This past week I attended the “Creating interactive, visual, data driven websites in WordPress” workshop hosted by theGCDI Digital Fellows. The workshop focused mostly on how to embed various forms of content on a WordPress page, and in turn, also helped to give me a better idea of the types of content I can create on the Commons for course assignments and research. One of the most important takeaways I had from the workshop was that embedding content is key for online publications – it keeps readers focused on the content at hand (stopping them from clicking out of your writing and getting lost in others tabs on the internet), and allows you to make more dynamic sites to showcase your research.
A few key terms outlined at the beginning of the workshop:
Embed: How to place content on your website directly to keep readers engaged and not link them elsewhere
Shortcode: An advanced shortcut that allows you to add features to your website that would normally require coding
Although the beginning of the workshop was tailored to individuals who had no previous background with the Commons and WordPress in general, they discussed types of privacy settings, general settings and page templates I found helpful:
In general, you can keep some pages in draft form and/or with certain privacy restrictions to keep your unfinished (or finished work) outside the public eye.
When you need to create group projects involving multiple users, simply go to your Dashboard -> “Users” -> “Add New Users” – users will then receive an invitation via email
It’s always good to consider the legal aspects involving some final WP publications, i.e. consider the ethical questions when posting social media research – you can often ask a user directly for their consent!
There are three types of templates you can choose from when creating a new Page on the Commons: Default (good for blogging), Teaching (good for setting up a course), Academic Portfolio (resume building)
We then moved into discussing WordPress Plug-ins and embedding for the majority of the workshop:
The automatic WordPress Block Editor set for Commons pages comes with a variety of pre-set plug-ins for embedding content like YouTube/SoundCloud/Vimeo/etc. You can find the list here!
Some sites/tech will not work this way, for instance Tableau. To directly embed these types of displays, try finding a shortcode on Google – or checking out this useful guide to Shortcodes on WordPress!
An example in action:
(Using Spotify embed – you can give a playlist for people to listen to while reading your research!)
California Wildfires Since 1950 The interactive map below displays the perimeters of 16,069 wildfires that have spread across California since 1950. California has a long history of being engulfed in smoke and flames on the daily and that hasn’t changed.
Hi all, sorry for the late post. Being sick the whole week I decided to begin this project wasn’t ideal and definitely kept me from really diving in. I wouldn’t usually share that but, sense we are sharing our experiences with the project I feel like it fits. As usual with most mapping based projects, the hardest part is finding the data you want in a form where it can be mapped. I searched for plenty of different ideas and datasets but, usually let to a lot of frustration. Sooner or later the idea of mapping the California wildfires came to mind. At first I thought I would only be able find a dataset with coordinates like long/lat which would only give me something like an origin or where the fire started. I also figured I’d only find a dataset with this years data but, lucky, I was wrong! I ended up finding out there is data out there of all California wildfires since 1950 and the perimeters of those fires.
With that, I was able to take the data into ArcGIS and map it onto an interactive map of California. The data had a few different fields to play with. The ones that I kept ended up being:
YEAR_: The decade the fire occurred
STATE: The state the fire occurred in
FIRE_NAME: The name of the fire
ALARM_DATE: Date the fire was reported
CONT_DATE: Date the fire was contained
CAUSE: What caused the fire
GIS_ACRES: How many acres the fire spread across
WIth that information we are able to see where, how and when a lot of these fires are occurring. To wrap the whole project together, I built a website where I could house the map and any other information I added to the project.
After testing various mapping platforms, including spending copious amount of time trying to teach myself Tableau, I decided to go with ArcGIS and ArcGIS Storymaps to showcase historic sites in the northeast that are implementing inclusive narratives to include the lives of free and enslaved people who lived and worked at these sites. I currently work for an historic site that is beginning to implement enslaved narratives through the use of art installations and community conversations. The following information is provided on my Storymap to situate the reader to what this Storymap entails:
In February 2020, staff from various museums gathered at Philipsburg Manor, New York to discuss how they are rethinking their current narratives to create inclusivity by including stories of enslaved and free peoples who lived and worked on these properties.
This network of like-minded institutions has acted as a space to work through the challenges of the interpretation of inclusive narratives. In the summer of 2021, this group created the Northern Slavery Collective, which has currently manifested as a Facebook Group and Page for the cohort to collectively share ideas, events, questions, and challenges of this interpretation process.
The organization is in its early stages, which is hopeful to expand publicly through a website and social media as a resource to the public and educational communities for understanding and learning about these forgotten stories. The public facing goal is to end the myth that slavery did not exist in the North or was mild in comparison to slavery in the South.
My Process
Messy Excel Data for TableauTableau, various sheets for each census. Bubble sizes difficult to adjust.
As I stated, I first spent hours converting census information into an excel to be inputed into a Tableau map to see the variation of enslaved population sizes between the North and the South. I felt this data to be a little flat, and couldn’t find what story I was trying to tell. The data was hard to manipulate, and the population sizes weren’t giving me what I wanted. It showed the vast difference in slave populations between the North and South while I wanted to show just how much slavery was actually involved in the North. While the numbers were smaller, enforced enslaved laborers in the North provided greatly to the development of Northern societies, including infrastructure and commodities. These are the stories I wanted to tell. Thinking back on the Northern Slavery Collective, I thought those historic sites would be a great way to share these stories.
Storymaps
I’ve used Storymaps in the past, so I knew what I was capable of doing and not doing. The interactive maps provide a user friendly visual, but the lack of multiple media pieces for each map entry is a let down. Also, the UI is a bit finicky when trying to sort the order of the sites on my map. I included the description listed above as an overview of the Storymaps, followed by a map of the various historic sites in the Northeast overlaid with the 1790 census population that I created in ArcGIS. (The ability to create maps in ArcGIS which can then be added to Storymaps was a huge bonus!) Below this visual is another map showing the locations of the historic sites with an image of the site that is interactive.
ArcGIS Storymaps historic site map.
I have been debating whether or not I want to include more details on this map section because I currently like the clean look. When I add text, it appears below the historic site titles where I wish it would only be visible when the historic site is clicked. When this happens, a new view pops up that can include more description, such as address and website.
Since I wanted to include the stories of these sites and include more images, I created another section for this purpose. Here I list the various sites and included descriptions that were provided mostly by the Historic Hudson Valley’s People Not Property project at Philipsburg Manor. This section is still being worked on as there are numerous sites to cover.
ArcGIS Storymaps visual details of each site.
ArcGIS map
As I stated before, I implemented a layered map of census data and historic site locations. ArcGIS made it very simple in that a user had already created a beautiful census map that I could use. When hovering the mouse over a region you can see the full details of the various census fields, including enslaved persons. By adding pinpoints of the historic houses, you can visually see houses in areas that are listed as having 0 enslaved people in those regions. This stark visual helps debunk the myth that slavery was not present in the north.
ArcGIS layered data map of 1790 Census and historic site locations
Overall, I think ArcGIS Storymaps was very user friendly for a non-Digital Humanities student and is very visually pleasing. I’m glad I attempted to try a different software, so in the future if I need to create a map with data and I have a longer time period, I would consider using Tableau after taking an informational workshops or watching many tutorials.
True to the name, the Westside Sound refers to a specific geographic area of San Antonio wherein the music thrived however it is important to note that while many of the music’s pioneers were from the Westside of San Anto, not all musical groups or prominant sites that contributed to the music were necessarily from that area – musicians and venues in the Southside, for example, made significant contributions to the music – so the name is multifaceted.
embedded view and link out to my project
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.
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.
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.
I played around with Prezi, Google Earth, ArcGIS, Esri Story Maps, and Tableau.
My mapping goals were:
Be Interactive
Display Photos with accompanying text
Be atmospheric
Link the ideas to be somewhat coherent while maintaining distance
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.
Information on the total number of Early Intervention Services received by Borough. Brooklyn received the most services with Manhattan and Staten Island receiving the least. When compared with the population of children in each Borough there was not a disparity between receipt of services across Boroughs. Receipt of EI services for eligible families divided by race and showed that White families were more likely to receive services than Black and Latino families. Location of agencies providing EI services throughout the New York City area with a gradient scale of Black population in Census Tracts.
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.
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.
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.
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.
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 125,812th 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.
The start of my math genealogyThe end of my math genealogyMy full math genealogy
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:
Initial data set (with 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!
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.
Lots more to look at at the 2020 site if you want more examples.
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