Proceedings Article10.1109/MDM.2018.00055
VIPTRA: Visualization and Interactive Processing on Big Trajectory Data
Xin Ding,Rui Chen,Lu Chen,Yunjun Gao,Christian S. Jensen +4 more
- 25 Jun 2018
- pp 290-291
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TL;DR: A new framework, VIPTRA, is presented, which builds upon UlTraMan, a distributed in-memory system for big trajectory data, and thus, it takes advantage of its capability of high performance.
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Abstract: Massive trajectory data is being collected and used widely in many applications such as transportation, location-based services, and urban computing As a result, abundant methods and systems have been proposed for managing and processing trajectory data However, it remains difficult for users to interact well with data management and processing, due to the lack of efficient data processing methods and effective visualization techniques for big trajectory data In this demonstration, we present a new framework, VIPTRA, to process big trajectory data visually and interactively VIPTRA builds upon UlTraMan, a distributed in-memory system for big trajectory data, and thus, it takes advantage of its capability of high performance The demonstration shows the efficiency of data processing and user-friendly visualization and interaction techniques provided in VIPTRA, via several scenarios of visual analysis and trajectory editing tasks
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Citations
Variable-Based Spatiotemporal Trajectory Data Visualization Illustrated
TL;DR: This review endeavors to provide a quick and thorough cognition and comprehension with regard to fundamental features and numerous outcomes in visual analytics for trajectory data, seeks to promote comparisons and criticisms about the descriptive framework for multivariate spatiotemporal trajectory data visualization, and aims to encourage the exploration of emerging methods and techniques.
Towards a reactive system for managing big trajectory data
TL;DR: The scope of this paper is to detail the system and discuss elasticity, routing strategies, load balancing, and the proper fault-tolerance mechanism of the Geolife project’s GPS trajectory dataset.
5
Poet: an Interactive Spatial Query Processing System in Grab
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- 03 Nov 2020
TL;DR: This work develops Poet, a progressive execution framework to continuously analyze user interactions and to perform progressive execution as soon as the system gains reasonable confidence regarding the user intentions, and finds that Poet helps reduce the query execution latency by up to 25x.
2
An Effective Spatio-Temporal Query Framework for Massive Trajectory Data in Urban Computing
Shiqiang Li,Weize Wang,Jiawei Shan,Heng Qi,Yanming Shen,Baocai Yin +5 more
- 01 Dec 2019
TL;DR: This paper proposes a distributed framework of massive trajectory data analysis based on HBase, and designs a temporal-based pre-partitioning strategy and develops a Multi-Level Index to speed up the process of spatio-temporal query.
2
HQ-Filter: Hierarchy-Aware Filter For Empty-Resulting Queries in Interactive Exploration
Akil Sevim,Ahmed Eldawy +1 more
- 01 Jun 2021
TL;DR: HQ-Filter as mentioned in this paper is a hierarchy-aware filter for empty resulting queries, which utilizes the hierarchical nature of the data to construct a configurable and probabilistic filter at the client-side with a minimal size and processing overhead.
2
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UlTraMan: a unified platform for big trajectory data management and analytics
Xin Ding,Lu Chen,Yunjun Gao,Christian S. Jensen,Bao Hujun +4 more
- 01 Mar 2018
TL;DR: This work extends Apache Spark with respect to both data storage and computing by seamlessly integrating a key-value store, and enhances the MapReduce paradigm to allow flexible optimizations based on random data access to achieve scalability, efficiency, persistence, and flexibility.