Breach Candy Network Diagram

For this week’s blog post, I decided to visualize the characters in “Breach Candy” by Samantha Subramanian.

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I decided to have characters connected together if it is explicitly stated that they know of each other, or if they appear in a scene together.

This network diagram reveals information about the character’s relationships because we can see that in this story, the Narrator and Kunal Kapoor seem to have the most connections. By seeing what people they are connected to, we can get a sense for how big of an impact that character has on the story.

Of course, there is much missing from this network diagram. There is no way to tell exactly what the relationships between these characters are. For example, the Narrator and Kunal Kapoor are friends, but Gerry Shirley and Dipesh Mehta are enemies. There is also no way to understand the trajectory of the narrative or story through this network diagram. It only shows the characters in the story and if they relate to one another, not how they are related or what specific impact they or their relationships have.

Risha Sanikommu

 

Mapping Decadence

I decided to analyze the maps in Mapping Decadence, which used ArcGIS to map the locations between several writers in the decadent movement and their publishers. There are several tabs on this website in which you can look at a specific writer’s location compared to their publishers. These writers are Jean Lorrian, Joris-Karl Huysman, Marcel Schwob, and Rachilde. There is also a map that includes all the authors and their publishers under the “mapping decadence” tab. These maps show the location of publishers as red pins, and the location of writers as other colored pins. When clicking on a pin on the map, there is some further information about the name of the writer or publisher, the address of the location, years lived there, and the books published. There are also lines between some pins, which when clicked on provide some more information about the books published. What these maps reveal is that location played an important role in the relationship between writers and publishers. It is clear that the general trend is that the writers lived close to their publishers. However, there is a lot information that is left unsaid from these maps as well.

Through my own research, I found out that the Decadent movement was a late 19th-century artistic and literary movement of Western Europe. It flourished in France, which is evident from the maps being centered around the city of paris. Although this may be implied from the maps, it is never stated or explained, suggesting that the intended viewer of these maps has some background information on the topic. There is also no narrative provided about the author’s or publisher’s life. Important information, such as why the author moved, or the kind of neighborhood they lived in, is left unstated. The about section of the page links to talks about these maps that revealed a lot of important information about the maps that are not immediately apparent. For example, at least in the starts of their careers, many of these authors lived in poorer neighborhoods because they were not wealthy. There are also factors such as family connections that allowed these authors to be put in touch with important publishers that are never mentioned in these maps. Although these maps allow one to grasp the importance of location, they only tell a partial story.

Turnball states that all maps are perspectival and subjective, which is clearly shown in these maps. They were created by a scholar who has extensive background information about these authors and were utilized the very specific purpose of showing the significance of location in the author’s and publisher’s lives. The creator seemed to have meant these maps to be a part of a bigger story that the causal observer is probably not aware of, making the maps somewhat disconnected and difficult to fully understand for the casual observer. The mapmaker leaving out information about the stories of these authors and publishers lives makes a significant difference on how the maps are perceived by the general public.

If I were to create an alternate map, I would focus on making it more accessible to the general public rather than creating it for scholars and people who already background information. I would do this by firstly, making sure to include the definition of the decadence movement and perhaps bios of the authors somewhere. I would also include a timeline with the map to show how and when the author moved around. I would put in little annotations of why they moved in their timeline and include more of their narrative on each pin in the map. I think it would also be interesting to see how the authors interacted with each other, or perhaps the same publisher, so I would try and include the connections between authors as well by linking them together on the map.

Written by Risha Sanikommu

Economic Data

Presidential approval and consumer confidence over time

I decided to analyze Economic Data from the Federal Reserve Economic Data. This data included unemployment rate, inflation rate, presidential approval, and consumer confidence for the years 1948 to 2016. After using Google Fusion tables to  look at relationships among the data, I decided to focus on presidential approval and consumer confidence in this shaded line graph because there is a clear correlation between these two elements. Presidential approval is the measure of the average approval poll rating for the incumbent president, and consumer confidence is measures the degree of optimism that consumers feel about the overall state of the economy and their personal financial situation.

When looking at this visualization, it’s easy to see the correlation between these two categories. The peaks and the valleys match up pretty consistently, and it makes sense that these two categories would be correlated. However, looking at the spreadsheet, I wasn’t able to see the relationship between them until I put it into a chart. Consumer confidence is on a higher scale than presidential approval is, so their numbers don’t match up, which makes it hard to see their relationship in the data set. It is easy to see through this chart that their slopes and changes over time do match up, suggesting that how much people approve of their present is related to how confident they are in the state of the economy. It is important to note that this visualization reveals a correlation and does not suggest any type of causation, but this information is still significant and shows how powerful a data visualization can be.

Written by Risha Sanikommu

LA Procurement

I decided to analyze the procurement dataset, which contains records of what the City of Los Angeles has bought since Fiscal Year 2012. These records contain fiscal year, department name, vendor name, transaction date, description, unit price, fund name, and other information. The Los Angeles City Controller website also uses some of this data and visualizes it on data cards, making it more accessible, user friendly, and easy to understand. These cards show how much the city of LA spent on certain items. When you click on the cards, it tells you what the items are, why they were bought, and some other facts related to the item.

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LA procurement data set
Data cards visualizing procurement data
Data cards visualizing procurement data

Wallack and Srinivasan define an ontology to be a way to represent reality through “systems of categories and their interrelations by which groups order and manage information about people, places, things, and events around them.” This procurement dataset represents the city through the eyes of the ‘state’ or governing institution. It breaks down what is procured into how much it costs, where it came from, etc. but hardly provides any information about what it’s specifically used for or why it was bought, and what impact it had after being procured. All these questions that this dataset fails to address are what  actually impact community members, whereas the information it addresses about where it comes from, what fund is being used to pay for it, etc. are what the governing body is more concerned about. The data card visualizations are better catered towards the ontology of community members as they show information of what exactly the items are and why the items were procured, which is on the level that citizens experience these procurements in their lives.

The ontology of the procurement data makes the most sense through the eyes of a government official who is perhaps in charge of the yearly budget or has other fiscal responsibilities in the state. It is very easy to see from this dataset how much these items cost, where the money is coming from, who it’s being paid to, etc. which is exactly the information that government budgeters need.

Although this dataset attempts to make what the city is procuring, how much it is spending on these items, and where they are coming from more transparent, it leaves out important information on a community level, such as what neighborhoods or areas these items are being given to, why they are being purchased, to whom these items will benefit, and what impact these items will make on the general community. To a general member of the city, these are the aspects of the data set that are more important than how much an item costs or where it is coming from. It seems that the city controller website is attempting to bridge the gap with the data cards, which clarify the procurements to an extent, but many questions still remain unanswered. When I look at the data cards, such as the one describing the city spending $1,159,775 on leasing golf carts, although I am able to learn that they are used for the City’s municipal golf courses, I am left questioning what neighborhoods or groups in LA most benefit from this and why the city decides to spend money on golf carts rather than some other matter.

If I was to start over with data-collection and create the data from a LA resident’s point of view, I would include not only what was bought and how much was spent on it, but also a description of what purpose the items serve, where it is being used, how much more or less is being bought than the year before, and the impact it has on the community. For example, for the data record of 6,670 soccer balls being bought, it would perhaps include what youth leagues the soccer balls are going to, how many more soccer balls were bought than last year, and show that they were bought because there was an increase in people joining the soccer league. The data cards presented on the city controller site includes more of this information than the procurement data set does, so they are definitely a step in the right direction to bridge the gap between community and state ontologies.

Risha Sanikommu

Finding Aid for the Walt Disney Productions Publicity Ephemera

The finding aid for the Walt Disney Productions Publicity Ephemera catalogues many of Disney’s feature-length and short subject films through a collection of press kits, press books, publicity stills, and other ephemera for their films. This collection contains objects from 1938 to the 1980s.

These items can reveal a lot about the narrative and history of Disney. Many of the objects in this collection are related to the advertising of these motion pictures, so a lot about how Disney markets themselves can be seen through these items. Disney has always been a family entertainment company, and these records show this through cataloguing the kind of films Disney produced and the way they were marketed, specifically to children and families. We might also be able to recognize the scope of these films as a whole, and the overall themes that Disney was trying to portray through them. Also, the biography mentions the decline of Disney’s reputation from 1966 to 1980. Because the collection has items from this time period, we might be able to see the effects of Disney’s decline on the publicity of the films produced during this time.

Although this collection is about Disney’s impactful films, the collection does not contain the films themselves, so it would be difficult to construct ideas of why their films are so impactful and significant based on ephemera alone. Another important part of the history of these films are how they were made and who worked on them. Also, although the decline of Disney’s popularity may be able to be noticed through the records, the reason for what caused the decline and the general history of Disney would be difficult to decipher from the records alone. The included biography of Disney helps remedy this by giving a general history of the company. To understand these records fully however, I believe it would be important to also have copies or at least summaries of the films themselves.

Risha Sanikommu

Photgrammar Deconstruction

Photogrammar is a web-based data visualization of 170,000 photographs from 1935 to 1945 found at http://photogrammar.yale.edu/. It allows not only for visualizing, but also organizing and searching these photographs. This website was created by the United States Farm Security Administration and Office of War Information (FSA-OWI).

The photogrammar map showing photograph density by county
The photogrammar map showing photograph density by county

The sources for this project come from the FSA-OWI File collection of images. Sponsored by the federal government, the Farm Security Administration — Office of War Information was given the task of documenting America, which produced a plethora of photographs from many well known photographers. The negatives were sent to Washington, DC where they were stored in a collection that eventually came to be known as the FSA-OWI File.

The processing for this project began with the cataloguing of the collection. Paul Vanderbilt joined the fSA-OWI in 1942 and created an organizing system for the collection that included the Lot Number system and Classification Tags system for the photographs. The lot numbers  signify a set of photographs organized around a shooting assignment, so they usually feature one photographs photos in a single place, and the classification tags have headings and subheadings that describe the subject matter of the photograph. This metadata allows users in Photogrammar to search through the collection. Apart from this, the Photogrammar team had to quantify the number of photos taken in each location and group them together by photographer, location, date, and classification in order to visualize it on their maps.

The presentation of this information is mainly done through maps. One of these maps shows the photographs by county, where the shade of color of the county represents the amount of photographs taken there. There is also a dot map that has different color dots for every different photographer. On these maps, you can zoom in and out, filter for a specific photographer, or adjust the time period that is shown. When you click on a county, it tells you the location and links to all the pictures taken in that county. It is important to note that the map only plots the approximately 90,000 photographs that have geographical information, whereas there is about 170,000 photographs total on record. These maps were created using leaflet, an open-source JavaScript library for mobile-friendly interactive maps, and CARTO, an open platform for location data.

There is also a section of the project called Photogrammar Labs where experimental visualization techniques are being used to represent these photographs, such as a treemap that traverses through the headings and sub-headings of the images, a metadata dashboard that represents the photographs in California with different charts and visualizations, and colorspace that allows the user to explore the photographs based on hue, saturation, and lightness.

Written by Risha Sanikommu