My project grew out of a problem: I wanted to know more about an artifact than what was available. This summer I visited the early Christian monastic site Clonmacnoise, located in County Offaly, Ireland, as part of an archaeological fieldwork program. There were many incredible ruins at the site, and I wanted to learn more about one, the remains of an 8th-century high cross. All the carved scenes and images on the cross were non-Christian, which surprised me. The description of the cross at the visitor’s center comprised just a few sentences and left me with a lot more questions. Since then, I have searched for more information about the iconography of that cross. I have also learned more about the images on the two other high crosses at this site, and this gave me the idea for this project.

I would like to create a website and archive that allows visitors to identify and “decode” the scenes and decorations on Irish high crosses. My inspiration for this project is, in part, a site that has generated 3D images of the structures and artifacts at Clonmacnoise. I recently learned that one artifact’s 3D images has a tooltip that reveals the specifics and background of its design. This is useful as even the Christian iconography is not always recognizable; a scene can contain locally influenced interpretations of a biblical story rather than more contemporary depictions. And some iconography is drawn not from the Bible but from local or regional history, or even from Classical and Norse mythology. The amazingly intricate and classically Irish interlaced designs can sometimes contain curious elements, too, including elements of human or animal bodies, or food, or weaponry.

My project would add the tooltip feature to images of the other two high crosses at the site to reveal expert interpretations of the images. It would also establish an iconography archive. Archiving the artwork of the crosses would allow researchers to quickly make comparisons and connections among craftspeople, locations and regional artistic influences. This would aid scholarship beyond Ireland, as early monks sometimes visited central and northern Europe and returned with artistic inspirations based on what they observed. Also, Ireland was the subject of raids by the Vikings, the English, and continental European factions; these influences can sometimes be seen in Irish culture and art.

Thinking about future plans for this project, a website like this would also be a helpful way to share monumental artifacts from the many Irish sites that are not staffed and are not even mapped. I was fortunate to visit a number of those sites as well; many are only known by local experts. Some of these localities are trying to attract more tourists, and a project like this could help raise interest. It would be amazing to collaborate with the Irish organization creating the 3D images and have these available to visitors as part of the archive as well.

My environmental scan found, besides the 3D image site, a few books with illustrations or photographs, and some large online repositories (the Getty, the Met, sites from Oxford and other universities), but I didn’t find one featuring or dedicated to cross imagery. If not unique, my project would at least be great to share with Clonmacnoise, whose visitors (almost 100,000 this year) would surely find a lot of learn and discuss after “decoding” the images on these ancient sculptural works of art.

This week I participated in an online workshop that was an introduction to the platform Omeka. It was hosted by Maggie Schreiner and Tuka Al-Sahlani, who are GCDI Digital Fellows. They first described Omeka, which is a free content management system used for creating archival and digital databases for museums, libraries, and other arts institutions. The Omeka platform allows users to upload digital images, videos, audio, and PDF materials and to use its archival-standard organization system to build online collections. We began by exploring several digital archival and database projects that featured digitized documents, photos and images, video, and mapping, and discussed what we noticed about them. Next, we went into breakout rooms to work with other students, examining a project of our choosing more closely. Another student and I chose a project created for CUNY to preserve and exhibit materials relating to its history as a public university in NYC. We liked the site’s participatory structure and its comprehensive essays on CUNY’s history. We did feel it was very text heavy, though, and that it could be strengthened by incorporating audio and visual elements, especially audio of the oral histories and an interactive timeline of significant events that helped shape the CUNY system. Our last task was to digitally archive an object from a collection of materials about the Grad Center’s building, which had been the flagship department store B. Altman (which I remember and definitely visited). I was given an illustration of boys’ clothing from the 1914-15 catalogue. I uploaded the image to the practice Omeka site we were provided with and entered metadata to build an archival entry for it. Overall, the workshop was a great way to see how Omeka works and to understand what it can offer institutions, and I look forward to exploring Omeka further.

For this assignment, I went to Google’s NGram Viewer and, first, thought about the data shown by the example graph. This was a comparison of the frequency of appearances of the words “Frankenstein,” “Albert Einstein,” and “Sherlock Holmes” from 1800 through 2020. As there were three lines charted on the same graph, it was easy to compare how mentions of each name rose, fell and intersected.  An interactive vertical line feature showed the names’ changing positions along the X-axis.  It was interesting and surprising to see how the frequency of each name’s mentions in publications varied over 224 years, and I tried to think of cultural and news events that may have coincided with the increases (and decreases). For example, I wondered if the name “Frankenstein” appeared more in certain years because of popular new movies based on or inspired by Mary Shelley’s 1818 story (1931, 1974, 1994 and 2015…the latter with Daniel Radcliffe) or based on news stories relating to genetically modified food (1990s).  

Next, I started my own search and entered the term “bell bottoms,” not really knowing what to expect beyond a surge of mentions of the pants style during the 1960s, which indeed occurred. Prior to that, the most mentions of bell-bottoms occurred during the 1940s. The Google NGram’s book-search feature, which I hadn’t used while exploring the previous graph, was super helpful in providing context for earlier highs and lows.  I learned that, prior to the 1960s, the most popular reference to bell-bottoms was for a style of pants developed for sailors; the wide bottoms meant the sailors could easily roll them up above the knee to prevent them from getting wet. Earlier in the century and further back into the mid- to late 19th century, the name “bell bottoms” appeared less often, but usually referred to a dandyish style of men’s pants. F. Scott Fitzgerald wrote about them in a fashion article (co-written with his wife, Zelda Fitzgerald) for McCall’s magazine in 1925. (I also learned that, mostly prior to 1960, “bell bottom” occasionally described chemical-processing equipment or the shape of certain tree roots.)  

In 1961, Life magazine reported that London designer Mary Quant had created “a line of low-waisted slacks” which, “in British nautical tradition,” featured bell-bottoms; this signaled movement away from the style’s more practical use, and the frequency of mentions quickly rose toward the term’s first significant high point, in 1971. Mentions declined sharply after this, hitting a relative low in 1982. The term began to appear more often beginning in the early 1990s, sometimes describing Halloween costumes, sometimes marking bad fashion choices (in literature and in magazines).  As the decade passed, the term’s appearance began to rise again, when it seems to have become less a signal for a fashion misfire than a symbol for the counterculture or the disco years. Mentions of “bell bottoms” continued to increase, reaching another high point in 1998, when it began to be associated with “vintage” looks worn by young people, funk musicians and skaters. “Bell bottoms” again peaked in frequency, in 2011, and most of these mentions seem to come from literature, fashion history texts, or appear in relation to decade-themed events. 

This exercise was a great way to try out text mining. As with any tool of this kind, of course, human interpretation of the results is needed to provide the best context, although reading the original documents found by the search feature can be exciting.  

I propose a DH project that pulls together voices and resources focusing on the use of AI in archaeology.  My guiding questions could be: What is the current  thinking about using AI in archaeology?  What are its uses, potential applications, and inherent and possible dangers?  How has AI changed the field already, and what might the future look like?   

This project would hopefully serve as a community forum to voice opinions, comment on others’ opinions and experiences, and, collectively, share knowledge that is truly constantly evolving.  The audience for this project are stakeholders in the field (archaeologists, researchers, cultural heritage and indigenous groups) and connected organizations and persons (museums, universities, cultural institutions, libraries, historians, curriculum developers, educators).  Today, news, discussions, scholarly research and general opinions about using AI in archaeology are more scattered across media outlets than consolidated, and this seems to constrain thinking to only specialized audiences in their given disciplines.

A Manifold site would support the many kinds of media that are currently circulating about this topic.  The use of AI in archaeology has changed the field dramatically in the relatively short time it has become widely available, and there are books, articles, blogs, videos, visualizations, social media posts, podcasts, open access research studies, and virtual meetings devoted to this topic appearing seemingly daily.  I was recently fortunate to be able to sit in on one very specialized–and closed–Zoom meeting about uses of AI and satellite data in archaeology. (A friend invited me.)  Throughout the two-day symposium, I wondered what others would add to the knowledge being shared by the speakers, as the implications and concerns of this technology are significant and different for many stakeholders.

There is a strong interdisciplinary and collaborative potential with this project, not just within the field, but one that includes a wide range of scientists and scholars, international art law experts, environmental groups, and social justice organizations, to name a few.  That is the project’s goal: to create a diverse, influential community that brings together highly invested parties in a discussion about the implications of using this powerful new technology in the important science of understanding human history through its material culture.

This week’s readings really spoke to questions of what’s important in the practice of developing the digital humanities.  Suber’s chapter on Open Access (OA) makes a strong case about how OA helps forward academic scholarship.  Suber notes that some have raised concerns about the potential of OA to invite plagiarism, misattribution, and misuse of a researcher’s publication. But Suber believes the benefits outweigh the risks: OA provides researchers with the “widest readership,” whereas traditional scholarship may appear only in specialized journals accessible only to other scholars. OA increases the chances of a researcher’s work becoming truly influential through this universal sharing.  Also, OA removes the pressure to create marketable scholarship, which can inhibit researchers who focus on more niche areas of study less attractive to publishers. I related well to this particular point, as my avocational interest in archaeology has sometimes led me to hit paywalls and other access barriers, likely because a focus is too niche to be available commercially.  

Fitzpatrick adds relatable comments on OA too, describing the anxiety, in the early days of the internet, of sharing their writing to an open online audience, but later celebrating the larger community that grew around it.  Fitzpatrick admits that stakes of publicly sharing ideas are much higher today, particularly for women and people of color, as more hateful and racist voices have found their way into the public mix.  Still, Fitzpatrick argues that the true value of OA is in its public service of providing access, but that creators need to keep innovating to find new ways of engaging all digital consumers. I couldn’t agree more; as a teacher and in educational administration, I worked hard to increase student and teacher access to learning outside the curriculum, and technology was often the medium through which this happened, or it was the focus of actual learning. 

Gold, Michael and Karlin describe how the digital humanities makes this possible. They note how Manifold integrates technologies in a way that helps bridge connections between the traditional manuscript and the online digital platform to become a unique and engaging resource combining the best of both with the benefits of interactivity and universal access.  Again, looking back on my work in education, I can see engagement with ideas truly taking off with even young students when they are able to connect ideas and sources with Manifold and other platforms to learn and to share their understandings. Finally, the concept of “minimal computing” provides a practical check for digital creators, according to Risam and Gil.  Obsessing over the “latest and greatest” in software, online platforms, and more when working in the digital humanities may be overlooking what is truly “necessary and sufficient” for creating meaningful projects.  They offer four questions for digital creators to ask themselves to help “resist the deficit model” and focus on what’s really important, and frame their point with real-life examples that show how limitations can actually drive creativity and problem solving. Also, Risam and Gil note how sometimes, issues of access that arise (connectivity, background knowledge, etc.) can find solutions when developers take a minimalist approach.  I connected with the ideas in this article, again thinking back to my career in education, because I so often needed to find ways to “make it work” with limited budgets, older equipment and with staff professional development, as there frequently was not enough time or energy for teachers to learn entirely new systems; thus, creative solutions often emerged.  And I definitely can see how prioritizing the “tried and true” over the “latest and greatest” can help digital humanities developers cut through hype and put ideas front and center.

This summer, I spent time in Ireland doing fieldwork at the country’s midlands monastic sites. For my praxis mapping project, I created a map of Ireland’s National Monuments, color-coded by county. This is a work in progress, as I’m trying to layer in visitor data from 2021-2023 to look for trends about how visitor numbers to site has changed over the past three years.

I used Tableau Public to create this map, mainly because I am now learning the program in the intro Data Viz and Design course. I am looking forward to trying the other mapping programs, especially as I am interested in remote sensing use to detect and monitor archaeological sites; ArchGIS is one that I have often seen cited.

I pulled the listing of national monuments dataset here: https://data.gov.ie/dataset/national-monuments-service-monuments-to-visit. This dataset shows Irish national monuments that are accessible to the public where visitors services are maintained. After creating an initial map with these, I used Tableau to color-code the monuments by county. I then tried the Tool Tip feature to add/eliminate data about each site (eliminating the longitude and latitudes in favor of descriptions of each monument).

I then located visitor data at the Office of Public Works at gov.ie: https://www.gov.ie/pdf/?file=https://assets.gov.ie/288264/b8df6873-57e8-4f91-9324-962100e3a395.pdf#page=null This was downloadable as a PDF, so I am in the process of working out exactly how to extract the data from the Excel file that I used Tableau to create from the PDF. As someone brand-new to mapping and to Tableau, this process is taking a while, but I am excited to continue and see which trends I can notice, and then think about additional questions raised by this visualization.

SongData (https://songdata.ca/) is a DH project started in 2018 at the University of Ottawa by Jada Watson and Andre Vellino to collect music industry data about country music songs to examine the inner workings of how the genre has developed over time, how it is still changing, and how its growth connects more broadly with cultural frameworks that emerge around it.  The project began with a need to understand inequalities in the radio playtime of women country artists: during a 2015 interview with radio consultant Keith Hill, he recommended that songs by female artists should comprise no more than 13%-15% of a station’s playlist. Hill described female artists as the “tomatoes” of the country music “salad.” SongData’s creators are looking to use this data to highlight gender discrimination in the country music genre by discovering trends and connections that could serve to keep songs by female artists low on the Hot Country Songs chart, and thus not as profitable as songs by male artists and groups. 

There are almost 20,000 songs in the project’s database whose sales led to ranking on Billboard magazine’s Hot Country Songs singles chart, from 1944 to the present.  The data for each single includes the artist, writer, producer, record label, and album, as well as the names and contributions of sound engineers and others who contributed to making the single. The creators note that there is simultaneously a clear bias against artists of color, including Indigenous performers in the genre, and they are working to use the data to help illustrate this discrimination as well. 

SongData uses several music industry databases to collect discographical and biographical information about the singles on the Hot Country Songs chart.  SongData creators use a Python script and RapidMiner to discover and analyze connections among music industry professionals that might have helped shape the genre over the years.  The SongData will be free to anyone interested in doing additional research about the development of the country music genre in the US. To date, they have completed a dataset of discographic and biographic information about charting country music singles from 1987-2017, and they published their first findings in 2019.  

What SongData is able to do is to quickly identify connections among record industry professionals and trends in sales of country music singles.  This data is drawn from several sources, and thus is best and most easily discovered through the use of digital gathering and analysis.  One shortcoming of the project is that, because of licensing agreements, they are not able to publish the Billboard Hot Country Songs charts.  While the analyses of the data can definitely help researchers spot trends and connections, being able to view the actual movement of the singles on the charts themselves would add weight to the project’s findings.  This project definitely has the potential to look at other genres in the music industry and discover more about how music genres are shaped behind the scenes.

I enjoyed the connections in this week’s readings about the nuances of data and digital tools: what they are, what they can show us, what they don’t reveal, how they both reflect and expose power imbalances, and how they can begin to correct some inequalities. Ramsay and Rockwell (2012) argue that digital tools are not simply performative but are themselves built theories, which are by design meant to facilitate further thought. Drucker (2011) discusses the contrasting terms “data”  and “capta,” the difference being that traditional “data” are quantitative, fixed objects, things that are given–like counts, responses, actions–to represent the discrete.  “Capta” on the other hand are described as things that are “taken” from those quantitative points.  Drucker presents a variety of data expressed in bar and line graphs, and then layers “capta” over those graphs using subtleties of the original data, if the right questions are asked of it.  Gallon (2016) writes that while some Black digital scholars are wary about embracing the digital tools that have been used to underrepresent and dehumanize Black people and culture, there is also the understanding how datasets, digital tools and platforms can be used to reveal racializations and inequitable systems of power, as well as recover artifacts and truths hidden or ignored through racism in scholarship. D’Ignazio and Klein (2020) show through Christine Draper’s famous use of what they call “data feminism” at NASA in the 1960s to crack the power hold of white male dominance in space engineering.  And Posner (2014) describes how “sources” are extracted, processed and transformed to create digital presentations that engage viewers and invite further questions about their topics. This group of readings was a great introduction to what is at the deep heart of digital humanities, mutable and powerful as it is by nature.