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Mobility Data Science: Perspectives and Challenges

Title: Mobility Data Science: Perspectives and Challenges
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 S.; Kim, Joon Seok; Kim, Kyoung Sook; Kröger, Peer; Krumm, John; Lauer, Johannes; Magdy, Amr; Nascimento, Mario; Ravada, Siva; Renz, Matthias; Sacharidis, Dimitris; Salim, Flora; Sarwat, Mohamed; Schoemans, Maxime; Shahabi, Cyrus; Speckmann, Bettina; Tanin, Egemen; Teng, Xu; 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; Dep Informatica; Sub Geometric Computing; Geometric Computing
Publication Year: 2024
Subject Terms: Environmental impacts; Geospatial intelligence; GPS data; Mobility Patterns; Spatiotemporal data; Urban Mobility; Signal Processing; Information Systems; Modelling and Simulation; Computer Science Applications; Geometry and Topology; Discrete Mathematics and Combinatorics
Description: Mobility data captures the locations of moving objects such as humans, animals, and cars. With the availability of Global Positioning System (GPS)-equipped mobile devices and other inexpensive location-Tracking technologies, mobility data is collected ubiquitously. In recent years, the use of mobility data has demonstrated a significant impact in various domains, including traffic management, urban planning, and health sciences. In this article, we present the domain of mobility data science. Towards a unified approach to mobility data science, we present a pipeline having the following components: mobility data collection, cleaning, analysis, management, and privacy. For each of these components, we explain how mobility data science differs from general data science, we survey the current state-of-The-Art, and describe open challenges for the research community in the coming years.
Document Type: article in journal/newspaper
File Description: application/pdf
Language: English
ISSN: 2374-0353
Relation: https://dspace.library.uu.nl/handle/1874/473001
Availability: https://dspace.library.uu.nl/handle/1874/473001
Rights: info:eu-repo/semantics/OpenAccess
Accession Number: edsbas.EEDB2F0A
Database: BASE