Abstract
Visual analytics of increasingly large data sets has become a challenge for traditional in-memory and off-line algorithms as well as in the cognitive process of understanding features at various scales of resolution. In this paper, we attempt a new web-based framework for the dynamic visualization of large data. The framework is based on the idea that no physical device can ever catch up to the analytical demand and the physical requirements of large data. Thus, we adopt a data streaming generator model that serializes the original data into multiple streams of data that can be contained on current hardware. Thus, the scalability of the visual analytics of large data is inherent in the streaming architecture supported by our platform. The platform is based on the traditional server-client model. However, the platform is enhanced by effective analytical methods that operate on data streams, such as binned points and bundling lines that reduce and enhance large streams of data for effective interactive visualization. We demonstrate the effectiveness of our framework on different types of large datasets.
Original language | English |
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Title of host publication | Proceedings - 2014 IEEE 13th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2014 |
Publisher | IEEE |
Pages | 686-692 |
Number of pages | 7 |
ISBN (Electronic) | 9781479965137 |
DOIs | |
Publication status | Published - 1 Jan 2015 |
Event | 13th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2014 - Beijing, China Duration: 24 Sept 2014 → 26 Sept 2014 |
Conference
Conference | 13th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2014 |
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Country/Territory | China |
City | Beijing |
Period | 24/09/14 → 26/09/14 |
Keywords
- Big data
- Dynamic visualization
- Streaming data
- Visual analytics
ASJC Scopus subject areas
- Computer Science Applications
- Safety, Risk, Reliability and Quality
- Computer Networks and Communications