TY - JOUR
T1 - Mobility Data Science
T2 - Perspectives and Challenges
AU - Mokbel, Mohamed F.
AU - Sakr, Mahmoud Attia
AU - Xiong, Li
AU - Züfle, Andreas
AU - Almeida, Jussara M.
AU - Anderson, Taylor
AU - Aref, Walid G.
AU - Andrienko, Gennady L.
AU - Andrienko, Natalia V.
AU - Cao, Yang
AU - Chawla, Sanjay
AU - Cheng, Reynold
AU - Chrysanthis, Panos K.
AU - Fei, Xiqi
AU - Ghinita, Gabriel
AU - Graser, Anita
AU - Gunopulos, Dimitrios
AU - Jensen, Christian S.
AU - Kim, Joon-Seok
AU - Kim, Kyoung-Sook
AU - Kröger, Peer
AU - Krumm, John
AU - Lauer, Johannes
AU - Magdy, Amr
AU - Nascimento, Mario A.
AU - Ravada, Siva
AU - Renz, Matthias
AU - Sacharidis, Dimitris
AU - Salim, Flora D.
AU - Sarwat, Mohamed
AU - Schoemans, Maxime
AU - Shahabi, Cyrus
AU - Speckmann, Bettina
AU - Tanin, Egemen
AU - Teng, Xu
AU - Theodoridis, Yannis
AU - Torp, Kristian
AU - Trajcevski, Goce
AU - van Kreveld, Marc J.
AU - Wenk, Carola
AU - Werner, Martin
AU - Wong, Raymond Chi-Wing
AU - Wu, Song
AU - Xu, Jianqiu
AU - Youssef, Moustafa
AU - Zeinalipour, Demetris
AU - Zhang, Mengxuan
AU - Zimányi, Esteban
N1 - DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.
PY - 2024/7/1
Y1 - 2024/7/1
N2 - 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.
AB - 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.
KW - Environmental impacts
KW - GPS data
KW - Geospatial intelligence
KW - Mobility Patterns
KW - Spatiotemporal data
KW - Urban Mobility
UR - http://www.scopus.com/inward/record.url?scp=85196966582&partnerID=8YFLogxK
U2 - 10.1145/3652158
DO - 10.1145/3652158
M3 - Journal article
SN - 2374-0353
VL - 10
SP - 1
EP - 13
JO - Transactions on Spatial Algorithms and Systems
JF - Transactions on Spatial Algorithms and Systems
IS - 2
M1 - 10
ER -