the total free population: a photo negative, if you will, of slavery. When looking at the density of the population that was free, large swathes of the South appear virtually depopulated. (Perhaps this is what a history book looks like that fails to take includes slaves?)

The population density of all free persons in 1860. Taken from the [interactive map][].
Figure 6: The population density of all free persons in 1860. Taken from the interactive map. [PNG]

Finally, the dynamics of the free African American population looked more like the free white population than the slave population. The Free African American population seems to have primarily settled along the Eastern seaboard and especially in the cities of the northern United States. Free African Americans were almost entirely excluded from most of the deep South, except the cities.

An animation of the free African American population from 1790 to 1860. Taken from the [interactive map][].
Figure 7: An animation of the free African American population from 1790 to 1860. Taken from the interactive map. [GIF]

Historians have long used maps of slavery to advance their arguments.9 I hope this map finds some use in making more arguments about the history of slavery, and especially for helping students to grasp the big picture of the “peculiar institution” which made the nation “half slave and half free.”10


  1. See Susan Schulten, Mapping the Nation: History and Cartography in Nineteenth-Century America (Chicago: University of Chicago Press, 2012), especially chapter 4 on slavery and statistical cartography. Also see the book’s companion website, which includes many images of maps of slavery.

  2. For one discussion of the problem of scale, see David Armitage and Jo Guldi. “Le Retour de la longue durée: Une perspective anglo-saxonne,” Annales, in press. Whatever the reason for the blockbuster success of Thomas Picketty’s Capital in the Twenty-First Century, it’s worth noting that the book is primarily a longue durée history of the structure of capital.

  3. I am grateful for suggestions from Yoni Appelbaum, John Hannigan, and Caleb McDaniel, who each looked at the map in development, though they will each find more things they wished were different.

  4. You might think of the visualization as 88 maps = 8 decades ✕ 11 variables.

  5. The map represents a lot of data, and I have not been able to make it snappy enough for my satisfaction, particularly for mobile devices. Hence the animated GIFs below.

  6. Of course there is far more to the history of slavery than just the Census data, which alone cannot answer any of the interpretative questions that historians have asked.

  7. This is remarkable given that in the Revolution many slaves escaped to or with the British army.

  8. Steven Deyle writes, “I believe it is safe to conclude that between 1820 and 1860 at least 875,000 American slaves were forcibly removed from the Upper South to the Lower South, and that between 60 and 70 percent of these individuals were transported via the interregional slave trade.” Steven Deyle, Carry Me Back: The Domestic Slave Trade in American Life (New York: Oxford University Press, 2005), 289.

  9. Perhaps I will provide a few examples in a future post.

  10. From Abraham Lincoln’s “House Divided” speech: “Either the opponents of slavery, will arrest the further spread of it, and place it where the public mind shall rest in the belief that it is in the course of ultimate extinction; or its advocates will push it forward, till it shall become alike lawful in all the States, old as well as new—North as well as South.”

Resources for Mapping US Boundaries Over Time

When making maps it’s not hard to find contemporary boundaries. The Census Bureau for the United States and Natural Earth for the rest of the world offer reliable shapefiles. Languages like R include packages which make accessing boundary data very easy. But when working on maps for history, using contemporary boundaries with historical data makes for glaring anachronisms. What I’ve wanted for research purposes are historical boundaries of the United States which include the changes for each year, and which I can trust because of the evidence of scholarship (e.g., citations) behind them. I also want these boundaries for teaching, so that geography can provide a backbone to the religious, cultural, social, and political changes I’m usually discussing. These are the sources that I’ve found with a few comments on their usefulness for research and teaching.

First, the single most useful resource that I’ve found is the Atlas of Historical County Boundaries from the Newberry Library. This atlas includes boundary files for states and territories from 1783 to 2000, and also for counties from 1629 to 2000. The boundaries are available as both shapefiles and KMZ files suitable for Google Earth. (I’ve found that it’s easier to get students up to speed using Google Earth than QGIS.) The boundary files are offered at various degrees of simplification, letting you pick between precision and file size without having to do the simplification yourself. For my purposes, the most important thing about the Newberry’s boundary data is that it comes in a single file. This means that you can more easily filter the boundaries by date, for example, in QGIS or D3. Making a complex map showing change over time gets a lot simpler when you can filter one file instead of having to merge many files. The maps come with impressive annotations, including citations for the boundaries for each feature, and discussions of what changed about the boundaries. The data is licensed CC-NC-SA. The Newberry Library also offers an online viewer for the files, which is clunky.1

Filtering the Newberry shapefiles to show the United States on January 1, 1851.
Figure 1: Filtering the Newberry shapefiles to show the United States on January 1, 1851. [PNG]

Second, Michael Porath has released a series of state- and territory-level shapefiles and GeoJSON files for 141 dates between March 4, 1789 and August 21, 1959. Porath writes, “All content for this visualization is taken verbatim from the original Wikipedia page Territorial evolution of the United States.” His shapefiles are especially useful if you want to make a map for a particular point in time, in which case you can just use the shapefile from the next earliest date. (Bonus: the shapefiles are available in a Git repository, and are licensed CC-SA.)

Porath has mapped the territorial changes himself in a project he calls “Manifest Destiny.” The many maps let you page through the territorial changes in the United States. For example, try paging through the maps which show the order in which southern states seceded from the Union in 1860–61. I can see how these maps could be used to good effect in the U.S. survey.

Michael Porath
Figure 2: Michael Porath’s maps displaying the United States on January 10, 1861. [PNG]

Third, the National Historical Geographic Information System offers state- and county-level shapefiles for each decade since 1790. The NHGIS shapefiles are meant for use with the historical census data offered by the NHGIS. Though I’ve used these shapefiles for general purpose mapping before,2 I can only recommend them for use when you are also using the NHGIS’s census data.3 The maps are only offered every decade, so many of the more interesting boundary changes are grouped together. The shapefiles have a peculiar projection, so for many uses you’ll have to re-project them.4 And the shapefiles are full resolution, so you’ll have to do the simplification yourself, which is tedious and error-prone. But to take advantage of the wealth of historical census data in the NHGIS, these shapefiles are quite useful.

Go forth and make maps without anachronism.


  1. I think the interface is provided by an ArcGIS web viewer.

  2. For mapping Catholic dioceses.

  3. As in this map of slavery in 1860.

  4. When I make maps in ggplot2, R sometimes chokes on fortified shapefiles that are not in EPSG 4326 or EPSG 3857, but otherwise does fine plotting and re-projecting the shapefiles itself.

The Two Purposes of Book Reviews

At the Anxious Bench, Thomas Kidd has a post titled “The Art of the Book Review.” Kidd argues:

When reviewing a book, be as charitable as possible. This is a “Golden Rule” issue. Once you’ve experienced the years of struggle behind producing a book, you should be cautious about casually dismissing the value of another author’s work. Even when I have major problems with a book, I try to praise it as much as I can, and include a few lines that a press could likely use to promote the book. …

It is certainly in-bounds to disagree with an author’s interpretation or ideological assumptions, of course. But do this in a polite way, as a means of discussion rather than denunciation.

I’d add that there are two kinds of book reviews: reviews that appear in professional, “serious” journals, and reviews that appear everywhere else. These reviews have entirely different purposes. When I get my copy of the American Historical Review or Church History, I browse the reviews for anything that is immediately interesting or relevant. But most of the time I come across reviews in journals through a search in JSTOR or some other database. In such cases I’m looking for reviews to find out the scholarly consensus about the worth of the book that has been established over time. And make no mistake, it takes time—years—for books to be reviewed in scholarly journals. I want those reviews to be the plainest possible explanation of what is good and bad about a book, perhaps even erring on the side of letting readers know where they could be mislead.

But plenty of reviews are published on blogs like Religion in American History, The Anxious Bench, and the S-USIH blog, as well as in general interest publications like magazines and newspapers. These reviews can be of the highest quality—for example, take Paul Putz’s recent review of Matthew Bowman’s The Urban Pulpit. But the purpose of these reviews is different. To borrow a phrase from Dan Cohen, their purpose is “catching the good.” When I read a review at one of these sites, I want the authors to alert me to the best books—books they’ve found useful for their research or teaching, or books that are a model of the historian’s craft. I can’t think of a reason why someone would publish a highly critical review in venues like those, especially since you get to pick what you review. If it’s a bad book, don’t bother reviewing it.

If you agree to write a review for a scholarly journal, then be as critical as you must, keeping in mind what Kidd writes about charity and generosity. But if you are writing a review for any other venue, find a book that’s good, and tell people about it.

A Better Map of Slavery in 1860

TL;DR I made a bad map of slavery, and there is a better map at the end of the post.

When I finished working the other night I tweeted the current state of the map of slavery that I had been making. Anthea Butler retweeted it, and then a lot of people saw it. (Not that many, but certainly more than will ever read the dissertation chapter the map is a part of.) I’m glad that people found the map interesting. But though there was nothing erroneous about the map, it certainly was not the best map of slavery possible. Here is the draft map:

Number of slaves by county in 1860 (quartile breaks)
Figure 1: Number of slaves by county in 1860 (quartile breaks) [PNG]

It’s easy to spot the biggest problem in that map: the values mapped to the colors are less than ideal. I suspect that most people who saw the map didn’t pay any attention to the legend at the bottom. And why should they have? Until I changed the numbers to a humanist-readable format the legend was almost incomprehensible. What the legend means is that the lightest yellow represents counties where there were 450 or fewer slaves living; the dark red represents counties where there were more than 5,380 slaves and fewer than 37,300 slaves.

Those numbers should give a reader pause: why should a county with 5,380 slaves be classified the same as a county with almost seven times as many slaves? The breaks in the first map are not arbitrary, but divide the counties into quartiles. That is, I ran a function which divided the counties into four even groups. This was a rough and ready way to classify the counties.

The trouble is that quartiles are not a particularly meaningful way to classify the counties. You might even argue—and this certainly wasn’t my intent—that it is a sensationalist way to classify the counties. By definition, using quartiles means that one-quarter of the counties on the map would be colored bright red. If this were a map of smokers, then one-fourth of the counties would be bright red; if it were a map of lung cancer, one-fourth of the counties would be bright red. That’s because when using quartiles, the breaks are determined by the count of the observations (i.e., the number of counties) rather than the value of the observations (i.e., the number of slaves in each county). Below is a histogram of the distribution of counties: you can see that a few counties had very large numbers of slaves, while most counties had relatively smaller numbers.

Histogram of number of slaves per county
Figure 2: Histogram of number of slaves per county [PNG, SVG, PDF]

But the question of how to categorize the counties is as much a historical question as it is a question for the techniques of data analysis. Though histories of slavery have often been written about large plantations where many slaves lived, historians have long known that many enslaved African Americans did not live on plantations, because most slaveholders owned only a few slaves. This is an important point, because the possibilities for slave culture and religion are very different on a farm with one or two enslaved African Americans than on a plantation with a hundred slaves. Below is a chart of the number of slaveholders by the number of slaves that they owned. 1 (Notice also how widespread slave ownership was: 395,216 slaveholders according to the 1860 census.)

Slaveholders by number of slaves owned in 1860
Figure 3: Slaveholders by number of slaves owned in 1860 [PNG, SVG, PDF]

What the charts of counties and slaveholders demonstrate is that dividing the counties into quartiles does not make for an accurate map. Fortunately there are better methods, in particular George Jenks’s algorithm for finding breaks in the data set. The Jenks method tries to make groups whose individual members are as close to each other as possible, but where each group in the aggregate is as much unlike the other groups as possible. Using that algorithm, we can divide the counties into more meaningful groups, as the chart below shows.

Histogram of slaves per county with breaks compared
Figure 4: Histogram of slaves per county with breaks compared [PNG, SVG, PDF]

Using the Jenks breaks, we get a much better map of where slaves lived in 1860. We can see all of the detail that was in the earlier map: the South’s fertile crescent through Virginia, North Carolina, South Carolina, George, Alabama, and Mississippi; the Mississippi, Missouri, and Tennessee river valleys; South Carolina as the state with the highest concentration of slaves. But this revised map has a higher resolution (if you will). We can now see cities like Washington, Charleston, Nashville, Mobile, and New Orleans—important since slavery must be understood in terms of slave markets, commodities markets, and capitalism. 2 The hinterland of slavery is also more clearly defined—important since the expansion of slavery was the issue in the sectional crisis. 3

Number of slaves by county in 1860 (Jenks breaks)
Figure 5: Number of slaves by county in 1860 (Jenks breaks) [PNG, SVG, PDF]

The lesson here is not that you should only make finished work public. But I hope that this look at the decisions that go into working with data demonstrates how a historian’s knowledge is more important than technological skill in making a historical map.


  1. In this case the categories come directly from the Census tables. As some people wrote to say, the proportion of African Americans in the total population is another way to measure this, but that’s the subject of another map.

  2. See Walter Johnson, Soul by Soul: Life Inside the Antebellum Slave Market (Cambridge, MA: Harvard University Press, 1999); Walter Johnson, River of Dark Dreams: Slavery and Empire in the Cotton Kingdom, 2013.

  3. The code and data for the map is on GitHub.