kottke.org posts about maps
This interactive map shows where the 79 million people who have immigrated to the US from 1820 to 2013 came from. In the past, incoming residents from Canada, Italy, Germany, and Ireland were prevalent, but more recently Mexico, China, and the Philippines have led the way.
What I think is particularly interesting about immigration to the U.S. is that each “wave” coming in from a particular country has a story behind it — usually escaping persecution (e.g. Jews escaping Russia after the May Laws were enacted, the Cuban Revolution) or major economic troubles (e.g. the Irish Potato Famine, the collapse of southern Italy after the Italian Unification).
There are plenty of dark spots on United States’ history, but the role it has played as a sanctuary for troubled people across the world is a history I feel very proud to be a part of.
The graph of incoming immigrants as a percentage of the total US population is especially instructive. Though higher than it was in the 60s and 70s, relative immigration rates are still far below what the country saw in the 1920s and before.
Last year, Eleanor Lutz made a medieval-style map of Mars. As a follow-up, she’s made a topographical map of Venus. The features on Venus are named for female mythological figures & notable women and Lutz provides a small biography for each one on the map. Among those featured on the map are:
Selu (Cherokee Corn Goddess)
Kali (Hindu Goddess, Mother of Death)
Sedna (Eskimo Whose Fingers Became Seals and Whales)
Ubastet (Egyptian Cat Goddess)
Here are the full lists of the craters, mountains, and coronae on Venus.
From the New Yorker, Rebecca Solnit on how the world’s places are mostly named after men.
A horde of dead men with live identities haunt New York City and almost every city in the Western world. Their names are on the streets, buildings, parks, squares, colleges, businesses, and banks, and their figures are on the monuments. For example, at Fifty-ninth and Grand Army Plaza, right by the Pulitzer Fountain (for the newspaper magnate Joseph Pulitzer), is a pair of golden figures: General William Tecumseh Sherman on horseback and a woman leading him, who appears to be Victory and also a nameless no one in par-ticular. She is someone else’s victory.
The biggest statue in the city is a woman, who welcomes everyone and is no one: the Statue of Liberty, with that poem by Emma Lazarus at her feet, the one that few remember calls her “Mother of Exiles.” Statues of women are not uncommon, but they’re allegories and nobodies, mothers and muses and props but not Presidents.
For her book Nonstop Metropolis: A New York City Atlas, Solnit and her co-author Joshua Jelly-Schapiro commissioned Molly Roy to make a subway map of NYC that uses only the names of the city’s prominent women for the station names.
It’s a map that reflects the remarkable history of charismatic women who have shaped New York City from the beginning, such as the seventeenth-century Quaker preacher Hannah Feake Bowne, who is routinely written out of history — even the home in Flushing where she held meetings is often called the John Bowne house. Three of the four female Supreme Court justices have come from the city, and quite a bit of the history of American feminism has unfolded here, from Victoria Woodhull to Shirley Chisholm to the Guerrilla Girls.
In March 1933, a unified Germany held its last relatively free election before WWII. Hitler had already become Chancellor but he held one last election, seeking a mandate under which to rule. This map shows which areas of Germany supported the Nazi Party most strongly.
However, it’s also important to note that while the Nazis won the most seats in 1933, they did not win a majority of them or the popular vote.
Support varied widely across the country. It was highest in the former Prussian territories in the north-east of Germany (with the exception of Berlin) and much weaker in the west and south of the country, which had, up until 1871, been independent German states.
Across Germany as a whole, the Nazis won 43.91% of the popular vote and got 44.51% of the seats. This made them by far the largest party in the German Reichstag, but still without a clear majority mandate.
I know history doesn’t repeat itself, but this sure is rhyming like Kanye.
Martin O’Leary is a research scientist who studies glaciers, but in his spare time, he built Uncharted Atlas, a program that auto-generates maps of fantasy lands (like from Game of Thrones or LOTR) and posts them to a Twitter account. The explanation of how the terrain is generated is quite interesting and includes embedded map generators that you can play around with (i.e. prepare to lose about 20 minutes to this).
There are loads of articles on the internet which describe terrain generation, and they almost all use some variation on a fractal noise approach, either directly (by adding layers of noise functions), or indirectly (e.g. through midpoint displacement). These methods produce lots of fine detail, but the large-scale structure always looks a bit off. Features are attached in random ways, with no thought to the processes which form landscapes. I wanted to try something a little bit different.
There are a few different stages to the generator. First we build up a height-map of the terrain, and do things like routing water flow over the surface. Then we can render the ‘physical’ portion of the map. Finally we can place cities and ‘regions’ on the map, and place their labels.
And here’s how the languages for the place names are generated; each map has its own generated language so all of the place names are consistant with each other and different from those regions shown on other maps.
I wanted to produce something which was a step above the usual alphabetic soup of generated placenames, and which was capable of producing recognisably distinct languages. The initial idea was that different regions of each map would have different languages, but I abandoned this because it was too hard to make it clear that this was what was going on, while still having the languages themselves be interesting.
The problem is to generate something like what the constructed languages (conlang) community call a ‘naming language’. This is a light sketch of a language, focusing purely on the parts which are necessary to produce names. So there’s little to no grammar, but a good sense of what the language sounds like, and how it’s written.
This is a map showing where all of the characters originated in Homer’s epic poem The Iliad. I know Greece is small by today’s standards, but it was surprising to me how geographically widespread the hometowns of the characters were. The Iliad is set sometime in the 11th or 12th century BC, about 400 years before Homer lived. I wonder if that level of mobility was accurate for the time or if Homer simply populated his poem with folks from all over Greece as a way of making listeners from many areas feel connected to the story — sort of the “hello, Cleveland!” of its time. (thx, adriana)
Update: I’ve gotten lots of feedback saying that not every character is represented in this map (particularly the women) and that some of the locations and hometowns are incorrect. Seems like Wikipedia might need to take a second look at it.
Update: The map was made using the Catalogue of Ships, a list of Achaean ships that sailed to Troy, and the Trojan Catalogue, a list of battle contingents that fought for Troy. That’s why it’s incomplete. An excerpt:
Now will I tell the captains of the ships and the ships in their order. Of the Boeotians Peneleos and Leïtus were captains, and Arcesilaus and Prothoënor and Clonius; these were they that dwelt in Hyria and rocky Aulis and Schoenus and Scolus and Eteonus with its many ridges, Thespeia, Graea, and spacious Mycalessus; and that dwelt about Harma and Eilesium and Erythrae; and that held Eleon and Hyle and Peteon, Ocalea and Medeon, the well-built citadel, Copae, Eutresis, and Thisbe, the haunt of doves; that dwelt in Coroneia and grassy Haliartus, and that held Plataea and dwelt in Glisas; that held lower Thebe, the well-built citadel, and holy Onchestus, the bright grove of Poseidon; and that held Arne, rich in vines, and Mideia and sacred Nisa and Anthedon on the seaboard.
W.E.B. Du Bois was an American author, sociologist, historian, and activist. Apparently Du Bois was also a designer and design director of some talent as these hand-drawn infographics show.
In addition to an extensive collection of photographs, four volumes containing 400 official patents by African Americans, more than 200 books penned by African-American authors, various maps, and a statuette of Frederick Douglass, the exhibition featured a total of fifty-eight stunning hand-drawn charts (a selection of which we present below). Created by Du Bois and his students at Atlanta, the charts, many of which focus on economic life in Georgia, managed to condense an enormous amount of data into a set of aesthetically daring and easily digestible visualisations. As Alison Meier notes in Hyperallergic, “they’re strikingly vibrant and modern, almost anticipating the crossing lines of Piet Mondrian or the intersecting shapes of Wassily Kandinsky”.
Update: Oh, this is great: Mona Chalabi has updated Du Bois’ charts with current data.
Wealth. If I had stayed close to the original chart, the updated version would have shown that in 2015, African American households in Georgia had a median income of about $36,655, which would fail to capture the story of inflation (net asset numbers aren’t published as cumulative for one race). Instead, I wanted to see how wealth varies by race in America today.
The story is bleak. I hesitated to use the word “worth”, but it’s the language used by the Census Bureau when they’re collecting this data and, since money determines so much of an individual’s life, the word seems relevant. For every dollar a black household in America has in net assets, a white household has 16.5 more.
The Infatuation has an interactive map of the best places to get soup dumplings, fried dumplings, wontons, and all that good stuff in NYC, plus ordering recommendations for each place.
You could easily quibble with the list itself — the numbers 1-17 aren’t supposed to be rankings per se, but it starts with lower Manhattan, then gets to Flushing and Sunset Park, and that’s it. Still, the nice thing about a map interface is that you don’t need to worry about who’s number 1 and who’s number 10 quite so much when you’re just trying to find a place in a nearby neighborhood that can deliver the goods. (God, I miss New York.)
Update: I mistook the numbers in the map’s list view for rankings and was all grumpy about all the Chinatown places being ahead of the Queens ones. As it turns out, some of the places have number ratings, some don’t, and the list is more a geographic sequence than anything else.
At The Awl, Victoria Johnson fondly remembers the books of her youth that contained extra material. Like maps.
If I ruled the world, or at least a publishing company, all books would contain as much supplementary information as possible. Nonfiction, fiction — doesn’t matter. Every work would have an appendix filled with diagrams, background information, digressions and anecdata. And of course, maps. Lots and lots of maps.
The Hobbit, Winnie the Pooh, and The Wizard of Oz all included great maps that expanded the story in the mind of the reader. Near the end of the piece, Johnson notes that The Hunger Games didn’t include a map of Panem and links to this fan-drawn map (image here):
The Capitol is in Denver.
D12 is Appalachia.
D11 shares a border with D12, is one of the largest districts, is South of D12, and is primarily used for growing grain and produce.
D10 is primarily used for raising livestock. They do NOT process the livestock in D10. However, to feed an entire nation, D10 is likely another very large District.
D9 processes food for the Capitol and the tesserae; therefore, it likely shares borders with the food production Districts (D4, D10, D11).
D8 produces and treats textiles and is a factory District. It is POSSIBLE to reach D12 from D8 on foot over a course of weeks/months. Therefore, it does not cross a large body of water.
May the maps be ever in your books.
Artist Matthew Rangel hikes through what looks like some of the most beautiful terrain in the world and makes these cartographic drawings based on his experiences. Lovely work. (via @djacobs)
It’s that time of year again. No, not Christmas or Hanukkah. As the year winds down, it’s an opportunity for Americans to investigate how differently they use words in different parts of the country. In December 2013, for example, people lost their damn minds over the NY Times’ dialect quiz. This year, you can play around with The Great American Word Mapper which uses Twitter data from 2014 to plot geographic usage patterns.
For instance, you can see where people use “supper” vs. “dinner” (see above). The map indicates mixed usage where I grew up, which checks out…we mostly said “supper” but “dinner” was not uncommon, particularly as I got older. Other results are less useful…the Twitter-based “soda” vs. “coke” vs. “pop” doesn’t tell you as much as directly asking people what they call soft drinks.
The swearing maps are always fun (see also the United States of Swearing)…I wonder why “shit” is so relatively popular in the South?
Some other interesting searches: “moma” (alternate spelling of “momma” in the South with a small pocket of usage around NYC for MoMA), “city” doesn’t give the result you might expect, the distribution of “nigger” vs “nigga” suggests they are two different words with two different meanings, and in trying to find a search that would isolate just urban areas, the best I could come up with was “kanye” (or maybe “cocktails” or “traffic”). And harsh, map! Geez. (via @fromedome)
This is cool and a little mesmerizing: animated US maps showing the most popular baby name in each state from 1910 to 2014 for boys and girls. There are three separate visualizations. The first just shows the most popular baby name in each state. Watch as one dominant name takes over for another in just a couple of years…the Mary to Lisa to Jennifer transition in the 60s and 70s is like watching an epidemic spread. Celebrity names pop up and disappear, like Betty (after Betty Boop and Betty Grable?) and Shirley (after Shirley Temple) in the 30s. The boy’s names change a lot less until you start getting into the Brandons, Austins, and Tylers of the 90s.
The next visualization shows the most particularly popular name for each state, e.g. Brandy was the most Louisianan name for female newborns in 1975. And the third visualization shows each name plotted in the averaged geographical location of births — so you can see, for example, the northward migration of Amanda during the 80s.
P.S. Guess what the most popular boy’s name in the state of my birth was the year I was born? And the most particularly popular boy’s name in the state I moved to just a year later? Jason. I am basic af.
Update: From Flowing Data, some graphs of the most unisex names in US history. (thx, paul)
If you were a religious reader of the encyclopedia and peruser of atlases like I was as a kid, you’ll love this video of interesting facts about almost 100 countries. There’s another video coming next week that’ll highlight the rest of the world’s countries…I’ll feature it here when they post it.
Update: I’ve embedded part 2 below the first video.
In this video, physicist Dominic Walliman explains how all of the various disciplines of physics are related to each other by arranging them on a giant map. He starts with the three main areas — classical physics, quantum mechanics, and relativity — and then gets into the more specific subjects like optics, electromagnetism, and particle physics before venturing across The Chasm of Ignorance (dun dun DUN!) where things like string theory and dark matter dwell.
Posters of The Map of Physics are available.
Google has updated their Timelapse feature on Google Earth, allowing you to scrub satellite imagery from all over the globe back in forth in time.
This interactive experience enabled people to explore these changes like never before — to watch the sprouting of Dubai’s artificial Palm Islands, the retreat of Alaska’s Columbia Glacier, and the impressive urban expansion of Las Vegas, Nevada. Today, we’re making our largest update to Timelapse yet, with four additional years of imagery, petabytes of new data, and a sharper view of the Earth from 1984 to 2016.
A good way to experience some of the most compelling locations is through the YouTube playlist embedded above…just let it run for a few minutes. Some favorite videos are the circular farmland in Al Jowf, Saudi Arabia, the disappearing Aral Sea, the erosion of the Breton National Wildlife Refuge in Louisiana, the urban growth of Chongqing, China, the alarmingly quick retreat of Alaska’s Columbia Glacier, and this meandering river in Tibet.
A site called FamilyBreakFinder produced a world map with every country’s tourism slogan on it. A few of my favorite slogans:
Netherlands: The original cool
Colombia: Colombia is magical realism
El Salvador: The 45 minute country
Slovenia: I feel sLOVEnia
Cape Verde: No stress
Morocco: Much mor
Bhutan: Happiness is a place
India: Incredible !ndia
Some of these countries should ask their ad agencies for their money back. (via @ftrain)
The North American Cartographic Information Society has published the third volume of The Atlas of Design, a book consisting of “beautiful and inspiring maps from around the world”.
National Geographic took a look at some of the maps included in the book.
The striking panorama above of Denali and the Alaska Range was created by draping satellite imagery over a three-dimensional model of the terrain. Brooke Marston, a cartographer at the U.S. State Department’s Bureau of Intelligence and Research, was inspired by the Austrian artist Heinrich Berann, who is famed for his beautiful panoramas of mountain ranges.
While Berann took some artistic license with the precise location and positioning of mountains in his panoramas, Marston’s map is true to the geography. The oblique, bird’s-eye view emphasizes the sheer size of the mountains while maintaining a closeness with the viewer. “Good oblique mapping can transport the viewer straight into the landscape,” Elmer says. “This map makes me feel lost among the jagged, cold, majestic mountains just looking at it.”
The New York Times took a map of the US and split it in two based on areas that voted for Clinton and Trump in the 2016 election. (Clinton’s map is pictured above.)
Mrs. Clinton’s island nation has large atolls and small island chains with liberal cores, like college towns, Native American reservations and areas with black and Hispanic majorities. While the land area is small, the residents here voted for Mrs. Clinton in large enough numbers to make her the winner of the overall popular vote.
That’s fun, but it’s another reminder of how strictly geographical maps distort election results.
P.S. They missed a real opportunity to call the chain of islands in the southern states The Cretaceous Atoll.
From the American Museum of Natural History, an animated timeline map of human population growth from 100,000 BCE to the present.
It took 200,000 years for our population to reach 1 billion. And only 200 years to reach 7 billion.
Interesting to see that the only sustained decline in the world’s overall population over the past 2000 years was during the bubonic plague outbreak during the Middle Ages.
That’s a portion of the 2012 US Presidential election map of the southern states broken down by county: blue ones went Barack Obama’s way and counties in red voted for Mitt Romney.
But let’s go back to the Cretaceous Period, which lasted from 145 million years ago to 65 million years ago. Back then, the coastline of what is now North America looked like this:
Along that ancient coastline of a shallow sea, plankton with carbonate skeletons lived and died in massive numbers, accumulating into large chalk formations on the bottom of the sea. When the sea level dropped and the sea drained through the porous chalk, rich bands of soil were left right along the former coastline. When that area was settled and farmed in the 19th century, that rich soil was perfect for growing cotton. And cotton production was particularly profitable, so slaves were heavily used in those areas.
McClain, quoting from Booker T. Washington’s autobiography, Up From Slavery, points out: “The part of the country possessing this thick, dark and naturally rich soil was, of course, the part of the South where the slaves were most profitable, and consequently they were taken there in the largest numbers.” After the Civil War, a lot of former slaves stayed on this land, and while many migrated North, their families are still there.
The counties in which slave populations were highest before the Civil War are still home to large African American populations, which tend to vote for Democratic presidential candidates, even as the whiter counties around them vote for Republicans. The voting pattern of those counties on the map follows the Cretaceous coastline of 100 million years ago — the plankton fell, the cotton grew, the slaves bled into that rich soil, and their descendants later helped a black man reach the White House.
The Information is Beautiful Awards have announced the shortlist of nominees for the best infographics, data visualizations, and data journalism for 2016. Literally hours of exploration here. Some well-deserved shouts out to Polygraph (multiple projects, including their breakdown of film dialogue by gender and age), Nicholas Felton’s Photoviz, climate spirals, FiveThirtyEight’s 2016 election forecast map, and many other projects you might have seen here or elsewhere.
The images above are from Adventures in Mapping, Polygraph, and Shipmap.
As I remarked last year, the Smoky Mountains website has the best fall foliage map in the business. The map covers the entire US and comes with a slider that lets you check the status weekend by weekend throughout the fall. Looks like the foliage will peak near Sept 30th in VT and Oct 14th in NYC and in the Smoky Mountains.
In today’s installment of terrifying graphics about climate change, the NY Times made a series of three maps showing the potential rise of 100 degree temperatures across the United States if current greenhouse gas emission trends continue through the end of this century. Look at the areas in orange and red on the 1991-2010 map: what sort of landscape do you picture? Keeping that landscape picture in your mind, look at the orange and red areas on the 2060 and 2100 maps. Yep! And Phoenix with 163 days above 100 degrees — that’s every day from March 25th to September 4th over 100 degrees.
P.S. A word about climate change and rising temperatures. The temperature that climate scientists typically reference and care about with regard to climate change is “the average global temperature across land and ocean surface areas”. According to the NOAA, the average temperature of the Earth in the 20th century was 13.9°C (57.0°F). In 2015, the average global temperature was 0.90°C (1.62°F) above that.
In order to avoid dangerous effects of climate change, climate scientists advocate keeping the global average temperature increase below 2 degrees (and more recently, below 1.5 degrees). In late 2015, 195 nations came together in Paris and agreed to:
[Hold] the increase in the global average temperature to well below 2°C above pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5°C above pre-industrial levels, recognizing that this would significantly reduce the risks and impacts of climate change
That’s degrees Celsius, not Fahrenheit. I don’t know about you, but as an American, when I hear 2 degrees, I think, oh, that’s not bad. But 2°C is an increase of 3.6°F, which does seem significant.
Note also that it specifies keeping the temperature “below pre-industrial levels” and not below 20th century levels. It is maddeningly difficult to track down an exact figure for the pre-industrial global temperature, partially because of a lack of precise data, partially because of politics, and partially because of the impenetrability of scientific writing. From a piece Eric Holthaus wrote for FiveThirtyEight earlier this year:
It sounds easy enough to measure global warming: see how hot it was, compare it to how hot it used to be. But climate scientists have several ways of measuring how hot it used to be. NASA’s base period, as I mentioned above, is an average of 1951-80 global temperatures, mostly because that was the most recently available 30-year period when the data set was first created. By chance, it’s also pretty representative of the world’s 20th-century climate and can help us understand how much warmer the world has become while many of us have been alive.
Other organizations go further back. The Intergovernmental Panel on Climate Change, the body of climate scientists that was formed to provide assessments to the United Nations, bases its temperature calculations on an 1850-1900 global average. There was about 0.4 degrees of warming between that time period and the NASA base period.
Climate scientists often refer to that 1850-1900 timespan as “pre-industrial” because we don’t have comprehensive temperature data from the 1700s. But meteorologist Michael Mann, director of Penn State University’s Earth System Science Center, has argued that an additional 0.25 degrees of warming occurred between the start of the Industrial Revolution (around 1750) and 1850. Including Mann’s adjustment would bring February 2016 global temperatures at or very near 2 degrees above the “pre-industrial” average.
I now completely understand why some people deny that anthropogenic climate change is happening. Seriously. I looked for more than 30 minutes for a report or scientific paper that stated the average global temperature for 1850-1900 and I couldn’t find one. I looked at UN reports, NASA reports, reports from the UK: nothing. There were tons of references to temperatures relative to the 1850-1900 baseline, but no absolute temperatures were given. Now, I don’t mean to get all Feynman here, but this is bullshit. When the world got together in Paris and talked about a 1.5 degree increase, was everyone even talking about the same thing? You might begin to wonder what the scientists are hiding with their obfuscation.
Anyway, the important point is that according to climate scientists, we are already flirting with 1.5°C of global warming since pre-industrial times. Which means that without action, the spread of those Phoenician temperatures across the circa-2100 United States is a thing that’s going to happen.
Frodo (and Sam) made their way from Hobbiton to Mordor in six months and now you can see the route they took on Google Maps. “This route has trolls.” LOL. Full size image here. (via bb)
Update: From 2002, Mapquest directions for walking from Hobbiton to Mt Doom. (thx, seth)
The population of NYC is equal to the combined populations of Vermont, Alaska, New Mexico, North Dakota, South Dakota, Wyoming, Montana, and West Virginia. Here’s what that looks like on a map.
Put another way: 16 US Senators represent as many people in those states as a fraction of one of New York States’ Senators represent the population of NYC. A Senator from Wyoming represents 290,000 people while one from New York represents 9.8 million people…and in California, there are 19 million people per Senator. That gives a Wyoming resident 65 times the voting power of a California resident.
Since 1963, Jerry Gretzinger has been working on a map of a world that doesn’t exist. The map is never finished. In the morning, when Gretzinger draws a card out of the deck that sets his task for the day, sometimes that card says “scan”. That means a portion of the map is scanned and archived, and the copy is reworked to “upgrade” that part of the map. And that’s not even the half of it…just watch the whole thing to see how the map has evolved over the years.
It now comprises over 3200 individual eight by ten inch panels. Its execution, in acrylic, marker, colored pencil, ink, collage, and inkjet print on heavy paper, is dictated by the interplay between an elaborate set of rules and randomly generated instructions.
Portions of the map have been shown in Florence, Paris, and New York and it’ll be shown at an upcoming exhibition in Japan. (But where he really wants to display it is in MoMA’s huge atrium.) Prints and original panels are available on Gretzinger’s eBay store. (via @lukaskulas)
One of the most popular map projections of the world is the Mercator projection:
It’s useful but misleading in important ways. With the the True Size Map, you can drag countries and continents around a Mercator map to uncover their true sizes. For example, it may not be apparent on a Mercator map that Australia is about the same size as the lower 48 US states (see above). Or that Africa is much larger than it seems on the map:
Or is it that North America is oversized on the map? Greenland certainly is. Its true size becomes more clear when you overlay it on India:
Mercator’s been around for hundreds of years, so luckily cartographers have invented dozens of other ways to visualize the world in 2D, each of which have their own strengths and disadvantages. You can view many of them here.
Update: I had somehow forgotten about this great scene from The West Wing discussing the geographic bias of the Mercator map:
(thx to the many who reminded me)
According to the first national election forecast by FiveThirtyEight, Hillary Clinton has an 80.3% chance of winning the Presidency.
A 20% Trump chance is waaaaay too close for my comfort…that’s better odds than ending up dead playing one round of Russian roulette. We gotta Mondale that Cheeto-faced shitgibbon.
From Clive Thompson, a history of the infographic, which was developed in part to help solve problems with an abundance of data available in the 19th century.
The idea of visualizing data is old: After all, that’s what a map is — a representation of geographic information — and we’ve had maps for about 8,000 years. But it was rare to graph anything other than geography. Only a few examples exist: Around the 11th century, a now-anonymous scribe created a chart of how the planets moved through the sky. By the 18th century, scientists were warming to the idea of arranging knowledge visually. The British polymath Joseph Priestley produced a “Chart of Biography,” plotting the lives of about 2,000 historical figures on a timeline. A picture, he argued, conveyed the information “with more exactness, and in much less time, than it [would take] by reading.”
Still, data visualization was rare because data was rare. That began to change rapidly in the early 19th century, because countries began to collect-and publish-reams of information about their weather, economic activity and population. “For the first time, you could deal with important social issues with hard facts, if you could find a way to analyze it,” says Michael Friendly, a professor of psychology at York University who studies the history of data visualization. “The age of data really began.”