Exploring Data Visualization #14

In this monthly series, I share a combination of cool data visualizations, useful tools and resources, and other visualization miscellany. The field of data visualization is full of experts who publish insights in books and on blogs, and I’ll be using this series to introduce you to a few of them. You can find previous posts by looking at the Exploring Data Visualization tag.

A day in the life of Americans: a data comic

A comic demonstrating the amount of time Americans spend sleeping, at work, free, or doing other activities from 4 a.m. to 3 p.m.

By illustrating the activity most Americans are doing at a given hour, Hong highlights what the average day looks like for an American worker.

Happy May, researchers! With the semester winding down and summer plans on the horizon, a lot of us are reflecting on what we’ve done in the past year. Sometimes it can be hard to determine what your daily routine looks like when you are the one doing it every day. Matt Hong created a cute and informative data comic about how we spend our time during the day, based on data from the Census Bureau. Check out Hong’s Medium page for more data comics.

What Qualifies as Middle-Income in Each State

A bar chart that shows the range of incomes that qualify as "middle-income" for households made up of four people, organized by state.

The distribution of middle-income for households made up of four people.

Nathan Yau at Flowing Data created an interesting chart that shows the range of income that is considered “middle-income” in each state and the District of Columbia in the United States. The design of the chart itself is smooth and watching the transitions between income ranges based on number of people in the household is very enjoyable. It is also enlightening to see where states fall on the spectrum of what “middle-income” means, and this visualization could be a useful tool for researchers working on wage disparity.

When People Find a New Job

A frequency trail chart that shows peaks based on the age when people change jobs.

The bottom of the chart shows jobs that people transition into later in life.

The end of the semester also means a wave of new graduates entering the workforce. While we extend our congratulations to those people, we often inquire about what their upcoming plans are and where they will be working in the future. For some, that question is straightforward; for others, a change of pace may be on the horizon. Nathan Yau of Flowing Data also created a frequency trail chart that shows at what age many people change career paths. As Yau demonstrates in a bar chart that accompanies the frequency trail chart, the majority of job switches happen early and late in life, a phenomenon which he offers some suggestions for.

A bar chart showing the distribution of the age at which people switch jobs. 15-19 is the highest percent (above 30%) and 55-64 is the lowest (around 10%)

The peak at the “older” end of the chart indicates some changes post-retirement, but also makes you wonder why people are still finding new jobs at age 85 to 89.

I hope you enjoyed this data visualization news! If you have any data visualization questions, please feel free to email the Scholarly Commons.

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Our Graduate Assistants: Michael Tahmasian

This interview is part of a new series introducing our graduate assistants to our online community. These are some of the people you will see when you visit our space, who will greet you with a smile and a willingness to help! Say hello to Michael Tahmasian!

What is your background education and work experience?

I have Bachelor’s degree in English from the University of Kansas and for a long time I had no idea what I wanted to do with that. After finishing my undergraduate degree, I moved with a friend to Chicago for “the next big adventure.” At first, I was a security guard at an art museum. Then I was a substitute teacher in the public schools. Eventually, I ended up as a CyberNavigator in two different branches of the Chicago Public Library, where I worked with patrons to help build their digital skills.

What led you to your field?

I’ve always loved teaching people things, but I struggled to see myself teaching in a traditional classroom. It just never felt right for me. When I finally realized the huge role that instruction played in librarianship—in small moments at the reference desk or through programming and workshops—everything clicked for me. I could see myself as a part of that space. There are so few places people can go to these days to get help learn new things without having to give something in return. I’m truly so excited to be a part of that.

What are your research interests?

My main area of interest is instruction, but to me that includes both those formal and informal settings; both workshops and one-off questions at a reference desk. Currently, I’m interested in how feminist theories can help us understand and improve instruction in both places. Our profession is focused on helping people get the information they need—and while I believe in that I think sometimes we lose sight of the people we’re supposed to help and focus solely on the information itself. Feminist theories allow us to challenge our field’s traditional values and focus on the people involved, patrons and librarians alike. These theories help us highlight the often-overlooked effective aspects of librarianship and the amount of emotional labor that goes into it. Not only do I think that this work should be acknowledged and celebrated, but I believe effective qualities like empathy need to be fostered within librarians through education and training. I think how we work with patrons and students is just as important as the content we’re trying to teach them and empathy is integral to that, understanding their emotional processes in using the library is integral to that. So really I’m interested in exploring how empathy and something like the ethics of care can be incorporated not only into our instruction at the desk or in the classroom, but also in the training of librarians.

What are your favorite projects you’ve worked on?

My ongoing work in the Scholarly Commons revolves around undergraduate research here at the University of Illinois, which has taught me so much about collaboration between academic libraries and other units across campus. I’ve worked a lot on managing intake of undergraduate research work into IDEALS, our institution’s digital repository, and creating education materials around that for both students and faculty.

Additionally, I was able to spend time over the year designing and piloting a workshop on editing podcasts with the software Audacity. The workshop served as a collaboration between the Scholarly Commons’ Savvy Researcher workshop series and the Media Commons in the Undergraduate Library. It was a wonderful chance to learn about designing a workshop and the challenges that come with that, especially one so focused on technology. The process challenged me to think about the availability of the technology and how we could work with what we had; the role attendees of the workshop would have in actively contributing to their own learning; the accessibility of my lesson and materials; and, how to market it all. Getting to test it out this spring was incredibly rewarding. Overall it went really well and I was excited to get feedback to help improve it for the next time around!

What are some of your favorite underutilized resources that you would recommend?

My favorite underutilized resource in the Scholarly Commons might be the space itself! Although this will change sometime in the future, right now we’re tucked away on the third floor of the Main Library. I think people who use the space genuinely love it—we have a lot of regulars. The space is really open for people to make what they want of it. If they need a quiet hideaway, this is great. If they need a place to work collaborate with others, there’s room for that too. Physically being in the space also allows people to see some of our other available resources—like our specialized software or our collection of books on data, programming, and research.

When you graduate, what would your ideal job position look like?

After graduation I am hoping to work as a Reference and Instruction Librarian in an academic library. I just want to be able to keep teaching people things, keep learning things myself, and be comfortable enough wherever I end up to finally adopt a dog. That’s the dream.

What is the one thing you would want people to know about your field?

You should never feel bad asking a librarian a question! I know it can feel awkward or weird, I’ve felt it too and I work in libraries. But librarians truly just want to help you with your problems, no matter how big or small. Stop by, give us a call, or chat with us online! We’re here for you

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Exploring Data Visualization #13

In this monthly series, I share a combination of cool data visualizations, useful tools and resources, and other visualization miscellany. The field of data visualization is full of experts who publish insights in books and on blogs, and I’ll be using this series to introduce you to a few of them. You can find previous posts by looking at the Exploring Data Visualization tag.

One Way to Spot a Partisan Gerrymander

Even though it feels like it was 2016 yesterday, we are more than a quarter of the way through 2019 and the 2020 political cycle is starting to heat up. A common issue in the minds of voters and politicians is fraudulent and rigged elections—voters increasingly wonder if their votes really matter in the current political landscape. Last week, the Supreme Court heard two cases on partisan gerrymandering in North Carolina and Maryland. FiveThirtyEight made an elegant visualization about gerrymandering in North Carolina. The visualization demonstrates how actual election outcomes can be used to extrapolate what percentage of seats will go to each party.

A graph that shows the Average Democratic vote share in the U.S. House plotted against the actual outcome. A pink line represents the average outcome and since it does not pass through (0, 0), that indicates partisan bias in the House election being studied.

If there is no partisan bias in voting districts, the outcome should be 50/50.

As you scroll, the chart continues to develop and become more complicated. It adds results from past elections to contextualize the severity of the current problems with gerrymandering. It also provides an example of the outcomes of a redrawn district map in Pennsylvania.

Mistakes, we’ve drawn a few

Two different charts that both represent attitudes in the UK toward Britain voting to leave the EU. The chart on the left is a sine chart which looks erratic while the chart on the right shows the averages of plotted lines and demonstrates clear trends.

The change from line chart to plotted points better demonstrates the trend of the attitudes toward Brexit.

Sarah Leo from The Economist re-creates past visualizations from the publication that were misleading or poorly designed. The blog post calls out the mistakes made very effectively and offers redesigns, when possible. They also make their data available after each visualization.

Seeing two visualizations of the same data next to one another really helps drive home how data can be represented differently–and how that causes different impacts upon a reader.

FastCharts

The Financial Times has made an online version of their quick chart-making tool available for the public. Appropriately titled FastCharts, the site lets you upload your own data or play around with sample data they have provided. Because this tool is so simple, it seems like it would be useful for exploratory data, but maybe not for creating more complex explanations of your data.

The interface of FastCharts, showing a line chart of global temperature anomalies from 1850 to 2017.

FastCharts automatically selects which type of chart it thinks will work best for your data.

Play with the provided example data or use your own data to produce an interesting result! For a challenge, see if any of the data in our Numeric Data Library Guide can work for this tool.

I hope you enjoyed this data visualization news! If you have any data visualization questions, please feel free to email the Scholarly Commons.

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Digital Humanities Maps

Historically, maps were 2D, printed, sometimes wildly inaccurate representations of space. Today, maps can still be wildly inaccurate, but digital tools provide a way to apply more data to a spatial representation. However, displaying data on a map is not a completely new idea. W.E.B. DuBois’ 1899 sociological research study “The Philadelphia Negro” was one of the first to present data in a visual format, both in map form and other forms.

map of the seventh ward of philadelphia, each household is drawn on the map and represented by a color corresponding to class standing

The colors on the map indicate the class standing of each household.

Digital maps can add an interesting, spatial dimension to your humanities or social science research. People respond well to visuals, and maps provide a way to display a visual that corresponds to real-life space. Today we’ll highlight some DH mapping projects, and point to some resources to create your own map!

(If you are interested in DH maps, attend our Mapping in the Humanities workshop next week!)

Sources of Digital Maps

Some sources of historical maps, like the ones below, openly provide access to georeferenced maps. “Georeferencing,” also called “georectifying,” is the process of aligning historical maps to precisely match a modern-day map. Completing this process allows historical maps to be used in digital tools, like GIS software. Think of it like taking an image of a map, and assigning latitude/longitude pairs to different points on the map that correspond to modern maps. Currently, manually matching the points up is the only way to do this!

A map from a book about Chicago placed over a modern map of Chicago.

A map of Chicago from 1891 overlaid on a modern map of the Chicago area.

David Rumsey Map Collection
The David Rumsey Map Collection is a mainstay in the world of historical maps. As of the time of writing, 68% of their total map collection has been georeferenced. There are other ways to interact with the collection, such as searching on a map for specific locations, or even viewing the maps in Second Life!

NYPL Map Warper
The New York Public Library’s Map Warper offers a large collection of historical maps georeferenced by users. Most maps have been georeferenced at this point, but users can still help out!

OpenStreetMap
OpenStreetMap is the open-source, non-proprietary version of Google Maps. Many tools used in DH, like Leaflet and Omeka’s Neatline, use OpenStreetMap’s data and applications to create maps.

Digital Mapping Humanities Projects

Get inspired! Here are some DH mapping projects to help you think about applying mapping to your own research.

Maps provide the perfect medium for DH projects focused on social justice and decolonization. Native-land.ca is a fairly recent example of this application. The project, started as a non-academic, private project in 2015, has now transformed into a not-for-profit organization. Native-land.ca attempts to visualize land belonging to native nations in the Americas and Australia, but notably not following the official or legal boundaries. The project also provides a teacher’s guide to assist developing a curriculum around colonization in schools.

map of florida with data overlay indicating which native tribes have rights to the land

The state of Florida occupies the territory of multiple native tribes, notably those of the Seminole.

Other projects use digital tools that show a map in conjunction with another storytelling tool, like a timeline or a narrative. The levantCarta/Beirut project uses a timeline to filter which images show up on the connected map of Beirut. We can easily see the spatial representation of a place in a temporal context. A fairly easy tool for this kind of digital storytelling is TimeMapper.

For a more meta example, check out this map of digital humanities labs by Urszula Pawlicka-Deger. Of course these DH centers do projects other than mapping, but even the study of DH can make use of digital mapping!

If you’re interested in adding maps to your humanities research, check out our workshop this semester on humanities mapping. There are also great tutorials for more advanced mapping on The Programming Historian.

And as always, feel free to reach out to the Scholarly Commons (sc@library.illinois.edu) to get started on your digital humanities project.

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2019-2020 Research Travel Grant!

Are you a researcher that needs very specific resources? Are you interested in working with the University of Illinois at Urbana-Champaign library’s vast collections? You are in luck!

A call for applications for the 2019-2020 Research Travel Grant have just opened! If you are a scholar at the graduate and post-doctoral level, you have until may 1st, 2019, to apply!

You will need to send a project proposal (no more than three pages) which clearly highlights how the work at the UIUC Library is part of your ongoing or future research, along with an updated CV, and a letter of recommendation from a local scholar in a relevant academic department of the University of Illinois at Urbana-Champaign.

But what types of materials could researchers take advantage of through our library? Well, in our nearly 14-million volume collection, there is wide variety!

One of our featured collections is the Audubon Folio. This piece was originally bought for one thousand dollars, and is one of 134 that remain intact.  With the original standing three feet tall, and weighing fifty-pounds, pieces facsimile copy the university library owns is on display outside the Literature and Languages Library.

Plate 217, the Louisiana Heron

The International and Area Studies library also has an impressive collection of South Asian comics. More than 1,600 of these comics are from India, with the library’s comic collection reaching nearly 10,000 titles in more than a dozen languages.

Comic Cover from Indrajal Comics Online

And there are so many more collections at the library!

The James Collins Irish Collection is “devoted to Irish history and culture, and includes 139 volumes of bound pamphlets, as well as 2,500 unbound pieces”, entire works and pieces from 127 volumes of newspaper clippings, political cartoons, and more! The library has collection ranging from the Spanish Golden Age to American Wit and Humor.

We certainly hoped we’ve sparked your interest in our vast collection! And check out even more pieces of our distinct collections here!

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Exploring Data Visualization #12

In this monthly series, I share a combination of cool data visualizations, useful tools and resources, and other visualization miscellany. The field of data visualization is full of experts who publish insights in books and on blogs, and I’ll be using this series to introduce you to a few of them. You can find previous posts by looking at the Exploring Data Visualization tag.

American segregation, mapped day and night

Is segregation in the United States improving? And if it is, what race sees the most people of different races? And do the answers to these questions change based on the time of day? Vox sets out to answer some of these questions through a video essay and an interactive map about segregation in the United States cities at work and at home.

A map of Champaign County showing data peaks where the highest population of Black people live.

This map shows the population density of Black people living in Champaign-Urbana, IL. The brighter the pink, the higher the percentage of Black people living only near Black people.

A map showing the areas in Champaign County populated by white people.

This map shows the population density of white people living in Champaign-Urbana, IL. The brighter the pink, the higher the percentage of white people living only near white people.

The map is interesting and effectively demonstrates the continued presence of segregation in communities across the United States. However, there is little detail on the map about the geographical features of the region being examined. This isn’t too much of a problem if you are familiar with the region you are looking at, but for more unfamiliar communities it leads to more questions than it answers.

NASA’s Opportunity Rover Dies on Mars

 

After 15 years on Mars, the Opportunity Rover Mission was officially declared finished on February 13th, 2019. The New York Times created a visualization that lets you follow Opportunity’s 28 mile path across the surface of Mars, which includes a bird’s eye view of Oppy’s path as well as images sent by the rover back to NASA. Opportunity was responsible for discovering evidence of drinkable water on Mars.

A map of the surface of mars with a yellow line showing the path of NASA's Opportunity rover. There is a small image in the corner of Santa Maria Crater taken by the rover.

The map of Opportunity’s path is accompanied by images from the rover and artists’ renderings of the surface of Mars.

The periodic table is a scatterplot. (Among others.)

 

The periodic table: a data visualization familiar to anyone who has ever set foot in a grade school science classroom. As Lisa Rost points out, the periodic table is actually just a simple scatter plot, with group as the x-axis and period as the y-axis. Or at least, that’s true of the Mendeleev periodic table, the one we are most familiar with. See some other examples of how to break down the periodic table on Rost’s post, which links to the Wikipedia article on alternative periodic tables. If you find a favorite, be sure to tweet it to us @ScholCommons! We are always curious to see what visualizations get people excited.

A visualization of the periodic table of the elements with the elements represented by different colored dots. The dot colors correspond to when in time the elements were discovered, which is coded in a key at the top of the chart. Yellow is before Mendeleev, blue is after Mendeleev, orange is BC, and black is since 2000.

A periodic table color coded by Lisa Rost to show when in time different elements where discovered.

I hope you enjoyed this data visualization news! If you have any data visualization questions, please feel free to email the Scholarly Commons.

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Transformation in Digital Humanities

The opinions presented in this piece are solely the author’s and referenced authors. This is meant to serve as a synthesis of arguments made in DH regarding transformation.

How do data and algorithms affect our lives? How does technology affect our humanity? Scholars and researchers in the digital humanities (DH) ask questions about how we can use DH to enact social change by making observations of the world around us. This kind of work is often called “transformative DH.”

The idea of transformative DH is an ongoing conversation. As Moya Bailey wrote in 2011, scholars’ experiences and identities affect and inform their theories and practices, which allows them to make worthwhile observations in diverse areas of humanities scholarship. Just as there is strong conflict about how DH itself is defined, there is also conflict regarding whether or not DH needs to be “transformed.” The theme of the 2011 Annual DH Conference held at Stanford was “Big Tent Digital Humanities,” a phrase symbolizing the welcoming nature of the DH field as a space for interdisciplinary scholarship. Still, those on the fringes found themselves unwelcome, or at least unacknowledged.

This conversation around what DH is and what it could be exploded at the Modern Languages Association (MLA) Convention in 2011, which featured multiple digital humanities and digital pedagogy sessions aimed at defining the field and what “counts” as DH. During the convention Stephen Ramsay, in a talk boldly title “Who’s In and Who’s Out,” stated that all digital humanists must code in order to be considered a digital humanist (he later softened “code” to “build”). These comments resulted in ongoing conversations online about gatekeeping in DH, which refer to both what work counts as DH and who counts as a DHer or digital humanist. Moya Bailey also noted certain that scholars whose work focused on race, gender, or queerness and relationships with technology were “doing intersectional digital humanities work in all but name.” This work, however, was not acknowledged as digital humanities.

logo

Website Banner from transformdh.org

To address gatekeeping in the DH community more fully, the group #transformDH was formed in 2011, during this intense period of conversation and attempts at defining. The group self-describes as an “academic guerrilla movement” aimed at re-defining DH as a tool for transformative, social justice scholarship. Their primary objective is to create space in the DH world for projects that push beyond traditional humanities research with digital tools. To achieve this, they encourage and create projects that have the ability to enact social change and bring conversations on race, gender, sexuality, and class into both the academy and the public consciousness. An excellent example of this ideology is the Torn Apart/Separados project, a rapid response DH project completed in response to the United States enacting a “Zero Tolerance Policy” for immigrants attempting to cross the US/Mexico border. In order to visualize the reach and resources of ICE (those enforcing this policy), a cohort of scholars, programmers, and data scientists banded together and published this project in a matter of weeks. Projects such as these demonstrate the potential of DH as a tool for transformative scholarship and to enact social change. The potential becomes dangerously disregarded when we set limits on who counts as a digital humanist and what counts as digital humanities work.

For further, in-depth reading on this topic, check out the articles below.

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February Push!

Hello, researchers!

Congratulations! You made it through your first month back of the spring semester. From class work, to pouring rain, to enough snow and ice and make the university look like it’s auditioning for a role as Antarctica, you’re pushing forward!

A dual-monitor computer in the Scholarly Commons. The background of the image shows the Scholarly Commons space, which is filled with out dual-monitor computers and various desks.

Take a minute to look over all the awesome resources we have, right here in the Scholarly Commons, to help you keep chugging along with your research.

We are open 8:30 a.m. to 6 p.m., Monday through Friday. Our various, dual monitor computers have software ranging from Adobe Photoshop to OCR which can be paired with our various scanners to make machine readable PDFs!

The Scholarly Commons space. A desk with a computer and a sign reading "Scholarly Commons" is shown.

Researchers can book free consultations thanks to our partnerships with CITL Data Analytics and Technology Services! In these meetings, you can learn about R, SAS, and everything else you need to just get started or to get past that tricky problem in your statistical research.

Beyond that, users can make appoints with our GIS specialist, and learn even more through our GIS resources. We have a ton of great books in our non-circulating reference collection that can help you learn about Python, GIS, and more!

The Scholarly Common reference collection. Six shelves filled with books.

 

And that’s not all: our Data Analytics & Visualization Librarian has put together a plethora of resources to help turn your data into art. Check out the four most common types of charts guide to get started!

The Scholarly Commons space. it contains several workstations with a carpeted floor.

And even this doesn’t cover all of our services!

If you need assistance finding numeric data, understanding your copyrights, cleaning up data in OpenRefine, or even starting up a project using text mining, we have the resources you need.

The Scholarly Commons has all the resources you need to succeed, so stop by anytime! We’re always happy to help.

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Exploring Data Visualization #11

 In this monthly series, I share a combination of cool data visualizations, useful tools and resources, and other visualization miscellany. The field of data visualization is full of experts who publish insights in books and on blogs, and I’ll be using this series to introduce you to a few of them. You can find previous posts by looking at the Exploring Data Visualization tag.

Data Visualization Office Hours and Workshops

A headshot of Megan Ozeran with a border above her reading Data Viz Help and a banner below that reads The Librarian is In

Our amazing Data Visualization Librarian Megan Ozeran is holding open office hours every other Monday for the Spring 2019 semester! Drop by the Scholarly Commons from 2-4 on any of the dates listed below to ask any data viz questions you might have.

Office hours on: February 25, March 11, March 25, April 8, April 22, and May 6.

Additionally, Megan will teach a joint workshop as part of our Savvy Researcher series titled “Network Analysis in Digital Humanities” on Thursday, March 7th. Megan and SC GA Kayla Abner will cover the basics of how to use NodeXL, Palladio, and Cytoscape to show relationships between concepts in your research. Register online on our Savvy Researcher Calendar!

Lifespan of News Stories

A chart showing the search interest for different news stories in October 2018, represented as colored peaks with the apex labeled with a world event.

October was one of the busier times of the year, with eight overlapping news stories. Hurricane Michael tied with Hurricane Florence for the largest number of searches in 2018.

According to trends compiled by the news site Axios, “news cycles for some of the biggest moments of 2018 only lasted for a median of 7 days.” Axios put together a timeline of the year which shows the peaks and valleys of 49 of the top news stories from 2018. A simplified view of the year in the article “What captured America’s attention in 2018” shows the distribution of those 49 stories, while a full site, “The Lifespan of News Stories,” shows search interest by region and links to an article from Axios about the event (clever advertising on their part).

#SWDchallenge: visualize variance

A graph showing the average minimum temperature in Milwaukee, Wisconsin, for January 2000 through January 2019. The points on the chart are connected with light blue lines and filled in with blue to resemble icicles.

Knaflic’s icicle-style design for minimum temperature.

If there were to be a search interest visualization for the past few weeks in the Midwest, I have no doubt that the highest peak would be for the term “polar vortex.” The weather so far this year has been unusual, thanks to the extreme cold due to the polar vortex we had in the last week of January. Cole Nussbaumer Knaflic from Storytelling with Data used the cold snap as inspiration for the #SWDchallenge this month: visualize variance. Knaflic went through a series of visualizations in a blog post to show variation in average temperature in Milwaukee.

I hope you enjoyed this data visualization news! If you have any data visualization questions, please feel free to email the Scholarly Commons.

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Google MyMaps Part II: The Problem with Projections

Back in October, we published a blog post introducing you to Google MyMaps, an easy way to display simple information in map form. Today we’re going to revisit that topic and explore some further ways in which MyMaps can help you visualize different kinds of data!

One of the most basic things that students of geography learn is the problem of projections: the earth is a sphere, and there is no perfect way to translate an image from the surface of a sphere to a flat plane. Nevertheless, cartographers over the years have come up with many projection systems which attempt to do just that, with varying degrees of success. Google Maps (and, by extension, Google MyMaps) uses perhaps the most common of these, the Mercator projectionDespite its ubiquity, the Mercator projection has been criticized for not keeping area uniform across the map. This means that shapes far away from the equator appear to be disproportionately larger in comparison with shapes on the equator.

Luckily, MyMaps provides a method of pulling up the curtain on Mercator’s distortion. The “Draw a line” tool,  , located just below the search bar at the top of the MyMaps screen, allows users to create a rough outline of any shape on the map, and then drag that outline around the world to compare its size. Here’s how it works: After clicking on “Draw a line,” select “Add line or shape” and begin adding points to the map by clicking. Don’t worry about where you’re adding your points just yet, once you’ve created a shape you can move it anywhere you’d like! Once you have three or four points, complete the polygon by clicking back on top of your first point, and you should have a shape that looks something like this:

A block drawn in MyMaps and placed over Illinois

Now it’s time to create a more detailed outline. Click and drag your shape over the area you want to outline, and get to work! You can change the size of your shape by dragging on the points at the corners, and you can add more points by clicking and dragging on the transparent circles located midway between each corner. For this example, I made a rough outline of Greenland, as you can see below.

Area of Greenland made in MyMaps

You can get as detailed as you want with the points on your shapes, depending on how much time you want to spend clicking and dragging points around on your computer screen. Obviously I did not perfectly trace the exact coastline of Greenland, but my finished product is at least recognizable enough. Now for the fun part! Click somewhere inside the boundary of your shape, drag it somewhere else on the map, and see Mercator’s distortion come to life before your eyes.

Area of Greenland placed over Africa

Here you can see the exact same shape as in the previous image, except instead of hovering over Greenland at the north end of the map, it is placed over Africa and the equator. The area of the shape is exactly the same, but the way it is displayed on the map has been adjusted for the relative distortion of the particular position it now occupies on the map. If that hasn’t sufficiently shaken your understanding of our planet, MyMaps has one more tool for illuminating the divide between the map and reality. The “Measure distances and areas” tool, , draws a “straight” line between any two (or more) points on the map. “Straight” is in quotes there because, as we’re about to see, a straight line on the globe (and therefore in reality) doesn’t typically align with straight lines on the map. For example, if I wanted to see the shortest distance between Chicago and Frankfurt, Germany, I could display that with the Measure tool like so:

Distance line, Chicago to Frankfurt, Germany

The curve in this line represents the curvature of the earth, and demonstrates how the actual shortest distance is not the same as a straight line drawn on the map. This principle is made even more clear through using the Measure tool a little farther north.

Distance line, Chicago to Frankfurt, Germany, set over Greenland

The beginning and ending points of this line are roughly directly north of Chicago and Frankfurt, respectively, however we notice two differences between this and the previous measurement right away. First, this is showing a much shorter distance than Chicago to Frankfurt, and second, the curve in the line is much more distinct. Both of these differences arise, once again, from the difficulty of displaying a sphere on a flat surface. Actual distances get shorter the closer you get to the north (or south) ends of the map, which in turn causes all of the distortions we have seen in this post.

How might a better understanding of projection systems improve your own research? What are some other ways in which the Mercator projection (or any other) have deceived us? Explore for yourself and let us know!

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