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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Olshannikova, E. Ometov, A. Koucheryavy, Y. |
| Copyright Year | 2014 |
| Description | Author affiliation: Dept. of Electron. & Commun. Eng., Tampere Univ. of Technol., Tampere, Finland (Ometov, A.; Koucheryavy, Y.) || United Print Center Ltd., St. Petersburg, Russia (Olshannikova, E.) |
| Abstract | This article attempts to summarize challenges in visualization methods for existing Big Data and beyond. Moreover, it classifies types of data, analytical methods, visualization techniques and tools, known up to date, with a particular emphasis placed on surveying evolution of visualization techniques over the past years. Following the identified shortcomings of the existing techniques, the role of human eyes physical limitations on perception of the large amounts of information is evaluated and presented along with discussion on Augmented Realty technology and its capabilities for visualization of Big Data and beyond. Based on the results, a novel approach is proposed -- it allows one to obtain represented information segment in a short period of time without any significant data losses by placing the most essential data in the central area of the human eye visual field. This article also discusses impact of new technologies, such as Augmented Reality displays and helmets, on the Big Data visualization. |
| Starting Page | 33 |
| Ending Page | 37 |
| File Size | 534871 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781479957798 |
| DOI | 10.1109/CBI.2014.42 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-07-14 |
| Publisher Place | Switzerland |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Visualization Social network services Big Data augmented reality evolution vizualization Augmented reality Three-dimensional displays Data visualization classification methodology survey Big data Software |
| Content Type | Text |
| Resource Type | Article |
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