@inproceedings{227e94c6090540adb68119b0ffc736d1,
title = "ScagnosticsViewer: Tracking time series patterns via scagnostics meatures",
abstract = "Visual analytics studies the integration of human perceptional ability and the data exploration process. Besides, high dimensional time series has become more and more popular data in daily applications and various domains. It is essential to study visual techniques for this type of data set. This paper is an applied work that extends successes of the scatterplot matrix (SPLOM) for cross-sectional data to the high dimensional temporal data sets. We have built a web-based application that contains various visual techniques to display the temporal data sets by SPLOM at each snapshot and animate the SPLOM to illustrate the evolution of the data sets. Two real data sets in different domains are utilized to demonstrate the advances of this approach. ",
keywords = "scatterplot, scatterplot matrix",
author = "Nguyen, {Ngan V.T.} and Nguyen, {Bao D.Q.} and Tommy Dang and Jon Hass",
note = "Publisher Copyright: {\textcopyright} 2020 ACM. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; null ; Conference date: 08-12-2020 Through 10-12-2020",
year = "2020",
month = dec,
day = "8",
doi = "10.1145/3430036.3430072",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
editor = "Nguyen, {Quang Vinh} and Ying Zhao and Michael Burch and Michel Westenberg",
booktitle = "Proceedings of the 13th International Symposium on Visual Information Communication and Interaction, VINCI 2020",
}