Mapping Native Land

Fall break is fast approaching and with it will be Thanksgiving! No matter what your traditions are, we all know that this year’s holiday season will look a little bit different. As we move into the Thanksgiving holiday, I wanted to share a mapping project to give thanks and recognize the native lands we live on.

Native Land is an open-source mapping project that shows the indigenous territories across the world. This interactive map allows you to input your address or click and explore to determine what indigenous land you reside on. Not only that but Native Land shares educational information about these nations, their languages, or treaties.  They also include a Teacher’s Guide for various wide age range from children to adults. Users are able to export images of their map, too!

Native Land Map

NativeLand.ca Map Interface

Canadian based and indigenous-led, Native Land Digital aims to educate and bring awareness to the complex histories of the land we inhibit. This platform strives to create conversations about indigenous communities between those with native heritage as well as those without. Native Land Digital values the sacredness of land and they use this platform to honor the history of where we reside. Learn more about their mission and impact on their “Why It Matters” page.

Native Land uses MapBox and WordPress to generate their interactive map. MapBox is an open source mapping platform for custom designed maps. Native Land is available as an App for iOS and Android and they have a texting service, as well. You can find more information about how it works here.

If you’d like to learn more about mapping software, the Scholarly Commons has Geographic Information Systems (GIS) software, consultations, and workshops available. The Scholarly Commons webpage on GIS is a great place to get started.

 The University of Illinois is a land-grant institution and resides on Kickapoo territory. Where do you stand?

University of Illinois Urbana-Champaign Land Acknowledgement Statement

As a land-grant institution, the University of Illinois at Urbana-Champaign has a responsibility to acknowledge the historical context in which it exists. In order to remind ourselves and our community, we will begin this event with the following statement. We are currently on the lands of the Peoria, Kaskaskia, Piankashaw, Wea, Miami, Mascoutin, Odawa, Sauk, Mesquaki, Kickapoo, Potawatomi, Ojibwe, and Chickasaw Nations. It is necessary for us to acknowledge these Native Nations and for us to work with them as we move forward as an institution. Over the next 150 years, we will be a vibrant community inclusive of all our differences, with Native peoples at the core of our efforts.

Free, Open Source Optical Character Recognition with gImageReader

Optical Character Recognition (OCR) is a powerful tool to transform scanned, static images of text into machine-readable data, making it possible to search, edit, and analyze text. If you’re using OCR, chances are you’re working with either ABBYY FineReader or Adobe Acrobat Pro. However, both ABBYY and Acrobat are propriety software with a steep price tag, and while they are both available in the Scholarly Commons, you may want to perform OCR beyond your time at the University of Illinois.

Thankfully, there’s a free, open source alternative for OCR: Tesseract. By itself, Tesseract only works through the command line, which creates a steep learning curve for those unaccustomed to working with a command-line interface (CLI). Additionally, it is fairly difficult to transform a jpg into a searchable PDF with Tesseract.

Thankfully, there are many free, open source programs that provide Tesseract with a graphical user interface (GUI), which not only makes Tesseract much easier to use, some of them come with layout editors that make it possible to create searchable PDFs. You can see the full list of programs on this page.

The program logo for gImageReader

The program logo for gImageReader

In this post, I will focus on one of these programs, gImageReader, but as you can see on that page, there are many options available on multiple operating systems. I tried all of the Windows-compatible programs and decided that gImageReader was the closest to what I was looking for, a free alternative to ABBYY FineReader that does a pretty good job of letting you correct OCR mistakes and exporting to a searchable PDF.

Installation

gImageReader is available for Windows and Linux. Though they do not include a Mac compatible version in the list of releases, it may be possible to get it to work if you use a package manager for Mac such as Homebrew. I have not tested this though, so I do not make any guarantees about how possible it is to get a working version of gImageReader on Mac.

To install gImageReader on Windows, go to the releases page on Windows. From there, go to the most recent release of the program at the top and click Assets to expand the list of files included with the release. Then select the file that has the .exe extension to download it. You can then run that file to install the program.

Manual

The installation of gImageReader comes with a manual as an HTML file that can be opened by any browser. As of the date of this post, the Fossies software archive is hosting the manual on its website.

Setting OCR Mode

gImageReader has two OCR modes: “Plain Text” and “hOCR, PDF”. Plain Text is the default mode and only recognizes the text itself without any formatting or layout detection. You can export this to a text file or copy and paste it into another program. This may be useful in some cases, but if you want to export a searchable PDF, you will need to use hOCR, PDF mode. hOCR is a standard for formatting OCR text using either XML or HTML and includes layout information, font, OCR result confidence, and other formatting information.

To set the recognition to hOCR, PDF mode, go to the toolbar at the top. It includes a section for “OCR mode” with a dropdown menu. From there, click the dropdown and select hOCR, PDF:

gImageReader Toolbar

This is the toolbar for gImageReader. You can set OCR mode by using the dropdown that is the third option from the right.

Adding Images, Performing Recognition, and Setting Language

If you have images already scanned, you can add them to be recognized by clicking the Add Images button on the left panel, which looks like a folder. You can then select multiple images if you want to create a multipage PDF. You can always add more images later by clicking that folder button again.

On that left panel, you can also click the Acquire tab button, which allows you to get images directly from a scanner, if the computer you’re using has a scanner connected.

Once you have the images you want, click the Recognize button to recognize the text on the page. Please note that if you have multiple images added, you’ll need to click this button for every page.

If you want to perform recognition on a language other than English, click the arrow next to Recognize. You’ll need to have that language installed, but you can install additional languages by clicking “Manage Languages” in the dropdown appears. If the language is already installed, you can go to the first option listed in the dropdown to select a different language.

Viewing the OCR Result

In this example, I will be performing OCR on this letter by Franklin D. Roosevelt:

Raw scanned image of a typewritten letter signed by Franklin Roosevelt

This 1928 letter from Franklin D. Roosevelt to D. H. Mudge Sr. is courtesy of Madison Historical: The Online Encyclopedia and Digital Archive for Madison County Illinois. https://madison-historical.siue.edu/archive/items/show/819

Once you’ve performed OCR, there will be an output panel on the right. There are a series of buttons above the result. Click the button on the far right to view the text result overlaid on top of the image:

The text result of performing OCR on the FDR letter overlaid on the original scan.

Here is the the text overlaid on an image of the original scan. Note how the scan is slightly transparent now to make the text easier to read.

Correcting OCR

The OCR process did a pretty good job with this example, but it there are a handful of errors. You can click on any of the words of text to show them on the right panel. I will click on the “eclnowledgment” at the end of the letter to correct it. It will then jump to that part of the hOCR “tree” on the right:

hOCR tree in gImageReader, which shows the recognition result of each word in a tree-like structure.

The hOCR tree in gImageReader, which also shows OCR result.

Note in this screenshot I have clicked the second button from the right to show the confidence values, where the higher the number, the higher the confidence Tesseract has with the result. In this case, it is 67% sure that eclnowledgement is correct. Since it obviously isn’t correct, we can type new text by double-clicking on the word in this panel and type “acknowledgement.” You can do this for any errors on the page.

Other correction tips:

  1. If there are any regions that are not text that it is still recognizing, you can right click them on the right and delete them.
  2. You can change the recognized font and its size by going to the bottom area labeled “Properties.” Font size is controlled by the x_fsize field, and x_font has a dropdown where you can select a font.
  3. It is also possible to change the area of the blue word box once it is selected, simply by clicking and dragging the edges and corners.
  4. If there is an area of text that was not captured by the recognition, you can also right click in the hOCR “tree” to add text blocks, paragraphs, textlines, and words to the document. This allows you to draw a box on image and then type what the text says.

Exporting to PDF

Once you are done making OCR corrections, you can export to a searchable PDF. To do so, click the Export button above the hOCR “tree,” which is the third button from the left. Then, select export to PDF. It then gives you several options to set the compression and quality of the PDF image, and once you click OK, it should export the PDF.

Conclusion

Unfortunately, there are some limitations to gImageViewer, as can often be the case with free, open source software. Here are some potential problems you may have with this program:

  1. While you can add new areas to recognize with OCR, there is not a way to change the order of these elements inside the hOCR “tree,” which could be an issue if you are trying to make the reading order clear for accessibility reasons. One potential workaround could be to use the Reading Order options on Adobe Acrobat, which you can read about in this libguide.
  2. You cannot show the areas of the document that are in a recognition box unless you click on a word, unlike ABBYY FineReader which shows all recognition areas at once on the original image.
  3. You cannot perform recognition on all pages at once. You have to click the recognition button individually for each page.
  4. Though there are some image correction options to improve OCR, such as brightness, contrast, and rotation, it does not have as many options as ABBYY FineReader.

gImageViewer is not nearly as user friendly or have all of the features that ABBYY FineReader has, so you will probably want to use ABBYY if it is available to you. However, I find gImageViewer a pretty good program that can meet most general OCR needs.

Statistical Analysis at the Scholarly Commons

The Scholarly Commons is a wonderful resource if you are working on a project that involves statistical analysis. In this post, I will highlight some of the great resources the Scholarly Commons has for our researchers. No matter what point you are at in your project, whether you need to find and analyze data or just need to figure out which software to use, the Scholarly Commons has what you need!

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Blogs for All: Making Accessible Posts in WordPress

As blogs continue to provide a low barrier to entry for authors to distribute content in all avenues from academia to entertainment, it is important to make sure that blog posts are just as easy to access for readers. Here at Illinois, our blogs are run through publish.illinois.edu, a WordPress-based publishing service. As we try to improve our services for all, especially our remotely available services, I wanted to use this week’s Commons Knowledge post to discuss improving accessibility in WordPress. Within the platform, making more accessible blog posts isn’t difficult nor does it require much time; however, building these practices into our workflow allows for posts to be accessible—not just for some, but for all.

Wordpress logo - a gray W in a circle

Continue reading

Scholarly Commons Software: Open Source Alternatives

Hello from home to all my fellow (new) work-from-homers!

In light of measures taken to protect public health, it can feel as though our work schedules have been shaken up. However, we are here to help you get back on track and the first thing to do is make sure you have all the tools necessary to be successful at home.

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Choosing an OCR Software: ABBYY FineReader vs. Adobe Acrobat Pro

What is OCR? OCR stands for Optical Character Recognition. This is the electronic identification and digital encoding of typed or printed text by means of an optical scanner or a specialized software. Performing OCR allows computers to read static images of text to convert them to readable, editable, and searchable data on a page. There are many applications of OCR including the creation of more accessible documents for the blind and visually-impaired, text/data mining projects, textual comparisons, and large-scale digitization projects.

There are a different software options to consider when you are performing OCR on you documents and it can be challenging to understand which one is best for you. So let’s break it down. Continue reading

Stata vs. R vs. SPSS for Data Analysis

As you do research with larger amounts of data, it becomes necessary to graduate from doing your data analysis in Excel and find a more powerful software. It can seem like a really daunting task, especially if you have never attempted to analyze big data before. There are a number of data analysis software systems out there, but it is not always clear which one will work best for your research. The nature of your research data, your technological expertise, and your own personal preferences are all going to play a role in which software will work best for you. In this post I will explain the pros and cons of Stata, R, and SPSS with regards to quantitative data analysis and provide links to additional resources. Every data analysis software I talk about in this post is available for University of Illinois students, faculty, and staff through the Scholarly Commons computers and you can schedule a consultation with CITL if you have specific questions.

Short video loop of a kid sitting at a computer and putting on sun glasses

Rock your research with the right tools!


STATA

Stata logo. Blue block lettering spelling out Stata.

Among researchers, Stata is often credited as the most user-friendly data analysis software. Stata is popular in the social sciences, particularly economics and political science. It is a complete, integrated statistical software package, meaning it can accomplish pretty much any statistical task you need it to, including visualizations. It has both a point-and-click user interface and a command line function with easy-to-learn command syntax. Furthermore, it has a system for version-control in place, so you can save syntax from certain jobs into a “do-file” to refer to later. Stata is not free to have on your personal computer. Unlike an open-source program, you cannot program your own functions into Stata, so you are limited to the functions it already supports. Finally, its functions are limited to numeric or categorical data, it cannot analyze spatial data and certain other types.

 

Pros

Cons

User friendly and easy to learn An individual license can cost
between $125 and $425 annually
Version control Limited to certain types of data
Many free online resources for learning You cannot program new
functions into Stata

Additional resources:


R logo. Blue capital letter R wrapped with a gray oval.

R and its graphical user interface companion R Studio are incredibly popular software for a number of reasons. The first and probably most important is that it is a free open-source software that is compatible with any operating system. As such, there is a strong and loyal community of users who share their work and advice online. It has the same features as Stata such as a point-and-click user interface, a command line, savable files, and strong data analysis and visualization capabilities. It also has some capabilities Stata does not because users with more technical expertise can program new functions with R to use it for different types of data and projects. The problem a lot of people run into with R is that it is not easy to learn. The programming language it operates on is not intuitive and it is prone to errors. Despite this steep learning curve, there is an abundance of free online resources for learning R.

Pros

Cons

Free open-source software Steep learning curve
Strong online user community Can be slow
Programmable with more functions
for data analysis

Additional Resources:

  • Introduction to R Library Guide: Find valuable overviews and tutorials on this guide published by the University of Illinois Library.
  • Quick-R by DataCamp: This website offers tutorials and examples of syntax for a whole host of data analysis functions in R. Everything from installing the package to advanced data visualizations.
  • Learn R on Code Academy: A free self-paced online class for learning to use R for data science and beyond.
  • Nabble forum: A forum where individuals can ask specific questions about using R and get answers from the user community.

SPSS

SPSS logo. Red background with white block lettering spelling SPSS.

SPSS is an IBM product that is used for quantitative data analysis. It does not have a command line feature but rather has a user interface that is entirely point-and-click and somewhat resembles Microsoft Excel. Although it looks a lot like Excel, it can handle larger data sets faster and with more ease. One of the main complaints about SPSS is that it is prohibitively expensive to use, with individual packages ranging from $1,290 to $8,540 a year. To make up for how expensive it is, it is incredibly easy to learn. As a non-technical person I learned how to use it in under an hour by following an online tutorial from the University of Illinois Library. However, my take on this software is that unless you really need a more powerful tool just stick to Excel. They are too similar to justify seeking out this specialized software.

Pros

Cons

Quick and easy to learn By far the most expensive
Can handle large amounts of data Limited functionality
Great user interface Very similar to Excel

Additional Resources:

Gif of Kermit the frog dancing and flailing his arms with the words "Yay Statistics" in block letters above

Thanks for reading! Let us know in the comments if you have any thoughts or questions about any of these data analysis software programs. We love hearing from our readers!

 

Featured Resource: QGIS, a Free, Open Source Mapping Platform

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.

the words "GIS day" in a stylized font appear below a graphic of a globe with features including buildings, trees, and water

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!

the QGIS logo

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. 

For more help, stop by to take a look at one of the QGIS guidebooks in our reference collection, or send us an email at sc@library.illinois.edu!

Have you made an interesting map in QGIS? Send us pictures of your creations on Twitter @ScholCommons!

 

A Brief Explanation of GitHub for Non-Software-Developers

GitHub is a platform mostly used by software developers for collaborative work. You might be thinking “I’m not a software developer, what does this have to do with me?” Don’t go anywhere! In this post I explain what GitHub is and how it can be applied to collaborative writing for non-programmers. Who knows, GitHub might become your new best friend.

Gif of a cat typing

You don’t need to be a computer wiz to get Git.

Picture this: you and some colleagues have similar research interests and want to collaborate on a paper. You have divided the writing work to allow each of you to work on a different element of the paper. Using a cloud platform like Google Docs or Microsoft Word online you compile your work, but things start to get messy. Edits are made on the document and you are unsure who made them or why. Elements get deleted and you do not know how to retrieve your previous work. You have multiple files saved on your computer with names like “researchpaper1.dox”, “researchpaper1 with edits.dox” and “research paper1 with new edits.dox”. Managing your own work is hard enough but when collaborators are added to the mix it just becomes unmanageable. After a never ending reply-all email chain and what felt like the longest meeting of all time, you and your colleagues are finally on the same page about the writing and editing of your paper. It just makes you think, there has got to be a better way to do this. Issues with collaboration are not exclusive to writing, they happen all the time in programming, which is why software-developers came up with version control systems like Git and GitHub.

Gif of Spongebob running around an office on fire with paper and filing cabinets on the floor

Managing versions of your work can be stressful. Don’t panic because GitHub can help.

GitHub allows developers to work together through branching and merging. Branching is the process by which the original file or source code is duplicated into clone files. These clones contain all the elements already in the original file and can be worked in independently. Developers use these clones to write and test code before combining it with the original code. Once their version of the code is ready they integrate or “push” it into the source code in a process called merging. Then, other members of the team are alerted of these changes and can “pull” the merged code from the source code into their respective clones. Additionally, every version of the project is saved after changes are made, allowing users to consult previous versions. Every version of your project is saved with with descriptions of what changes were made in that particular version, these are called commits. Now, this is a simplified explanation of what GitHub does but my hope is that you now understand GitHub’s applications because what I am about to say next might blow your mind: GitHub is not just for programmers! You do not need to know any coding to work with GitHub. After all, code and written language are very similar.

Even if you cannot write a single line of code, GitHub can be incredibly useful for a variety of reasons:
1. It allows you to electronically backup your work for free.
2. All the different versions of your work are saved separately, allowing you to look back at previous edits.
3. It alerts all collaborators when a change is made and they can merge that change into their own versions of the text.
4. It allows you to write using plain text, something commonly requested by publishers.

Hopefully, if you’ve made it this far into the article you’re thinking, “This sounds great, let’s get started!” For more information on using GitHub you can consult the Library’s guide on GitHub or follow the step by step instructions on GitHub’s Hello-World Guide.

Gif of man saying "check it out" and pointing to the right.

There are many resources on getting started with GitHub. Check them out!

Here are some links to what others have said about using GitHub for non-programmers:

What’s In A Name?: From Lynda.com to LinkedIn Learning

LinkedIn Learning Logo

Lynda.com had a long history with libraries. The online learning platform offered video courses to help people “learn business, software, technology and creative skills to achieve personal and professional goals.Lynda.com paired well with other library services and collections, offering library users the chance to learn new skills at their own pace in an accessible and varied medium. 

However, in 2015—twenty years after its initial launch—Lynda.com⁠⁠ was purchased by LinkedIn. A year later, Microsoft purchased LinkedIn for $26.2 billion. And now, in 2019, Lynda.com content is available through the newly-formed LinkedIn Learning.

Charmander evolving into Charmeleon

Sometimes, evolution is simple (like when it gets you one step closer to an Elite-Four-wrecking Charizard). Sometimes, it’s a little more complicated (like when Microsoft buys LinkedIn which just bought Lynda.com).

The good news is that this change from Lynda.com to LinkedIn Learning includes access to all of the same content previously available. This means that, through the University Library’s subscription, you still have access to courses on software like R, SQL, Tableu, Python, InDesign, Photoshop, and more (many of which are available to use on campus at the Scholarly Commons). There are also courses on broader, related topics like data science, database management, and user experience

Setting up your own personal account to access LinkedIn Learning is where things get just a little trickier. As a result of the transition from Lynda.com to LinkedIn Learning, users are now strongly encouraged to link their personal LinkedIn accounts with their LinkedIn Learning accounts. Completing courses in LinkedIn Learning will earn you badges that are automatically carried over to your LinkedIn account. However, this additional step—using a personal LinkedIn account to access these course—also makes the information about your LinkedIn Learning as public as your LinkedIn profile. Because Lynda.com only required a library card and PIN, this change in privacy has received push-back from libraries and library organizations across the country.

Obi-Wan Kenobi looking confused with caption reading [visible confusion]

This new policy change doesn’t mean you should avoid LinkedIn Learning, it just means you should use it with care and make an informed decision about your privacy settings. Maybe you want potential employers to see what you’re proactively learning about on the platform, maybe you to keep that information private. Either way, you can get details on setting up accounts and your privacy settings by consulting this guide created by Technology Services.

LinkedIn Learning can be accessed through the University Library here.