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!
Wikipedia is a central player in online knowledge production and sharing. Since its founding in 2001, Wikipedia has been committed to open access and open editing, which has made it the most popular reference work on the web. Though students are still warned away from using Wikipedia as a source in their scholarship, it presents well-researched information in an accessible and ostensibly democratic way.
Most people know Wikipedia from its high ranking in most internet searches and tend to use it for its encyclopedic value. The Wikimedia Foundation—which runs Wikipedia—has several other projects which seek to provide free access to knowledge. Among those are Wikimedia Commons, which offers free photos; Wikiversity, which offers free educational materials; and Wikidata, which provides structured data to support the other wikis.
Wikidata is a great tool to study how Wikipedia is structured and what information is available through the online encyclopedia. Since it is presented as structured data, it can be analyze quantitatively more easily than Wikipedia articles. This has led to many projects that allow users to explore data through visualizations, queries, and other means. Wikidata offers a page of Tools that can be used to analyze Wikidata more quickly and efficiently, as well as Data Access instructions for how to use data from the site.
An example of a project born out of Wikidata is the Wikidata Human Gender Indicators (WHGI) project. The project uses metadata from Wikidata entries about people to analyze trends in gender disparity over time and across cultures. The project presents the raw data for download, as well as charts and an article written about the discoveries the researchers made while compiling the data. Some of the visualizations they present are confusing (perhaps they could benefit from reading our Lightning Review of Data Visualization for Success), but they succeed in conveying important trends that reveal a bias toward articles about men, as well as an interesting phenomenon surrounding celebrities. Some regions will have a better ratio of women to men biographies due to many articles being written about actresses and female musicians, which reflects cultural differences surrounding fame and gender.
Of course, like many data sources, Wikidata is not perfect. The creators of the WHGI project frequently discovered that articles did not have complete metadata related to gender or nationality, which greatly influenced their ability to analyze the trends present on Wikipedia related to those areas. Since Wikipedia and Wikidata are open to editing by anyone and are governed by practices that the community has agreed upon, it is important for Wikipedians to consider including more metadata in their articles so that researchers can use that data in new and exciting ways.
Data visualization is where the humanities and sciences meet: viewers are dazzled by the presentation yet informed by research. Lovingly referred to as “the poster child of interdisciplinarity” by Steven Braun, data visualization brings these two fields closer together than ever to help provide insights that may have been impossible without the other. In his book Data Visualization for Success, Braun sits down with forty designers with experience in the field to discuss their approaches to data visualization, common techniques in their work, and tips for beginners.
Braun’s collection of interviews provides an accessible introduction into data visualization. Not only is the book filled with rich images, but each interview is short and meant to offer an individual’s perspective on their own work and the field at large. Each interview begins with a general question about data visualization to contribute to the perpetual debate of what data visualization is and can be moving forward.
Antonio Farach, one of the designers interviewed in the book, calls data visualization “the future of storytelling.” And when you see his work – or really any of the work in this book – you can see why. Each new image has an immediate draw, but it is impossible to move past without exploring a rich narrative. Visualizations in this book cover topics ranging from soccer matches to classic literature, economic disparities, selfie culture, and beyond.
Each interview ends by asking the designer for their advice to beginners, which not only invites new scholars and designers to participate in the field but also dispels any doubt of the hard work put in by these designers or the science at the root of it all. However, Barbara Hahn and Christine Zimmermann of Han+Zimmermann may have put it best, “Data visualization is not making boring data look fancy and interesting. Data visualization is about communicating specific content and giving equal weight to information and aesthetics.”
A leisurely, stunning, yet informative read, Data Visualization for Success offers anyone interested in this explosive field an insider’s look from voices around the world. Drop by the Scholarly Commons during our regular hours to flip through this wonderful read.
And finally, if you have any further interest in data visualization make sure you stay up to date on our Exploring Data Visualization series or take a look at what services the Scholarly Commons provides!
Although the push for open access is decades old at this point, it remains one of the most important initiatives in the world of scholarly communication and publishing. Free of barriers like the continuously rising costs of subscription-based serials, open access publishing allows researchers to explore, learn, build upon, and create new knowledge without inhibition. As Peter Suber says, “[Open access] benefits literally everyone, for the same reasons that research itself benefits literally everyone.”
Peter Suber is the Director of the Harvard Office for Scholarly Communication; Director of the Harvard Open Access Project; and, among many other titles, the “de facto leader of the worldwide open access movement.” In short, Suber is an expert when it comes to open access. Thankfully, he knows the rest of us might not have time to be.
Suber introduces his book Open Access (a part of the MIT Press Essential Knowledge Series) by writing, “I want busy people to read this book. […] My honest belief from experience in the trenches is that the largest obstacle to OA is misunderstanding. The largest cause of misunderstanding is the lack of familiarity, and the largest cause of unfamiliarity is preoccupation. Everyone is busy.”
What follows is an informative yet concise read on the broad field of open access. Suber goes into the motivation for open access, the obstacles preventing it, and what the future may hold. In clear language, Suber breaks down jargon and explains how open access navigates complex issues concerning copyright and payment. This is a great introductory read to an issue so prominent in academia.
My undergraduate degree is in Classical Humanities and French, and like many humanities and liberal arts students, computers were mostly used for accessing Oxford Reference Online and double checking that “bonjour” meant “hello” before term papers were turned in. Actual critical analysis of literature came from my mind and my research, and nothing else. Recently, scholars in the humanities began seeing the potential of computational methods for their study, and coined these methods “digital humanities.” Computational text analysis provides insights that in many cases, aren’t possible for a human mind to complete. When was the last time you read 100 books to count occurrences of a certain word, or looked at thousands of documents to group their contents by topic? In Text Analysis with R for Students of Literature, Matthew Jockers presents programming concepts specifically how they relate to literature study, with plenty of help to make the most technophobic English student a digital humanist.
Jockers’ book caters to the beginning coder. You download practice text from his website that is already formatted to use in the tutorials presented, and he doesn’t dwell too much on pounding programming concepts into your head. I came into this text having already taken a course on Python, where we did edit text and complete exercises similar to the ones in this book, but even a complete beginner would find Jockers’ explanations perfect for diving into computational text analysis. There are some advanced statistical concepts presented which may turn those less mathematically inclined, but these are mentioned only as furthering understanding of what R does in the background, and can be left to the computer scientists. Practice-based and easy to get through, Text Analysis with R for Students of Literature serves its primary purpose of bringing the possibilities of programming to those used to traditional literature research methods.
Hailed by one of our librarians as a brilliant and seminal text to understanding data visualization, the truthful art is a text that can serve both novices and masters in the field of visualization.
Packed with detailed descriptions, explanations, and images of just how Cairo wants readers to understand and engage with knowledge and data. Nearly every page of this work, in fact, is packed with examples of the methods Cairo is trying to connect his readers to.
Cairo’s work not only teaches readers how to best design their own visualizations, but goes into the process of explaining how to *read* data visualizations themselves. Portions of chapters are devoted to the necessity of ‘truthful’ visualizations, not only because “if someone hides data from you, they probably have something to hide” (Cairo, 2016, p. 49). The exact same data, when presented in different ways, can completely change the audience’s perspective on what the ‘truth’ of the matter is.
The most I read through the truthful art, the harder time I had putting it down. Cairo’s presentations of data, how vastly they could differ depending upon the medium through which they were visualized. It was amazing how Cairo could instantly pick apart a bad visualization, replacing it with one that was simultaneously more truthful and more beautiful.
There is specific portion of Chapter 2 where Cairo gives a very interesting visualization of “How Chicago Changed the Course of Its Rivers”. It’s detailed, informative, and very much a classic data visualization.
Then he compared it to a fountain.
The fountain was beautiful, and designed in a way to tell the same story as the maps Cairo had created. It was fascinating to see data presented in such a way, and I hadn’t fully considered that data could be represented in such a unique way.
the truthful art is here on our shelves in the Scholarly Commons, and we hope you’ll stop and give it a read! It’s certainly worthwhile one!
We’ve talked about Docear the Visual Citation Manager on the blog before, before my time, but it’s been a while we’ll revisit it. Though, the most recent major update to the software was in 2015, and based on the forums it seems that Docear has struggled with finding funding. However, the researchers behind this project are still active. That being said, in the worst case scenario, Docear is an open source project and if things went south, you could still get your information out. If you are considering relying on this software for organizing very long term research projects you need to use an external cloud backup service as their My Docear service is no longer available and supported if it ever existed at all.
Docear is an open source mind mapping, reference, and citation management software for those who want a visual way to keep their research organized. It is available for Windows, Mac, and Linux computers. Docear provides plenty of support and useful instructions through their official user manual. The examples on the app itself for trying out the mind map and PDF capability incorporate some of the research behind the product itself and makes for an informative, if somewhat meta, experience. Docear staff like to compare the software to Zotero and Mendeley, but it’s a very different type of beast. Specifically, a combination of Jabref (without the OpenOffice support) and Freeplane for mind maps, and, depending on what type of PDF viewer you use, a document annotation software. To enjoy the full capability of this software you also have to download PDF X-change viewer, though you can still do some annotating with other less supported PDF editors. Docear also uses Mr. DLib or Machine-readable digital library cataloging. While Mr. DLib has not really caught on elsewhere, it is featured as part of JabRef and specifically powers the article recommendation function. If they ever get their funding together, Docear could become a space where you can research, organize, and write an article. And unlike some of the software options discussed on this blog and in our LibGuides, you can download Docear from a zip file and run it to full capacity on Scholarly Commons computers.
Although Docear is not quite the all-encompassing research suite the creators envisioned, there are still lots of funky little features not found in other services. For example, in the Tools and Settings tab you can add map locations with OpenMaps (unfortunately there is no search function — you have to zoom and select your location) to add a geographic component to your otherwise mental map,which you can see by clicking on “View Open Maps Location” later.
You can also add time alerts for time management in Tools and Settings. But before we get ahead of ourselves, it’s easy to add a node with keyboard shortcuts and the node panel in the toolbar. You can add links to websites and other nodes right in your mind map by right clicking on a node. Apparently, you can add formulas to your mind map using LaTex but I didn’t try it, as I am not one of the people who cares about that sort of thing.
And while you do have the option of writing in Docear itself, there is a plugin for MS Word, but only on Windows. On the one hand, the plugin is old and hasn’t been updated in a few years, and it doesn’t work on the computers at Scholarly Commons. But on the other hand, since it’s based in BibTeX, if it actually does work the way they say it does, you should be able to use it with any BibTeX bibliography, and not just Docear. This means, it could give you that MS Word integration that you might be lacking with another reference manager.
Overall, if you wanted a reference manager and document annotator that is easy to get started on this is NOT the one for you, but for those patient enough to deal with the learning curve, Docear can be a good addition to your research strategy. I really hope this project gets the funding it needs to fully live up to its potential, but for now it’s still a solid option for researchers looking for a unique way to organize their work.
E-portfolios (sometimes spelled ePortfolio) and digital portfolios are websites where you can display your academic achievements and works for the world to see. These professional websites are often created with a specific career goal in mind and display examples that demonstrate how you meet the competencies of your career goal. Digital portfolios can be used to supplement a LinkedIn profile, and some graduate programs even require the creation of an e-portfolio in lieu of writing a master’s thesis or even as a graduation requirement.
Should I make an e-portfolio with e-portfolio software?
A lot of online portfolio software creation tools aimed at educators make sites that tend to look very formatted. Essentially, what you end up working with is close in appearance to a Google Sites page. Oftentimes, individuals pay for their own site, if funds are not provided by your university. The University of Illinois supports use of the ePortfolio site Digication, which is free to faculty, students, and staff. That being said, default templates for e-portfolios tend to be… ugly. You may consider using these if your school subscribes to them, or if you want a free portfolio site for your fifth graders. Otherwise, probably not.
Issues to consider when choosing an e-portfolio software: digital preservation, usability, aesthetics, and cost. You also want to consider the most important question here: Am I better off using Google Sites?
Mahara is a New Zealand-based open source e-portfolio software. You need your own server to use Mahara, but you can customize the software to your liking if you know how or have a very supportive IT department. For all of my server-free readers, FolioSpaces is a web application based on Mahara, but feels a lot more like a social network for third graders. Users are unable to customize the background of their sites unless you pay up to $9.95 a year. On FolioSpaces you create “portfolios” that are actually sections where you can store different aspects of your work. FolioSpaces is an odd public space where you are likely to see posts from high school students from Michigan who really could benefit from spell check. Still, this could be a good free option for folks looking for a portfolio creation tool for their students’ classwork. However, you will probably save a lot of time and trouble, as well as have more control over privacy settings, by just using Google Sites, especially if you have Google for Education (and if you are a student at Illinois, you do).
Digication is an e-portfolio alternative. U of I students, faculty, and staff can easily create, share, and access ePotfolios for free, and continue to access them after graduation. Digication has pretty intuitive steps for creating an ePortfolio. One great aspect is the easily editable custom URLs you can create for your portfolio. With Digication, you can either use a pre-made template (some more aesthetically pleasing than others), or customize your own theme. Because we have access to Digication through the University of Illinois, it has some themes that are better suited to our needs than some of the other ePortfolio options on this list, because they are geared to a UIUC audience.
One of the best parts of Digication are the options to allow comments and “conversations” on your ePortfolio, which are a great social aspect that encourage interaction between yourself and your audience.
Like all of these options, there are pros and cons to using Digication, but it’s definitely a path to explore. For more information on Digication at the U of I, head to the ePortfolio Resources at Illinois page.
Portfolio Gen provides free pages, as well as paid options that have more space and no “Powered by Portfolio Gen” widget on the page. Frankly, most of the themes on Portfolio Gen seem very childish, and seem to cater to an audience of younger students creating (tacky) portfolios. They are, however, the easiest to use e-portfolio software, and it would be nice if they could expand their theme options to have some better-suited for adults.
My default portfolio and landing page took about five minutes to make and looked like this:
In my opinion, this is probably the most promising e-portfolio builder that is specifically built for this purpose. Pathbrite is free for individual users but costs money for institutions. You can create a free, simple site with a Google account and incorporate documents like a resume/CV and a writing sample directly from your Google Drive from the side bar “Add Work” tab and/or by dragging and dropping the icon of the type of work you want to add to your portfolio site. Although this looks similar to the Weebly drag and drop, it will give you options to upload from all sorts of places. You can arrange uploaded items by dragging and dropping them around on your page. A particularly nice feature is that you can also incorporate screenshots and links to websites you have created by simply clicking “Web link” and including the link to the website you want to share so you don’t have to screenshot it yourself.
That being said, on the “Style and Settings” tab on the side bar you have a very limited amount of control over the way that the different items are arranged on your site. You can choose between light and dark and resume views and a couple of different ways to arrange the layout of how your work will appear, but that’s about it.
My default portfolio and page took about 15 minutes to make and this is how it turned out:
Overall, I am not a big fan of any of these options. At the end of the day, I still think you’re probably better off working with a regular CMS like WordPress, Weebly, or even the most basic of site creation tools, Google Sites. If you are an artist, photographer, or some other kind of all around creative genius there are web site builders and e-portfolio designs that specifically cater to you that look nice; however, this post is focusing on researcher/educator e-portfolios that aren’t as image heavy.
And if you’re a UIUC faculty member you’re in luck, because soon you will be able to create an e-portfolio through an Illinois Experts where you can showcase your research and accomplishments.
UPDATE 11/14/2017: Those post initially and incorrectly stated that the University of Illinois at Urbana-Champaign does not provide free access to any ePortfolio site. However, we just learned that we do! University of Illinois students, faculty, and staff can create a free ePortfolio on Digication, which they can continue to access even after they have left the school. We apologize for our mistake, and hope that this news comes as a pleasant surprise for our readers!
And make sure to check out our two fabulous LibGuides on online scholarly presence:
Data science is a special blend of statistics and programming with a focus on making complex statistical analyses more understandable and usable to users, typically through visualization. In 2012, the Harvard Business Review published the article, “Data Scientist: The Sexiest Job of the 21st Century” (Davenport, 2012), showing society’s perception of data science. While some of the excitement of 2012 has died down, data science continues on, with data scientists earning a median base salary over $100,000 (Noyes, 2016).
Here at the Scholarly Commons, we believe that having a better understanding of statistics means you are less likely to get fooled when they are deployed improperly, and will help you have a better understanding of the inner workings of data visualization and digital humanities software applications and techniques. We might not be able to make you a data scientist (though certainly please let us know if inspired by this post and you enroll in formal coursework) but we can share some resources to let you try before you buy and incorporate methods from this growing field in your own research.
As we have discussed again and again on this blog, whether you want to improve your coding, statistics, or data visualization skills, our collection has some great reads to get you started.
In particular, take a look at:
The Human Face of Big Data created by Rick Smolan and Jennifer Erwitt
- This is a great coffee table book of data visualizations and a great flip through if you are here in the space. You will learn a little bit more about the world around you and will be inspired with creative ways to communicate your ideas in your next project.
Data Points: Visualization That Means Something by Nathan Yau
- Nathan Yau is best known for being the man behind Flowing Data, an extensive blog of data visualizations that also offers tutorials on how to create visualizations. In this book he explains the basics of statistics and visualization.
Storytelling with Data by Cole Nussbaumer Knaflic
- The expanded book version of Cole Nussbaumer Knaflic’s blog and workshop series of the same name, Storytelling with Data is particularly aimed at folks doing business analytics, though most of the strategies cross over into other disciplines. We have the print version but if you can’t make it to the space it’s also available as an ebook through the University Library Online Collection.
LibGuides to Get You Started:
- Qualitative Data Analysis: Your Options for Programs
- Visualizing Your Data
- Finding Social Science Data
- Introduction to Data Management for Undergraduate Students
- Text Mining Tools
There are also a lot of resources on the web to help you:
- This is not an accredited masters program but rather a curated collection of suggested free and low-cost print and online resources for learning the various skills needed to become a data scientist. This list was created and is maintained by Clare Corthell of Luminant Data Science Consulting
- This list does suggest many MOOCS from universities across the country, some even available for free
- This is a project-based data science course created by Vik Paruchuri, a former Foreign Service Officer turned data scientist
- It mostly consists of a beginner Python tutorial, though it is only one of many that are out there
- Twenty-two quests and portfolio projects are available for free, though the two premium versions offer unlimited quests, more feedback, a Slack community, and opportunities for one-on-one tutoring
- A DIY data science course, which includes a resource list, and, perhaps most importantly, includes links to reviews of data science online courses with up to date information. If you are interested in taking an online course or participating in a MOOC this is a great place to get started
- Another curated list of data science learning resources, this time based on Zed Shaw’s Learn Code the Hard Way series. This list comes from Mitch Crowe, a Canadian data science
So, is data science still sexy? Let us know what you think and what resources you have used to learn data science skills in the comments!
Twine is a tool for digital storytelling platform originally created by Baltimore-based programmer Chris Klimas back in 2009. It’s also a very straightforward turn-based game creation engine typically used for interactive fiction.
Now, you may be thinking to yourself, “I’m a serious researcher who don’t got no time for games.” Well, games are increasingly being recognized as an important part of digital pedagogy in libraries, at least according to this awesome digital pedagogy LibGuide from University of Toronto. Plus, if you’re a researcher interested in presenting your story in a nonlinear way, letting readers explore the subject at their own pace and based on what they are interested in, this could be the digital scholarship platform for you! Twine is a very easy-to-use tool, and allows you to incorporate links to videos and diagrams as well. You can also create interactive workflows and tutorials for different subjects. It’s also a lot of fun, something I don’t often say about the tools I review for this blog.
Twine is open source and free. Currently, there are three versions of Twine maintained by different repositories.There is already a lot of documentation and tutorials available for Twine so I will not be reinventing the wheel, but rather showing some of Twine’s features and clarifying things that I found confusing. Twine 1 still exists and there are certain functions that are only possible there; however, we are going to be focusing on Twine 2, which is newer and updated.
What simple Twine games look like. You would click on a linked blue or purple text to go to the next page of the story.
The Desktop version is identical to the online version; however, stories are a lot less likely to be inadvertently deleted on the desktop version. If you want to work on stories offline, or often forget to archive, you may prefer this option.
Story editor in Twine 2, Desktop edition with all your options for each passage. Yes I named the story Desktop Version of Twine.
You start with an Untitled passage, which you can change the title and content of. Depending on the version of Twine you have set up, you write in a text-based coding language, and connect the passages of your story using links written between brackets like [[link]] that automatically generate a new passage. There are ways to hide the destination. More advanced users can add logic-based elements such as “if” statements in order to create games.
You cannot install the desktop version on the computers in Scholarly Commons, so let’s look at the browser version. Twine will give you reminders, but it’s always important to know that if you clear your browser files while working on a Twine project, you will lose your story. However, you can archive your file as an HTML document to ensure that you can continue to access it. We recommend that you archive your files often.
Here’s a quick tutorial on how to archive your stories. Step 1: Click the “Home” icon.
This is also where you can start or import stories.
Save Your File
Note: You should probably move the file from Downloads and paste it somewhere more stable, such as a flashdrive or the Cloud.
When you are ready to start writing again you can import your story file, which will have been saved as an HTML document. Also, keep in mind if you’re using a public or shared computer, Twine is based on the browser, so it will be accessible to whoever is using the browser.
And if you’re interested in interactive fiction or text-based games, there are a lot of platforms you might want to explore in addition to Twine such as: http://inform7.com/ and https://textadventures.co.uk/ and http://www.inklestudios.com/inklewriter/
Let us know in the comments your thoughts on Twine and similar platforms as well as the role of games and interactive fiction in research!