Currently, 24 people are confirmed dead after a tornado swept through Moore, Okla., on Monday, leaving devastation in its wake.
Nathan Phillips's insight:
Slate's Chris Kirk (@cperryk) mapped the locations, paths, and death tolls of each tornado that killed at least one person since 1950 in the U.S. I continue to be a bit confused by this map. When I've worked with young people while they read maps, I often ask them to talk about the map. What do they see? What do they understand? What makes sense? What doesn't? What questions do they have?
As a way of thinking about my confusion in reading this map as well as the possibilities for spatial analysis that are here, I'll try and produce that kind of a reading (answering the questions above). Here, then, is a bit of a close reading/think aloud from my reading of the map:
Kirk writes that the "area and transparency of each circle reflects the number of people killed." With a quick glance, it's easy to see the relative differences in circle size. Zooming into diferent circles and selecting them (by rolling over with the mouse) reveals three distinct data points for each tornado: date it occurred, Fujita scale score (which I understand as a relative measure of wind speeds), and number of people killed. The size of the circle does seem to correspond to the number of people killed, though Kirk doesn't include a key, so I'm not sure what the scale is or how to think about relative sizes at a glance. In other words, at a glance, I can't get an impression for an approximate number of deaths based on the size of the circle. With a key, I think it would be possible to do this.
But the real confusion for me comes with the use of transparency to reflect the number of people killed. I'm confused because I see almost no variation in the transparency. Again, without a legend, it's difficult to determine what scale Kirk might have in mind here or how he's shifting the relative transparency based on the number of deaths. But to my eye, I see almost no variation. The one exception to this is the 2011 Joplin, Missouri, tornado, in which 158 people were killed. The circle for this tornado is visibly less transparent than others on the map. At a glance, the circle for the 1953 tornado near Flint, Michigan, which killed 116 people, is also slightly darker than those around it.
As I've thought about the map since I first saw it, I realized one way in which relative transparency does reflect death toll: the layering of transparent circles over multiple events indicates areas of the United States in which tornadoes have been more deadly on aggregate over the last 60 years. For example, at a scale in which several states are visible (but not pulled all the way out), the area around Birmingham, Alabama, looks particularly dark due to the layering of circles. And zooming in confirms that this has been a deadly area over time. Over the last 60 years, about 150 people have died in this area from about 10 tornadoes.
One way in which I would like to be able to better read the map is to use the length of the tornado paths to think about the connection between length of path and death toll. Is there a connection? Using the map, it's hard to answer that question in any systematic way because looking at path lengths means zooming in quite closely. However, one argument seems clear: some storms have very long paths and kill very few people. Other storms have short paths and kill many more people. I suspect this is largely related to the population density of the area where the tornado hits--and this is something that's not represented at all on the map.
On February 13, the Spurs and Cavaliers were tied at 93 with about 15 seconds left in the game. Dion Waiters was dribbling near midcourt and about to
Nathan Phillips's insight:
As a Clevelander, this one isn't easy to share because part of Grantland's Kirk Goldsberry's (@kirkgoldsberry) analysis of Tony Parker focuses on a game in which the Spurs beat the Cavs because of Parker's great decision making. But...that's not the part that's interesting for "Maps Are Arguments." Goldsberry includes two shot charts for Parker. The first is in black and white and tells the story of the frequency and spatial distribution of Parker's shots. The second is in color and adds another variable--Parker's efficiency.
I love these kind of maps not only because I love sports, but also because Goldsberry's spatial analysis makes it possible to identify what's great about Tony Parker's game. Also, by first displaying only the black and white map and then following it with the color map (with the addition of a new variable), Goldsberry expertly scaffolds his readers in interpreting the maps and their relationship to his argument. For educators, like me, who are trying to figure out how to teach with maps and spatial analyses like these, Goldberry's piece is a great example.
Again, from the amazing UCL spatial analysis team (@edthink, @spatialanalysis, @oobr) and thanks to the real time Twitter data from @trendsmap comes this map of linguistic diversity, as represented by tweets in New York City over a three year period (January 2010 to February 2013). This is a different and new way to think about ethnic and racial diversity. How does the Twitter distribution compare to Census data? What do linguistically diverse tweets represent? It would be interesting to map conversations and connections over social media. In other words, who was on the other end of these tweets?
What's remarkable here is both the availability to display something like this thanks to publicly available and large data sets but also the new questions that arrise in thinking about what these data (and the data display) mean for learning across space and time.
We usually read weather maps--correctly--as displaying current conditions and/or short term predictions about upcoming weather patterns. This map from the National Climatic Data Center at NOAA (via @APHumanGeog's Seth Dixon) does something different: it displays the probability of a white Christmas (that is, snow on December 25) across the continental United States based on past weather patterns.
With Rogers Hall, Emily Shahan, Jennifer Kahn, and Emily's math literacies students, we've been thinking this semester about the mathematics behind data displays like these. How were these data generated? What do they mean? What is our impression, as readers, when we come across a thematic map like this?
The metaphor we've used to think about unpacking the mathematics is "dissection." If we dissect this data display, what can we determine about its constituent parts? What would young people need to know in order to read, make sense of, and act on a map like this? How is the mathematics more/less hidden here than when we're looking at a more traditional weather map? How do our expectations for the genre of "weather map" play into what we can read and understand with this map?
Thanks to Katie Taylor (@KayteeTaylor) for pointing me to this website: Neatline.org. The provide tools for creating web-based exhibits of maps with added narrative and thematic layers, what the site calls "interactive spatial and temporal interpretation." Unlike some of the thematic maps in my scoop.it collection, these aren't so much maps to explore; rather, they're methods for creating map arguments and as web-based, layered, narrative map performances.
Four years ago, Channel One News, the weekday news program for middle and high school kids featured a dynamic area cartogram as a way of making the point that some states have much more electoral weight than others. In that broadcast, the map of the United States, featuring the familiar red and blue states indicating presidential election results, became animated. States with smaller populations squeezed into tiny shapes, while states with large populations expanded. At the time, we didn't know this kind of map was called an area cartogram; we called it a "squishy map." It does a nice job of making this case: some states matter more than others when it comes to US presidential elections.
Seeing the map on Channel One also launched me into work that continues with my dissertation. What kind of sense do kids make from complex representations like an area cartogram? In the Channel One broadcast in 2008, the map was presented as part of a sensible lesson about "electoral weight." With Vanderbilt professors Rogers Hall and Kevin Leander, we wondered if the map made sense to kids and if the argument was strengthened by the map.
Four years later, I'm still working on those questions and others like them. In the mean time, here's another awesome area cartogram. In this case, NPR's "It's All Politics" blogger Adam Cole makes an argument about the advertisement spending of superPACs and other outside groups. Which states matter to these groups? And how much do they spend per voter on these ads? The squishy maps tell the story. Cole has a great video here as well--it's whimsical and informative. Finally, another move by Cole in these maps is the scaling of elections at the level of the state by popular vote. This means that states that are more contested turn purple (half blue and half red) rather than the color of the winning candidate from the last election.
From Slate.com, a map showing the ratio between median income of women and median income of men among men and women employed in 2010. There's a state-level map and a county-level map to explore.
Recently, I've been working with professors Rogers Hall and Emily Shahan and fellow doc student Jennifer Kahn on thinking about statistical analyses and data visualizations in popular media--"statistics in the wild." Emily's math literacies students--Master's and undergraduate pre-service teachers--have beeen looking for examples of presentations of stats in the wild and discussing the way these data visualizations are presented, understood, and might be used in K-12 settings.
This map seems to me a provocative example of our work and a map with real potential for discussion and dissection with students. As the comments to the article point out, there are lots of questions about what's behind this presentation and how the comparison between men and women is working. For example, the legend explains that the map shows "cents the average employed woman makes per $1 the average employed man makes." But how do we think about "average" employed people when the data come from median incomes? Does this map argue that women with equal experience and ability are being paid less than men for the same job? If not, what is it arguing? And how do we come to make sense of the argument?
Via Ollie: "James Cheshire, a geography lecturer at the University College London, mapped common surnames in London."
In this map from James Cheshire (@spatialanalysis), last names are mapped across London, with the most frequent last names for each section of the city listed and scaled by frequency. Additionally, names are colored by origin (e.g., English, Welsh, Pakistani, Greek, etc.). What's produced is a vision of the diversity of London and the segregation or integration of parts of the city as seen through last names.
This is a clip from the TV show West Wing (Season 2-Episode 16) where cartography plays a key role in the plot. In this episode the fictitious (but still on Facebook) group named "the Organization of Cartographers for Social Justice" is campaigning to have the President officially endorse the Gall-Peters Projection in schools and denounce the Mercator projection. The argument being that children will grow up thinking some places are not as important because they are minimized by the map projection. While a bit comical, the cartographic debate is quite informative even if it was designed to appear as though the issue was trivial.
Questions to Ponder: Why do map projections matter? Is one global map projection inherently better than the rest?
From Renee DiResta's No Upside comes this interactive map of questions about each state. DiResta entered "Why is [state] so..." into Google search and then included the top four autocomplete suggestions.
Mesmerizing clip. Bicycle routes by pizza delivery people (tracked by GPS) are displayed as blue dots moving through Manhattan leaving visible traces. Also visualized are the shipping routes of pizza ingredients. For educators, how do these mobilities and geographies help us and our students to think about our movements through space and time? What opportunities to learn are afforded by our movements and what resources for teaching and learning come to us through flows and streams of commerce, media, and people? Of course I'm indebted to my Space Learning and Mobility (SLaM) colleagues at Vanderbilt for helping me think about this. Check out our work at http://www.sci.sdsu.edu/tlcm. Related to this PBS clip, be sure to check out Katie Headrick Taylor's studies of youth mobility.
Navigate court maps and view analysis of every shot taken over the ’11-'12 season for the Miami Heat and Oklahoma City Thunder.
Who said geography has nothing to do with sports?!? While there are many cultural and economic impacts on sport preference and prevalence, let's discuss the geography of the hardwood and a spatial analysis of the shot selections between the two teams. Clearly 'place matters' to many NBA players as their success on the court depends on finding their preferred spots within the flow of offense.
Another great interactive thematic map from Slate. This one shows census response rates and majority political party supported by county. Seeing this makes me wonder, as always, what insights my high school students would have while checking out the map.
A great collection from Aleks Buczkowski (@abuczkowski) at Geoawesomeness (@geoawesomeness) of different web maps produced by news agencies depicting the path of the Oklahoma tornado. For educators, a comparative set like this makes possible close reading and analysis of the different possibilities when mapping. What do each of these maps show? What do they hide? What's the story of each map? What's the argument? How would they be different if we remixed them? How do mapmakers utilize satellite imagery in connection with street maps and thematic layers to tell this story of destruction and tragedy?
Reading these maps together can be more than an exercise in interpreting different storytelling/mapping methods; it can extend to an exercise in the possibilities for making spatial arguments and for remixing or producing maps to tell different stories.
What happens to a community with no "digital shadow" on the web?
Nathan Phillips's insight:
Thanks to @tyhollett for pointing me to this great read from @emilymbadger and @AtlanticCities about the inequities in our experiences with and of the "geoweb." Even better, the piece introduces the idea of the geoweb, the ephemeral but real digital data layers that sit atop the world we live in.
From the piece:
"All of this information, Graham stresses, doesn’t exist in some kind of virtual world that's separate from the real one. The two are intimately intertwined: We use digital information to navigate and understand the physical world, and in turn our experiences of place impact how we then contribute to the information about them."
My friend and fellow Vandy grad student, Ty Hollett (@tyhollett), has been thinking seriously about the geoweb and learning for a few years, and his thinking and work in connection with our research team's work (Kevin Leander and Rogers Hall leading) has focused most recently on bridging physical and virtual spaces for learning. How can we harness, engage with, and contribute to the geoweb in a way that supports learning for youth and all people? A key question is digital curatorship, which is one explanation for the different experiences of people interacting with the geoweb, as described in this article--when locations are curated digitally in linguistically or culturally diverse ways, how do we find and support those diversities for learning?
Ed Manley (UCL Geomatic Engineering) produced this great map of private hire vehicles in London (note my avoidance of the “T” word). He was able to obtain the GPS tracks...
Nathan Phillips's insight:
From Mapping London (http://mappinglondon.co.uk/): Ed Manley, a PhD student at University College London, created this map using GPS tracks from one company's cab drivers in London. Represented here are 700,000 journeys. The most popular routes are in red, followed by orange, yellow, white, and gray. Ed is able to make some analytic arguments about the map--I'm guessing other Londoners who knew the city would also be able to analyze the cab drivers' routes. For example, he notes that the most popular cab routes are in"stark contrast with respect to the flow of most traffic in London."
I can't make any analytic arguments becuase I don't know London's grid or typical traffic routes. For me, this map operates on a different level. I have an aesthetic reaction to the mesmerizing, organic nature of the map. And that reminds me of some of Katie Headrick Taylor's work. You can find Katie at @KayteeTaylor and also katieheadricktaylor.tumblr.com.
In one project that Katie led, she worked with youth to create GPS drawings in their neighborhoods. A GPS drawing is created in much the same way this map was made. "Drawers" travel (on foot or in a vehicle) with a GPS device that records track points at regular intervals and connects these into tracks--traces of where the person has been. Drawers intentionally walk routes that draw pictures or spell out words when the GPS tracks are revealed and laid on the map back at the computer. (For examples of amazing GPS drawings, see Jeremy Wood's work here: gpsdrawing.com.)
So getting back to the aesthetic response and what I learned from Katie's work: The youth that we worked with on this project wanted their drawings to work as aesthetic objects. They wanted to impress their friends with their ability to draw with sometimes technically challenging devices. And this leads to some questions as we think about the role of maps--and especially producing, analyzing, and responding to maps. What does it mean to want to represent my neighborhood by tracing something interesting, funny, or beautiful over top of it? For these youth, how did their relationships to the neighborhood change when they "wrote" words and drew images over their neighborhoods? How do Londoners react to this Manley map--how does it make them feel (differently) about their city?
Via the always amazing NY Times graphics folks comes this gem: a map depicting the shift in the electorate (to the right or left) state by state. What we see is a map that reminds me of the wind map (http://hint.fm/wind/), which shows, in real time, the movement of wind across the U.S.
In the NY Times political change map, movement to the right or left is depicted both as a color (the standard red and blue) but also as a distance by little flowing strands that wave across the landscape. I assume this is county by county data we're seeing. You can toggle between 2008 and 2012, which creates a very different political wind pattern.
The set of maps and graphics on this page also argue for other reasons that Mitt Romney lost the 2012 U.S. presidential election. The "Hispanic Voters Increase Support" map makes a case not only for an increase in support from Hispanic voters in Florida, but also for the impace of an increase in Hispanic population in the state from 2008 to 2011.
The Daily Beast's Andrew Sullivan said America was in a "cold civil war" on ABC News's "This Week," arguing that if current projections hold, Romney will entirely win the Confederacy. On the show, George Will disagreed. In this blog post, Sullivan includes the video clip and then drops a couple maps to make his point.
From Atlantic Cities, a complicated and layered argument about the geography of the finance industry after the fall of the economy. Atlantic Cities co-founder Richard Florida (@Richard_Florida) discusses three maps and determines that the geographical spread of financial centers is larger than one might have imagined and also that finance has grown in the wake of the financial crisis.
From Robert Krulwich's NPR blog comes a perfect example of what we might call an extended "map argument." Here, Krulwich starts with a political oddity: there's the band of Democtratic voting blue counties in a sea of Republican red that stretches through the Deep South. The perfect set up for a question: Why?
Krulwich, predictably, doesn't start where I might with the demographics of those counties. He gets there, but he goes back much much further in the history of the region to explain why it has ended up being a politically blue place. The reason: plankton 100 million years ago that left the region, millions of years later, with fertile soil. Slave-owning cotton farmers were most successful with their crops in these regions and so brought more slaves. After the Civil War, many former slaves stayed on this land and their families now make up large African-American populations in counties that voted for Obama (the band of blue).
What's impressive to me about Krulwich's argument is his use of maps, layered thematic maps--historical, geological, political, agricultural--to make this case. It operates similar to the "map performances" I've investigated from John King at CNN and with high school students, but in a different format--the blog.
Daniel Trone mapped Bruce Springsteen's 1500+ shows over 40 years, and Brian Timoney explains this "as a study in spatial diffusion--how phenomena such as innovation, fashion, or disease spread geographically." Trone maps not only the location of shows, but the "heat" they generate, which he calculates, according to Timoney, "as a function of the location of the show, the size of the venue, and inversely correlated with the overall population within 40km of the concert location" Springsteen's career seen this way is a story about growing a name in rock in a pre-internet era of word-of-mouth discussion of great bands and concerts. One of Timoney's arguments is that because Springsteen, when he was getting started, would play multiple shows in the same city over a number of nights, that made it possible for word of the music to spread from night to night and for new audiences to catch a show after hearing about Springsteen from a friend who had attended the night before. The argument here is also about how music spreads across the country and what prompts that kind of spread. For some brief commentary/thoughts on Trone's map and Timoney's arguments, see Josh Jones at Open Culture (http://bit.ly/S9SWPK), David Haglund at Slate (http://slate.me/SMpbEw), and Sarah Kliff on the Washington Post Wonkblog (http://wapo.st/R2tPtR). An interactive version of Trone's map is available here: http://maputopia.com/springsteen/. And the story behind the making of the map from Daniel Trone is available here: http://bit.ly/Ph9Jdr. ;
This is an amazing look at Google's efforts to "ground truth" their maps. While unlike other thematic maps I have posted here, this story helps us to see and think about the ways in which places are all imbued with information--information that can be represented digitally and that supports our movements through virtual and physical space. But not just our movements. And that's what I'm thinking most about in relationship to maps as arguments. Google is working to distribute collective intelligence across the map so that way finding and place finding are easier. But this same infrastructure could be used to layer thematic data that would express our collective beliefs, desires, hopes, and tragedies. We might move through the physical world and, using Google's map, see not only that Kentucky Fried Chicken is on the next corner and that the road curves slightly up ahead, but also that this part of the city has seen a dramatic reduction in crime, or an increase in youth civic involvement, or a recent shift in political affiliations, or an influx of talented musicians. How would this change the way we move through and interact with physical places?
In the latest awesomeness from Atlantic Cities, Richard Florida maps the concentration of musicians and music-related businesses. Some of the results might be surprising (but not the number one music scene: Nashville). Florida argues that clusters of talent lead to innovation.
I can remember when we were looking for homes in Nashville before moving here in 2007. In many homes we saw musical instruments and recording equipment--often one room would be dedicated to music production. I wonder if the concentration of musicians not only creates innovation but, in the words of London's Olympics theme, also inspires a generation of upcoming musicians.
From Seth Dixon: "Read more from Slate’s special issue on the future of food. Which counties, states, and countries have the biggest stake in food and its future? Look to these three maps to find out. Where do most farmers live? Which countries feed the world? Which states produce the highest crop value per capita? This series of interactive maps with data at a variety of scales will allow students to explore these questions. What to understand the spatial patterns of food production and the geographic factors behind agricultural variation? They are ripe for the picking."