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An extensible coordination model for coordinated and multiple views and approaches to aid the visual analysis process

Grant number: 13/03452-0
Support type:Regular Research Grants
Duration: November 01, 2014 - October 31, 2016
Field of knowledge:Physical Sciences and Mathematics - Computer Science
Principal Investigator:Danilo Medeiros Eler
Grantee:Danilo Medeiros Eler
Home Institution: Faculdade de Ciências e Tecnologia (FCT). Universidade Estadual Paulista (UNESP). Campus de Presidente Prudente. Presidente Prudente, SP, Brazil
Assoc. researchers:Milton Hirokazu Shimabukuro ; Rogério Eduardo Garcia ; Rosane Minghim


Following the FAPESP's recommendations of sending distinct proposals in a unique one, this project presents two works. The first proposal aims at adapting the coordination model developed in the main researcher doctored. Distinct visual techniques can be simultaneously employed to explore datasets. To that, coordination techniques can be used to facilitate the exploration and avoid the overload that the user suffers in context changing among distinct visualization techniques. In the main researcher's doctored was proposed a model which was developed based on a tool known as Projection Explorer (PEx), what complicates its extension to other systems. As a result of this project, we intend to make available an extensible coordination model, which can be easily used by any system that needs to employ coordination mechanisms among multiple views. In the way of this proposal related to coordination, we also intend to develop a software architecture to support remote coordination among multiple views, enabling the collaboration among researches. Additionally, we will adapt one coordination technique to document collection exploration for generating semantic maps to highlight more documents of interest. Hence, an ontology will be employed for the step of creating a mapping among views. The second proposal is related to mechanisms to improve the visual analysis of datasets, in which intend to improve the dataset analyses by means of a hybrid visualization approach, by mixing two visualization techniques into a unique view: one technique to highlight the relationship among instances (e.g., multidimensional projection) and other to highlight the relationship among instance attributes (e.g., parallel coordinates). (AU)