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Maintained by: Elisa E. Beshero-Bondar (eeb4 at Creative Commons License Read the course description and syllabus in TEI XML. Last modified: Monday, 06-Jan-2020 22:23:17 UTC. Powered by firebellies.

Spring 2020: Classes meet M W F 2 - 2:50 PM in 136 McKenna Hall

Syllabus: Spring 2020

Course Enrollment and Electives Info:

Instructor Team

Course Projects

Explanatory Guides and Exercises: Complete List

Class Web Resources

All the Tools You Need As We Begin:

Download and install the following software on your own personal computer(s) on or before the first day of class. These software tools are available in our campus computing labs, too.

  1. All students: <oXygen/> XML Editor. The University of Pittsburgh has purchased a site license for this software, which is installed in the Pitt computer labs on multiple campuses, and it’s in use in courses here at Greensburg and at Oakland. The license also permits students enrolled in the course to install the software on their home computers (for course-related use only). When installing this on your own computers, you will need the license key, which we have posted on our course Announcements section of Canvas.
  2. All students require a good means of secure file transfer (SFTP) for homework assignments and projects (also available in the campus computer labs). There are several good options available. We recommend you download and install on your own computers one (or more) of the following, depending on your platform: (Feel free to experiment with these and others!)
    • Windows users: one of the following FTP clients—the functionality is similar:
      • FileZilla (This is our favorite client because it behaves the same way across platforms.)
      • WinSCP (This is one we used for a long time, since the 1990s, but we now use SSH and Filezilla more frequently.)
      • SSH Secure Shell Client
    • Mac users:
    • Linux users: You probably don’t need to install anything, but look at how your system handles secure file transfer (SFTP). (FileZilla or other clients designed for Linux environments.)
  3. Read the Course Description and this Syllabus page to see how this course works on a day-to-day basis.
  4. This course fulfills general education requirements in Q2, NS, SS, and HM, and it fulfills a core requirement for the Digital Studies Certificate at Pitt-Greensburg. Think about where this course might fit in your academic career, and how you might apply the skills you learn here.
  5. No coding experience? Don’t worry! You are in very good company. We don’t expect any of you to have written a line of computer code before now. Past students in this course who never saw anything like markup or XML code have designed projects (like these) and even spoken about them at an undergraduate conference! You’ll help continue some of these projects we’ve started, and you’ll learn to build and create digital tools for yourself with skills we hope you will keep developing.

Coding and Data Visualization: Course Description

This course is all about doing interesting things with texts using computers and digital technology. In this course, you will learn methods for marking, extracting, and analyzing data from digital documents to produce visualizations such as graphs, charts, diagrams, maps, which you will design in the context of real projects. This course is meant to be complementary with the Coding and Digital Archives course, but where the emphasis in that course is on curating and preparing reading views of documents, this course concentrates on analyzing data to produce informational graphics. Neither course is meant to be a prerequisite for the other: you may take either one as a beginner. Returning students (in either semester) serve as student instructor-mentors to beginning students for units and assignments they have already completed confidently.

Our class is one of the core courses of Pitt-Greensburg’s Digital Studies Certificate, and it satisifes a range of general education requirements in quantitative reasoning, behavioral sciences, and humanities. That is because this course is distinctively interdisciplinary in engaging formal and quantitative reasoning through computer coding in ways that matter to students in humanities and social sciences who are not training to be computer scientists. Students gain hands-on experience in this course with applying computer coding to represent and investigate cultural materials. As we design projects together, you will gain practical experience in editing and you will certainly fine-tune your precision in writing and thinking. You will also be learning in an openly collaborative environment (as professional coders learn and work) with an emphasis on building sustainable and freely accessible resources on the public web.

Students who complete this course will gain skills in practical hands-on programming, digital project management, and web development. Their digital projects will distinguish them as investigators and makers, able to wield computers creatively and effectively for human interests. Your success will require patience, dedication, and regular communication and interaction with us, working through assignments on a daily basis. Your success will not require perfection, but rather your regular efforts throughout the course and your documenting of problems when your coding doesn’t yield the results you want. Homework exercises are a back-and-forth, intensive dialogue between you and your instructors, and we plan to spend a great deal of time with you individually over these as we work together. Our guiding principle in developing assignments and working with you is that the best way for you to learn and succeed is through regular practice as you hone your skills. Our goal is not to make you expert programmers (as we are far from that ourselves). Instead, we want you to learn how to apply coding technologies for your own purposes, how to track down answers to questions, how to think your way algorithmically (step-by-step) through problems to find good solutions.

Survey of Coding Technologies Covered:

We work primarily with eXtensible Markup Language (XML) because it is a powerful tool for modelling texts that we can adapt creatively to our interests and questions. XML represents a standard in adaptability and human-readability in digital code, and it works together with related technologies with which you will gain working experience: You’ll learn how to write XPath expressions: a formal language for searching and extracting information from XML code which serves as the basis for transforming XML into many publishable forms. You’ll learn to write XSLT: a programming “stylesheet” transforming language designed to convert XML to publishable formats. In this course, you will also learn XQuery, an XPath-based language designed to query XML as a database, and we will use XQuery to extract information and plot it in charts in graphs in Scalable Vector Graphics (SVG). You will learn how to design your own systematic coding methods to work on projects, and how to write your own rules in schema languages (like Schematron and Relax-NG) to keep your projects organized and prevent errors. Since one of the best and most widely accessible ways to publish XML is on the worldwide web, you’ll gain working experience with HTML code (a markup language that is a kind of XML), styling HTML with Cascading Stylesheets (CSS), and adding dynamic features to your website with JavaScript.

Learning Objectives:

Optional Textbook:


Homework Exercises (30%):

To keep up with this class, you must work on exercises regularly. Each day will involve some small assignment, to prepare you for the next of class, and to help you to build your course project. Students must complete on time at least 90% of all assigned homework exercises in order to pass the course. For students who complete the 90% requirement, the homework taken all together, is worth 30% of your course grade.

Coding assignments: Coding exercises in this course are about your active learning, and not—as in other courses—a way of testing whether you have already learned something we covered in class or in an assigned reading. You may often need to look up how to do something that you don’t already know how to do. Often, there will be multiple ways of accomplishing the task and we are not simply looking for you to do things perfectly in just one way. We are instead looking for a record of your learning process as you take on a challenge. Documenting problems is key to learning, and sometimes just writing out what you are trying to do helps lead you to a solution! When we post solutions for homework assignments, part of your homework may be to write a comment to review what you missed and assessing what you needed to do for the correct answer. There may be times when you don’t get the result you want in the homework, and that is to be expected! In those cases you can still get full credit for the assignment if you’ve made a serious attempt and if you submit, along with your code, a description of what else you tried, what results you expected, what results you got, and what you think went wrong. Getting stuck is part of the learning process and the instructors will be happy to help unstick you as long as you’ve described your understanding of the problem and your attempts to resolve it on your own.

The instructors will read and evaluate all student homework, and will post an assessment in the Canvas Grade Center. Coding assignments are assessed as check plus, check, and check minus, or redo. Don’t think of these as grades, since they all receive full credit; they are feedback, for learning purposes, about how well you engaged with the assignment. If you have not engaged with the assignment adequately (whether that means solving the tasks or discussing the coding obstacles you encountered and how you dealt with them), we will ask you to meet with us to review the issues and then complete a followup (redo) task in order to receive credit. For assignments with posted solutions, we invite you to review the posted solution on GitHub and comment on it (we will show you how to do this) to address something you learned from the solution or did in a different way. For some assignments where we review posted solutions and line-comments together in person or in class, we will write back to you with individual comments only if your specific submission raises an issue that we don’t address elsewhere. If we don’t return your assignment, that means that we have nothing to add to our posted solution, but should you have any specific questions after you’ve read our posted solution, please ask the instructors.

Issue posts: Throughout the course, we’ll assign discussion posts on our class GitHub site in which you will respond to online readings or evaluate web resources. Your posting should do more than summarize the article or site (which you could just do by skimming or reading the first paragraph), but should demonstrate a thoughtful reflection on specific ideas and issues. When evaluating a web resource, don’t simply praise or condemn it without going into details about why a key component is effective or poorly designed. Good posts demonstrate care and reflection, and you may choose to respond to the overarching ideas of a piece, or to selected details of specific interest. These posts are scored as check plus, check, and check minus.

Participation: In Class and on the DH-ClassHub (15%):

Coding and programming in real life is a social activity, and professionals in the real world aren’t “know-it-all” experts who work alone, but rather are tuned into discussion boards and regularly ask and answer questions to stay sharp and to learn from their community. In this class, we want you to work together and talk to each other and your instructors as your community resource, so we have built this into our course participation grade as a formal expectation. Beginning by week two, we’ll expect each student to post at least once per week on our course GitHub repo, and we strongly encourage you to do more than this minimum. Earn an A in participation by asking questions, making suggestions, and sharing helpful resources you’ve found. Help each other out by trying to answer questions on GitHub (and read the instructor posts too as we wade in to help). Your instructors will likely be dominating the class time as we model concepts and methods, so the GitHub Issues board gives the students a good space to form into a coding community to help each other and reflect together. Also, if you have a question about an assignment, always think of our GitHub Issues board as your first resource to check for helpful hints and to post your questions, because others may have the same question and answers are best shared! Of course you may e-mail us, but we really prefer you go the discussion board first, and doing so is, after all, worth course credit as your participation grade.

Tests (15%):

As scheduled throughout the course there will be several (probably about five or six) tests on the various kinds of coding we are learning in the course, and we will drop the lowest grade. All but the first test will be take-home and assigned over a weekend. They are open-book, open notes, but they must be completed individually and are designed to demonstrate that you have learned from the class material, coding assignments, and posted solutions. Tests may resemble homework assignments, but unlike homework exercises, these are given letter grades. These are given grades because they are evaluative and involve demonstrating what you have learned after we have finished a coding unit.

Project (40%):

Throughout the semester you will be working as part of a team on a course project. Early in the semester each student posts a proposal for a semester project to work with a text (or collection of texts) in the public domain and a set of research questions to explore in a coding project. Teams will form around a selection of these projects in mid-September and begin work, performing document analysis, developing and implementing a system of markup and project rules, marking up text following that system, writing programs to conduct research and create a resource to share on a public website you will develop together that represents your investigation and your conclusions. Each project team must meet regularly together and with a project mentor (one of the instructor team) outside of class for project planning and discussion. Each of the project components described below adds up to 40% of your grade for the course.

Project Checkpoints There will be a series of project checkpoints to complete, by set due dates throughout the semester. Each is worth 5% of the final course grade (a total of 20%) and a letter grade on the following scale: exceeds target (A+), meets target (A), some progress (B), negligible progress (C), no progress(F). Each checkpoint will expect you to complete a stage of serious work on the course project with your project team. Project Checkpoints are met using the Issues and/or Projects tabs on your project GitHub repository and by posting files on the project website on newtFire.

The course project develops throughout the semester, but is fully assembled in the final weeks of the course and submitted in two places, through code and documentation shared in your GitHub repository and on your project website due in Finals Week. Projects are evaluated as a team effort, but if unequal effort is observed, project members may receive different project grades accordingly. The Final Project grade is worth 20% of the course grade.

Grading Scale:

Grades are calculated and posted on Canvas, and follow this standard scale: A: 93-100%, A-: 90-92%, B+: 87-89%, B: 83-86%, B-: 80-82%, C+: 77-79%, C: 73-76%, C-: 70-72%, D+: 67-69%, D: 60-66%, F: 59% and below. In taking the course on a S / NC (pass-fail) basis, students must earn a C to receive Satisfactory credit. We give G grades (incomplete) at our discretion and only in conformity with the University Registrar policy:

Course Policies:

Each day we are covering material that builds on earlier material and assignments, so your success depends upon regular attendance and completing each assignment on time.


We strictly require your attendance, as it is not only a setback to yourself but to the entire class and the success of our projects if students are repeatedly absent. Students must attend at least 90% of our class meetings in order to pass the course (that is, a maximum of four absences for any reason). Late arrival—particularly a pattern of repeated late arrivals—may be counted as absences at our discretion. To be considered attending for a class period, you must be present in the classroom by the beginning of class and until class is dismissed. For your own sanity, do not miss two consecutive classes. If you are experiencing a genuine emergency or crisis, alert us and provide documentation. (We do not want you to attend class if you have a fever or flu-like symptoms! If you are a Greensburg student and wish to be excused from two or more consecutive class meetings due to your own documented illness, please contact one of the following: the Office of the Vice President for Academic Affairs, Prof. Jackie Horrall (724-836-7482 or jhorrall at, our Campus Health Center (Pamela Reed, 724-836-9947 or pmr20 at, or the Director of Counseling, Gayle Pamerleau (gaylep at, who can then officially alert all of your professors.


Your daily homework for this course is time-sensitive! Coding assignments, response papers, and other homework exercises must be uploaded to CourseWeb (or to Box, or the Sandbox server as specified), by the date and time indicated by the instructors. Homework assignments will be posted online to our class website and linked from our schedule, so students who miss class are nevertheless expected to consult the schedule and submit assignments on time. Because we post and share answers to homework exercises after submission deadlines, we will not accept late homework submissions. In order to pass the course, students must submit at least 90% of the regular homework assignments, and complete at least 90% of the work in each component of the course.

Exam Policy:

Similarly, because we will be posting answers or sharing them in class, we do not give make-up examinations or allow people to write exams after the solutions are posted. However, we will drop your lowest exam score for the class, so that you may miss one exam without penalty.

Classroom Courtesy:

Our class is fast paced, and requires that we all be making the best use we can of our in-person class sessions. Arriving late and leaving early disrupts the important collective mental activity of class. So does in-class texting and checking your cell phone. While class is in progress, talking disruptively, leaving the classroom, texting or using a cell phone or computer, reading a newspaper, or other distracting behavior will be actively discouraged, and may result in a deduction in your Participation grade. Please respect what we do in the classroom: attend class regularly, and come prepared to contribute your questions and ideas.


Each student is issued a University email address ( upon admission. This email address may be used by the University for official communication with students. Students are expected to read email sent to this account on a regular basis. Failure to read and react to University communications in a timely manner does not absolve the student from knowing and complying with the content of the communications. The University provides an email forwarding service that allows students to read their email via other service providers (e.g., Hotmail, AOL, Yahoo). Students who choose to forward their email from their address to another address do so at their own risk. If email is lost as a result of forwarding, it does not absolve the student from responding to official communications sent to their University email address. To forward email sent to your University account, go to, log into your account, click on Edit Forwarding Addresses, and follow the instructions on the page. Be sure to log out of your account when you have finished. (For the full Email Communication Policy, go to

Academic Integrity

Source Citation and Plagiarism: One goal of our course is to reflect on how best to cite sources in digital contexts. We will consider how and why such citations differ from documenting printed texts. We will also consider the ease and frequency with which digital texts and graphics are plagiarized on the worldwide web, and discuss how the omission of source citations detracts from the authority of a digital information resource. We expect you to practice mindful source citation, and plagiarism on your part will have very serious consequences.

Plagiarism falsely represents another source’s words or ideas as your own, and, if you commit plagiarism in this course, you will receive a final course grade of F and be reported to the Vice President of Academic Affairs. Representing the voice of another individual as your own voice constitutes plagiarism, however generous that person may be in “helping” you with an assignment. Turning in an assignment generated collectively under the name of a single individual is considered plagiarism. When instructed to collaborate on a project, project collaborators share collective authorship and should identify themselves directly as a team. To avoid plagiarism, cite your sources whenever you quote, paraphrase, or summarize material, or use digital images from any outside source (including websites, articles, books, course readings, Canvas postings, or someone else’s notes). When using the “copy” and “paste” features as you read and research, be sure that you are carefully marking that these passages are unprocessed from their source, so that you know to process it later. Forgetting to do so not only produces sloppy work but (whether you intended it or not) results in a false representation. As long as you make a good faith and clear effort to cite your sources, you will not be faulted for plagiarism, but your work will be penalized if citations are inaccurate, unclear, or lack important information. Cheating on exams or exercises will also receive a final course grade of F and will be reported to the Vice President of Academic Affairs.

Disability Services:

If you have a disability for which you are or may be requesting an accommodation, please contact both your instructor and the Director of the Learning Resources Center, Dr. Lou Ann Sears, Room 240 Millstein Library Building (724) 836-7098 (voice) or los3 at as early as possible in the term. The Learning Resources Center will verify your disability and help to determine reasonable accommodations for this course.


We gratefully acknowledge David Birnbaum’s Digital Humanities course as our starting point and resource for much of our development. Other useful resources include:

Projects and Sites That Inspire Us