期刊名称：Bulletin of the Technical Committee on Data Engineering
出版年度：2015
卷号：38
期号：2
出版社：IEEE Computer Society
摘要：Past decades have witnessed extensive studies from both academia and industries over trajectory data,which are generated from a diverse range of applications. Existing literature mainly focuses on rawtrajectories with spatio-temporal features such as location, time, speed, direction and so on. Recently,the pervasive use of smart mobile devices like smart phones, watches and bands have brought aboutmore generation of trajectory by personal users (instead of companies or organizations) and from onlinespace (instead of physical space), where individuals can decide when and where to log on and share theirlocations with others. The more discentralized and contextualized trajectory sources have brought someunique challenges for database management with respect to the quality and semantics of trajectoriesdata. With more applications and services relying on trajectory data analysis, it is necessary for usto think about how these new issues will affect the traditional way that trajectories are digested andprocessed. In this paper we will elaborate on these challenges and introduce our recent progress in therespective directions. The message we try to deliver is that raw trajectories themselves no longer satisfythe requirement of today’s mainstream applications. To really release the power of trajectory-basedapplications, we should go beyond the raw trajectory data by enhancing their quality and semantics,which calls for novel computing architectures, paradigms and algorithms with sufficient capabilities tomanage and analyse the enhanced trajectory data.
