Indiana University-Purdue University Indianapolis (IUPUI) / Spatio-temporal data is becoming very popular in the recent times, as there are
large number of datasets that collect both location and temporal information in the
real time. The main challenge is that extracting useful insights from such large data
set is extremely complex and laborious. In this thesis, we have proposed a novel 2D
technique to visualize the spatio-temporal big data. The visualization of the combined
interaction between the spatial and temporal data is of high importance to uncover
the insights and identify the trends within the data.
Maps have been a successful way to represent the spatial information. Addition-
ally, in this work, colors are used to represent the temporal data. Every data point
has the time information which is converted into relevant color, based on the HSV
color model. The variation in the time is represented by transition from one color to
another and hence provide smooth interpolation. The proposed solution will help the
user to quickly understand the data and gain insights.
| Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/11833 |
| Date | 15 November 2016 |
| Creators | Baskaran, Savitha |
| Contributors | Fang, Dr. Shiaofen |
| Source Sets | Indiana University-Purdue University Indianapolis |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
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