
Project Presentation: Carousel Mapping Project


What follows is more a philosophical meandering on our readings on Social Media this week. As such, the pieces we read are not cited specifically, but rather inspired this loose discourse:
As a *geriatric* millennial, I gleefully transitioned from chat rooms, to Geocities pages, to AOL/ICQ chat rooms, and inevitably to MySpace. MySpace was your personal space to share anything and everything you would like about yourself. And we tended to overshare. This was the age of posting random thoughts, pictures of every meal, but also a way to legitimately keep up with friends and family.
In retrospect the rapid-fire transitions from social media platform to platform have been relatively seamless until one takes the time to put the brakes on and look back. Facebook was like a MySpace plus, but quickly deteriorated towards pushing promoted materials (and of course misinformation). Instagram and Twitter were platforms we hopped on next, striving to recapture that “authenticity” increasingly lost. Instagram brought us back to images of our friends and families, and Twitter allowed for an open and international forum to share thoughts. Until- again, an inevitable slouch towards promoted content and a propensity for circulating misinformation.
This breakneck change in how we consume, and now create media content also passed us by. Where I was once enthusiastic to share my thoughts and pictures from the latest social gathering, I have largely stopped. Like so many of us, I have friends who have been, or currently are micro-influencers whose social media presence began to take on a language of branding, marketing, and eventually, a least a little advertising. Besides my personal disinterest in being a known entity, the strain of continuing to come up with content to support your profile, and boost interaction and reach- tires me out just thinking of it. Not to mention the fear of generating the unintended ire not only of the public at large, but possibly by current and future employers.
And to the question, of who owns this content? While the creator does have the power to ultimately remove their content and/or profile from these platforms, posts may have been captured by other means. Do we know if the platforms that hosted them truly delete their information? And where one wants to aggregate data from posts whether for commercial or academic purposes- where is the line drawn on who owns what? When is consent for use called for? Is embedding an individual post enough credit? What of scraping large amounts of data? And the logistics of getting informed consent, especially when using massive troves of data? Of course, the platforms themselves hold the bulk of these keys.
We’ve known this, and we’ve known that each new platform that has the potential to be the next place to find our collective authenticity will inevitably by spoiled for the purpose of increasing revenue- but yet, we often stay on the ride perhaps a little too long- until eventually the ride naturally comes to an end, or some sort of brakes are suddenly pressed, allowing us the moment to finally reflect on the racetrack we find ourselves on, and will likely stay on.
This week’s readings were an excellent practical and philosophical introduction to new modes of scholarly communication. Overall, a theme I noticed is a call towards overturning traditional academic and publisher power dynamics. Fitzpatrick (2021) brings to the table a more public and open discourse with the “public” both inside and outside academia to reach greater audiences and have wider impact with one’s scholarship. I’ve often grappled with the notion of great ideas staying within ivory towers, that may have little impact outside academia’s walls. New forms of sharing and publishing ideas in a more open and democratic fashion can break down these walls, while also improving the internal academic discourse on subjects that more align with the wider public’s needs and interests. Fitzpatrick found that blogs vastly improved their reach with their ideas, much more than work done in silos for dissertations and scholarly publication. Further, inviting more members of the public into a modified peer-review process helped their own academic pursuits, while perhaps enhancing other’s forays into their own research, whether they were affiliated with an academic institution or not.
Although blogs as we knew them seem to have had their hey-day in terms of reach, I do know that Substack (which is heavily blog-based, along with other modalities) has had a significant amount of pull with academic authors while also potentially providing subscription based revenue directly to the original content creator. With the increasing insignificance of the platform formerly known as Twitter, some of those that had cultivated a following for their ideas have moved onto different platforms such as Substack to continue the conversation. The challenge to keep up with changing platforms continues however.
Speaking of compensation, Suber’s (2012) OA book introduction argues that because academics receive a salary from their academic institute, and they have traditionally not been compensated for their writing, that they are prime for the OA movement. This is true, but I feel this argument leaves out that those in academia are often under-compensated for their labor, particularly those lower in rank, who conversely, are the most in need of getting published. That is not to make an argument against OA, but to highlight that disparity and to provide an update touched on in Risam and Gil’s (2022) paper. Since OA has made a bit of splash, the traditional academic publishers have taken notice and have created their own OA models. Big names like ElSevier, Taylor & Francis, Wiley/Springer, Sage, etc. promote the “good” of OA, but not at the expense of their profit. Instead, many offer models to pay to play. In as such, the author, or the academic institution must pay a fee (usually quite substantial) in order for that article to be published in OA format. The draw being that since these are the traditional academic publishers, they typically host more “prestigious” journals, which academic institutions favor when considering a faculty members promotion or tenure. Then on top of that- the academic institutions’ Library is still paying exorbitant amounts in order to have access to the non-OA content from those publishers in a subscription based model whose prices increase each year.
The implications of these increasingly complex models is beyond the scope of this blog post, but it does further illuminate the glowing potential of “green” OA in university commons and the Manifold publishing platform. Our very own professors and JoJo (2022) are putting up the good fight in not only creating polished and democratic forms of publishing, but are also adding interactive elements to enhance the “eBook” experience. From working in the K-12 sphere in the 2010s, and being exposed as a Librarian to academic textbooks, I have seen an increase in the big publishers including these interactive and multimedia elements to their official textbooks. However, these come at a huge expense that is often not sustainable for most K-12 schools or individual college students to support since they require each individual student to purchase an access code for these textbooks. Manifold can start to break down these barriers as we continue to push for the normalization of OER texts in Higher Ed, that will hopefully have a trickle down effect for K-12 and general publishing over time.
Today I attended another GC Digital Initiatives workshop How do you do DH? It was presented by a fellow DH student. In it, we were given a general overview of what DH is and why it might be used. We talked about different methods and tools used within DH. There was some interactivity to check for understanding, and to also gain insight on participant’s individual interests.
We also participated in a breakout room group activity where we were given a project to analyze to determine if it was a DH project, what methods and tools were used, and if the project was successful in whatever goal it had intended to pursue. Projects ranged from dissertations simply published online, a podcast series as dissertation, a gamified DH experience, and an online digital exhibit.
Overall, this was a good introduction to the topic, especially if one is completely new to DH. I made sure to save a copy of the slides which included links to helpful websites to determine which tools to use for what methods. The presentation was very approachable, and made me want to seek out other workshops from the GC Digital Initiatives in the future.
Today I attended the GC Digital Initiatives online workshop Intro to Python. The session was 2-hours long, which is about as long as you would like a workshop to be to not get total brain fatigue. However, as may be evident, Python is a complex tool that requires hours of dedication to understand and then experiment with implementing.
I have no experience with this programming language, and felt like I was in the right place. The level of the content was right from the beginning, providing baby steps to start to understand the foundation of the logic of this tool. As discussed in a previous class, we worked synchronously together through a new asynchronous tutorial offered via the DHRIFT site. This provided a clear and organized structure for the class, as well as an aesthetically pleasing, but also delightfully minimal visual to follow along with.
We were introduced to types, variables, running scripts, functions, errors, lists, and more. Cleverly the DHRIFT site had a live Python code editor embedded into the page so we could all practice without needing to download and install any software, or be moving back and forth through several windows. The moderator engaged us in thinking through problems and there were mini-quizzes we did together to check our understanding.
Overall it was a good experience, and was professionally and kindly done. Just for my own personal sake, I am not wrapping my head around how this tool is actually used and implemented and if it is worth the time vs. output ratio. I think I would really need to put in some serious hours to begin to crack this code. All in all though, it was good. Again, just personally, I think I would rather pursue other digital tools that are more approachable before diving into Python.
As mentioned already in class, I think the DHRIFT site is a great (and developing) site to find asynchronous and approachable tutorials for a variety of digital tools. I am looking forward to checking out their text mining tutorial next.
For this project I wanted to source readily available data. First I thought of different country and cities census data, but couldn’t really hone in on the data that I wanted to extract to visualize. After something thinking, I thought about race differences in regards to the maternal mortality rate.
Using data from the National Center for Health Statistics, National Vital Statistics System, mortality and natality data files available on this site I decided to visualize the maternal mortality rate by race for the year 2022. The information for 2023 is still tentative, and 2024’s information is still in progress.
I used SankeyMATIC to build the visualization- once again trying to find a more plug and play tool, rather than learning how to use a tool from scratch. This site provides a template and the user can change things around based on their needs. It is very simplistic and manual.
I had originally intended to put more years of data in, but found that to be an overwhelming task to do manually in this short time frame, so went with 2022. I was then struck at the limited breakdown by race. This made me wonder who may have been misrepresented, or not represented at all. I also found that the term “Non-Hispanic” was not consistent in word order within the data. Specifically, Asian, Non-Hispanic was one listing, while Non-Hispanic Black was another. I decided to make the language consistent. Also, the data was presented as Asian, Black, White, and Hispanic. After inputting the data, I found the visualization a bit jumbled and decided to put them in order of least to most.
I was disappointed to not figure out how or if it is possible to put a title on the visualization, so tried to be clear about what these numbers were (Maternal Deaths per 100,000 Live Births 2022).
It also became evident that this data could easily be misconstrued. It would appear that the highest maternal death rate is for White Non-Hispanics. However, over the years the understanding is the burden and tragedy of maternal deaths falls heavily on the Black community. Was 2022 an outlier? Being picky and choosy with this information could cause true harm, from a misinterpretation of a national tragedy, to a lack of accountability and advocacy to correct it.
Not to mention that it doesn’t illustrate how the United States is an outlier at having such high rates of maternal deaths compared to other “industrialized” nations. In other words THIS IS NOT NORMAL overall.

Probably way more reliable version from Statista.
You will find more infographics at Statista
For this assignment I had planned on created a global map of the history of how the term algorithm has come to be and be used as a concept. The inspiration was from a book I’m reading Filterworld: How Algorithms Flattened Culture by Kyle Chayka. I researched a few mapping tools such as ARCGIS, Tableau, and Leaflet, but determined the learning curve to understand how to approach them was far greater than the time I had to complete this assignment. I wound up using EasyMapMaker instead (https://www.easymapmaker.com/) which graciously supplied some sample excel sheets that I could easily modify with my information.
I modified my initial excel sheet to the longitude and latitude of various ancient cities/countries reference in the early history of algorithms (ie: Baghdad, Greece) and including a link to further information, an accompanying image, and a brief description. Sadly, I kept receiving an error message that the locations were not all found. This seems to be due to geographical limitations of EasyMapMaker. Upon further investigation, it seems only a few handfuls of countries can be used with this platform. Are these limitations of a free platform without the support to staff a larger swath of countries, or? Below is a list of most of the countries available- which is not completely Euro-centric, but limited nonetheless.

Facing this limitation and time crunch I switched gears and thought of the Panama Diaspora in the United States (FYI the Panamanian Parade is October 12th near the Brooklyn Museum). I quickly modified my algorithm spreadsheet with information for the Brooklyn parade, San Francisco, and a Diablo Rojo (iconic bus) in Washington DC. I stopped here due to time constraints, but can think of a dance group in Orlando and a “Reina” competition in Austin, Texas off the top of my head. There would of course be more data upon further research.
The map itself is ok considering the ease of use and total lack of previous experience:
https://www.easymapmaker.com/map/8d403dec03bbebb540b99e9164ef664b
6/10, would recommend for ease of use and if concerned with one particular country within their list, rather than a global map. Did not test more granular addresses, but seem to have this capability particularly in the United States.
A personal Digital Humanities Definition
From the very beginning of our readings this week, I resonated with Pannapackers’ 2011 observation that Digital Humanities are now simply “the Thing” and the seeming inevitability of DH simply being “the humanities”. With the proliferation of digital tools and their applications towards enhancing the study and access of humanities, it became necessary to find a term to describe this emerging way of doing things. And although tools will continue to develop or evolve, the incorporation of digital tools with the humanities is here to stay.
I find Digital Humanities best as an umbrella term in which these different ideas and technologies can be more concretely defined within. For example, what are the applications of mapping software to express topics in the humanities, and how does one use them? What are common data visualization techniques and outputs that can be incorporated with better understanding of humanities related topics? What humanities topics in general may best be represented via digital means over the written word? And so on…
I think that Digital Humanities is part of a wave of a burgeoning interdisciplinarity not just in academia, but those that are curious enough to explore and create. We are all increasingly participating across dynamic and collaborative media, so why not apply this to scholarship in order to truly lift whatever area of study is put out? Instead of waiting for “response papers” to add to the scholarly conversation, why not have the ability to comment and add to it now? And to open that ability up to anyone? Instead of a static article or book, why not have the ability to continually add or revise? Instead of limiting who publishes, why not open it to all?
How do the sites and projects reflect the issues in the readings
The sites and projects all reflect a way of presenting and providing access to different sets of data and information in a digital format. More specifically, Torn Apart/Separados speaks to a DH “that matters” and can bring about awareness of social issues to motivate action from the public. The Early Caribbean Digital Archive and Colored Conventions Project provides access to connect researchers and members of a diaspora to better understand that time in history, make connections today, and perhaps better understand themselves. They too seek to contribute to the decolonization of the archives and provide representation for traditionally marginalized voices from the past. The Reviews in Digital Humanities journal archive complements all of the readings in being able to browse through various DH projects that exemplify various aspects discussed within.