A look at the music through a spatial lens

For this praxis mapping assignment, I wanted to create a somewhat unconventional map that would visualize something that may not otherwise be mapped or associated with a physical geographic place. While my topic certainly references a physical location, I chose to incorporate places of the past and present that might visualize ties to areas outside of the specific place referenced in the title “The Westside Sound.”

My mapping project is to be incorporated into a larger project that aims to portray the story of Chicano Soul music with a focus on “The Westside Sound,” often thought of as the roots of Chicano Soul, referring to the Westside of San Antonio, Texas, where the music was born. I like to explain this niche genre as follows:

The Westside Sound is to San Antonio what Motown is to Detroit.

Considering my professional work surrounding Conjunto music (as the Program and Marketing Coordinator for Conjunto Heritage Taller), I aim to keep much of my graduate work within the realms of my interests and work with regional music and culture that is deeply rooted in my community — this mapping praxis assignment included. Derived from a mix of various musical styles, including some aspects of conjunto music, Chicano Soul was, and still remains, a prominent staple in San Anto history and culture. The intended primary audience is a broad mix of music enthusiasts, especially those interested in the styles that influenced and shaped Chicano Soul (i.e. R & B, rock n’ roll, Motown), as well as San Antonio locals and historians. A long-term goal for this project is that this serves as an archival project as well, documenting, recounting, and preserving the history of the Westside Sound.

The main narrative components of this project aim to communicate the following:

• Mapping the “Westside Sound” – a map of prominent venues, studios, radio stations, festivals, retailers, etc. that were/are significant to the musical style.
  • Details about the areas in which prominent artists/groups were formed.

Data

I collected the data for this project, using mostly methods of manual collection, organizing, and research. The data is mostly text and categorical with some quantitative/numeric values. Below are some variables I used:

• Coordinates (Lat, Long) of “significant places”
• Record Labels
• Venues
• Recording studios
• Nightclubs / Bars
• Record shops
• Date of “significant event”
• Photos, videos
• Addresses
• Descriptive text

Methodology

I decided to utilize the JavaScript library Leaflet for my map. After exploring different libraries and tools, Leaflet, by Mapbox, proved to be a good option to execute my map. I did however struggle with binding my data to Leaflet, so I used a very manual approach in my coding for the map by inputting my data for each point within my code. I want to investigate methods of binding data to Leaflet as this manual process is not ideal for larger datasets – luckily my dataset was simple and small. While Leaflet has tooltip and label features, the amount of data that I wanted to include in tooltips was not ideal for a small tooltip box. I eventually found a Leaflet plugin that allowed me to implement a sidebar. The sidebar feature was more suitable for the details I chose to reveal on user click, which included media filed and text. I was very pleased with this plugin and can imagine using it for future projects. For the legend, I used a D3 scale where my legend data was the domain and my chosen color palette was the range. I then appended circles to represent each style and text labels. Since the legend data was very simple, I was able to select colors that flowed well with my chosen color scheme of the whole webpage.

While I wanted to include many more geographic points my project, I did not have enough time to execute those ideas (the data collection, organization, and binding). The data collection process was very timely, since I was manually collecting and organizing the data myself, so I hope to identify more practical methods moving forward. Another aspect I hope to incorporate in my map is references to locations made in many Westside Sound songs.

For the less technical aspects, such as the title/cover photo at the top of the webpage, I utilized Canva.

Praxis I Assignment – Caroline Kelly

Interpretation of the Assignment

With the limitless potential of “Create a map of something that is not necessarily -or traditionally thought of as – mappable” my approach to this assignment was most driven to map something not typically represented in the physical world and one that I find most difficult to articulate, my internal thought process.  Though the assignment was open-ended the limiting agent was technical ability. 

Ideas

I vacillated between doing something meaningful such as the disparity of services to children with disabilities or something I already have a strong grasp of the data such as the identification of a painting.

I was most interested in creating a visualization of a thought or an idea map that could not just illustrate the connection between different ideas and symbols that exist in an internal schema but also evoke the same sensation.

Thoughts on Maps

Thoughts on Maps

Harness the power of maps to tell stories that matter. ArcGIS StoryMaps has everything you need to create remarkable stories that give your maps meaning.

Click Here for the Story Map

Selecting the Mapping Tool

I played around with Prezi, Google Earth, ArcGIS, Esri Story Maps, and Tableau. 

My mapping goals were:

1. Be Interactive 
2. Display Photos with accompanying text
3. Be atmospheric
4. Link the ideas to be somewhat coherent while maintaining distance
5. Ability to overlap items on top of the map (this had to be abandoned)

With limited Java ability for Leaflet and the nausea-inducing effects of Prezi – I ended up using both ArcGIS Story Maps and Tableau. 

Designing the Map

I let the technology dictate how I would illustrate the structure of an internal thought process. Memory plays such a big part in the way we think about things that the narrative nature of the Story Map would provide needed structure.

I also approached the building of the map like a painting focusing on the palette and atmosphere instead of accurately depicting reality. In Esri I selected a base map
“Firefly Imagery Hybrid” for its dark appearance that could be like the internal world of the mind or even an MRI. 

Memories don’t usually include country or state boundaries so I removed them from the reference layer. I maintained the representation of streets and buildings as they are part of a sense of a place and one’s place in it.  

I structured the narrative somewhat autobiographically with places and thoughts on cartographic subjects such as the Center of the World, Internal Worlds, Stars, Models, the Human Body, Organizational Structure and tied them in with locations from my neighborhood, school, places I’ve traveled and worked. 

Still, I felt this was lacking and a Map of a Thought about Maps was far too meta even for me. 

I also created an infographic that is rooted in the present and future. For this I used Tableau. I found minimal data from “The Status of NYC Children” on the data.ccc.newyork.org website for services received by children in New York City’s Early Intervention Program, a federally mandated program that provides services to children with developmental delays and disabilities. I also utilized NYC Data to find demographic information on the population of children in each borough.

Problems

Being a novice in all of these platforms created a steep and time-consuming learning curve and the limitations in access as an unpaying customer in Esri limited a lot of the functioning I wanted. I was frustrated by the poor graphic design and editing features in Acris. I was not successful in putting what I wanted visually in the parameters of the mapping platform and was disappointed that the story progressed in a linear structure. 

For the Tableau portion, I was very restricted by the data shared by the government and non-profit agencies and could not report on the discrepancies that exist in the borough and racial demographics for children needing critical medical services. Other agencies reported FOIL requests for their dataset. I also had a lot of issues getting data from the census converted to zipcode and ended using the layer on Tableau. 

I also experienced self-censorship due to the permanence and public nature of posted assignments. I wish I had spent more time developing skills in one of the mapping platforms instead of first thinking about what I should do. I wish I had added many more data points for the map that went across the globe. Also, Google Earth may have been a better option for synthesizing that internal cinematic effect. 

Going Forward

I will be working on the data for Early Intervention Services and doing a FOIL request as this also relates to my professional life. I am still deeply interested in mapping ideas and want to focus more on the interactive element of the viewer and developing the technical skills to do so.

Update: the images would not show on the Commons website, so the link to my map is here:

I changed my initial project because I decided I would do something a bit more personal. As such, I was determined to map my math genealogy. According to their website, The Math Genealogy Project aims to “compile information about ALL the mathematicians in the world.” , and for any individual who has received a doctorate in mathematics, the website shows:

“

• The complete name of the degree recipient
• The name of the university which awarded the degree
• The year in which the degree was awarded
• The complete title of the dissertation
• The complete name(s) of the advisor(s)”

I can’t recall where I first heard of the website, but I know it was one of my previous math professors who mentioned it to me. Note: as this website lists any individual who has earned a doctorate in mathematics, I am not actually on the site since I only have a master’s degree in math, so this map does not include where I attended college. On the MGP website, after you enter the name of, say, your advisor, you keep clicking on successive advisors and move backwards chronologically. Because of the functionality of the website, I had to create the data set myself based on each entry, which was somewhat tedious. I initially tried a different math advisor, but the scope of their genealogical locations was not broad enough to make a compelling map and there were too many duplicate locations. As a result, I moved on a second advisor to create the data set I used for the map. Upon initially using this website years ago, I was surprised to learn that my math lineage included both Laplace and Poisson, two famous, brilliant, and influential mathematicians. Knowing this made me feel like I descended from math royalty—if there is such a thing. My math genealogy started in Paris, France and had stops across America, but none farther west than Austin, TX—ending where my advisor earned his PhD, in Ann Arbor, Michigan. In all, it includes two countries and 8 cities. It spans from 1735 to 1980, when my advisor earned his PhD. If I achieved a PhD in mathematics today, I would be the 125,812^th descendant of my mathematical apical ancestor.

When I first uploaded the data set, the only location field I had was “City”. Unfortunately, that was not sufficient to map all the locations because clearly some city names are duplicates. I should have thought of that before. Ultimately, I went back to the data set and added “State” and “Country” fields so that Tableau could works its magic and more easily narrow down the location. This worked and my locations were mapped with points at each city.

I then had each dot on the map labeled by city name and the number of descendants from the doctorate in question underneath the city name. At this point, I thought the map was decent, but I figured I could add more depth to it.

From the original map I created, unless I added the year as a label, there would be no way for anyone to determine the chronological order of events, so to make the map more visually appealing I wanted to created arcs that appeared in reverse chronological order from one city to the next. Well, first, I wanted to include arcs and then I wanted to animate them, so they popped up from one city to the next in chronological order, so I set out to try to animate my map. Creating the arcs proved more difficult than I expected. I followed directions I found online very specifically, and I found it incredibly cumbersome. I had to completely revise the structure of my data set which left me very annoyed. Instead of creating arcs between the points like what I saw in the example, it mapped everything to a single point in Canada (note: none of the locations in my data set are in in Canada). I was very confused. I concluded that some of the duplicates in my data set (where the advisor and doctoral student earned their degree from the same institution) may have been messing up the pathway I created so I tried to remove the duplicate rows (which didn’t affect the route because the city was repeated to see what happened). This somehow worked! My genealogy was routed on the map – though without any points at the cities, just apexes where the arcs met. I then figured out how to create two maps, one with the points and the other with arcs, and combined them to make my final map.

Ultimately, I was able to figure out how to animate the map, but only by using filters which was not what I want. Ideally, I would like the map to open and for the viewer to see a point bouncing on arcs from city to city. I am not quite there yet.

Though what I describe above only took a few paragraphs to explain, I spent a significant amount of time learning how to generally operate Tableau and constructing my data set so that it had optimal functionality when I uploaded it. Putting the finishing details on the map at the end took the most time out of everything.

As promised, here’s an overview of the DataVis Praxis project, due 10/21 for those who choose this option over the text analysis option due later this term.

Visualization Assignment (Due Date 10/21)

Create a data visualization using one of the tools described in “Digital Humanities Tools: Data Visualization Tools” (I suggest starting with Tableau Public or Palladio, especially if you are new to datavis). As with the mapping praxis assignment, you may create any type of visualization you’d like; I just want you to attempt working with one of these pieces of datavis software. Since we’ve already done a mapping praxis assignment, please avoid a geospatial visualization.

Please create a blog post describing your experience(s) creating the data visualization and connect your experience(s) with one or two readings from class thus far, particularly from the “Data and Visualization” week.

Examples from past 700 students:

• Elena Abou Mrad’s visualization of favorite cuisines in NYC
• Patricia Belen’s Drucker-inspired visualization of the objective impact of subjective events in the life of painter Artemisia Gentileschi
• Lane Vineyard’s graph of languages spoken by petitioners for bankruptcies in NYC
• Brianna Caszatt’s graph of duration of Supreme Court Justices’ terms: nicely iterative and process-focused narrativehttps://dhintro2020.commons.gc.cuny.edu/visualizing-supreme-court-justice-term-lengths/

Lots more to look at at the 2020 site if you want more examples.

Several of the pieces we’ve read this week–especially Drucker’s, Cottom’s, and Guiliano/Heitman’s–ask questions about the objectivity of “data” and its role in cultural analyses and narratives. These pieces made me think of a “golden oldie” of cultural theory, The Order of Things by the French poststructuralist thinker Michel Foucault, an enormously influential theory of how the West has constructed its own “ways of knowing” by obscuring the contingencies of certain knowledge and projecting a fantasy of a pure, objective knowledge.

The book begins with, you guessed it, a riff on Borges. Here is the first page more or less in full:

The point, of course, is not the obvious and chauvenistic one: what a zany people those Chinese are!? The point, rather, is more like “what must our Encyclopedias look like to the Other? How are our regimes that make “data” and its analysis seem so transparent and objective equally absurd and humorous and continent when looking in from the outside?

Note: Due to the storm last Thursday, I was unable to post prior to class on 9/23 so I am combining thoughts from the last two weeks of reading.

I went into the section of the curriculum about mapping very nervous about what I could produce and how I could use any available software. In short, I did not think my skillset lent itself well to this project. The article on Finding the Right Tools for Mapping really helped me narrow down my selection and I was ultimately able to download Tableau. I have not actually mapped anything yet so let’s see how that goes.

With respect to mapping, coincidentally, I had two recent experiences prior to reading the section that indicated how little thought I put into reading maps. While conversing with a friend of mine who hails from Ireland, I was surprised and confused to learn that Ireland, a nation I had viewed on maps for decades, was both smaller than the state of Indiana in both geographic square footage and population. Then, on a recent trip to St. Lucia for my friend’s wedding, my first venture into the Caribbean, I was surprised to hear a gentleman state that the population of the nation-island was about 180,000. I immediately thought I misheard, and he must have been referring to the population of the capital or something. I was wrong. Upon hearing both pieces of information, I thought, “How is this possible?” Though I cannot confirm this with 100% certainty, I always felt like the size of those two countries on maps were not appropriately proportioned to the larger countries. In fact, I didn’t even know Ireland was small country – in geographic area or population. Based on the reading, it’s clear I did not understand the concept of distortion—namely scale and projection. This begs the question for me of what purpose a map serves.

Should maps carry representations of sovereignty? Of course, I think, if that is the purpose of the map. If one is strictly looking for directions from point A to B or analyzing international scale, I doubt sovereignty is of much importance at that time.  The utility of maps as it relates to sovereignty, however, does not devalue the importance of how sovereignty can be represented on maps. The truth is, sovereignty is not one of the common reasons people look at maps. And, more often than not, folks incorrectly presume the borders and boundaries that enclose nations on maps represent some level of sovereignty.

Moving on the data visualization section, I was optimistic that the readings would resonate more with me as a mathematician. After reading all articles for this section, I felt educated, but not entertained. For me, the balance between education and entertainment is important as it relates to engagement with the subject matter. The academic space seems to take the fun out of data viz. Without question, there are important social issues to address via data viz, but exclusively doing that narrows the reach of the field and can make it less appealing to the layperson. With that said, what purpose does the value of data viz truly serve if it only appeals to those who are already thoroughly familiar with its use and function? Strictly focusing on social science or humanities matters creates and insular and exclusive data viz community of similarly minded individuals who are already aware of the powers of the visualizations. This seems to limit the potential exposure of these concepts to broader audiences.

My earliest experiences with large data sets and their representations started in high school when I was taking AP statistics and had to create several projects. At the time, I was heavily interested in sports statistics, box office grosses, and billboard sales—none of which hold any significant social capital. Through these avenues, I began to memorize, cross-reference, compare, and visualize different sets of data related to batting averages, opening weekend grosses, and first week album sales that I remember to this day. Nothing about those experiences felt academic and I knew of no data viz jargon (as it likely did not exist at the time), but the same concepts of reduction and spatial variables resonated with me then—even if I didn’t know it at the time. Reading these definitions, in many ways, erodes the experience as it takes it from something interesting and fun to something pedantic and stuffy. In my opinion, it should be clear that the applications of the digital humanities concepts that are discussed transcend the academic landscape.