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Towards Mobility Data Science (Vision Paper)

Fuente: arXiv

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Bibliographic Details
Main 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-Seok, 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, 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
Format:	Preprint
Published:	2023
Subjects:	Other Computer Science
Online Access:	Acceder al recurso
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_version_	1866911790607106048
author	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-Seok 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 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
author_facet	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-Seok 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 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
contents	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.
format	Preprint
id	arxiv_https___arxiv_org_abs_2307_05717
institution	arXiv
publishDate	2023
record_format	arxiv
spellingShingle	Towards Mobility Data Science (Vision Paper) 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-Seok 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 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 Other Computer Science 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.
title	Towards Mobility Data Science (Vision Paper)
topic	Other Computer Science
url	https://arxiv.org/abs/2307.05717