Towards Mobility Data Science (Vision Paper)

arXiv - CS - Other Computer Science Pub Date : 2023-06-21 DOI:arxiv-2307.05717

Mohamed MokbelUniversity of Minnesota, Minneapolis, USA, Mahmoud SakrUniversité Libre, Brussels, Belgium, Li XiongEmory University, Atlanta, USA, Andreas ZüfleEmory University, Atlanta, USA, Jussara AlmeidaFederal University of Minas Gerais, Belo Horizonte, Brazil, Walid ArefPurdue University, West Lafayette, USA, Gennady AndrienkoFraunhofer IAIS, St. Augustin, Germany, Natalia AndrienkoFraunhofer IAIS, St. Augustin, Germany, Yang CaoKyoto University, Kyoto, Japan, Sanjay ChawlaQatar Computing Research Institute, Doha, Qatar, Reynold ChengUniversity of Hong Kong, Hong Kong, China, Panos ChrysanthisUniversity of Pittsburgh, Pennsylvania, USA, Xiqi FeiGeorge Mason University, Fairfax, USA, Gabriel GhinitaUniversity of Massachusetts at Boston, Boston, USA, Anita GraserAustrian Institute of Technology, Vienna, Austria, Dimitrios GunopulosUniversity of Athens, Greece, Christian JensenAalborg University, Denmark, Joon-Sook KimOak Ridge National Laboratory, USA, Kyoung-Sook KimAIST, Tokyo Waterfront, Japan, Peer KrögerUniversity of Kiel, Germany, John KrummUniversity of Southern California, Log Angeles, USA, Johannes LauerHERE Technologies, Germany, Amr MagdyUniversity of California, Riverside, USA, Mario NascimentoNortheastern University, Boston, USA, Siva RavadaOracle Corp., Nashua, USA, Matthias RenzUniversity of Kiel, Germany, Dimitris SacharidisUniversité Libre, Brussels, Belgium, Cyrus ShahabiUniversity of Southern California, Log Angeles, USA, Flora SalimUniversity of New South Wales, Sydney, Australia, Mohamed SarwatArizona State University, Tempe, Maxime SchoemansUniversité Libre, Brussels, Belgium, Bettina SpeckmannTU Eindhoven, Netherlands, Egemen TaninUniversity of Melbourne, Australia, Yannis TheodoridisUniversity of Piraeus, Greece, Kristian TorpAalborg University, Denmark, Goce TrajcevskiIowa State University, Ames, USA, Marc van KreveldUtrecht University, Netherlands, Carola WenkTulane University, New Orleans, USA, Martin WernerTechnical University of Munich, Munich, Germany, Raymond WongHong Kong University of Science and Technology, Hong Kong, China, Song WuUniversité Libre, Brussels, Belgium, Jianqiu XuNanjing University of Aeronautics and Astronautics, Nanjing, China, Moustafa YoussefAUC and Alexandria University, Egypt, Demetris ZeinalipourUniversity of Cyprus, Nicosia, Cyprus, Mengxuan ZhangIowa State University, Ames, USA, Esteban ZimányiUniversité Libre, Brussels, Belgium

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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.

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迈向移动数据科学(愿景文件)

移动数据捕获移动对象(如人、动物和汽车)的位置。随着配备gps的移动设备的可用性和其他便宜的位置跟踪技术，移动数据被无处不在地收集。近年来，移动数据的使用在交通管理、城市规划和健康科学等各个领域产生了重大影响。在本文中，我们介绍了移动数据科学的新兴领域。为了实现移动数据科学的统一方法，我们设想了一个包含以下组件的管道:移动数据收集、清理、分析、管理和隐私。对于这些组成部分，我们解释了移动数据科学与一般数据科学的不同之处，我们调查了当前的艺术状态，并描述了未来几年研究界面临的开放挑战。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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arXiv - CS - Other Computer Science

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