@inproceedings{d3e986b8ba4041de98c87cf2591dc9b6,
title = "A multi-scale correlative approach for crowd-sourced multi-variate spatiotemporal data",
abstract = "With the increase in community-contributed data availability, citizens and analysts are interested in identifying patterns, trends and correlation within these datasets. Various levels of aggregation are often applied to interpret such large data schemes. Identifying the proper scales of aggregation is a non-trivial task in this exploratory data analysis process. In this paper, we present an integrated visual analytics environment that facilitates the exploration of multivariate categorical spatiotemporal data at multiple spatial scales of aggregation, focusing on citizen-contributed data. We propose a compact visual correlation representation by embedding various statistical measures across different spatial regions to enable users to explore correlations between multiple data categories across different spatial scales. The system provides several scale-sensitive spatial partitioning strategies to examine the sensitivity of correlations at varying spatial extents. To demonstrate the capabilities of our system, we provide several usage scenarios from various domains including citizen-contributed social media (soundscape ecology) data.",
author = "Thomas Gorko and Calvin Yau and Abish Malik and Matt Harris and Tee, {Jun Xiang} and Ross Maciejewski and Cheryl Qian and Shehzad Afzal and Bryan Pijanowski and David Ebert",
note = "Funding Information: The authors would like to thank the researchers at the Center for Global Soundscapes for their help, as well as the reviewers for enhancing the structure and the content of this paper. This work was funded by the NSF and U.S. Department of Homeland Security VACCINE Center{\textquoteright}s under Award Number 2009-ST-061-CI005. Publisher Copyright: {\textcopyright} 2018 IEEE Computer Society. All rights reserved.; 51st Annual Hawaii International Conference on System Sciences, HICSS 2018 ; Conference date: 02-01-2018 Through 06-01-2018",
year = "2018",
language = "English (US)",
series = "Proceedings of the Annual Hawaii International Conference on System Sciences",
publisher = "IEEE Computer Society",
pages = "1691--1700",
editor = "Bui, {Tung X.}",
booktitle = "Proceedings of the 51st Annual Hawaii International Conference on System Sciences, HICSS 2018",
}