Year: 2022
Type: article
Abstract: This report documents the program and the outcomes of Dagstuhl Seminar 22021 "Mobility Data Science". This seminar was held January 9-14, 2022, including 47 participants from industry and academia. The goal of this Dagstuhl Seminar was to create a new research community of mobility data science in which the whole is greater than the sum of its parts by bringing together established leaders as well as promising young researchers from all fields related to mobility data science. Specifically, this report summarizes the main results of the seminar by (1) defining Mobility Data Science as a research domain, (2) by sketching its agenda in the coming years, and by (3) building a mobility data science community. (1) Mobility data science is defined as spatiotemporal data that additionally captures the behavior of moving entities (human, vehicle, animal, etc.). To understand, explain, and predict behavior, we note that a strong collaboration with research in behavioral and social sciences is needed. (2) Future research directions for mobility data science described in this report include a) mobility data acquisition and privacy, b) mobility data management and analysis, and c) applications of mobility data science. (3) We identify opportunities towards building a mobility data science community, towards collaborations between academic and industry, and towards a mobility data science curriculum.
Authors: Mokbel, Mohamed, Sakr, Mahmoud, Xiong, Li, Züfle, Andreas, Almeida, Jussara, Anderson, Taylor, Aref, Walid, Andrienko, Gennady, Andrienko, Natalia, Cao, Yang, Chawla, Sanjay, Cheng, Reynold, Chrysanthis, Panos, Fei, Xiqi, Ghinita, Gabriel, Graser, Anita, Gunopulos, Dimitrios, Jensen, Christian, Kim, Joon-Sook, Kim, Kyoung-Sook, Kröger, Peer, Krumm, John, Lauer, Johannes, Magdy, Amr, Nascimento, Mario, Ravada, Siva, Renz, Matthias, Sacharidis, Dimitris, Shahabi, Cyrus, Salim, Flora, Sarwat, Mohamed, Schoemans, Maxime, Speckmann, Bettina, Tanin, Egemen, Theodoridis, Yannis, Torp, Kristian, Trajcevski, Goce, van Kreveld, Marc, Wenk, Carola, Werner, Martin, Wong, Raymond, Wu, Song, Xu, Jianqiu, Youssef, Moustafa, Zeinalipour, Demetris, Zhang, Mengxuan, Zimányi, Esteban
Institutions: University of Minnesota, Université Libre de Bruxelles, Emory University, George Mason University, Universidade Federal de Minas Gerais, Purdue University West Lafayette, Fraunhofer Institute for Intelligent Analysis and Information Systems, Kyoto University, University of Hong Kong, University of Pittsburgh, University of Massachusetts Boston, AIT Austrian Institute of Technology GmbH, National and Kapodistrian University of Athens, Aalborg University, Pacific Northwest National Laboratory, AIST Tokyo Waterfront, National Institute of Advanced Industrial Science and Technology, Christian-Albrechts-Universität zu Kiel, Microsoft (United States), University of California, Riverside, University of Alberta, University of Southern California, UNSW Sydney, Arizona State University, Eindhoven University of Technology, The University of Melbourne, University of Piraeus, Iowa State University, Utrecht University, Tulane University, Technical University of Munich, Hong Kong University of Science and Technology, Nanjing University of Aeronautics and Astronautics, Alexandria University, University of Cyprus
Language: English
Subfield: Transportation
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4412340772