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Conference proceeding
A Knowledge Sharing Approach to Foster Interdisciplinary Pedestrian Dynamics and Epidemiological Modeling Research and Practice
Proceedings of Ninth International Congress on Information and Communication Technology ICICT 2024, London, Volume 2, Vol.2 (London), pp.313-324
Lecture Notes in Networks and Systems
International Congress on Information and Communication Technology (ICICT 2024), 9th (London, England, 02/19/2024–02/22/2024)
2024
Web of Science ID: WOS:001326995600025
Abstract
A significant challenge to interdisciplinary computational science arises from the difficulty of using models from diverse domains. We show that combining the concepts of knowledge sharing-a component of knowledge management-and recommender systems, which have traditionally been viewed as separate undertakings, can help address the above limitation. In particular, we describe the VIPRA Recommender System (VRS), which enables transformative interdisciplinary science using pedestrian dynamics for epidemiological modeling. VRS provides a venue through which researchers can share capabilities of modeling systems and practitioners can receive assistance in identifying and using systems that meet their modeling needs, such as recommendations of suitable models and their input parameters. We present a usability study to establish its usefulness as a tool to empower interdisciplinary science using models from a variety of domains.
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Details
- Title
- A Knowledge Sharing Approach to Foster Interdisciplinary Pedestrian Dynamics and Epidemiological Modeling Research and Practice
- Publication Details
- Proceedings of Ninth International Congress on Information and Communication Technology ICICT 2024, London, Volume 2, Vol.2 (London), pp.313-324
- Resource Type
- Conference proceeding
- Conference
- International Congress on Information and Communication Technology (ICICT 2024), 9th (London, England, 02/19/2024–02/22/2024)
- Publisher
- Springer Nature
- Series
- Lecture Notes in Networks and Systems
- Number of pages
- 12
- Grant note
- National Science Foundation; National Science Foundation (NSF)
- Copyright
- © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024
- Identifiers
- WOS:001326995600025; 99381590967306600
- Academic Unit
- Computer Science; Hal Marcus College of Science and Engineering
- Language
- English