Web Application

A Visualization Tool and Assessment Framework for Civic Technology Use in the DMV Area: The Case of 311 Systems During the COVID-19 Outbreak

The 311 systems that city officials currently deploy can efficiently detect non-emergency civic issues such as potholes and trash. From a socio-technical perspective, residents can re-appropriate the technology for their own purpose adding new capacities and affordances not initially intended. For example, when Hurricane Irma hit Miami in 2017, residents used 311 systems to report disaster-related issues, which led city officials to adapt the system by creating a new category.

Making Information Deserts Visible: Computational Models, Disparities in Civic Technology Use, and Urban Decision Making

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.

Toward Identifying Values and Tensions in Designing a Historically-Sensitive Data Platform: A Case-Study on Urban Renewal

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.

Heuristics for Assessing Computational Archival Science (CAS) Research: The Case of the Human Face of Big Data Project

Computational Archival Science (CAS) has been proposed as a trans-disciplinary field that combines computational and archival thinking. To provide grounded evidence, a foundational paper explored eight initial themes that constitute potential building blocks. In order for a CAS community to emerge, further studies are needed to test this framework. While the foundational paper for CAS provides a conceptual and theoretical basis of this new field, there is still a need to articulate useful guidelines and checkpoints that validate a CAS research agenda.

A Tool for Estimating and Visualizing Poverty Maps

"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.

Remapping Southside Community: Storytelling Urban Renewal Impact

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.

Mapping Inequality

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.

Open Data Impact Map

The Center for Open Data Enterprise is a non-profit organization that aims to maximize the value of open data as a public resource that anyone can use. As a means to promote the impact and value of using open data, the center designed and developed the Open Data Impact map. As a Data Science & Technology Fellow at the Center for Open Data Enterprise, I have worked on the Open Data Impact Map, which is a searchable, centralized database of open data use cases from around the world. The map shows the distribution of organizations in the world that make use of open data.

On Information Deserts

Information accessibility problems include diverse types of human- and system-driven barriers that make it difficult for individuals to access desired information. These issues have been studied in two main streams: (1) a human-centered view based on the understand­ing of individual-level characteristics such as physical impairment and economic status, and (2) a technology-focused view that emphasizes system-based factors such as the information filtering techniques and interface designs.

Drupal Course Management Module for UMD Websites

This project was designed to provide most up-to-date courses information to University of Maryland College of Arts and Humanities (ARHU) websites. Since most ARHU websites were implemented with Drupal (Content Management System), a Drupal module was developed to migrate the university's course catalogs into Drupal databases. For crawling the course catalogs, Brady Law (CS student)'s Python scripts were modified and re-implemented.

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