Short Paper

New Kids on the Block? Exploring Onboarding Strategies of Prospective Professionals in Cybersecurity

This paper explores how prospective professionals, including those outside of educational institutions, approach entering the cybersecurity field. Through qualitative interviews with individuals planning a cybersecurity career, we explore diverse challenges they face during their journey to enter the profession. Our preliminary analysis suggests their challenges may include a lack of awareness of occupational culture, insufficient domain-specific language, visibility into the practitioner community, and differences in expectations between new and practicing professionals.

Examining the Shift in Political Inclination of Korean Middle School Language Textbooks between the Independence and the Korean War (1945–1953): A Network Modeling Approach

This study leverages network modeling methodologies to examine the distribution of political inclinations in Korean middle school language textbooks from 1945 to 1953. The textbooks included in this study are 82 textbooks, where 37 of which from the U.S. military government period (1945-1948), 30 of which from the South Korean government establishment period (1948-1950), and 15 of which from the wartime period (1950-1953).

An Evaluation of GPT-4V for Transcribing the Urban Renewal Hand-Written Collection

In November 2024, OpenAI released GPT- 4V(ision), which includes Optical Character Recognition (OCR) capabilities. Given that much of the data curation, processing, and cleaning can be managed through user-friendly prompts (i.e., chat), we aim to conduct an initial assessment of GPT-4V’s effectiveness in transcribing hand-written documents from the urban renewal collection. If GPT-4V can accurately digitize hand-written documents through carefully crafted prompts, it could become a valuable tool for nonexperts in transcribing historical documents on a large scale.

Towards an Expectation-Oriented Model of Public Service Quality: A Preliminary Study of NYC 311

The 311 system has been deployed in many U.S. cities to manage non-emergency civic issues such as noise and illegal parking. To assess the performance of 311-mediated public service provision, researchers developed models based on execution time and the status of execution. However, research on user satisfaction suggests that the level of individuals’ perception is asymmetric with respect to the quality of services, because negative experiences have a stronger impact on people’s dissatisfaction than positive experiences do for satisfaction.

Multi-Generational Stories of Urban Renewal: Preliminary Interviews for Map-based Storytelling

Urban renewal was a project of the American government that aimed to reconstruct poor urban neighborhoods. Because community-level data that shows the underlying mechanisms of urban renewal has not been curated in a systematic way, due to the complexity and volume of the relevant archival collections, we aim to digitally curate property acquisition documents from the urban renewal projects that affected the Southside neighborhood of the city of Asheville, North Carolina, in the form of a map-based, interactive web application. This paper reports early findings from interviews.

Digital Curation of a World War II Japanese-American Incarceration Camp Collection: Implications for Sociotechnical Archival Systems

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.

Towards Understanding Communication Behavior Changes during Floods Using Cell Phone Data

Natural disasters such as hurricanes, floods or tornadoes affect millions of individuals every year. As a result, governments spend millions of dollars in emergency response allocating resources to mitigate the damages. Effective resource allocation requires a deep understanding of how humans react when a disaster takes place. Due to the multiplicity of human behavior, however, it is not trivial to understand human behaviors at large scale during and after the disaster.

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.