Author: leo6

“Blue Moon”is an essay written by renowned Japanese writer Hiromi Kawakami, and published in Granta 127: Japan.  In this extremely rhetorical piece, Kawakami put the inevitable inaccuracy of translation and the fragility of life in parallel, thus relating her personal transition in embracing the fact of her little chance to survive the malignant tumor to the difficulty in translating Japanese haiku to the Russian audience.  As she explained, “Things are always, at best, a  near miss. We get through, sometimes just barely”. Finally, while she was composing a poem, the mixed feeling of sadness for transitory happiness flashed across her mind on a snowy day in Russia.

I created an edge list of characters in the essay and defined the connection as they met each other in person. Then I uploaded the excel to Google Fusion Tables to generate the network chart.

 

This network graph demonstrates the direct contacts between characters. It echoes with the tone of the essay, which depicts the author as the center figure and focus on her own transition. However, the graph fails to reveal the nature of these relationships, specifically the factors which triggers the development of the author’s mentality. The chart also lacks the importance of each character’s role in the essay. I believe that it can still be optimized with further consideration.

 

This week, I examined the 19th Century Caribbean Cholera Timemap  created by Duke University Haiti Laboratory. The interactive program offers both a timeline and a map, while locating all documented cases of Cholera outbreak, hurricanes, tropical storms, and news coverage in the Caribbean. As demonstrated by the timeline, the Timemap features 3 major periods of cholera outbreaks (1833-1834, 1850-1856, 1865-1872). It includes the location relative to other outbreaks and the corresponding primary media sources. Clicking on each event will make the map display a short description of the outbreak, storm, or news article.

I believe that this map reflects a scholarly (statistician or epidemiologist) , point of view of cholera outbreaks. As the news articles reported by mainstream media at the time, the map only illustrates the mathematical  data of people affected by cholera, instead of mentioning the life and suffering of the individuals. Such a focus distinguishes the map from a traditional research in the humanities: it excels at factual representation of deaths resulted from the Cholera outbreaks and the climate conditions; however, it fails to measure the data in a historical and humanities context.

The creators of this map assume that all Cholera outbreaks are recorded and mostly published. Yet, lack of documentation does not equal to nonexistence. For casual viewers, this map seemed to be a complete collection of every hurricane, outbreak, and storm that took place. However, the chronological and geographical attribute of this map make obtaining and maintaining a comprehensive record nearly impossible. The display of the map also hides valuable details about the Cholera outbreaks, such as their cause, carrier, and severity. Furthermore, the mapping team attempts to relate Cholera outbreaks across the Caribbean to a single variable: climate. By labeling the amount of outbreaks and stormy weathers as the only pair of value, a correlation in between becomes obvious. But in this way, potential correlations between Cholera and other variables are easily overseen.

To make an alternate map, I would first narrow down the scale of the map to focus on the Caribbean region, since the original design of a global map was a waste of resources and functionality. Instead, I would leave more space to show the details of each location and outbreak. Secondly, the model of display can be improved by designing independent icons to represent each of the 4 data types, so that events such as storms and Cholera outbreaks can be distinguished from each other. Also, offering an option to display a heat map can lead to a better visualization than the original scatter plot. Moreover, if records like immigration patterns or economical status across the region are available, I would introduce them into the map as well to show other potential factors of Cholera outbreaks.  Last but not least,  there seems to be a minor bug where viewers can select timelines even prior to year 1833, although there is no information available back then.

 

Combining colors and aligning elements have always been hard for me. Definitely will try to make my website aesthetic next time!

My horrible production

My blog for this week features the visualization of “NYC Tenement Photographs“.  The dataset includes photographs taken by inspectors of the New York city tenement house department from year 1934 to 1938.  Although there are as many as 1102 photos in collection, only 6 data types are present. This obviously leads to difficulty in both finding information about each photo and classifying by vague attributes. For example, the last datatype was “Title”, which is a combination of the name of the building in the photo and its corresponding address; some of the photos do not even have an address attached. Also, the photo urls in this dataset direct to the webpage that displays the photo, instead of the photo itself. After looking into the coding system of digital collections at the New York Public Library, I discovered most of the true urls of the photos which unfortunately, still fail to display on Google Fusion Tables. Thus, the first tool that I utilized was Wordle , a website that creates word clouds according to the frequency of words used in the selected text. By entering the Title data, I was able to create this word cloud. It indeed tells some of the essential and most frequently used information, such as the heavily populated area (Manhattan) and the  most common type of the buildings (storefronts). However, I still want a more clear and direct visualization.

I filtered out all of the photos with a building address by using OpenRefine. It resulted in 416 effective items, which I used Tableau to split the building type from the Title section, leaving lines of address alone in a new row. By optimizing the dataset, I was able to map the locations of photos.  And I think it provides a better visualization of the geographical distribution of NYC Tenements.

The dataset I select today is the City Payroll Data, which includes quarterly payroll information for all Los Angeles City Departments since 2013, updated by the Los Angeles City Controller’s Office. As displayed in the spreadsheet, the data are assorted according to various types: Row ID, Year, Department, Title, Payroll Department, Record Number, Job Class Title, Employment Type, Hourly or Event Rate, Projected Annual Salary, Q1 Payments, Q2 Payments, Q3 Payments, Q4 Payments, Payments Over Base Pay, % Over Base Pay, Total Payments, Base Pay, Permanent Bonus Pay, Longevity Bonus Pay, Temporary Bonus Pay, Lump Sum Pay, Overtime Pay, Other Pay & Adjustments, Other Pay (Payroll Explorer), MOU, MOU Title, FMS Department, Job Class, Pay Grade, Average Health Cost, Average Dental Cost, Average Basic Life, Average Benefit Cost, Benefits Plan and Job Class Link. While there are 285008 rows stored,  a record in this specific dataset refers to the aforementioned profile of a department in the city.

Wallack and Srinivasan, in their writing, suggested that the ideological effects of the way in which sources have been divided into data could be recognized as either meta-ontology or community ontology.  Since the dataset is clearly collected and uploaded by Los Angeles City Controller’s Office, there is no doubt that it is an information system operated by the state.  Reflected through the design of certain data types is the official perspective that creates this dataset:  Average Health Cost, Average Dental Cost, Average Basic Life and Average Benefit Cost are all calculated as expenditure from the government, instead of the real costs of the citizens.  Thus, the current dataset caters to purposes of budgeting and shows less concerns from the community.  It makes the most sense for officials who are monitoring the annual expenditure as well as analysts interested in policymaking and institutional design.

On the one hand, this dataset demonstrates a detailed, official payroll information of all Los Angeles City Departments; on the other hand, however, it fails to evaluate the effect of the payments on workers. To compensate for its shortcoming, I would try to shed some lights on the well-being of the community : for example, tackling income inequality will be much easier if the dataset contains the distribution of salaries among different gender, race and ethnicity in the same department. Similarly, comparing people’s average spending on health related issues to the corresponding payment from the government will make more sense than a unilateral payroll information.  By and large, more community concerns can be covered with this approach, and the dataset can present more than one perspective although mostly applying meta-ontology.

For this week’s blog, I select “Finding Aid for the Collection of Material about Japanese American Internment, 1929-1956 bulk 1942-1946” to interpret and evaluate the collections of Japanese American Internment during the WWII. As shown in the scope and content note, the collection includes publications and press releases by the War Relocation Authority (WRA), as well as yearbooks and pamphlets that focused on the Manzanar and Minidoka internment camps, created by Japanese American internees and advocacy groups. It also includes recordings and transcripts of speeches and selections of published articles on subjects such as segregation within camps, the loyalty of Japanese Americans, resettlement, and the internment process.

 

The Container List introduces the contents within each of the 3 series. First, Series 1 consists of 2 boxes of publications and speeches sponsored by the WRA. The box and folder listing suggests narratives from an official perspective: reports for the living condition in the camps, and pamphlets advocating Japanese Americans internment, resettlement, and enlistment in the armed forces.

Series 2, on the other hand, includes a box of yearbooks and newsletters written and produced by Japanese American internees from the camps. Thus, it can be inferred that in this section,  the internees produce narratives about their lives in the camps.

Ultimately, Series 3 contains a box and a map folder which include printed materials and a recording of a radio broadcast. Since the creators vary from the Japanese American Citizens League to the American Council on Public Affairs, narratives of this section features external reflections on the internment of Japanese Americans.

Based on the records in this collection, I think it is still hard to get a comprehensive understanding of Japanese American Internment. One of the drawbacks in the collection is that except for box 1 of series 1,  all  of the remaining files are organized in alphabetical order. Instead of grouping the archive according to a specific timeline or topic, the current approach make viewers difficult to compare and analyze historic details such as the change of people’s attitude and treatment inside the camp as the war progressed. Also, the lack of sources from the internees’ perspective (contrast to the 2 boxes of official documents) can lead to significant misrepresentation.  Moreover, since this collection features two of the internment camps, it would be more subjective if a broader view on the relationship between the two camps and the other camps is available: did the two mentioned here offer superior resources for the internees? Or were they among the worst camps in the country? To compensate for these shortcomings, I’ll suggest to upgrade the collection by including more interviews and diaries of the internees, assort the documents in a chronological order, and evaluate the status of the featured camps in comparison to other camps in general.

 

Inventing Abstraction, 1910–1925 celebrates the centennial of Abstract Art as an interactive website accompanying a MoMA exhibition of the same title. Although the physical exhibition was only available from December 23, 2012 to April 15, 2013, the online display continues to educate viewers on the origins of abstraction. By demonstrating the emergence of abstraction in the form of a network connecting modern artists across countries and media, the exhibition relates to the most influential works in the early stage of abstraction in a broad range.

Sources:

Organized by Leah Dickerman, Curator, with Masha Chlenova, Curatorial Assistant, Department of Painting and Sculpture, the exhibition includes paintings, drawings, books, sculptures, films, photographs, sound poems, atonal music, and non-narrative dance to draw a cross-media portrait of early abstraction.  The curators selected works of 92 artists who were active during year 1910 to 1925,  and created a spreadsheet consisting the information of all of the aforementioned artists to determine the representative works and social networks on display. The selected artworks were photographed, scanned, transcribed, recorded, restored, shipped, and installed to integrate into the exhibition.  It is revolutionary that wide ranging sources, including early dance films and recordings of poetry and music, are brought into the galleries of early abstraction. The unprecedented collection of American vanguard art works is also groundbreaking to witness.

Processes:

 

The process of the exhibition was achieved via MoMA staff’ creation (including the curatorial and design team ), as well as the support from the Columbia University Software and Second Story.

On the one hand, the The Artist Network Diagram  was a significant component of both the interactive interface in the website exhibition and the outline of the physical exhibition.  Its creation started from curators   collecting the literal description of selected artists and their relationship. Scholars in the Columbia University then constructed a digital dot-graph based on the original chart. Furthermore, graphic designers sorted out a visually organic improvement on the graph. It was the 1936 MoMA exhibition Cubism and Abstract Art and the now-legendary diagram on the cover of its catalog that offered inspiration. Designers incorporated the Alfred chart (Alfred H. Barr, Jr, the founding director of the MoMA) with the concept of social network. Thus, a comprehensive network graph of early abstraction artists was made.

Second Story, on the other hand, contributed to the process by coding the sources and data into the network frame.  Creating an interactive diagram which enables the viewer to compare, relate and learn the artist information, artwork and conversations, the tech team utilized their mastery in programming to make the virtual exhibition possible.

Presentations:

Inventing Abstraction, 1910–1925 offers a multimedia visualization of the origins of abstraction. Suggested in a diagram, the spread of abstraction is about relationships and collective participation. The website presents a dynamic, 3D diagram of the connections between the artists, so that as visitors interact with the diagram, they can explore detailed networks, view artist portfolios, and draw their own conclusions about influence, impact, and invention.

The home page offers a brief introduction of the exhibition theme and the diagram to the viewers. By clicking Explore Connections, the viewer will enter the most essential part of the website – connections in between the artists. On the left and right side of the website, there are two  virtual buttons available for control: return to the previous page and a changeable scale. Such designs facilitate users’ experience when switching from different connections.  There are two navigation bars at the top and bottom. The primary navigation includes links to Connections, Artists, Conversations, and Programs & Events, while the secondary navigation leads to About the Exhibition, Network Diagram, Checklist, Publication, Music, Blog, Credits and MoMA.

Clicking the “Artists” link offers viewers an alphabetized list of featured artists, with the essential ones highlighted in red. Clicking on an artist’s portfolio enables viewers to examine detailed information about the artists and his/her artwork.