{"title":"关于我们生活步骤的管理与分析","authors":"N. Pelekis, Y. Theodoridis, D. Janssens","doi":"10.1145/2594473.2594478","DOIUrl":null,"url":null,"abstract":"Huge volumes of location information are available nowadays due to the rapid growth of positioning devices (GPS-enabled smartphones and tablets, on-board navigation systems in vehicles, vessels and planes, smart chips for animals, etc.). In the near future, it is unavoidable that this explosion will contribute in what is called the Big Data era, raising high challenges for the data management research community. Instead of trying to manage bigger and bigger volumes of raw data, future Moving Object Database (MOD) systems need to extract and manage (the minimum necessary) semantics of movement. Such semantics can foster next-generation location-based services (LBS) and locationbased social networking (LBSN) applications, building more efficient and effective applications, while in parallel opening new research directions in the field of transportation, urban planning etc. In this article, we first present a novel model that enables the unified management of (raw GPS) trajectories and their semantic counterpart, and then we discuss challenges and solutions on the multidimensional analysis of such real-world semantic-aware mobility databases and data warehouses. Our recent experience from an interdisciplinary EU project we've been participating makes us confident that the envisioned approach will inspire the next wave of research in mobility data management and exploration field.","PeriodicalId":90050,"journal":{"name":"SIGKDD explorations : newsletter of the Special Interest Group (SIG) on Knowledge Discovery & Data Mining","volume":"25 1","pages":"23-32"},"PeriodicalIF":0.0000,"publicationDate":"2014-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"On the Management and Analysis of Our LifeSteps\",\"authors\":\"N. Pelekis, Y. Theodoridis, D. Janssens\",\"doi\":\"10.1145/2594473.2594478\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Huge volumes of location information are available nowadays due to the rapid growth of positioning devices (GPS-enabled smartphones and tablets, on-board navigation systems in vehicles, vessels and planes, smart chips for animals, etc.). In the near future, it is unavoidable that this explosion will contribute in what is called the Big Data era, raising high challenges for the data management research community. Instead of trying to manage bigger and bigger volumes of raw data, future Moving Object Database (MOD) systems need to extract and manage (the minimum necessary) semantics of movement. Such semantics can foster next-generation location-based services (LBS) and locationbased social networking (LBSN) applications, building more efficient and effective applications, while in parallel opening new research directions in the field of transportation, urban planning etc. In this article, we first present a novel model that enables the unified management of (raw GPS) trajectories and their semantic counterpart, and then we discuss challenges and solutions on the multidimensional analysis of such real-world semantic-aware mobility databases and data warehouses. Our recent experience from an interdisciplinary EU project we've been participating makes us confident that the envisioned approach will inspire the next wave of research in mobility data management and exploration field.\",\"PeriodicalId\":90050,\"journal\":{\"name\":\"SIGKDD explorations : newsletter of the Special Interest Group (SIG) on Knowledge Discovery & Data Mining\",\"volume\":\"25 1\",\"pages\":\"23-32\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-03-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SIGKDD explorations : newsletter of the Special Interest Group (SIG) on Knowledge Discovery & Data Mining\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2594473.2594478\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIGKDD explorations : newsletter of the Special Interest Group (SIG) on Knowledge Discovery & Data Mining","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2594473.2594478","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Huge volumes of location information are available nowadays due to the rapid growth of positioning devices (GPS-enabled smartphones and tablets, on-board navigation systems in vehicles, vessels and planes, smart chips for animals, etc.). In the near future, it is unavoidable that this explosion will contribute in what is called the Big Data era, raising high challenges for the data management research community. Instead of trying to manage bigger and bigger volumes of raw data, future Moving Object Database (MOD) systems need to extract and manage (the minimum necessary) semantics of movement. Such semantics can foster next-generation location-based services (LBS) and locationbased social networking (LBSN) applications, building more efficient and effective applications, while in parallel opening new research directions in the field of transportation, urban planning etc. In this article, we first present a novel model that enables the unified management of (raw GPS) trajectories and their semantic counterpart, and then we discuss challenges and solutions on the multidimensional analysis of such real-world semantic-aware mobility databases and data warehouses. Our recent experience from an interdisciplinary EU project we've been participating makes us confident that the envisioned approach will inspire the next wave of research in mobility data management and exploration field.