The past couple of weeks have been a whirlwind for everyone as we’ve all sought to adjust to working, attending school, socializing, and just carrying out our daily lives online. Here at the Scholarly Commons, we’ve been working hard to ensure that this transition is as smooth as possible for those of you relying on specialized software to conduct your research or do your classwork. That’s why this week we wanted to highlight some resources essential to anyone using or teaching with GIS as we work through this period of social distancing.
One of the first challenges encountered by anyone seeking to start a new GIS project is where to find good, high quality geospatial data. The field of geographic information science has a bit of a problem in which there are simultaneously too many possible data sources for any one researcher to be familiar with all of them, as well as too few resources available to help you navigate them all. Luckily, The GIS Guide to Public Domain Data is here to help!
This week, geographers around the globe took some time to celebrate the software that allows them to analyze, well, that very same globe. November 13th marked the 20th annual GIS Day, an “international celebration of geographic information systems,” as the official GIS Day website puts it.
But while GIS technology has revolutionized the way we analyze and visualize maps over the past two decades, the high cost of ArcGIS products, long recognized as the gold standard for cartographic analysis tools, is enough to deter many people from using it. At the University of Illinois and other colleges and universities, access to ArcGIS can be taken for granted, but many of us will not remain in the academic world forever. Luckily, there’s a high-quality alternative to ArcGIS for those who want the benefits of mapping software without the pricetag!
QGIS is a free, open source mapping software that has most of the same functionality as ArcGIS. While some more advanced features included in ArcGIS do not have analogues in QGIS, developers are continually updating the software and new features are always being added. As it stands now, though, QGIS includes everything that the casual GIS practitioner could want, along with almost everything more advanced users need.
As is often the case with open source software alternatives, QGIS has a large, vibrant community of supporters, and its developers have put together tons of documentation on how to use the program, such as this user guide. Generally speaking, if you have any experience with ArcGIS it’s very easy to learn QGIS—for a picture of the learning curve, think somewhere along the lines of switching from Microsoft Word to Google Docs. And if you don’t have experience, the community is there to help! There are many guides to getting started, including the one listed in the above link, and more forum posts of users working through questions together than anyone could read in a lifetime.
Have you made an interesting map in QGIS? Send us pictures of your creations on Twitter @ScholCommons!
We at the University of Illinois are lucky to have a library that offers access to more journals and databases than any one person could ever hope to make their way though. The downside of this much access, however, is that it can be easy for resources to get lost in the weeds. For the typical student, once you are familiar with a few databases or methods of searching for information, you tend to not seek out more unless you absolutely need to.
This week, we wanted to fight back against that tendency just a little bit, by introducing you to a database which many readers may not have heard of before but contains a veritable treasure trove of useful geographical information, the Big 10 Academic Alliance Geoportal.
This resource is a compilation of geospatial content from the 12 universities that make up the BTAA. Types of content available include maps (many of which are historic), aerial imagery, and geospatial data. Researchers with a specific need for one of those can easily navigate from the Geoportal homepage to a more specific resource page by selecting the type of information they are looking for here:
Alternatively, if you don’t particularly care about the type of data you find but rather are looking for data in a particular region, you can use the map on the left side of the display to easily zoom in to a particular part of the world and see what maps and other resources are available.
The numbers on the map represent the number of maps or other data in the Geoportal localized in each rough region of the world, for example, there are 310 maps for Europe, and 14 maps for the Atlantic Ocean. As you zoom in on the map, your options get more specific, and the numbers break down to smaller geographic regions:
When the map is zoomed in close enough that there is only one piece of data for a particular area, the circled numbers are replaced with a blue location icon, such as the ones displayed over Iceland, Sweden, and the Russia-Finland border above. Clicking on one of these icons will take you to a page with the specific image or data source represented on the map. For example, the icon over Iceland takes us to the following page:
Information is provided about what type of resource you’re looking at, who created it, what time period it is from, as well as which BTAA member institution uploaded the map (in this case, the University of Minnesota).
Other tools on the home page, including a search bar and lists of places and subjects represented in the Geoportal, mean that no matter what point you’re starting from you should have no problem finding the data you need!
The Geoportal also maintains a blog with news, featured items and more, so be sure to check it out and keep up-to-date on all things geospatial!
Do you have questions about using the Geoportal, or finding other geospatial data? Stop by the Scholarly Commons or shoot us an email at firstname.lastname@example.org, we’ll be happy to help you!
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 Cummings!
What is your background education and work experience?
I earned my BA in anthropology and political science at Grinnell College in Grinnell, Iowa. During my time at Grinnell, I spent a semester working in the archives at the Drake Community Library, the public library in town, after which I was hired to work at the College library in Government Documents and Circulation. I also got some introductory instruction experience in my senior year, working as a writing mentor for a first-year tutorial course. I have been in my current position as a GA in the Scholarly Commons for the past year, and I plan to graduate from Illinois with my Masters in Library and Information Science this coming May.
What led you to your field?
I started to contemplate librarianship as a career path while I was in college. After working a few jobs in different parts of the library, and getting to know several librarians, I found that I really enjoyed the variety of work that goes into good library service. I had been interested in academia for a while, but I wasn’t sure if a traditional professor job was right for me. I’ve found that academic library work encompasses everything I would want from an academic job but is much more my style than professorship.
What are your research interests?
Combining my background in anthropology with library science, I am interested in how societies create, use, and understand information and what sociocultural factors go into those processes. The nature of librarianship is constantly changing as our society’s relationship to information changes, for instance with the advent of the internet age. I’ve also long been interested in mapping and cartography, in particular the politics of mapmaking and how maps, which are often thought of as neutral, actually represent the cultural biases of the mapmakers. (Check out this West Wing clip for more on that.).
What are your favorite projects you’ve worked on?
I’ve recently started doing a number of consultations getting researchers started with using GIS. There’s something really gratifying about one-on-one consultations; it feels good to be able to either help someone complete their work or get them started and then connect them with someone else who can. That’s one of the big reasons I wanted to be a librarian in the first place, so that I can provide that level of support to people who wouldn’t otherwise be able to get it. Sure, there are lots of books you can read and videos you can watch to help answer the questions people come to me for, but I don’t think there’s any substitute for one-on-one sessions.
What are some of your favorite underutilized resources that you would recommend?
Our Lib Guides! The Scholarly Commons maintains guides on just about every subject area that we offer support on, and we’re constantly updating them to improve the quality of our service. Check them out on our website!
When you graduate, what would your ideal job position look like?
I would be good with a number of different kinds of jobs in an academic library setting. I’m definitely looking into lots of digital scholarship positions that would allow me to continue the type of work that I’ve been doing here in the Scholarly Commons, but I’m also looking into some good old-fashioned reference jobs as well! I’m currently taking a class on metadata, and the thought of applying for some metadata librarian jobs has recently been floating across my mind, but I think I’d better wait to see how I end up doing in that class before applying for any of those…
What is the one thing you would want people to know about your field?
We’re here to help! Even when students come to the Scholarly Commons with a specific question that they want help with, they often seem surprised at just how willing we are to provide support to them. But that’s what we’re here for! None of us would have entered the field of librarianship if we didn’t have a commitment to providing high quality help to our patrons, so please stop by and ask us all of your questions!
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 projection. Despite 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:
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.
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.
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:
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.
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!
In this era of rapid technological change, it is easy to fall into the mindset that the “big new thing” is always an improvement on the technology that came before it. Certainly this is often true, and here in the Scholarly Commons we are always seeking innovative new tools to help you out with your research. However, every now and then it’s nice to just slow down and take the time to appreciate the strengths and benefits of older technology that has largely fallen out of use.
There is perhaps no better example of this than the Arctic World Archive, a facility on the Norwegian archipelago of Svalbard. Opened in 2017, the Arctic World Archive seeks to preserve the world’s most important cultural, political, and literary works in a way that will ensure that no manner of catastrophe, man-made or otherwise, could destroy them.
If this is all sounding familiar to you, that’s because you’ve probably heard of the Arctic World Archive’s older sibling, the Svalbard Global Seed Vault. The Global Seed Vault, which is much better known and older than the Arctic World Archive, is an archive seeds from around the world, meant to ensure that humanity would be able to continue growing crops and making food in the event of a catastrophe that wipes out plant life.
Indeed, the two archives have a lot in common. The World Archive is housed deep within a mountain in an abandoned coal mine that once served as the location of the seed vault, and was founded to be for cultural heritage what the seed vault is for crops. But the Arctic World Archive has made truly innovative use of old technology that makes it a truly impressive site in its own right.
Perhaps the coolest (pun intended) aspect of the Arctic World Archive is the fact that it does not require electricity to operate. It’s extreme northern location (it is near the northernmost town of at least 1,000 people in the world) means that the temperature inside the facility is naturally very cold year-round. As any archivist or rare book librarian who brings a fleece jacket to work in the summer will happily tell you, colder temperatures are ideal for preserving documents, and the ability to store items in a very cold climate without the use of electricity makes the World Archive perfect for sustainable, long-term storage.
But that’s not all: in a real blast from the past, all information stored in this facility is kept on microfilm. Now, I know what you’re thinking: “it’s the 21st century, grandpa! No one uses microfilm anymore!”
It’s true that microfilm is used by a very small minority of people nowadays, but nevertheless it offers distinct advantages that newer digital media just can’t compete with. For example, microfilm is rated to last for at least 500 years without corruption, whereas digital files may not last anywhere near that long. Beyond that, the film format means that the archive is totally independent from the internet, and will outlast any major catastrophe that disrupts part or all of our society’s web capabilities.
The Archive is still growing, but it is already home to film versions of Edvard Munch’s The Scream, Dante’s The Divine Comedy, and an assortment of government documents from many countries including Norway, Brazil, and the United States.
As it continues to grow, its importance as a place of safekeeping for the world’s cultural heritage will hopefully serve as a reminder that sometimes, older technology has upsides that new tech just can’t compete with.
In the wake of the 2016 presidential election, many people, on the left and right alike, came together on the internet to express a united sentiment: that the media had called the election wrong. In particular, one man may have received the brunt of this negative attention. Nate Silver and his website FiveThirtyEight have taken nearly endless flak from disgruntled Twitter users over the past two years for their forecast which gave Hillary Clinton a 71.4% chance of winning.
However, as Nate Silver has argued in many articles and tweets, he did not call the race “wrong” at all, everyone else just misinterpreted his forecast. So what really happened? How could Nate Silver say that he wasn’t wrong when so many believe to this day that he was? As believers in good data visualization practice, we here in the Scholarly Commons can tell you that if everyone interprets your data to mean one thing when you really meant it to convey something else entirely, your visualization may be the problem.
Today is Election Day, and once again, FiveThirtyEight has new models out forecasting the various House, Senate, and Governors races on the ballot. However, these models look quite a bit different from 2016’s, and in those differences lie some important data viz lessons. Let’s dive in and see what we can see!
The image above is a screenshot taken from the very top of the page for FiveThirtyEight’s 2016 Presidential Election Forecast, which was last updated on the morning of Election Day 2016. The image shows a bar across the top, filled in blue 71.4% of the way, to represent Clinton’s chance of winning, and red the rest of the 28.6% to represent Trump’s chance of winning. Below this bar is a map of the fifty states, colored from dark red to light red to light blue to dark blue, representative of the percentage chance that each state goes for one of the two candidates.
The model also allows you to get a sense of where exactly each state stands, by hovering your cursor over a particular state. In the above example, we can see a bar similar the one at the top of the national forecast which shows Clinton’s 55.1% chance of winning Florida.
The top line of FiveThirtyEight’s 2018 predictions looks quite a bit different. When you open the House or Senate forecasts, the first thing you see is a bell curve, not a map, as exemplified by the image of the House forecast below.
At first glance, this image may be more difficult to take in than a simple map, but it actually contains a lot of information that is essential to anyone hoping to get a sense of where the election stands. First, the top-line likelihood of each party taking control is expressed as a fraction, rather than as a percent. The reasoning behind this is that some feel that the percent bar from the 2016 model improperly gave the sense that Clinton’s win was a sure thing. The editors at FiveThirtyEight hope that fractions will do a better job than percentages at conveying that the forecasted outcome is not a sure thing.
Beyond this, the bell curve shows forecasted percentage chances for every possible outcome (for example, at the time of writing, this, there is a 2.8% chance that Democrats gain 37 seats, a 1.6% chance that Democrats gain 20 seats, a <0.1% chance that Democrats gain 97 seats, and a <0.1% chance that Republicans gain 12 seats. This visualization shows the inner workings of how the model makes its prediction. Importantly, it strikes home the idea that any result could happen even if one end result is considered more likely. What’s more, the model features a gray rectangle centered around the average result, that highlights the middle 80% of the forecast: there is an 80% chance that the result will be between a Democratic gain of 20 seats (meaning Republicans would hold the House) and a Democratic gain of 54 (a so-called “blue wave”).
The 2018 models do feature maps as well, such as the above map for the Governors forecast. But some distinct changes have been made. First, you have to scroll down to get to the map, hopefully absorbing some important information from the graphs at the top in the meantime. Most prominently, FiveThirtyEight has re-thought the color palette they are using. Whereas the 2016 forecast only featured shades of red and blue, this year the models use gray (House) and white (Senate and Governors) to represent toss-ups and races that only slightly lean one way or the other. If this color scheme had been used in 2016, North Carolina and Florida, both states that ended up going for Trump but were colored blue on the map, would have been much more accurately depicted not as “blue states” but as toss-ups.
Once again, hovering over a state or district gives you a detail of the forecast for that place in particular, but FiveThirtyEight has improved that as well.
Here we can see much more information than was provided in the hover-over function for the 2016 map. Perhaps most importantly, this screen shows us the forecasted vote share for each candidate, including the average, high, and low ends of the prediction. So for example, from the above screenshot for Illinois’ 13th Congressional District (home to the University of Illinois!) we can see that Rodney Davis is projected to win, but there is a very real scenario in which Betsy Dirksen Londrigan ends up beating him.
FiveThirtyEight did not significantly change how their models make predictions between 2016 and this year. The data itself is treated in roughly the same way. But as we can see from these comparisons, the way that this data is presented can make a big difference in terms of how we interpret it.
Will these efforts at better data visualization be enough to deter angry reactions to how the model correlates with actual election results? We’ll just have to tune in to the replies on Nate Silver’s twitter account tomorrow morning to find out… In the meantime, check out their House, Senate, and Governors forecasts for yourself!
All screenshots taken from fivethirtyeight.com. Images of the 2016 models reflect the “Polls-only” forecast. Images of the 2018 models reflect the “Classic” forecasts as of the end of the day on November 5th 2018.
Geographic information systems (GIS) are a fantastic way to visualize spatial data. As any student of geography will happily explain, a well-designed map can tell compelling stories with data which could not be expressed through any other format. Unfortunately, traditional GIS programs such as ArcGIS and QGIS are incredibly inaccessible to people who aren’t willing or able to take a class on the software or at least dedicate significant time to self-guided learning.
Luckily, there’s a lower-key option for some simple geospatial visualizations that’s free to use for anybody with a Google account. Google MyMaps cannot do most of the things that ArcMap can, but it’s really good at the small number of things it does set out to do. Best of all, it’s easy!
How easy, you ask? Well, just about as easy as filling out a spreadsheet! In fact, that’s exactly where you should start. After logging into your Google Drive account, open a new spreadsheet in Sheets. In order to have a functioning end product you’ll want at least two columns. One of these columns will be the name of the place you are identifying on the map, and the other will be its location. Column order doesn’t matter here- you’ll get the chance later to tell MyMaps which column is supposed to do what. Locations can be as specific or as broad as you’d like. For example, you could input a location like “Canada” or “India,” or you could choose to input “1408 W. Gregory Drive, Urbana, IL 61801.” The catch is that each location is only represented by a marker indicating a single point. So if you choose a specific address, like the one above, the marker will indicate the location of that address. But if you choose a country or a state, you will end up with a marker located somewhere over the center of that area.
So, let’s say you want to make a map showing the locations of all of the libraries on the University of Illinois’ campus. Your spreadsheet would look something like this:
Once you’ve finished compiling your spreadsheet, it’s time to actually make your map. You can access the Google MyMaps page by going to www.google.com/mymaps. From here, simply select “Create a New Map” and you’ll be taken to a page that looks suspiciously similar to Google Maps. In the top left corner, where you might be used to typing in directions to the nearest Starbucks, there’s a window that allows you to name your map and import a spreadsheet. Click on “Import,” and navigate through Google Drive to wherever you saved your spreadsheet.
When you are asked to “Choose columns to position your placemarks,” select whatever column you used for your locations. Then select the other column when you’re prompted to “Choose a column to title your markers.” Voila! You have a map. Mine looks like this:
At this point you may be thinking to yourself, “that’s great, but how useful can a bunch of points on a map really be?” That’s a great question! This ultra-simple geospatial visualization may not seem like much. But it actually has a range of uses. For one, this type of visualization is excellent at giving viewers a sense of how geographically concentrated a certain type of place is. As an example, say you were wondering whether it’s true that most of the best universities in the U.S. are located in the Northeast. Google MyMaps can help with that!
This map, made using the same instructions detailed above, is based off of the U.S. News and World Report’s 2019 Best Universities Ranking. Based on the map, it does in fact appear that more of the nation’s top 25 universities are located in the northeastern part of the country than anywhere else, while the West (with the notable exception of California) is wholly underrepresented.
This is only the beginning of what Google MyMaps can do: play around with the options and you’ll soon learn how to color-code the points on your map, add labels, and even totally change the appearance of the underlying base map. Check back in a few weeks for another tutorial on some more advanced things you can do with Google MyMaps!
Try it yourself!