Mapping New Activity in My Neighborhood Post-Covid-19

Introduction – Optimism

Notionally, and for some time now, I’ve planned on memorializing the changes in my neighborhood’s public space use after the start of the COVID-19 in New York City in March 2020. Like most communities, Sunnyside Queens spontaneously organized activities in public spaces to compensate for virus transmission risks indoors during times of high infection and hospitalization rates. Religious services, organized sports leagues/tournaments, exercise classes and nighttime teenager socializing blossomed in Torsney/Lou Lodati Park across from my apartment building over 2020, all of which persists throughout 2021, and all of which remains unsanctioned by a governmental or non-governmental organization. While I understand the role government can play in organizing efforts in large populations, autopoietic social activities strike me as immanently interesting, and the thought that a community with a diverse set of heritages and social needs unaddressed could coordinate usage of shared space during government shutdown of indoor buildings reassured me emotionally. In the depth of a crisis, the idea that my neighbors could collaborate together to help each other helped sustain my confidence in human beings during a period of time it was easy to feel unsure.

While the format and medium for my extended project were unspecified, I took the mapping praxis project as an opportunity to try GIS as a potential tool for communicating the changes I saw in my neighborhood. After all, a map seemed an obvious way to depict evens in space. My initial plan for the praxis assignment focused on two types of events: regular, recurring events distributed through different dayparts of my own devising, and mobile events such as protests in the summer of 2020. While I’ve worked with geographical coordinates and plotting in the past, I wanted to venture out slight into drawing my own layers, as a nod to the subjective nature of the project as a whole.

Mapping with QGIS – Idealism, Disappointment, Naivety

My choice of tools for mapping was based on a varying ideological commitment to open source software over the last twenty years of my life. QGIS was only open source tool I found on the list of recommended tools provided for the purposes of this praxis project that didn’t require Javascript (Leaflet), a language I’m familiar with but far from expertise. At the time, I was using FreeBSD at home, so installing the software was handle by running `pkg install qgis-ltr`

in the terminal. Once I had QGIS installed, I found Klas Karlsson’s superlative Youtube channel had a reasonable enough primer to get me up and running.

My choice to use free and open source software for my praxis assignment caused difficulties in executing what I envisioned for three reasons. The first was there were some rough edges in storing polygon shapes while saving map layers that were hard to troubleshoot in a graphical user interface this complex. For instance, I had trouble saving both temporary layers as perminent layers.

Error while trying to convert a temporary scratch layer to a permanent one

Because I was saving to a simple flat file database (SQLite), I guessed that the error above related to some permissioning set in the package provided in the FreeBSD repositories, though I couldn’t find any support channels to resolve this problem. I had to redraw polygons a quite a few times and in the right order of operations to save them as layers on my map. My second hurdle came when I wanted to save my map. The purpose for saving the map data was two fold: first, it would be handy to continue my work on another computer (a laptop in this case) and secondly, I wanted ideally to have my mapping data available to others. However, I wasn’t able to save my data, no matter how much I futzed with the permissions on the files specified in the error message below:

My third complication in using QGIS to render my project as I wanted can be attributed to either naivety if we’re being generous, and foolishness if we’re not. My research ended at the words “open source”, which meant I didn’t realize that QGIS “only” supports static maps. The problem with this limitation given my project is that it would take considerable effort to connect more maps at more than one zoom level, a necessity for plotting the marches/protests in my neighborhood and relating that to the park across from my apartment building. More on this limitation later. In the end, I compiled several maps plotting out various regular activities in the park for different dayparts which you can review below:

With all of these challenges, there was recourse in the Grad Center community to learn and grow in terms of learning the tools of the trade. While the GIS workshop this semester focused what I might call quantitative approach to mapping (i.e. taking spacial data and plotting it on a map), I found the conversations with the much smaller DARC + Sound Studies working group a more productive space to explore how a seasoned GIS scholar might approach my project. When presenting my struggles with this praxis project there, attendees advised me to understand the relative strengths of software used in mapping. QGIS is extremely powerful for creating plot points, geometry and layers. These scholars recommended exporting the spacial data and creating the interactivity in either ArcGIS (various formats) or even using a tool like Leaflet (GeoJSON is best). Unsurprisingly, in mapping picking the right tools for the job should be considered above some sort of ideological purity test (loyalty to free and open software). The reality is, mapping is a complex topic. Look no further than the three tiered top GUI menu that awaits you when you launch QGIS among many other interface elements presented to a new user.

Merely the top tiered menus available in QGIS

In spite of the difficulties I faced in this praxis assignment, I’m not entirely sure that traditional mapping satisfies the subjective nature of representing change in space as geographically small as a neighborhood. Perhaps a SpecLab inspired visualization trying to demonstrate the sociability of each type of activity in the Torsney Park would be more insightful. For instance, a cookout might be heavily social, whereas an exercise class or religious service may not. Instead, what I produced in these maps might be better suited as tabular data with type activities (exercise, religious, sports, socializing), a categorical dimension like time of day and day of the week and age of attendees.

Final Project: Sound Analysis of Virtual Worlds

I’m interested in analyzing the sound of Virtual Worlds (VW). VW include the entire scope of interactions we have in virtual environments, which would include gaming, social networks, e-learning, and Zoom meetings.

The project stemmed from an idea that plagues me every time, I log in to play a multiplayer game or browse TikTok: why would anyone want to do anything else? What is it that draws (drags?) us in so completely when playing a game online or compels us to infinitely scroll? The immediate effect of these VW is the all-encompassing sound design that gets its claws in us using a diverse, multifaceted system of feedback audio, human voices, in-game elements, and sound tracking.

Hypothesis:

The sound levels of these VW is caustic, transgressive, overblown, on the border of intelligibility, and break the rules of radio broadcasting standards but yet we are entranced and astounded. Why do we run away from disorder and chaotic scenarios in real life but embrace them, indeed are drawn to them in VW? It may be necessary to add a second visual element analysis to my project, because as an addendum to this principle point I propose that truly novel visual scenarios (games) or amateur video (TikTok) avoid charges of caustic and offensive sound. My guess is that we become a sleuth and play an active role in figuring out what exactly is going on.

Alright, now to cool this prose down a bit. I would have to do some research into sound design in VW, with a focus on how human voices through a microphone are factored in. I’d also have to look a bit into how of sounds attract or repel attention. Ultimately I’m looking to hopefully pin on the sound levels and sound quality of these VW as offending broadcasting standard of loudness and incomprehensibility, but strangely attracting or compelling us..

Methods:

Using Audacity to record “system audio” I will gather Wav files from different game sessions (Apex Legends, Black Ops, maybe Roblox, etc…) maybe 15 minutes at a time. and then importing them into Ableton. For tiktok videos, I’ll grab them from the browser and recording with Audacity. The program to analyze the sound is a plug in from IZotope called Insight 2 that works in Ableton. Here’s what the dashboard looks like.

There are 4 circled areas each designating a different mode of analysis.

There are two which are intuitive and I aim to utilize them, at least in the beginning. The “Loudness” area in the top left has a dropdown which designates different broadcasting standards and allows the user to see in real-time when sound levels offend those levels. In the bottom left “Sound Field” is something I would be interested in seeing if certain VW tend to fall to the left or right field. This would be a secondary investigation to the first, but it might reveal something interesting. There are bunch of ways to analyze sound including using a spectrogram, but I have yet to learn more about them

closer look at Broadcast Standards options.

An initial experiment I’d like to conduct is “how much time in the red” does a sound sample last for? This would give allow us to see how long it disobeys loudness broadcast level standards.

Another experiment would be to measure “quality” and the distortion levels, I don’t think this should be too hard to get out of the analyzer.

Eye(s) in Poe’s Short Stories

The impetus for this project was inspired by a quote from a recent article I read on Poe.

Poe’s fetish objects point towards a larger tradition of objectifying the terrors of the soul in Gothic literature. Old stone walls, devices of torture, evil eyes, casks of Amontillado, tufts of hair, purloined letters, and, above all, the ancient entanglement of death and beauty.

https://www.thesmartset.com/poe-boy/

I thought, since I love horror, the grotesque, gothic literature and film, that I’d like to see how body parts are treated in the prose of Poe. With Prof. Allred we thought it best to focus solely on the short stories, the reason being that language is more concise in shorter works of prose, and less functional.

On GitHub I have deposited the Txt file I used which compiles 69 of Poe’s shorts stories. The reason for including more than just his horror/thriller stories was to take the corpus and ensure I didn’t miss any mention of body part in the oeuvre. A bit of a brute force method, but at this point I didn’t have a very clear hypothesis, and needed to get some useful fragments of text. Using Voyant Tools, the following is the frequency list of terms highlighted by those worthy of note.

Rank : Term : Count
12 : eyes : 295
14 head 283
24 hand 214
33 body 196
34 feet 196
38 mind 187
50 death 167
68 : eye :151

A combined 446 times for eye/eyes. Eye* which includes eyelid, eye-glasses, etc… appears 471 times. Deciding to focus on the clear winner here, I exported the sentence fragments which contained “eye” or “eyes”; with a word context of 10 per each side of the term, then sent that back through Voyant to try to pinpoint characteristically grotesque phrases.

A semblance of a thesis I started out with was that Poe informed our notion of the grotesque, and I was hoping here to get some meaty adjective-noun parings, or at least sentence fragments which demonstrated this sensibility. I didn’t find that initially in Voyant, below is a “link” chart demonstrating most common occurrence in which “eyes” or “eye” and words which appear next to them.

not so useful

I was really hoping for “dripping eye”, “groaning eyes”, “disgusting eye”, or “ugly eyes”. It seems Poe isn’t as obvious a grotesque writer as I once hoped and I would have to dig deeper into the sentence to find what I was looking for. Off to AntConc to take a closer look!

“Eyes” rather than “eye” revealed an interesting et of singular appearances

relatively grotesque, right?

I was hoping to see a repetition of certain phrases, that would certainly cement the stamp of “grotesque” on an author right? Poe was more subtle than that, and his juicier bites of prose are saved for a select for of the horror works:

“deliberately cut one of its eyes from the socket” – The Black Cat “They were
wild, bold, ravenous—their red eyes glaring upon me” – The Pit and the Pendulum “deep-set eyes glared with unnatural lustre” – The Gold-Bug “The face was fearfully discolored, and the eye-balls protruded” – The Murders in the Rue Morgue.

Would it have been worth it to have the short stories arranged by publication date? I didn’t double check that when compiling my list, but something to keep in mind for the future. I could have traced easily his use of the term over the course of his writing. Another consideration when compiling a corpus is to nest the texts in a meaningful way. I could have done it my genre, or are least “obviously horror/mystery” and “the rest”.

JSTOR Text analyzer suggested I read up on the latest Ophthalmology research.

eye health

Interesting to note “Eye irritation” was labeled an identified term, and I take this to mean the exact term was found in the text. Dress hooks are a tool for sewing which utilize an eye closure.

What I’d like to propose is that Poe has not informed our notion of the grotesque in relation to the body in any consistent way. There are scattershot instances of it across his work, and while “eyes” and “eye” appear more than any other body part, this fact can be credited to his detective novels. His apparent influence stems from a few influential stories which loom large in the public eye.

A difficult mode of investigation that I chose from the outset, which I won’t repeat again was to tie up an accepted scholarly term like “grotesque” with text mining. The term reflects a mood or sensibility rather than a string of letters. I very well have missed notions of the topic in a fragment because it was the whole paragraph which spelled out the mood. the grotesque is found after all in the vulgar expansions in size or of use which doesn’t hinge on an identifiable term.

Last ditch effort! I took from the complete short story collection, phrases which mentioned a body part at all. I identified: arm, face, feet, hand, head, mouth which were statistically significant and thought I’d try to see which grotesque terms show up the most in relation to the set.

what this shows is general use, feet being the least used, and arm being the most.

It has slowly dawned on me that what I wasn’t searching for could be found in repetition or frequency, at all. Which makes the prospect of using a distant reading mode difficult. I was instead looking for singular instances of the grotesque which are used sporadically and for effect in Poe’s work. At least I was able to pinpoint which body parts were used most often in his work, which might be important for a specific kind of academic study.

After posting edit thoughts: What I wanted to measure was sentiment, which isn’t what these programs identify. Ideally there could be a program which shades sentences or even paragraphs in different colors depending on their intensity or coolness, parochial or transgressive qualities. There are sentiment analysis tools used for decoding Social Media posts, and I wonder if they could have helped me.

Olivia Maccioni / Text Mining with Pandemic Food Writing

Project Introduction

As someone who works in the restaurant industry, I am always thinking about food and dining. The COVID Pandemic had, and continues to have, a major impact on the industry, so I was excited to dig deeper into its effects, particularly in New York City, through this project.

Coming out every week, The New Yorker “Tables for Two” restaurant reviews have remained a staple in New York City food writing, even through the pandemic. While it might not be the most robust writing on the state of food more generally, I thought it would be a good place to start for analyzing trends in dining. It also has a dramatic impact on restaurants, and is sometimes responsible for huge booms in visitation.

As I’ve shared in class, I have trouble coming up with research questions, but always know the sorts of topics I’m interested in. I shared this with Filipa and she noted that sometimes with text mining, it’s best to simply upload the corpus in question and see what comes up. I chose to work with all of the “Tables for Two” reviews of 2019 and 2020 in order to have a bigger corpus to work from, and to be able to compare the before and after effects of the pandemic more specifically. I knew I wanted to focus more deeply on the corpus rather than learning a new software/tool for the assignment, so I choose Voyant for its ease of uploading and working with texts.

Starting with Voyant

Getting started, I tried simply uploading the links to all of the reviews, but came across a mess of words. Each New Yorker digital review contains links to other articles published in said edition, along with dozens of links to various New Yorker digital features and common website lingo. After inputting the webpages for analysis, the most common words that appeared in the word cloud were not very helpful:

While words from the site and related articles could certainly prove interesting to explore (and definitely heightened the use of the word pandemic), it proved too time consuming to try and remove each repetitive word using Voyant’s “Define” option. I also found that said option was not very successful, and often kept words and variants of words I hoped to remove in the cloud. In turn, I went the old fashioned way of cleaning my data, and copied and pasted only the text of each article into a Word Document. Of course, this still required some cleaning, so after some more massaging of removing words like “new” “restaurant” “food” and “yorker,” I got started exploring my texts.

(As a quick aside, I took some time to really think about what it means to remove words from a textual analysis. Every text comes with context, and it felt a little like cheating to be removing the reviews from their origin point – especially if I wanted to compare the state of dining to the rest of the world in 2020. That said, it ultimately felt like doing so would create a different project altogether — or maybe, could be something to focus on for my final project.

Before getting started, I also wanted to learn a bit more about the different features that Voyant offered as a new user, so I watched a few really helpful YouTube videos. I posted them below for anyone interested:

Working with Voyant

I wanted to start easy – what words have become more common in restaurant reviews this year than in the previous year? Unsurprisingly, words like “pandemic,” “home,” “frozen,” “closed,” “cooking,” and “takeout” came to the top in 2020. Alternatively, “pandemic” “frozen” and “closed” were not featured in any 2019 reviews, and “home” was only used in relation to discussing a chef or restauranteur’s “hometown”.

The popularity of the word “chicken” in 2020 was a surprise, so I did a bit more research, and came upon articles on the chicken shortage in America during COVID-19. Here, I was able to see popularity of an item during COVID that correlated to a larger food shortage in the country. Interesting! The popularity of the word “people” in 2020 also caught my eye, so I looked to compare its use with 2019 using the “Context” feature:

2020
2019

I’m not sure if you would call this a “sentiment” analysis, but you can certainly see the growth in relating the word “people” to more complex issues in 2020. In other words, concepts around “people” in dining and restaurants in 2020 has expanded beyond the world of food in 2020 into conversations of equity and need. Seemed like a plus!

That said, I was surprised to see the lack of conversations on racial equity in particular, given the BLM protests in 2020 that sparked discussions of white supremacy in the industry. Here is where I wished I would have done things differently, but kept my mistake for the sake of learning:

I was hoping to see if there was a trend in speaking about black-owned restaurants during the BLM protests that did not continue into the rest of 2020. As we’ve discussed in class, that summer often resulted in lip service to black populations, rather than actual moves towards equity. Since I did not categorize my reviews by month (which would have required separate Word Documents per month), I was only able to analyze trends as a whole in 2020. This made me realize that Voyant is really a tool used best when comparing different texts as whole units rather than comparing a single text as a unit. Since I didn’t go the time route, I looked at how the word “black” was used in the reviews in 2020 vs. 2019:

The screenshots are unclear since Voyant could not seem to finish loading this analysis, but it shows that in 2020 the word “black” was used with the word “entrepreneur” and “lives” matter” vs. 2019 with “tart” “avocado” and “pepper”. Of course, these results don’t look so good for The New Yorker, and I’m not surprised.

As a final exploration, I went to another corpus, Whetsone Magazine, and their 2020 digital articles on food during the pandemic. Whetsone Magazine is a black-led publication on food by Stephen Satterfield. Whetsone’s 2020 article word cloud did not even contain words like “pandemic” or “takeout” but rather words like “family” “father” “women” and “love”. This reminded me of conversations that we’ve also had in class around what types of content is shared by communities facing trauma, and where words like “joy” and “love” fit in. That said, of course it’s important to also mention that Whetsone’s 2020 articles range in content other than just restaurant reviews, but it shows a different sort of focus on eating during a global crisis.

Whetstone Magazine’s 2020 Articles

Where to go from here

Overall, I struggled with this project in that I felt the tool really just helped to prove assumptions I had about texts, rather than surprise me with new learnings. Of course there is always a use case for proving yourself right! Next time I use a tool like Voyant, I would try to focus on further categorizing texts before I upload them for analysis by things like time, genre or author, in order to get some more nuanced readings of subjects through comparison.

If I were to continue this project for my final project in the course, I would be interested in comparing reviews from either different publications, cities, or topics rather than years…asking research questions like:

  • Which cities saw the biggest changes in approaches to dining out in 2020?
  • What publications most holistically reviewed the impacts of the BLM movement on restaurant equity in 2020?
  • How did changes in dining out compare to other service industries like theatre, film or hospitality more generally?

Finding Golgonoonza in Jerusalem

project overview

Project website: https://storymaps.arcgis.com/stories/30b82e70672f4b7ea86be57e289d794a

My project is a map of an imaginary city composed of characters, figures, ideas, “psyches” fleshed out with photographs from a real city fraught with political and religious tension. It’s a bit of a confusing project to be sure, dazed, let’s say. It also doesn’t offer much in the way in commentary on William Blake. Instead it is meant to offer visual clues at the symbolic level of this city of imagination and art built by Blake’s character Los. Its goal is to instill in the visitor a sense of wonder, enchantment, and confusion but at the same time a realization that concrete/pictorial references can be linked to even the most fanciful ideas. Blake, famous for his illustrated poems, never did an engraving of Golgonzoola. Characters featured in his other poems have been represented visually, these include: Urizen, Hela, Har, Enitharmon, Orc. None of these are mentioned in his description of Golgonzoola, that’s why it’s so difficult to mentally grab a hold of. It also features: “sixty−four thousand Genii, guard the Eastern Gate: /  And sixty−four thousand Gnomes, guard the Northern Gate”. Not the kind of thing that one can easily visualize. The whole description boggles the mind. To bring it back to earth a bit I thought it would be fun to couch the typography of real world locations.

Disclaimer: This is not a commentary on the state of the Middle East, the Israeli/Palestinian conflict, territorial claims, or any other geoplitical issue. In fact, the choice of locations is based almost arbitrarily on where the travel group brought my group. Certainly there are Muslim, Armenian, and Christian parts of Old Jerusalem which someone could have placed as the “center”. It came to me in a dream last night that the “center” of each city has simply the most efficient point for everyone to gather, and only a modern conception of that place understanding it as principal or

First Steps

Golgonzoola mandala

The idea came to me during one of my obsessive research frenzies after I first encountered the mandala of Golgonooza. It was created by a user at a blog, and is not an original artwork by Blake. There is a section from “Jerusalem: The Emanation of The Giant Albion” which details an imaginary city with quite defined cardinal points and a center. Bulls, Cherubs, and Seven Forms amongst other symbols are described at different Gates of this city resulting in one of his most obtuse sections of verse.

I really love the abstract quality of it, and since I’m in Jerusalem I thought I’d try to flesh out some of the places from this verse using photography. The link that allowed me to place Golgonooza (thought to be an interior world) was a quote by the scholar Kenneth Johnston saying it  “”the urban form of Jerusalem in the fallen world”. It should be acknowledged that the connections are loose and interpretive.

Data Collection

geotagged photo

The iphone has a great geotagging system, even in airplane mode. I walked to a location with the description of the Gates in mind: “an act of true love” “Eden” “forms of war”, etc… and attempted to find scenes which resembled these sensibilities. I made sure to walk horizontally in order to place the Gates net to each other on the mandala, but of course they could have been arranged another way. It was a fantastic way to explore a city.

The software I used was StoryMaps from ArcGIS which was very intuitive. It accommodated the idea I had in my mind almost immediately. Unfortunately it’s a finicky system with weird saving issues, long load times, and a click-based UI that doesn’t always work. I wish, for example, the pictures could be made to appear larger or that the tagging system worked in a more comprehensive way.

I hope this post helps explain the generation and execution of this project. In truth, I haven’t wrapped my head around what its stated aim could be. Is it a mnemonic device, experimental lit crit, travel guide, photo journal, or pedagogical aid? The project is meant to instill a sense of wonder about Blake’s poetry and hopefully inspire further reading.

Mapping NYC 311 Service Complaint Data for Beaches and Pools

NYC OpenData 311 Service Requests and Complaints for Beaches, Pools and Saunas for 2019 to 2021.

Like any research project in the Digital Humanities, this praxius mapping project is a continuous work in progress. The data set I chose was attained from NYC OpenData website focusing on 311 Service Requests and Complaints. I found myself concerned on the topic 311 Service Requests and Complaints of Beaches, Pools, and Saunas in all 5 Boroughs of New York City from 2019 to 2021. This concern comes from my personal training as a water safety instructor and the passion for providing the essential life skills of swimming and water safety, inclusively, to every community. This data set of 311 Service Requests and Complaints of NYC Beaches, Pools, and Saunas from 2019 to 2021, provides not only the area and year of the incident but also the type of incident it was in which would help lead an initiative on how to provide prompt water safety measures to the area.

The NYC OpenData website contains a copious amount of data pertaining to the common requests and complaints of New Yorkers to 311 services. As New York City is a large city with a multitude of quandaries and dilemmas, there are many different types of complaints and requests. The NYC OpenData source provides these different categories of 311 service requests and complaints ranging from noise complaints to sanitation discrepancies and illegal parking, to name only a few, and gives the essential information of when it was reported, in what location did this incident occur, what department agency does this incident correspond with and if the incident was reported later as resolved. Having this data recorded is vital in showing potential and progress in taking necessary precaution and responsibility in protecting New Yorkers from water safety hazards.

The Process:

  1. Go to: https://data.cityofnewyork.us/Social-Services/311-Service-Requests-from-2010-to-Present/erm2-nwe9
  • Search: 311 Service Requests
  • Choose: 311 Service Request from 2010- Present (2021)
  • Find: the Data Dictionary and download Excell Sheet
  • Look for: “Complaint type” in the column name, which shares the core value in data set and the topic of incident; “Descriptor” which further details of the incident; “status” which shows if the incident has been resolved or is pending; “location variables”; and a new feature, “open_data_channel_type,” which provides information on how the complaint or request was submitted, either by phone call or online.
  •    Press: “View Data,” at the top of the NYC OpenData site
    • Set up a filter by:
      • Choosing “conditional formatting”
      • Change to “Complaint Type”
      • Change the “is” to “contains”
      • Put in the Text Box: “Beaches, Pools and Saunas”
  • Add a new filter:
    • Choose: “Created date”
    • Choose: “is after”
      • ** I only collected about 2 years worth of data because I didn’t want my computer to crash, plus I wanted a small but compact scope of a few years of data for comparison
    • Choose: your dates of research
  • Go To export
    • Choose: CSV for Excel
    • Download Data
    • Open Tableau
    • Import file as a text file
    • Start mapping by clicking on “Sheet 1”

Utilizing Tableau:

I choose to work with Tableau because it was the first data platform I was exposed to at the Graduate Center, in my Intro to Data Visualization course, and I had been previously working with it for my other classes. With that being said, I have only had one month’s worth of experience using Tableau for the use of this specific project. But for this project, I feel Tableau is incredibly appropriate for conveying the essential needs in organizing and aesthetically pinpointing the data set onto a map. I have liked my experience working with Tableau because this system allows the creator to be resourceful and innovative in the conception process. This is definitely artistry to Tableau that goes along with the territory of visualization. After playing around with the features of Tableau for a while, there are many options in creating what would be best to convey certain mapping data for each data set. I chose a gradient map, so I could show each incident of each year on one map, using different colors for each year. By using labels and details, I was able to add the location, type of facility, incident types, and if the incident was resolved.

Realizations:

Within two to two and a half years worth of NYC 311 Service Requests and Complaint Data, there have only been 398 complaints and requests reported to NYC 311 Services. It’s not the most riveting data but it is essential to view what needs to be improved in water safety environments for the New York City public. The boroughs with the most 311 complaints, from least to greatest, are Staten Island, Brooklyn, and Queens. As I look over the data set and see it organized as a map in Tableau, I’ve come to realize that the purpose of this map is to see improvements in conditions, or not, and to address these necessary requests and complaints to the New York City government for that they can enforce necessary action to protect New York City residents for their water safety.

Things to Work On:

I would like to continuously work on this map. I think more factors could be added to make the subject matter more personable. The importance of water safety is to prevent as many water-related deaths as possible. Maybe, I could find a data set that records the number of fatalities from drowning in New York City and have this correspond with the 311 Service Requests and Complaints for Beaches, Pools and Saunas. I would also like to work on my map formatting and maybe try to add the name of each facility as well as color code each borough instead of labeling it.

Olivia Maccioni – Mapping Project

Map of my refrigerator (and pantry)
Zoomed into NY-area

Project Introduction

For my mapping project, I decided to “map my refrigerator (and pantry).” As someone with a big interest in food, I was curious to see where the everyday items I was consuming actually came from, and if my pantry/fridge is really as “global” as I think living in a city like New York. I had big dreams of mapping the journey from farm to distribution center to delivery route to grocery store (to delivery) to home, but after meeting with a Digital Fellow, realized my dreams may be too ambitious for my current mapping skills. We decided it could be a good start to begin trying to map origin points of an item, and that QGIS would be a good software from which to explore the visual aspects of such a simple data set…but I soon realized it would be much harder to find the data than i imagined..

Note: Since the project was completed on my computer on QGIS, I don’t believe it’s possible to post a link. Please let me know if it is!

Capturing Data

I began with the concept of mapping my most recent Fresh Direct delivery. However, after looking at a few items and doing some google investigation, I realized that a majority of the items were a dead end. I decided to expand my reach into a random selection of items in my fridge/pantry from differing sources (FreshDirect, H Mart, bought locally, etc.) and see where it would take me. To get a large enough sample set, I went with 20 items, and another list of 10 items that had interesting dead ends:

I decided to categorize items by country and item type to see if there were trends between the two. However, I would some come to realize that a majority of my items were from the NY-area (which didn’t do much in terms of the country discussion). Finding the actual coordinates of the place of production/growing was quite difficult. For many products, it was impossible to find the locations where the items were made, but very easy to find their corporate office (i.e. Fuji Apples or Ocean Mist Farms spinach).

Surprisingly, the items that were advertised as straight from the source actually had no listed source at all., e.g. FreshDirect noted their 2-year aged Parmesan came from a “small cheese-maker in the Apennine hills of Emilia-Romagna,” but it was not possible to find a name/location of origin. Other companies, like Bumble Bee for tuna, even went so far as to have an individual can tracker, again to no avail – the can was listed as “Made in Thailand,” but was the fish? Not sure. A not so surprising find was that Trader Joe’s was not as transparent as they say, with almost no information on their packaging as to where the products were coming from.

For the items I DID find an origin location for (defined here as where the item was likely grown/canned/produced), I collected the relative long/lats for the map. What’s important to note here is the serious risks taken in the delineation of “origin” – companies could be lying, Google Maps could be wrong (especially in the case with the Tahini site in occupied Palestine), more complex products (such as take-out) are really the result of dozens of products, and sometimes I had to take a guess that the factory I received the product from was the one closest to my delivery point. I tried to illustrate these complexities in the “Notes” categories listed above.

My final points for mapping were:

Cleaned data for QGIS map

Mapping with QGIS

After a quick introductory lesson from a CUNY Digital Fellow (shouts out Rilquer!), I went into the mapping process. I spent a solid hour trying to figure out what was wrong with my coordinates when half of them showed up in Antarctica, and quickly realized I needed to clean up my longitudes/latitudes. Then, in combining them with a map of states/countries downloaded from an open source site, Natural Earth Data, they magically appeared! To make it more interesting for people to read, I decided to label them with the item name, and coordinate the colored points by category type – which as denoted earlier, didn’t do much in terms of analysis. I also played around with the “Heatmapping” feature to try and delineate areas trends in purchase locations. Again, given there wasn’t too much variety in my sample set (yes I am a lazy grocery store delivery person), it was not surprising that Fresh Direct was mostly local to NY.

What did strike me in seeing the items visualized was just how many of my products come from the New York area – and how one of my furthest sourced items was meat (yikes). I did some research to see if that was the case, or if that was a matter of FreshDirect actually being fairly “fresh” and “direct.” What I found was that NY is actually quite a hot spot for growing, particularly around vegetable and yogurt – which was evident in my map! That said, it’s also important to think about how grocery stores may reduce their products to local/closer regions in order to save money.

Source: Farm Bureau New York

Where to go from here

I would love to do more with this concept for my final project. First off, I could have worked with a much larger data set in order to really pick apart some trends, but was restricted in terms of what was actually in my house and how easy their production locations were to find, alongside the general timeline/scope of this introductory project. Moving forward, I’d love to consider mapping certain aisles in a store (perhaps those labeled “ethnic), a whole section of my pantry, a certain recipe, a larger home’s refrigerator, etc. The possibilities are endless!

I also think an ultimate goal is trying to map the routes that these products are taking and start to get a sense for how “local” local products really are, or better visualize where my food is coming from. In doing so, I would need to learn a bit more about how to map routes, and whether QGIS is the right software for the task. And more questions – would I also want to visualize the date behind the route’s environmental impact, cost, etc.? The questions are endless!

Maps Always Were Present: Blog 2

The grammatical confusion in this title is meant to convey my understanding of the digital maps we use in our daily lives and I’d like to highlight two interesting ones. Aside from digital maps which contain sliders and filters to control the year in view, maps are always a representation of the present that has passed us by. This isn’t to say they represent the past, but represent a present which is now past… Ok, maybe they are the same thing. Maybe a “frozen past” is a better way to signify this, but even this doesn’t touch the admittedly fuzzy sense I’m trying to get across. Maybe what I’m trying to get at is: the map is always the past, even if it signifies a present that we understand/recognize.

The Snapchat Map

IMAGE HERE

By zooming out on the globe screen, one can see parts of the world populated with avatars that symbolize snapchat activity. Clicking on any of these will present a series of video that were recently posted. 

Caveat: One may get the feeling that in cases where there is no snapchat activity it is representative of a part of the world that is boring, without an interesting daily life, etc… The reality is that they may not have access to mobile technology which hosts the App, or the App itself may be banned from that country.

The Citizen Map

IMAGE HERE

The homepage of this app is a map which tracks past and present criminal activities. Users can upload photos, video, and even live stream events as they unfold. Icons represent car accidents, physical altercations, and 

Caveat: The map is updated according to criminal activity heard by the citizen tem and logged into the app manually by them. My guess is that there may be a bias on the part of the loggers to “finish” maps in higher crime areas, choosing to add them there, rather than more spare areas. From the Bonilla and Hantel piece: “the map reifies the truth of what it represents”. In which case populating areas with the icons of crime that might be more immediate, but minor, (think scuffles or fender benders) but cumulatively to the mind of the viewer are seen as a sign of high crime rates.

Also going back to the Bonilla and Hantel piece. I liked two solutions for creating maps which are “no longer anchored by political sovereignty as a regulatory ideal of postcolonial independence”. The past defines the present and if the tool for carving up territory as a “technology of possession” here are two interesting ways to get beyond that function. The time-lapse which is a good way of getting out of the “spatial-temporal” mode. But even more interesting to me was the “Slave Revolt in Jamaica, 1760–1761: A Cartographic Narrative” map which does a solid job of providing key literary elements to support the historical events.

Final thoughts: Is a map an archive? How do maps represent fissures in the terrain like earthquakes and tsunamis?

David Leshinski – Blog #1

With this now being my second course that I will be taking in the Digital Humanities space, the thought of defining exactly what it is still seems like something that I couldn’t do if my life depended on it. Going into this field, my first thought of Digital Humanities was that it was a combination of working with data and a whole lot of writing about data. To some extent, I’m sure that could be true, but it doesn’t encapsulate the entire scope of what digital humanities is or what it could be. Today, my idea has shifted sightly on what is but, even then I still don’t believe it covers the field as a whole. The way I look at digital humanities now is simple- using data to represent human activities and using human activities to represent data. It might not be perfect (and it may be completely wrong), but I think it does a decent job.
In the “Torn Apart / Separados” visualization project, we see human activities being represented by digital data. The creators were able to map territories and color code each territory to represent what side of the political spectrum the congressional representative is on. While exploring the site, there are a handful of other visualizations such as one to represent the flow of ICE awards to specific companies throughout the four year span of 2014 – 2018, one to show the ownership of these contracting companies by protected groups such as minorities and women, one to show the banality of ICE Funding using a tree map, one to represent the streams of re-displaced people throughout the United States, and a visualization that gives the contact information for allies where those seeking help can go. While there are portions of the project that are written to provide you with the creators understanding, the main use of this project is created through written code to visualize the data and allow us, the viewer, to explore and come to our own understanding of the ICE activities and funding.
In terms of the “Colored Conventions Project,” we see the latter part of my definition of Digital Humanities- using human activities to represent data. This site is not created by marvelous coding pieces or data visualizations created through Tableau but, is instead a massive archive of real pieces of history. The Colored Conventions Project is a collection of pieces relating to gatherings that were held across the United States and Canada from 1830 until after the Civil War. In this collection, we are able to find pieces of physical data that have been preserved and uploaded into this massive archive. In this example, the data is still humanized, and in its true form. It isn’t aggregated or summarized to draw conclusions, but organized and labeled for us to analysis and learn about. The data is drawn directly from the readings and the images that make up the archive.
Digital Humanities is one of the most unique fields there is. It is filled with creative freedom and expression which makes it hard or near impossible to come down to one definition, just like other forms of art. My understanding of using data to represent human activities and using human activities to represent data may work here, but there are plenty of amazing DH projects out there where this may not be the case.

Blog 1

1.

I appreciate Ramsay’s comment regarding the ability to code or “build something” as a key consideration in one’s acknowledgement that they are a DH scholar. This struck me as useful in drawing a line in the sand in a field where a “definitional dilemma” seems to rear its head regarding the field from time to time. The problem with this, however, is that the scope of projects available to burgeoning scholars intending to code from the ground up in my view are limited. One could create a “collaboratively built tool that enables other scholars to add descriptive metadata to digitized manuscripts” but would another project really be necessary to practitioners when there is already Hypothesis and Manifold?

And with so many useful text analysis (Voyant), geo-spatial mapping, and data viz tools (Tableau) readily available, why the emphasis on knowing a computer programming language? Maybe the point is to have a working-knowledge of coding. In the same way a Literature major might need to know how to compose a sonnet. They may not be experts in the achievement of this goal, but can create one from the “ground up”. Alternatively can a Philosophy major be considered a scholar if they are unable to write a paper incorporating symbolic logic? It may not fit the end goal of their research which relies perhaps more on the merits of literary value rather than math and an Analytical style.

Maybe the issue of ground-level working knowledge of a skill? Wittgenstein famously came to Cambridge without having read Aristotle, which is very much in line with Keats’ Negative Capability. In the Humanities we don’t have a distinction between working knowledge and technical knowledge the same way other faculties like Social Science might have. A social scientist who can’t run a lab or has difficulty with statistics, seems to fail the tenets of the field, but what does that look like in the Humanities? Would it be one’s ability to mention at the drop of a hat five major themes from Songs of Innocence and Experience? Is a Literature major’s scholarly status docked for not having read Blake?

2.

So DH is a “motley of effort” (Krauss) and since I’m also taking a Pedagogy course this semester I’ve been made aware of two big sectioned off areas of DH. One in which the field makes a commitment to grappling with the fine points of online and hybrid learning in a way that is equitable and caters to the needs of students; the other is one which leans towards public scholarship: “addressing our work not simply to ‘the public’ but also… to specific communities” (Brennan). With social, racial, historical concerns to the fore. Its the explanation and pedagogical utility of DH projects that I feel could benefit from a reevaluation.

At least two of the projects offer an “explore” tab which breaks down the crucial elements of research and offers up the historic reasons for why a project is so vital. These explore tabs are inherent to most DH projects I’ve seen online and go a long way towards reckoning with the issue that ”scholarship that is not always fully legible to those not versed in the particular methods or conversations taking place in that domain”.

If this breakdown of core concepts is such a common occurrence, then it seems to me that; in the same way that there are just a few standards of notation software available that most people have agreed to use, can’t there be a software that organizes these Archive-heavy projects for people? The problem I run into is that, I know that project which perform archival work: gathering documents and organizing them across a timeline are set up the same way. That is, they have sections organized into: Explore, Find out More, Dig Deeper, Outline View modes, etc… Sometimes when I want to quickly switch from one to the other to compare the two, the UI is set up in such a way that I have to flip through pages and pages or differently organized and color-coded navigation views just to have the two side-by-side. I wonder if there isn’t room for a more Unified Approach to Archival Projects.