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Visualization to support identifying relevant attributes in time-varying multidimensional data

Grant number: 12/24537-0
Support type:Scholarships in Brazil - Doctorate
Effective date (Start): June 01, 2013
Effective date (End): April 30, 2017
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Principal researcher:Maria Cristina Ferreira de Oliveira
Grantee:Aurea Rossy Soriano Vargas
Home Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Associated research grant:11/22749-8 - Challenges in exploratory visualization of multidimensional data: paradigms, scalability and applications, AP.TEM
Associated scholarship(s):15/12831-0 - Visual exploration to support the identification of relevant attributes in multidimensional time-varying data, BE.EP.DR


The goal of this PhD project is to investigate Multidimensional Visualization techniques to support exploratory data analysis tasks related to identifying relevant attributes to understand the behavior of phenomena involving multiple variables. We seek to investigate and propose a visual framework for analyzing multidimensional data that describe a phenomenon´s behavior over time, assisting data analysts in identifying the relevant attributes. The proposed framework must be interactive and allow users to drive the analysis process and input his/her domain knowledge. This project involves a partnership with researchers from the Department of Cartography of the Faculty of Science and Technology of UNESP at Presidente Prudente. These researchers study the effects of ionospheric scintillation on GPS measurements, and are developing a database that records observations concerning this purpose. This problem features an ideal application domain to identify the requirements and validate the techniques to be proposed inthis project, as it involves the investigation of the role of different attributes in the temporal behavior of the phenomenon. The proposed framework must be applicable to this and other problems of a similar nature.

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
SORIANO-VARGAS, AUREA; VANI, BRUNO C.; SHIMABUKURO, MILTON H.; MONICO, JOAO F. G.; OLIVEIRA, MARIA CRISTINA F.; HAMANN, BERND. Visual analytics of time-varying multivariate ionospheric scintillation data. COMPUTERS & GRAPHICS-UK, v. 68, p. 96-107, . (15/12831-0, 11/22749-8, 12/24537-0)
SORIANO-VARGAS, AUREA; HAMANN, BERND; DE OLIVEIRA, MARIA CRISTINA F.. TV-MV Analytics: A visual analytics framework to explore time-varying multivariate data. INFORMATION VISUALIZATION, v. 19, n. 1, . (17/05838-3, 12/24537-0, 15/12831-0)
Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
VARGAS, Aurea Rossy Soriano. Visual exploration to support the identification of relevant attributes in time-varying multivariate data. 2018. Doctoral Thesis - Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) São Carlos.

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