Visualization of spatio-temporal data in two dimensional space

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.

Discipline thesis:degree_discipline

Computer & Information Science

Grantor

Purdue University

Year dc:date.issued

2016

Author dc:creator

• Baskaran, Savitha

Advisor dc:contributor.advisor

• Fang, Dr. Shiaofen

• Visualization
• Spatio-temporal data
• Time model
• Taxi dataset

Language dc:language.iso

en_US

DOI

10.7912/C2GQ01

Identifier URI

http://dx.doi.org/10.7912/C2/2339

OAI identifier oai:identifier

oai:scholarworks.indianapolis.iu.edu:1805/11833