ARH 607 Digital Art History

The Christian Kannon, The Buddhist Madonna: Maria Kannons in Japanese Christian Worship

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• In working with objects that are not from the United States, how does one balance American copyright law with those of other countries?
• Do laws about fair use of art by teachers apply to the education departments of museums?
• Do copyright laws apply to objects with “full ownership” (i.e. a donor has given an institution an object(s) with no requirements for its display and usage) in a collection?
• How should museums negotiate displaying artistic works that violate copyright laws? (i.e. readymades)

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“The Buddhist Madonna, The Christian Kannon” exhibition features the dual Christian and Buddhist visual imagery that Japan’s “hidden Christian” population used to conceal their faith during the era of Christian prosecution during the Edo period (1603-1868) and uphold their syncretic faith. The main topic of the exhibition’s focus is Maria Kannon statues, icons of the bodhisattva Kannon (Sanskrit-Avalokiteśvara) that acted as objects for Marian worship, but it will feature other hidden Christian artifacts and videos.

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NOTE: I attempted to upload the csv file to my blog, but WordPress unfortunately does not support that file type for security reasons. However, I have included the Excel version of the document and the link to its csv Google Spreadsheet too.

Omeka Dublin Core Metadata – Sheet1 (Excel Version)

Omeka Dublin Core Metadata (Google Spreadsheet Version)

In “An Outline for Computational Art History”, Lev Manovich presents a set of questions that art historians can use in creating digital projects or investigations. He recommends 3 steps:

1. Which stage in the process of circulating art do you want to analyze?
2. What types of data do you want to analyze?
3. At which point in the stage of data processing would you like to be?

As digital methods grow in popularity among the humanities and art history fields, it is vital for one to consider the procedures of his or her investigation. Art historians may underestimate the amount of collaboration and effort they will have to put into a project, and Manovich’s outline can establish realistic and effective expectations. Manovich’s process can also assuage the fears of art historians unfamiliar with digital technology and investigations. In its outlining of categories, it assures them that they can engage with data at the level which they feel most apt and can ask others to help fill gaps in digital prowess.

ImageJ software, created by Lev Manovich, uses algorithms and plugin tools to visually analyze and organize large quantities of images at the macro level. Though I only spent three days experimenting with the software and plugins, art historians and those who study two-dimensional images may enjoy its ability to discover patterns in hundreds or thousands of images. Through analyzing images objectively, ImageJ breaks from the tradition of subjective investigation in the humanities, which can answer and create new research questions.

However, ImageJ may be a bit daunting to someone who has little experience extracting data from ZIP files, running macros, and installing plugins. In order to make some of the software’s plugins work, ImageJ requires using images of the same size and spreadsheets with information correlated to the images. Creating a spreadsheet may take additional time, but users can customize variables and macros like ImageMeasure can analyze quantitative variables, such as hue, that users can copy into spreadsheets. With practice and time, users unfamiliar with computer science can create image folders and data sheets to take full advantage of ImageJ’s capabilities.

The ImagePlot macro was my favorite plugin to use because one can compare variables of a set of images with an X-Y axis to discover patterns or see how variables affect one another.

The ImageSlice plugin condenses images into slivers and displays them side by side. While this tool may help one see numerous images all at once, I do not know how one can use this tool to answer a research question, since it organizes images by file name.

Unfortunately, I was unable to make ImageMontage work, but after judging the screenshots of the plugin on the ImageJ website, the tool appears to be suited for massive sets of images. Most computers’ file viewers only display 20 images simultaneously, while ImageMontage can display hundreds or thousands in a single view, useful for macro-level analysis

Digital Harlem

Three members of the Arts eResearch Unit at the University of Sydney built the structure of Digital Harlem, a project built on the research of four historians in the university’s Department of History. The Australian Research Council Discovery Grant, University of Sydney-Sesqui Research and Development Grant helped fund this interactive digital project.

Using information from legal records, newspapers, archival and published sources, the digital map project documents the events, inhabitants, and buildings of the Harlem neighborhood in New York City from 1915-1930. The creators state that by using records that document the everyday lives of lower-class individuals, this project diverges from standard scholarship on Harlem’s middle class individuals and artists. In combining Google Maps with the website’s database with recorded events, one can see the development of businesses at specific addresses and the spatial relationships between the events and locations of people’s lives. However, by limiting the database to secondary sources, Digital Harlem loses valuable information from the personal accounts of Harlem’s residents.

One can choose filters based on “Events” (ex. Weddings or Robberies), “People”, and “Places” (by street address or type of building, i.e. Bank or Church), and create layers to answer personalized research questions about the social geography of early 20^th century Harlem. For example, if one asks “From 1920-1925, were speakeasies located far away from police stations?” one can create layers based on time and type of location, and Digital Harlem will display all of the points and documents related to the inquiry on the Google Maps box. However, one cannot see digital copies of the documents listed in a location’s tab, limiting the access and publishing to those who have worked on Digital Harlem itself.

One can also click on a data point to see which individuals, businesses, and events were associated with a particular address from 1915-1930. While the Events and Places tabs do not require prior knowledge of an event or place, the People tab does not function. Even if one knows the name of a specific individual mentioned in a previous record, Digital Harlem will not generate any records. Links under the “Featured Section” redirects to an external WordPress article on a specific subject (i.e. Harlem Hospitals) with historic photographs and a customized Google Map with filters related to the subject. However, not all of the links to customized Google Maps work, but the ones that do redirect users to the Digital Harlem website allows one to add additional filters, prompting further research questions.

GhostMetropolis- A Featured Collection of HyperCities

Part of the larger HyperCities project created by University of California Los Angeles professors Todd Presner, David Shepard, and Yoh Kawano, GhostMetropolis answers how primary sources and maps can help in understanding the history of cities and human geographies. The three professors have created projects, but anyone can build a new HyperCity project that answers an individual question. Users can incorporate media such as Google Earth, Picassa picture viewer, YouTube, Twitter, Vimeo Video Player, which give users a clearer understanding of how geography and social environments impacts lifestyles. If one needs help in creating his or her own project, the “HyperCities Construction Kit”, “FAQ”, and “HyperCities Source Code” pages can help.

However, if one cannot install Google Maps because one is using a public computer (i.e. a library computer) or the computer does not have a supported browser (Safari, Chrome, and Firefox), then the website has little available content. In opening the GhostMetropolis homepage, it displays a grid list of all the projects, which focus on cities such as Fukushima, Japan, Los Angeles, and Rome. Clicking on a project title will commence the path, which encourages visitors to explore and experiment with the multimedia layout. The “Map Library” option overlays historic maps on a larger digital map which one can easily toggle on/off.

GhostMetropolis has several shortcomings. The grid interface on the first place is not easy to navigate, especially if one wants to find a specific page or project. Additionally, Presner, Shepard, and Kawano do not give information on the funding of the project, nor does the layout of the website allow one to easily cite or link to external bibliographical sources. However, due to the collaborative nature of the larger HyperCities project, the original authors or contributors can devise methods and tools to improve the site’s bibliographic weaknesses.

T-RACES (Testbed for the Redlining Archives of California’s Exclusionary Sapces)

T-RACES claims on its website to be one of the first digital “‘humanities grids’”. Authored by Richard Marciano (University of Maryland), Chien-Yi Hou, and David Goldberg (Director of University of California Humanities Research Institute), T-RACES has interactive maps and preserves documents about the redlining process under the Home Owners Loan Corporation (HOLC) as part of President Franklin D. Roosevelt’s New Deal. The project investigates the process behind redlining and how it had/has an impact on racial-economic discrimination and access in California and North Carolina college cities. However, the demo only gives access to two North Carolina cities as opposed to eight in California.

The T-RACES homepage provides links to all of the project’s pages, but one may have difficulty in discovering the information about the project located in the “Regional Networks” button at the bottom of the page. From the Homepage, the “Regional Redlining”, “Color Codes”, “National Redlining”, “Before HOLC”, “About HOLC”, and “Beyond HOLC” pages provide historical and socio-economic context on the redlining process using maps and excerpts from government documents. The “About Us” page lists contributors and “References” provides links to articles that mention the T-RACES project. The “News” tab is the only location on the website that provides information about funding; an article about a IMLS grant that the project received.

The highlight of the website, the “Demo” page provides interactive Google Maps of the color-coded “security areas” maps used to divide cities into districts. A University of North Carolina-developed data grid (central catalog) and HASS (Humanities, Arts, and Social Sciences Grid) infrastructures by the UC Humanities Research Institute provide the backbone of the Google Maps, in which one can view security area and specific districts all at once or selectively. One can toggle layers on and off to see the social-geographic connections between areas and how divisions in the 1930s affected districts visible on the Google Map of present cities. The “Tools” section has a variety of bibliographic material, including documents on redlining, the KMC file for export, and a query tool to search the documents. While the T-RACES demo currently does not support scholarship outside of the academic sphere, the project can grow and support more cities.

Holocaust Geographies Collaborative-Mapping Mobility in the Budapest Ghetto and Arrests of Italian Jews 1943-1945

The Holocaust Geographies Collaborative, headed by Waitman Beorn, Alberto Giordano, Simone Gigliotti, Tim Cole, Anna Holian, Anne Knowles, and Paul Jascot as part of the Stanford University Spatial History Project investigates how understanding space, geography, scale, and location impacted the development and consequences of the Holocaust. In particular, maps and timelines demonstrate how the Holocaust was a spatial phenomenon. The Spatial History Project of Stanford, funded by the Vice Provost for Undergraduate Education, Andrew M. Mellon Foundation, Wallenberg Foundation Media Places Initiative provided funding to the project, information that the authors list at the bottom of its homepage. However, the Holocaust Geographies Collaborative project does not permit editing, scholarship, or projects outside of the project.

The “Mapping Mobility in the Buddhist Ghetto” feature uses an introductory video, digital map, voiceover narration, and drag-able animations to map the foot-traffic activity on a specific day within a Jewish ghetto. It strives to answer how the city plan and curfews impacted the movement of Budapest Jews, Nazis, and bystanders. The accompanying narration adds another layer of understanding, which one could not grasp from the map alone. Layers that one can toggle on/off to show landmarks, change the time of day, and adjust the speed permit one to interact with the map in the way one prefers. However, the text accompanying the map does not provide footnotes nor bibliographic material, which limits users’ access to learning outside of the project.

The “Arrests of Italian Jews”, 1943-1945 documents the dispersal patterns of the arrests of Italian Jews during the Holocaust with an interactive map. Users can manipulate sliders to select ranges of time and dates, which appears in dots on the map above. When one hovers over a specific region, the scatterplot and several bar graphs on the right side record distances and demographics of the arrested persons based on a particular time frame and location. The sliders are a bit difficult to manipulate and users may have a difficult time creating meaning from the scatterplot. However, the map in the top left corner, with color-coordinated circles, better illustrates the variable of distance from where the arrest occurred to the person’s last residence.

1. How do I turn my research into a searchable format? I always take so many notes and I waste so much time trying to go through them trying to find one piece of information.
2. What is a “content model”?
3. What is “natural language processing”?
4. What exactly is “cultural analytics”?
5. What is “ambient data”?