Spring 2025 Syllabus (Schedule) Classes meet M W F 10:10
- 11am in Lilley Library 006.
This contains a detailed explanation of course policies and the basis for
grades.
This link jumps to the closest day to today's date. Review the schedule as we get
started to get a sense of how this course will work on a daily basis.
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.
- <oXygen/>. (You will probably have this installed from DIGIT
100 or 110.) The DIGIT program has purchased a site license for this
software, which is installed in Burke 153, Kochel 77, the Lilley Library
computers, and Witkowski 109, as well as the computer labs in Hammermill.
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.
- AntConc:
(You may have this installed from DIGIT 100.) Free corpus text analysis
tool.
- We will ask you to install Python version 3.8 or higher on your computer,
and install PyCharm Edu to assist in learning and writing Python code with
syntax checking. Follow instructions and links from Pycharm ( https://www.jetbrains.com/help/pycharm/quick-start-guide.html#meet
) paying attention to what you need for your own computer systems. Feel free
to download and explore Pycharm Edu on your own before we start working with
it together: https://www.jetbrains.com/pycharm-edu/. Also, configure Anaconda so
it is available to work within Pycharm following this guide: https://www.jetbrains.com/help/pycharm/conda-support-creating-conda-virtual-environment.html.
(We will provide guidance on this in class.)
- Zoom: Make sure your Zoom installation is up-to-date, and
you are ready to connect. Sometimes we will record portions of class
meetings and tutorial sessions for future reference to share over Zoom. Look
for these in Canvas Announcements and use the Zoom menu option in Canvas to
access these meetings.
- We will use GitHub for for sharing code and for project management. Create
an account (choose the free options) at the https://github.com and install the GitHub client software for your
operating system on your own machine on your computer. (We will explain how
to use git and GitHub this in our course.)
- We will use the Slack chat platform for discussion and for asking questions
(see https://slack.com/help/articles/218080037-Getting-started-for-new-members).
Download and install the Slack client, configuring your account to use use
your Penn State email address (the official address, which looks like
xyz123@psu.edu, and not an alias based on your name that you may have set
up), so you can join our Slack workspace: DIGIT-coders. When you receive an
invitation to join this workspace you should accept.
- Later in the semester we may ask you to install a local copy of the eXist-db
XML database, which you can download from https://exist-db.org/.
- Not much coding experience? Don’t worry! 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 academic conferences! You
will learn to develop your own digital tools and how to manage digital
projects as teamwork.
Class Web Resources:
| Week 1 |
Class topics
|
Do before class
|
M 01-13
|
- Welcome! Intro to the course and theme of text analysis and
re-mediation, and visualization.
- Hands-on warm-up with Scaleable Vector Graphics: SVG in oXygen
XML Editor.
- Genuary activities.
|
Respond to Dr. B’s Canvas announcement,
install/update oXygen XML Editor. |
W 01-15
|
Data to numbers to shapes with legible, human-readable SVG
code. |
- Install/update oXygen XML Editor if you have not done so
already.
- SVG Exercise 1: Orientation
- Join / reactivate the Digit Coder's Slack
|
F 01-17
|
- Class protocols for handling code files: GitHub and version
controlled file management. Making a branch on the
textAnalysis-Hub. Review adding, pulling, adding, committing,
and pushing.
- Gentle XPath orientation / review: Pulling data from Digit 110
projects to plot in SVG
|
|
| Week 2 |
Class topics
|
Do before class
|
M 01-20
|
Martin Luther King Day: No classes. |
... |
W 01-22
|
Git Branching and Pull Requests |
SVG + Git Branching Exercise |
F 01-24
|
Orientation: Programming your visual design: XSLT to SVG |
SVG Exercise 3
|
| Week 3 |
Class topics
|
Do before class
|
M 01-27
|
- Contemplating the flow of text to image via code.
- Improving designs / layout on websites: XSLT to SVG
- Preview Regular Expressions (Regex) unit
|
XSLT to SVG Orientation Exercise, with Git PR Practice
|
W 01-29
|
- Structuring and regularizing data from documents with
markup.
- Introduce document analysis with Regular Expressions: the dot,
the backslash, numbers (
\d, repetition indicators,
matching on lines, and autotagging. Greedy and non-greedy
matching.
- Preview Intro to Regular Expressions
- Choosing a license for
your project GitHub repo.
|
XSLT to SVG Orientation Exercise 2, with Git PR
Practice
|
F 01-31
|
- Regular Expressions: Thinking (and writing) in markdown,
algorithmically. The fine art of
Looking
Stuff Up in the Regex tutorials: Character sets, symbols,
capturing groups.
|
-
XSLT to SVG Orientation Exercise 3, with Git PR
Practice
- Watch Regex Orientation Videos:
-
Regex Exercise 1
|
| Week 4 |
Class topics
|
Do before class
|
M 02-03
|
Regex greedy and non-greedy matches. |
Regex Exercise 2. As you work on this, consult our
Intro to Regular Expressions and the Regular Expressions Quick Start. |
W 02-05
|
Regex in XSLT / xsl:analyze-string |
-
Regex Exercise 3
- (By the end of the day): Five Days of Git: Part
1: Record completion on Canvas as part of GitHub
Test
|
F 02-07
|
- Semester project ideas
- Validity for a project: what is a schema? What is schema
validation?
- Validation for Google Sheets
- How to write a Relax NG schema (review for some / intro for
others)
|
-
Regex Exercise 4: applying
xsl:analyze-string
- Five Days of Git: Part 2: Record completion on
Canvas as part of GitHub Test
|
| Week 5 |
Class topics
|
Do before class
|
M 02-10
|
- Good projects: ideas, sources, teamwork expectations:
discussion
- Relax NG: data types and mixed content
- Troubleshooting and debugging Relax NG
|
- Relax NG Exercise 1 (before class)
- Five Days of Git: Part 4: Record completion on
Canvas as part of GitHub Test
|
W 02-12
|
-
Introduce Regex Test
- Relax NG schemas for project management
- Project ideas
|
- Relax NG Exercise 2 (before class)
- Five Days of Git: Part 5: Record completion on
Canvas as part of GitHub Test
|
F 02-14
|
- Review / discuss project proposal assignment
- Relax NG: Common problems (mixed content, repetition
indicators). Simplifying your code. Documenting your
schemas
|
- Respond to Requirements to Initiate Semester Projects
- Project proposals part 1: Post proposal ideas
in Slack Project Proposals + Discussion
-
Relax NG Exercise 3
|
| Week 6 |
Class topics
|
Do before class
|
M 02-17
|
Form project teams!
|
- Project proposals part 2: Respond to Slack
Project Proposals + Discussion before class
-
Complete Regex Test
|
W 02-19
|
- GitHub Pages review / Project websites
- Setting up bash profiles, shell script aliases
- Looking ahead: Building project text corpora: Resources and
approaches to
scraping
- Copyright, proprietary ownership, legality issues
|
- Project Milestone 1: Set up Project GitHub +
Slack channel, arrange regular team meeting times
|
F 02-21
|
- Shell scripts
- Checking / troubleshooting Java installations
- TBD: XPath / XQuery or Web Scraping Intro
|
- Shell Script Alias assignment
- Part 1: Installations for Java, XProc / ixml
|
| Week 7 |
Class topics
|
Do before class
|
M 02-24
|
Document analysis and XSLT for Web Scraping |
- TBD: XPath / XQuery or Web Scraping Exercise
- Installation prep for XProc and ixml: Install CoffeePot and
Markup Blitz on your local machine, following our instructions
at Configuring XProc and ixml processors. We recommend CoffeePot
for new users because it offers more debugging options than
Markup Blitz, but Markup Blitz is likely to be faster (and often
much faster) with very large input files.
|
W 02-26
|
- Document analysis and XSLT for Web Scraping
- Prep for ixml
|
- Read Norm Tovey-Walsh’s Invisible XML introductory tutorial and annotate with
Hypothes.is
- Install either XML Calabash 3 or MorganaXProc-IIIse on your
local machine, following our instructions at Configuring XProc
and ixml processors. You will not be able to complete the XProc
portion of this unit if you have not installed at least one of
these processors.
|
F 02-28
|
Class on Zoom: Special guest Dr. David Birnbaum
introduces Invisible XML (ixml): crafting your own grammars |
- Complete readings / annotations
- Test installations of Coffee Pot / Markup Blitz for today. (For
Monday, you'll need Calabash or Morgana)
|
| Week 8 |
Class topics
|
Do before class
|
M 03-03
|
Class on Zoom: Dr. David J. Birnbaum discusses XProc 3.0
Dr. B is attending a Symposium in Tokyo this
week.
|
|
W 03-05
|
Class on Zoom: Dr. David J. Birnbaum on Using Invisible
XML and XProc 3.0 together
- Class on Zoom: Topic [TBD]: Eliminating ambiguity in ixml. Will
ixml work in my project?
- Building a pipeline with
XProc
|
- Read/annotate the remainder of Martin Kraetke’s XProc 3.0
Tutorial. Your goal is to acquaint yourself with the
content without memorizing it at this stage, so concentrate on
the parts that are likely to be of wide use (especially XSLT
Transformations in XProc), but notice what else is there so that
you can Look Stuff Up as the need arises.
- Complete the
XProc Exercise. Create your own XProc pipeline with at
least two steps. One possibility is to use two XSLT
transformations that are chained together to produce a single
output or two that read the same input and create different
output, but feel free to use non-XSLT steps, as well. Submit
your primary input document (if there is one), your XProc
pipeline document, and any secondary input that your pipeline
may require (e.g., if you have an
<p:xslt>
step that reads an external XSLT stylesheet, include that
stylesheet in your submission).
|
F 03-07
|
Project team workday |
Project Milestone |
Sun 3-09 - Sat 3-15
|
Spring Break
|
Enjoy this week! |
| Week 10 |
Class topics
|
Do before class
|
M 03-17
|
- ixml / XProc vs. Python in projects: Pipelines for text
processing, discussion of next steps
- Checking / troubleshooting Pycharm and Python installations
- Pycharm Edu tutorial work together. Manipulating strings wtih
Python, and Pythonic data structures (lists, tuples,
dictionaries).
|
[TBD] Readings on AI, large language models, word embeddings. |
W 03-19
|
- Python tutorial Q/A: tinkering.
- Python at command line vs. in the Pycharm IDE (or oXygen, VS
Code, etc)
|
- Pycharm Edu tutorials: through Strings
unit (submit evidence of completion via screen
capture on Canvas).
|
F 03-21
|
Getting started with Natural Language Processing (NLP)
with Python: installations/imports: nltk, spaCy, gensim |
Pycharm Edu Community tutorials: Complete the Tutorial
through the Condition expressions unit (submit evidence
of completion via screen capture on Canvas).
|
| Week 11 |
Class topics
|
Do before class
|
M 03-24
|
- Word embeddings and the concept of
cosine similarity : a
humanities perspective
- NLP and large language models, vs. customized, specialized
modeling.
|
Pycharm Edu Community tutorials: Get at least
partway through Classes and Objects unit. |
W 03-26
|
Writing your own Python: Web scraping with Beautiful Soup
and LXML e-tree |
Finish Pycharm Edu Intro to Python tutorials: Classes
and objects, Modules and packages, File input and output. Submit
evidence of completion via screen capture on Canvas. |
F 03-28
|
- Revisiting pipelines: scraping, cleaning, preparing outputs
- NLP: Named Entity Recognition (NER), sentiment analysis:
problems and possibilities
|
Python exercise 1: web scraping / NER and/or
sentiment analysis |
| Week 12 |
Class topics
|
Do before class
|
M 03-31
|
- Moving between
unstructured and structured
documents for data modeling. XQuery and Python pipelines.
|
Python exercise 2: NER / word embeddings (cosine
similarity exercise) |
W 04-02
|
XQuery data
pulls |
XQuery Exercise
1 |
F 04-04
|
Visualizing / troubleshooting / problem solving. Applying
to projects. |
- Python exercise 4: tinkering with / visualizing topic
modeling
- Readings / examples re limits of NLP libraries, language / time
barriers
|
| Week 13 |
Class topics
|
Do before class
|
M 04-07
|
Processing / Visualizing XQuery data |
eXist-dB / XQuery output and Cytoscape
project prep: Installations |
W 04-09
|
- XQuery and Python methods: Network Analysis vs. Topic
Modeling
- XQuery FLWOR statements
- XQuery to TSV or JSON for network analysis
|
Network Analysis Exercise 1:
structured data extraction |
F 04-11
|
- XQuery work on FLWOR statements
- Network statistics: degree, closeness, eigenvector centrality
measures. Path steps. The concept of eccentricity and
distance.
|
Network Analysis Exercise 2:
Cytoscape import / visualization |
| Week 14 |
Class topics
|
Do before class
|
M 04-14
|
Network Analysis: Debugging the source files via
visualization |
Network Analysis Exercise 3:
Refining and exporting network visualizations |
W 04-16
|
- Introduce Python / XQuery Test
- Schematron, Python Assertions, and other debugging methods
|
Looking for trouble: Project
bug-finding exercise |
F 04-18
|
Python and XML handshake: Saxon C Library: XPath, XSLT,
XQuery in Python |
... |
| Week 15 |
Class topics
|
Do before class
|
M 04-21
|
- Project documentation and reflection: What do you know? What is
not certain? Documenting the limits.
- Mermaid.live / markdown to flow diagrams
|
|
W 04-23
|
Return to SVG: Project visualizations |
Documentation: Flow diagram exercise
|
F 04-25
|
Catch-up day. |
Python / XQuery Test
|
| Week 16 |
Class topics
|
Do before class
|
M 04-28
|
Putting it all together: Discussion, analysis,
documentation, web work. Ethics in public-facing digital data
representation. |
Project development sprint, prep for DIGIT Works
presentation |
W 04-30
|
Team sprint day in class |
Project development sprint, prep for DIGIT Works
presentation |
F 05-02
|
Last Day! Project Milestone: Teams deliver DIGIT
Works presentations |
Prep for presentations |
|
Finals Week: May 5 - 9
|
To Complete
|
W 5-07
|
Semester projects due by 11:59pm
Finish developing projects, and send a post to me on GitHub and
Canvas to indicate your team is finished.
|
