Dr. Shih-Lung Shaw is Alvin and Sally Beaman Professor and Arts and Sciences Excellence Professor of Geography as well as the Director of Confucius Institute at the University of Tennessee, Knoxville. He received his Ph.D. and M.A. degrees from The Ohio State University and his B.S. degree from National Taiwan University. His research interests cover GIS for transportation (GIS-T), space-time GIS, time geography, transportation planning and modeling, and human dynamics. His recent research has focused on space-time analytics of human dynamics in a hybrid physical-virtual world based on various types of individual tracking data such as cell phone data, taxi tracking data, travel-activity survey data, and online social media data. Dr. Shaw is a Fellow of the American Association for Advancement of Science (AAAS) and a recipient of the Edward L. Ullman Award for Outstanding Contributions to Transportation Geography from the Association of American Geographers (AAG). He served as the Head of the Department of Geography at the University of Tennessee, Knoxville and is the current Chair of the Research Committee of the University Consortium for Geographic Information Science (UCGIS). He also serves on the editorial board of International Journal of Geographical Information Science, Journal of Transport Geography, Travel Behaviour and Society, and Geographical Research (China). For additional information, please visit http://geography.utk.edu/about-us/faculty/dr-shih-lung-shaw/.
GIScience for Human Dynamics Research
Shih-Lung Shaw, Ph.D.
Alvin and Sally Beaman Professor &
Arts and Sciences Excellence Professor
Department of Geography
University of Tennessee
Knoxville, TN 37996-0925
Third International Conference on Spatial Data Mining and Geographical Knowledge Services (ICSDM 2017), Wuhan, China, September 21-22, 2017
Due to advancements of location-aware technology, mobile technology, and information and communication technology (ICT), we have seen many important changes to how people carry out their activities and interactions and how the urban, economic, and social systems operate in today’s world. With the arrival of a Big Data era, unprecedented data collection of a wide range of human activities in both physical and virtual spaces offer great opportunities for us to better understand human dynamics. However, the current theoretical and technical frameworks of geographic information systems (GIS), which are based on the concept of absolute space, are limited in taking full advantages of using various individual tracking data to gain insights on human dynamics. Human dynamics are not just space-time trajectory paths that are described by specific absolute locations in physical space. Many activities and interactions in our daily lives take place within various contexts that are not based on the concept of absolute space. How an activity is situated relative to other people and entities (i.e., relative space), how an activity is related to other people and entities (i.e., relational space), and how an activity is perceived in an actor’s mind (i.e., mental space) are all critical to the understanding and analysis of human dynamics. The conventional GIS data models based on an absolute space approach have major limitations of dealing with human dynamics beyond the concept of absolute space. Torsten Hagerstrand suggested some useful concepts such as situation, project, thereness, and diorama in the context of time geography that are important to the understanding of human dynamics from the perspectives of relative space, relational space, and mental space. This presentation will discuss specific time-geographic concepts to illustrate a need of developing a multiple-space GIS framework that can integrate absolute space, relative space, relational space, and mental space to better support human dynamics research in a hybrid physical-virtual space and within a space-time context.