Mobility Data Science (Dagstuhl Seminar 22021)

Mohamed F. Mokbel; Mahmoud Attia Sakr; Li Xiong; Andreas Züfle; Jussara M. Almeida; Taylor Anderson; Walid G. Aref; Gennady L. Andrienko; Natalia V. Andrienko; Yang Cao; Sanjay Chawla; Reynold Cheng; Panos K. Chrysanthis; Xiqi Fei; Gabriel Ghinita; Anita Graser; Dimitrios Gunopulos; Christian S. Jensen; Joon-Sook Kim; Kyoung-Sook Kim; Peer Kröger; John Krumm; Johannes Lauer; Amr Magdy; Mario A. Nascimento; Siva Ravada; Matthias Renz; Dimitris Sacharidis; Cyrus Shahabi; Flora D. Salim; Mohamed Sarwat; Maxime Schoemans; Bettina Speckmann; Egemen Tanin; Yannis Theodoridis; Kristian Torp; Goce Trajcevski; Marc J. van Kreveld; Carola Wenk; Martin Werner; Raymond Chi-Wing Wong; Song Wu; Jianqiu Xu; Moustafa Youssef; Demetris Zeinalipour; Mengxuan Zhang; Esteban Zimányi

doi:10.4230/DagRep.12.1.1

Mobility Data Science (Dagstuhl Seminar 22021)

Mohamed F. Mokbel
, Mahmoud Attia Sakr
, Li Xiong
, Andreas Züfle
, Jussara M. Almeida
, Taylor Anderson
, Walid G. Aref
, Gennady L. Andrienko
, Natalia V. Andrienko
, Yang Cao
, Sanjay Chawla
, Reynold Cheng
, Panos K. Chrysanthis
, Xiqi Fei
, Gabriel Ghinita
, Anita Graser
, Dimitrios Gunopulos
, Christian S. Jensen
, Joon-Sook Kim
, Kyoung-Sook Kim

Peer Kröger, John Krumm, Johannes Lauer, Amr Magdy, Mario A. Nascimento, Siva Ravada, Matthias Renz, Dimitris Sacharidis, Cyrus Shahabi, Flora D. Salim, Mohamed Sarwat, Maxime Schoemans, Bettina Speckmann, Egemen Tanin, Yannis Theodoridis, Kristian Torp, Goce Trajcevski, Marc J. van Kreveld, Carola Wenk, Martin Werner, Raymond Chi-Wing Wong, Song Wu, Jianqiu Xu, Moustafa Youssef, Demetris Zeinalipour, Mengxuan Zhang, Esteban Zimányi

Research output: Contribution to journal › Article › Academic › peer-review

28 Downloads (Pure)

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.

Original language	English
Article number	1
Pages (from-to)	1-34
Number of pages	34
Journal	Dagstuhl Reports
Volume	12
Issue number	1
DOIs	https://doi.org/10.4230/DagRep.12.1.1
Publication status	Published - 2022

Access to Document

10.4230/DagRep.12.1.1

pdfFinal published version, 4.54 MBLicence: CC BY

Cite this

Mokbel, M. F., Sakr, M. A., Xiong, L., Züfle, A., Almeida, J. M., Anderson, T., Aref, W. G., Andrienko, G. L., Andrienko, N. V., Cao, Y., Chawla, S., Cheng, R., Chrysanthis, P. K., Fei, X., Ghinita, G., Graser, A., Gunopulos, D., Jensen, C. S., Kim, J.-S., ... Zimányi, E. (2022). Mobility Data Science (Dagstuhl Seminar 22021). Dagstuhl Reports, 12(1), 1-34. Article 1. https://doi.org/10.4230/DagRep.12.1.1

@article{26525876263e49c8b4bd4e8cd61037a9,

title = "Mobility Data Science (Dagstuhl Seminar 22021)",

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. ",

author = "Mokbel, \{Mohamed F.\} and Sakr, \{Mahmoud Attia\} and Li Xiong and Andreas Z{\"u}fle and Almeida, \{Jussara M.\} and Taylor Anderson and Aref, \{Walid G.\} and Andrienko, \{Gennady L.\} and Andrienko, \{Natalia V.\} and Yang Cao and Sanjay Chawla and Reynold Cheng and Chrysanthis, \{Panos K.\} and Xiqi Fei and Gabriel Ghinita and Anita Graser and Dimitrios Gunopulos and Jensen, \{Christian S.\} and Joon-Sook Kim and Kyoung-Sook Kim and Peer Kr{\"o}ger and John Krumm and Johannes Lauer and Amr Magdy and Nascimento, \{Mario A.\} and Siva Ravada and Matthias Renz and Dimitris Sacharidis and Cyrus Shahabi and Salim, \{Flora D.\} and Mohamed Sarwat and Maxime Schoemans and Bettina Speckmann and Egemen Tanin and Yannis Theodoridis and Kristian Torp and Goce Trajcevski and \{van Kreveld\}, \{Marc J.\} and Carola Wenk and Martin Werner and Wong, \{Raymond Chi-Wing\} and Song Wu and Jianqiu Xu and Moustafa Youssef and Demetris Zeinalipour and Mengxuan Zhang and Esteban Zim{\'a}nyi",

year = "2022",

doi = "10.4230/DagRep.12.1.1",

language = "English",

volume = "12",

pages = "1--34",

journal = "Dagstuhl Reports",

issn = "2192-5283",

publisher = "Schloss Dagstuhl - Leibniz-Zentrum f{\"u}r Informatik",

number = "1",

}

Mokbel, MF, Sakr, MA, Xiong, L, Züfle, A, Almeida, JM, Anderson, T, Aref, WG, Andrienko, GL, Andrienko, NV, Cao, Y, Chawla, S, Cheng, R, Chrysanthis, PK, Fei, X, Ghinita, G, Graser, A, Gunopulos, D, Jensen, CS, Kim, J-S, Kim, K-S, Kröger, P, Krumm, J, Lauer, J, Magdy, A, Nascimento, MA, Ravada, S, Renz, M, Sacharidis, D, Shahabi, C, Salim, FD, Sarwat, M, Schoemans, M, Speckmann, B, Tanin, E, Theodoridis, Y, Torp, K, Trajcevski, G, van Kreveld, MJ, Wenk, C, Werner, M, Wong, RC-W, Wu, S, Xu, J, Youssef, M, Zeinalipour, D, Zhang, M & Zimányi, E 2022, 'Mobility Data Science (Dagstuhl Seminar 22021)', Dagstuhl Reports, vol. 12, no. 1, 1, pp. 1-34. https://doi.org/10.4230/DagRep.12.1.1

TY - JOUR

T1 - Mobility Data Science (Dagstuhl Seminar 22021)

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-Sook

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 - Shahabi, Cyrus

AU - Salim, Flora D.

AU - Sarwat, Mohamed

AU - Schoemans, Maxime

AU - Speckmann, Bettina

AU - Tanin, Egemen

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

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

U2 - 10.4230/DagRep.12.1.1

DO - 10.4230/DagRep.12.1.1

M3 - Article

SN - 2192-5283

VL - 12

SP - 1

EP - 34

JO - Dagstuhl Reports

JF - Dagstuhl Reports

IS - 1

M1 - 1

ER -

Mobility Data Science (Dagstuhl Seminar 22021)

Abstract

Access to Document

Fingerprint

Cite this