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
{"title":"迈向移动数据科学(愿景文件)","authors":"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","doi":"arxiv-2307.05717","DOIUrl":null,"url":null,"abstract":"Mobility data captures the locations of moving objects such as humans,\nanimals, and cars. With the availability of GPS-equipped mobile devices and\nother inexpensive location-tracking technologies, mobility data is collected\nubiquitously. In recent years, the use of mobility data has demonstrated\nsignificant impact in various domains including traffic management, urban\nplanning, and health sciences. In this paper, we present the emerging domain of\nmobility data science. Towards a unified approach to mobility data science, we\nenvision a pipeline having the following components: mobility data collection,\ncleaning, analysis, management, and privacy. For each of these components, we\nexplain how mobility data science differs from general data science, we survey\nthe current state of the art and describe open challenges for the research\ncommunity in the coming years.","PeriodicalId":501310,"journal":{"name":"arXiv - CS - Other Computer Science","volume":"15 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Towards Mobility Data Science (Vision Paper)\",\"authors\":\"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\",\"doi\":\"arxiv-2307.05717\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mobility data captures the locations of moving objects such as humans,\\nanimals, and cars. With the availability of GPS-equipped mobile devices and\\nother inexpensive location-tracking technologies, mobility data is collected\\nubiquitously. In recent years, the use of mobility data has demonstrated\\nsignificant impact in various domains including traffic management, urban\\nplanning, and health sciences. In this paper, we present the emerging domain of\\nmobility data science. Towards a unified approach to mobility data science, we\\nenvision a pipeline having the following components: mobility data collection,\\ncleaning, analysis, management, and privacy. For each of these components, we\\nexplain how mobility data science differs from general data science, we survey\\nthe current state of the art and describe open challenges for the research\\ncommunity in the coming years.\",\"PeriodicalId\":501310,\"journal\":{\"name\":\"arXiv - CS - Other Computer Science\",\"volume\":\"15 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Other Computer Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2307.05717\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Other Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2307.05717","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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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