Towards Mobility Data Science (Vision Paper)
Abstract
Mobility data captures the locations of moving objects such as humans, animals, and cars. With the availability of 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 significant impact in various domains including traffic management, urban planning, and health sciences. In this paper, we present the emerging domain of mobility data science. Towards a unified approach to mobility data science, we envision 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.
Cite
@article{arxiv.2307.05717,
title = {Towards Mobility Data Science (Vision Paper)},
author = {Mohamed Mokbel and Mahmoud Sakr and Li Xiong and Andreas Züfle and Jussara Almeida and Taylor Anderson and Walid Aref and Gennady Andrienko and Natalia Andrienko and Yang Cao and Sanjay Chawla and Reynold Cheng and Panos Chrysanthis and Xiqi Fei and Gabriel Ghinita and Anita Graser and Dimitrios Gunopulos and Christian Jensen and Joon-Seok Kim and Kyoung-Sook Kim and Peer Kröger and John Krumm and Johannes Lauer and Amr Magdy and Mario Nascimento and Siva Ravada and Matthias Renz and Dimitris Sacharidis and Cyrus Shahabi and Flora Salim and Mohamed Sarwat and Maxime Schoemans and Bettina Speckmann and Egemen Tanin and Xu Teng and Yannis Theodoridis and Kristian Torp and Goce Trajcevski and Marc van Kreveld and Carola Wenk and Martin Werner and Raymond Wong and Song Wu and Jianqiu Xu and Moustafa Youssef and Demetris Zeinalipour and Mengxuan Zhang and Esteban Zimányi},
journal= {arXiv preprint arXiv:2307.05717},
year = {2024}
}
Comments
Updated to reflect the major revision for ACM Transactions on Spatial Algorithms and Systems (TSAS). This version reflects the final version accepted by ACM TSAS