Tag Archives: dh

Bandurapedia

The bandura is Ukraine’s national instrument, and a symbol of its independence and resistance. For my personal connection with the bandura, I’ve been taking lessons for a little over a year now. While Ukrainian cultural heritage is being targeted in the war, I wanted to learn how to play a traditional instrument. Recently, I’ve also inherited my godfather’s bandura. To me, playing the bandura connects me to my Ukrainian roots as well as my Ukrainian-American identity. I always perk up at the chance to share this wonderful instrument with others, since my saying “I play the bandura” inevitably results in the question “Oh, what is that?”

This past year, I went to a concert performed by the Women’s Bandura Ensemble of North America (WBENA), of which my teacher is a member. After the show, she came up to me and mentioned that a lot of the songs they played that evening were sad. That moment clicked for me. I began wondering what songs are commonly played, and why? There are so many different types of songs that can be played on the bandura – modern, folk songs, dumy (epic poems), dance songs, religious songs, etc.

So, for my project, I decided to try to map out each of the songs at each of the WBENA’s performances to dig into the context behind them and see what trends arose. Yes, I picked the WBENA because I am the most familiar with this ensemble, but I’m also interested in doing this project with them because A. They are a North American ensemble and B. they are an all-female ensemble. Most bandura ensembles are all-male, and the bandura is traditionally considered a male coded instrument. By doing my project on the WBENA, I wanted to look into and share these two perspectives.

The project itself is a Wax-based website hosted for free on GitHub Pages. I’ve had some previous experience with Wax and wanted the website to continue on without worrying about costs after its completion. I also like how efficient and lightweight the framework is – from a simple csv, you can populate a series of pages on a given collection. Also, given that this project is based around a set of PDF’s and tags, the project doesn’t need anything too complex. Each program will have a song list, and each song in that list will lead to its own page providing context (such as language, composer, genre, themes, etc) and (where applicable) lyrics and an embedded audio or YouTube clip.

For the project, the team would be working very closely with the WBENA, ensuring that they are 100% on board with what we’re publishing and also turning to them as a resource for our research into the songs.

This project is fairly unique – the only similar website that I was able to find in my search is Songs of Truth, a website for the CD recording of the Julian Kytasty bandura concert of the same name. In this site, however, each song has lyrics (where applicable) and the program notes from the concert on its own page. For my site, I’d like to situate each performance in its own time and see what songs and themes repeat. I’d like for people to come and take a deep dive into the repertoire and discover the rich history and bright future of bandura music and the people who play it.

Workshop: Beginning Game Design with Python

Back in October, I attended a workshop from GC Digital Fellow teaching attendees how to use pygame. I had previously used RenPy, a Python framework for writing visual novels, but hadn’t had much luck trying to learn game engines such as Godot. Before the workshop, our instructor, Zach, provided us with a GitHub link with the assets we’d need as well as instructions to download the pygame software. In addition to the images we’d need to create our game – a Frogger clone – we’d find a copy of the finished code, which we would use as a reference when building the game from scratch.

On the day of the workshop, Zach patiently took us through developing each aspect of the game, from the basic variables that we’d need to plug in later to a basic class for objects in the game to character movement. Along the way, he would mention additional measures that we could take on our own time, such as sealing off all four sides of the screen from player movement (meaning that the player can’t go “out of bounds” so to speak). I would often find myself detouring to tweak aspects of my game so that I could gain a deeper understanding of how each part of the code worked.

While we didn’t have time to get through the whole game, we had set up each element of the game and had the final code to reference after the workshop ended. At the end, we were challenged to tweak this final code to create a more interesting game, which I wound up doing. I took the challenge to have the treasure chest (the goal to complete the level) appear in a random position after the first level. I had the enemies increase in speed as the levels progressed at different rates, and moving in different directions. I also changed their movement pattern to loop around when they left the screen rather than bounce back and forth. I added a level counter, and had the game loop back to the first level in the event that the player loses. Through the workshop, I had the foundation and freedom that I needed to truly play and explore in the software.

This workshop, which uses free software and shares assets and instructions through a public repository on GitHub, made me think of our previous discussion on Open Educational Resources. The materials are freely available, and even without the guidance of the workshop, people can learn how to get started with pygame. Furthermore, although the project itself starts out fairly linearly, this form of instruction allows the participants the freedom to pursue their own interests with the software. For me, this is the best way to learn programming – to be able to not only ask your own questions, but answer them as well.

game play screenshot from my game "Frog-man"

Intro to Mapping with QGIS Reflection

On November 20th, I attended the Intro to Mapping with QGIS workshop led by Parisa Sateyesh through CUNY digital fellows. The workshop started with short introductions that included each participant’s interest in mapping with QGIS. I was excited for this workshop as it related to my final project goal of mapping language change in Scotland.  

I enjoyed the introduction to the practical part of the workshop. Ms. Sateyesh discussed how maps are not neutral representations of a universal reality, rather they are social constructs. Maps are tools of communication and are often used to represent relationships of power. Ms. Sateyesh shared her screen to show a fascinating map that questions our assumptions about the United States. It was a map of indigenous territories. Rather than the stark lines and colors separating the colonized states, this map had many overlapping structures and almost translucent colors to allow for the overlapping areas.  

I also enjoyed how Ms. Sateyesh went through chronologically the questions one must ask themselves when one wants to build a map. For example, one must ask “what story do I wish to tell?”, “What is my budget”, “What is my timeline?”, and “Do I want a static or interactive map?” Finally, one must find the proper data files to create a map. At the very least, one ust have a spatial data file that contains the geometry points to populate in QGIS. After that, one must gather the data files relevant to the research question. 

For the practical part of the workshop, we aimed to create a map of NYC that plots 10 popular sites to compare neighborhood data on median household income. To begin, we cleaned our data files and imported the spatial data into QGIS. I quickly found that my computer could not handle running zoom and QGIS at the same time. To continue with the workshop, I closed QGIS and followed along while taking notes on each step. Once it came time to import the secondary location data file, most of my peers had technical difficulties. The facilitators helped by explaining which settings to toggle, but it was unclear why those settings were that way. Overall, the technical difficulties took away some time and we did not end with the map we set out to create. During my mapping praxis project, I played around with QGIS before settling on Tableau for my final product. I found the ‘playing around’ and trial and error to be very effective in helping my understanding of the software. I did not find the workshop to help my understanding as much. 

Overall, I highly enjoyed the conceptual discussion on mapping with QGIS and the organization suggestions provided by the facilitators. 

AI: Humanity’s Frankenstein’s Monster?

In Mary Shelley’s novel Frankenstein; Or, the Modern Prometheus, the titular Victor Frankenstein devotes his college career to manufacturing life. Once he figures out how to accomplish this, he immediately runs out of the house in fear of his own creation. This creation, functionally a newborn, learns from Victor’s neglect and selfishness as well as the fear and disgust of those around him to become a villain to Victor and his family. The creature is not made evil. He instead learns of pain and the desire to lash out as a direct result from the world around him, especially from his creator.

When we think of AI, we think of a brilliant, apathetic, arcane assemblage of math, logic, and technology that can easily outsmart its creator. We imagine HAL 9000, Auto, or Ultron, potentially conscious beings that can turn against us all in the name of following their programming. AI is, in this train of thought, a villain in its own right that we were foolish enough to flip on.

Yet, much like Frankenstein’s Creature, AI isn’t a naturally malevolent force. It also isn’t some objective force inherently better than its creator. It is only as good as the influences that it can learn from. And it learns from us. It needs to be fed data to learn from before it can make any judgments or create any responses, and, as previously discussed in this class, our data is far from objective.

Like the Creature, AI is often seen as this Boogeyman in its own right – solely responsible for stealing jobs and leading to increased oppression. To clarify, AI is absolutely used to do these things, but it is not a sentient force that can be held responsible. As Dr. Lauren Klein points out, corporations and government agencies using AI want it to be perceived as this objective black box to obscure their own goals. Corporations who are looking to use AI to replace jobs would cut down work forces and look for cheaper labor without AI existing. Law enforcement racially profiles citizens with or without facial recognition software. With or without an algorithm, humanity grapples with who owns what information. Furthermore, doctors may not be so inclined to use biased AI note taking software during appointments if they weren’t so bogged down with work from the corporate healthcare model so prevalent in American society. The evils of AI are nothing more than children of the ignorance and greed of those in power.

Conscientious use of AI could result in allowing us to see situations from a different angle (i.e. in the case of Deep Blue or Alpha Go), or to lessen the emotional or physical toll of processing data. On its surface, AI is first and foremost a tool. Unlike the Creature, it doesn’t have an emotional state nor a desire to lash out at the world. It simply does what we tell it to do. If it floods the internet with indiscernible gray text, then, despite the horror stories going into print, that will be the result of people breaking the tap on the faucet for any number of reasons including additional ad space, pure malice, or the innately human desire to simply see what would happen.

The irony in writing this is that I, personally, am most inclined to, like Frankenstein, run out of the house on AI when I can recognize it. I refuse to use AI to generate text, code, or (especially) imagery. For the former, I would like to keep my own skills sharp and make sure that I understand what I am engaging with. For the latter, I refuse to benefit in any way off of the stolen artwork of artists who neither provided consent nor were in any way adequately compensated. With all that being said, even as someone who does her best to avoid AI (and almost certainly fails in some regard), I do believe that we need to analyze the problems with AI at the human source.

Blogpost: (PRAXIS) Text Analysis of the US Constitution using Voyant for the first time.

My Experience with Voyant.

Before resolving to use Voyant, I initially explored Google N-gram but found it “kinda” difficult to navigate for deeper insights. Voyant, on the other hand, felt much more user-friendly, especially with its collection of very helpful features. The Cirrus tool, which creates a word cloud, stood out immediately. It highlights the most frequent words in a corpus, offering a quick, visual snapshot of key terms. Another useful feature was Terms, which displays the frequency of terms across the document, making it easy to track word usage patterns.

Links, a network diagram tool, was particularly helpful for exploring how words co-occur, offering insight into relationships between key concepts. The Reader view displayed the full text, allowing me to highlight and analyze terms within the document directly. Additionally, TermsBerry, a playful bubble chart, allowed me to visualize word frequency and connections in an engaging manner.

Other features, such as Trends, as well as Context and Bubblelines, added even more depth to the analysis. Voyant also provides statistics such as word counts, vocabulary density, and readability scores, making it not only visually engaging but also a quantitative tool for text analysis. Its ability to generate instant visual feedback and downloadable outputs made it ideal for my praxis.

Analyzing the U.S. Constitution

First, as part of the mining, I searched on Google for a txt. file of The US Constitution, and was able to find THE
CONSTITUTION OF THE UNITED STATES OF AMERICA As Amended on www.govinfo.gov which I highlighted all, copied, and pasted into the Voyant reader for analysis.

Using Voyant to analyze the U.S. Constitution was an interesting experience. The corpus was a single document, containing 39,243 words and 1,896 unique word forms. Voyant’s summary statistics revealed key insights, such as a vocabulary density of 0.048, indicating high repetition in language, and a readability index of 10.001, suggesting that the text is accessible to a broad audience.

From the Cirrus tool, it was revealed that the most frequent words in the text were terms like “shall” (1,268 occurrences), “states” (592), “congress” (396), “state” (387), and “president” (370). These terms reflect the U.S. Constitution’s focus on governance, authority, and the distribution of power.

Voyant Cirrus for analysis of The US Constitution

The Links tool allowed me to explore how these terms are connected. For example, it was interesting to see how frequently “states” and “congress” appeared together, highlighting their relationship in the text.

The Reader view allowed me to read the full document while tracking specific words, and TermsBerry provided an interactive visualization of word frequency, which made it easy to explore patterns and relationships between terms.

The Trends (which combines line and bar charts for term frequency over time)

In summary, Voyant offered a visually engaging, data-oriented approach to analyzing the U.S. Constitution, making the analysis both colorful, accessible, and insightful. As a prospective Digital Humanist, I will very likely be using it much more in the future.

Kelechi Iwuagwu – (A Data Analysis & Viz Candidate, CUNY Grad Center)

#Blogpost: Intro to R Workshop.

On Thursday, October 11, 2024, at about 6 pm, I attended an insightful introduction to R workshop organized by Zachary Lloyd and Chen Zou, fellows at the Graduate Center Digital Initiatives (GCDI). The session was aimed at beginners and focused on the essentials of using R, an open-source programming language widely utilized for statistical analysis, data transformation, survey analysis, Machine Learning, etc.

While the w/shop was ongoing, I took minutes of the session, noting down highlights which made me miss some initial concepts in setting up the software for practice. I privately chatted with Chen during the workshop who was truly patient in carrying me along irrespective of my slow-paced learning curve of the tool. We were asked to create a posit account, which enabled us to access R on a cloud for practice.

The session began by distinguishing between R and RStudio, where R serves as the engine – the core programming language, while RStudio serves as the user-friendly interface (UI) where coding, data visualization, and manipulation take place that allows users to interact with R seamlessly. The instructor also introduced foundational concepts like Boolean operations (1/0, TRUE/FALSE, YES/NO), arithmetic functions (+,-, /,*), and vectors – which she mentioned are lists of items or variables of the same type. We also learned basic R syntax such as how to assign values to variables using the “<-” operator and how logical operations like `==` (equal to) and `!=` (not equal to) work in R.

One of the key takeaways was the instructor’s reiteration of the importance of practicing typing out codes instead of often falling for the temptation of copying and pasting, as it helps build muscle memory. The workshop also emphasized the value of making mistakes, which is a major part of the learning process in programming. As she mentioned, “Every programming language takes time to understand. It just takes consistent practice to become the best at it”.

We explored libraries like Tidyverse, a collection of packages designed to simplify data wrangling and visualization in R. Functions such as `view()` and `head()` were demonstrated for examining data, with the former opening a new page in RStudio and the latter displaying default the first six rows of a dataset in the console.

After being shown several examples, we did some practice exercises that enabled us to get a glimpse of how R functions. Most of my colleagues in the workshop seemed to be getting it, as there were multiple correspondences on the Zoom chat bar, which also meant that the workshop was hands-on.

On a final note, the workshop was a good introduction to R, emphasizing the importance of continuous practice and exploration. Whether for data visualization, machine learning, or statistical analysis, R offers a flexible and powerful toolset for data professionals.

Interestingly, the workshop ended at 8:04 pm with a Google digital evaluation form, which made me reflect on the increasing importance of digital documentation and feedback within digital humanities. As a potential digital humanist, every evaluation or rating not completed on a digital platform might as well be considered non-existent, reinforcing the role of digital tools in modern academic and research processes.

– Kelechi Iwuagwu (A Data Analysis & Viz CUNY GradCenter Candidate).

Reflecting on “The Possibly Impossible Research Project”, while embracing Failure for intellectual progress.

In “The Possibly Impossible Research Project,” Rebekah Fitzsimmons and Suzan Alteri introduced first-year students at Georgia Tech to archival research focused on forgotten women authors of science books from the Romantic and Victorian (1770s – 1830s) periods. This collaboration with the Baldwin Library of Historical Children’s Literature aimed to expose students to the systemic marginalization of women in the sciences and challenge the idea that women were historically uninvolved in STEM. At an institute that admitted female students into regular classes only in 1952, this feminist-oriented assignment provided an eye-opening opportunity for students to research the overlooked contributions of women to scientific advancement.

Students encountered numerous frustrations as they struggled to locate biographical information for the assigned authors. The challenge reflected real-world research setbacks, pushing students to ask why so little documentation existed about these intellectual lionesses. Their frustrations often became evident through class discussions and social media exchanges. Alongside conventional research methods, students used digital tools like Twitter and WordPress to document their process, fostering collaboration and building professional research skills.

Through this process, students contributed to the recovery of forgotten histories, shedding light on how women’s writing in science education shaped scientific discourse. This initiative illustrates the value of archival research in undergraduate education, promoting both discovery and the importance of documenting the research journey, even when it’s incomplete.

Moreover, Fitzsimmons’ varying approach challenged the conventional classroom dynamic, where students expect professors to have all the answers. This new model allowed students to grapple with failure and setbacks, learning to persist through “brick walls” and to explore creative solutions—valuable lessons that they will carry into future research and professional endeavors.

What is Digital Humanities? Definitions and Perspectives.

Before diving into the different definitions of Digital Humanities (DH), it’s worth exploring the etymology of the words themselves. Understanding the roots of “digital” and “humanities” should give us insight into the field’s core purpose.

The word digital originates from the Latin word “digitus”, meaning “finger or toe”. Historically, humans used fingers for counting and basic calculations, making them the earliest “digital” tools. Over time, “digital” evolved to describe anything manipulated by numbers or “digits,” which led to its use in technology. Towards the mid-twentieth century in the 30s, “digital” came to signify a system of electronic signals based on binary code (a series of 0s and 1s). In this sense, “digital” refers to the way we now manipulate information electronically, a modern parallel to how fingers once helped us count. 

www.vocabulary.com

Now, combine this with humanities—the study of human culture, history, language, and expression. When put together, Digital Humanities reflects a merging of traditional humanistic study with the power of digital technology to study, analyze, and interpret vast amounts of data, offering new methods of exploring human culture with respect to time.

 Defining Digital Humanities

There isn’t one fixed definition of Digital Humanities; rather, it covers a broad range of approaches that vary based on perspective. At its core, DH uses computational tools to advance the study of humanities subjects such as literature, history, philosophy, and art. This could involve analyzing texts using algorithms, visualizing historical data, or creating digital archives. For example, researchers might apply text-mining techniques to large collections of literature to uncover patterns in language or themes that would be impossible to detect manually.

Another major aspect of DH involves digitization and the creation of digital archives. In this sense, digital tools are used to preserve rare texts, manuscripts, or cultural artifacts that can be accessed and studied by a global audience. For instance, projects like the Caribbean Digital Archive make historically significant, pre-20th-century Caribbean texts available online, bringing marginalized voices into the spotlight. This aspect of DH emphasizes inclusivity and open access, helping to democratize knowledge.

Furthermore, collaboration is a key feature of Digital Humanities. Researchers from different fields—historians, coders, data scientists—work together to build interactive platforms like digital exhibitions or visualizations that engage not only academic circles but also the public. This interdisciplinary approach makes DH dynamic and far-reaching.

Lastly, some view DH as having a social justice focus. – Digital tools can be used to expose inequalities or recover stories that have been erased by traditional archives. Projects that map historical immigration patterns or highlight the role of enslaved peoples in shaping culture are examples of how DH plays a crucial role in activism.

DH is an evolving field that blends the “fingerlike” manipulation of data with deep, humanistic questioning. Whether through computational analysis, the creation of digital archives, interdisciplinary collaboration, or social justice projects, Digital Humanities is transforming how we explore and interpret human culture. Just as early humans used their digits—fingers & toes—for counting, we now use digital tools to process and engage with vast amounts of data, offering new ways of seeing the world and its histories. This fusion of the ancient and modern makes Digital Humanities both a continuation of and a revolution in the study of humanity.

A digital humanities world.

Kelechi Iwuagwu (PRagmatic)

Data Analytics & Viz, The Graduate Center, CUNY