Aging, Technology, and Intergenerational Information Engagement (2025 - current)
This project investigates how intergenerational collaboration can enhance older adults’ access to, understanding of, and engagement with health and social information in a digital society. Building on perspectives from information science, health communication, and gerontology, the study connects college students and older adults in libraries and community centers where they collaboratively seek, share, and evaluate information using AI-driven and advanced digital tools. Through this experimental, community-based framework, the project examines how college students can be trained and supported to act as caregivers and information intermediaries, facilitating trustful and empowering interactions with older participants. By combining qualitative observation and quantitative assessment, this research aims to develop effective intergenerational learning and information literacy programs that promote digital inclusion, social connectedness, and healthy aging. Ultimately, it seeks to build a sustainable model for community engagement where technology and human connection jointly advance well-being across generations.
Research Team
Sanghee Oh (PI, SKKU), Sueyoen Syn (CUA)
Student Researchers: Hyunsoo Yoon, Barun Hwang, Sungha Moon
Work-in-progress studies
Life -long education and information practice
A systematic review of caregivers' information seeking behaviors
SKKU FAIR Research (2025-2027, 3-year project). Funded by SKKU
Project Description: FAIR-Based Biomedical Data Management and Sharing
This project aims to establish a FAIR-based data-sharing ecosystem in the biomedical domain by enhancing the findability, accessibility, interoperability, and reusability of research data. Recognizing that biomedical data directly affect human life and health, the project integrates expertise from library and information science, software engineering, and health sciences to develop frameworks and technologies that improve data utility and governance across its life cycle.
Specifically, it seeks to (1) introduce and apply the FAIR principles to maximize data usability, (2) leverage AI and automation to advance machine-actionable data sharing beyond traditional repositories, and (3) design sustainable data governance models that ensure transparency, reproducibility, and ethical data stewardship. The project contributes to building an intelligent open-science infrastructure that promotes research integrity, accelerates scientific discovery, and strengthens Korea’s global competitiveness in biomedical data management and open research.
Research Team
Wonsik Shim (PI, SKKU), Youngseek Kim (SKKU), Sanghee Oh (SKKU), Juhee Cho (SKKU)
Student Researchers: Seyun Sim (SKKU), Yoonseo Park (SKKU)
Selected publications/presentations
Oh, S., Park, Y., & Sim, S. (2025). Exploring Data Sharing in Medical and Health Sciences through Mega Journals. Proceedings of the Association for Information Science and Technology, 62(1), 1616-1618.
Regional Disparities in Information Perceptions and Resource Distribution in Korea (2023-2026, 3-year project). Funded by National Research Foundation of Korea
This three-year project aims to understand and visualize information inequality across regions in South Korea through the development of an AI-powered visualization platform. In the first year, we will establish comprehensive metrics for assessing informational disparities grounded in the Local Information Landscapes (LIL) theory. The second year will focus on developing an AI-based predictive model to forecast future trends, using data derived from surveys and open library resources. By the final year, we plan to deliver a user-friendly prototype that enables the exploration of regional information gaps. Integrating perspectives from information science, data science, and information technology, this study employs both qualitative and quantitative approaches. Beyond theoretical advancement—such as extending LIL theory to the health and education domains—the project seeks to inform policy-making, promote data transparency, and strengthen AI and data literacy among local communities. Ultimately, the research aims to foster equitable information access and support evidence-based decision-making in the digital era.
Research Team
Jongwook Lee (PI, KNU), Sanghee Oh (SKKU), Myeong Lee (GMU), Seungwon Yang (LSU). Kwonho Choi (KNU), Minsook Park (FSU)
Student researchers: Hyunsoo Yoon, Sungha Moon, Daechan Yang, Hojin Park, Chaeri Son
Selected Publications/Presentations
Yang, S., Yang, D., Son, C., Park, H., & Oh, S. (2025). Examining Urban and Rural Information Needs through Topic Modeling: A Case of South Korea. Proceedings of the Association for Information Science and Technology, 62(1), 1144-1148.
Oh, S., Lee, M., & Lee, J. (2025, accepted). Information awareness, access and socioeconomic deprivation: a cross-jurisdictional study of local health information. Aslib Journal of Information Management.
Lee, M., Lee, J., Kang, W., & Oh, S. (2023). Aggregate‐Level Analysis of Information Behavior: A Study of Public Library Book Circulation. Proceedings of the Association for Information Science and Technology, 60(1), 1025-1027.
Kang, W., Lee, M., Lee, J., & Oh, S. (2023). AI or Authors?: A Comparative Analysis of BERT and ChatGPT's Keyword Selection in Digital Divide Studies. Proceedings of the Association for Information Science and Technology, 60(1), 1004-1006.