We describe computational treatments of archival collections through a case study of World War II Japanese-American Incarceration Camps. Camp staff and police officers compiled so-called "internal security" reports relating to alleged cases of "disorderly conduct, assault, theft, loss of property, and accidents" in the camps, and an index to these reports comprising over 25,000 index cards to the reports. The sheer size of these collections is pushing archivists and researchers to consider new forms of processing for collections at scale.
Today's digital revolution is fostering remarkable innovations. The landscape of innovation is rapidly changing and thus difficult to navigate or study. Understanding broader participation in innovation requires large datasets on the innovation participants and their activities. As organizational and industry boundaries become fuzzy in the digitized world, small data analysis cannot fully explain how boundaries shift and evolve. Open innovation leads to overlapping roles of designer and user, making it inadequate to examine innovation development and adoption separately.
"Multi-scale mass-deployable cooperative robots are a next-generation robotics paradigm where a large number of robots that vary in size cooperate in a hierarchical fashion to collect information in various environments. While this paradigm can exhibit the effective solution for exploration of the wide area consisting of various types of terrain, its technical maturity is still in its infant stage and many technical hurdles should be resolved to realize this paradigm." (Choo et al., 2013)
This research will develop a foundational tool for understanding how civic technologies are used and how information inequalities manifest in a city. User data from new civic technologies that reveal inequalities in the information environments of citizens has only recently become available. Since a large portion of data is demographically or geospatially biased due to varying human-data relationships, computational social scientists have used data modeling and algorithmic techniques to adjust the data and remove biases during data-processing.
Urban renewal was a national initiative from the 1960s through 70s aimed at improving so-called “blighted” areas, and resulted in the displacement of many vibrant communities. While the underlying mechanisms of urban renewal have been examined, there have been very few data-driven, evidence-based studies that take into account the histories and interests of former residents. The “Human Face of Big Data” project started as a digital curation effort to design and develop a web-based, big data platform that provides insights and analytics into the mechanisms of this process.
"Poverty maps" are designed to simultaneously display the spatial distribution of welfare and different dimensions of poverty determinants. The plotting of such information on maps heavily relies on data that is collected through infrequent national household surveys and censuses. However, due to the high cost associated with this type of data collection process, poverty maps are often inaccurate in capturing the current deprivation status.
This project aims to build a map-based platform that presents historical documents of the nation-wide, urban renewal project in 1960's and 70's and to provide easy-to-use interfaces that can be used by former residents, archivists, researchers, and citizens. Ultimately, this platform aims to reconstruct a virtual neighborhood where people can share their memories by creating social networks of former residents.
Over the past four years, teams of archivists have digitized portions of National Archives RG195: General Records of the Home Owners’ Loan Corporation [HOLC]. The records include surveys, memorandums, and maps of American neighborhoods in the 1930’s. Now that the records are available digitally, students and faculty members are working to curate the collection and “data-fy” the information contained within.
In a creative process, divergent thinking needs to be stimulated to generate novel ideas; yet these ideas must be synthesized to produce something valuable. Hence to foster creativity in developing IT products, creators need to manage the tension between novelty and value. Since the forces affecting the novelty-value tension often exist outside a creator's group or organization, we apply organizational ecology theory to propose an industry-level, ecological model for understanding the novelty of IT products.
This project was conducted in 2008 for my bachelor's thesis in the Department of Electrical Engineering at Seoul National University (it was more like a capstone project rather than a thesis, since the focus of the project was mainly at implementing algorithms rather than analyzing the performance of algorithms using concrete measures, e.g., recall and precision). I implemented an image retrieval system prototype that takes an image as input, and outputs most similar images from the image database.