Visual analytics of time-varying multivariate ionospheric scintillation data

Author(s)

Soriano-Vargas, Aurea ^[1] ; Vani, Bruno C. ^[2] ; Shimabukuro, Milton H. ^[2] ; Monico, Joao F. G. ^[2] ; Oliveira, Maria Cristina F. ^[1] ; Hamann, Bernd ^[3]

Affiliation

^[1] Univ Sao Paulo, ICMC, BR-13566590 Sao Carlos, SP - Brazil

^[2] Sao Paulo State Univ UNESP, FCT, BR-19060900 Presidente Prudente, SP - Brazil

^[3] Univ Calif Davis, Dept Comp Sci, Davis, CA 95616 - USA

• Document type: Journal article
• Source: COMPUTERS & GRAPHICS-UK; v. 68, p. 96-107, NOV 2017.
• Web of Science Citations: 3

Abstract

We present a clustering-based interactive approach to multivariate data analysis, motivated by the specific needs of scintillation data. Ionospheric scintillation is a rapid variation in the amplitude and/or phase of radio signals traveling through the ionosphere. This spatial and time-varying phenomenon is of great interest since it affects the reception quality of satellite signals. Specialized receivers at strategic regions can track multiple variables related to this phenomenon, generating a database of observations of regional ionospheric scintillation. We introduce a visual analytics solution to support analysis of such data, keeping in mind the general applicability of our approach to similar multivariate data analysis situations. Taking into account typical user questions, we combine visualization and data mining algorithms that satisfy these goals: (i) derive a representation of the variables monitored that conveys their behavior in detail, at multiple user-defined aggregation levels; (ii) provide overviews of multiple variables regarding their behavioral similarity over selected time periods; (iii) support users when identifying representative variables for characterizing scintillation behavior. We illustrate the capabilities of our proposed framework by presenting case studies driven directly by questions formulated by collaborating domain experts. (C) 2017 Elsevier Ltd. All rights reserved. (AU)

• FAPESP's process: 11/22749-8 - Challenges in exploratory visualization of multidimensional data: paradigms, scalability and applications
• Grantee: Luis Gustavo Nonato
• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 15/12831-0 - Visual exploration to support the identification of relevant attributes in multidimensional time-varying data
• Grantee: Aurea Rossy Soriano Vargas
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• FAPESP's process: 12/24537-0 - Visualization to support identifying relevant attributes in time-varying multidimensional data
• Grantee: Aurea Rossy Soriano Vargas
• Support Opportunities: Scholarships in Brazil - Doctorate