Mapping nominal values to numbers for effective visualization

Author(s):  
G.E. Rosario ◽  
E.A. Rundensteiner ◽  
D.C. Brown ◽  
M.O. Ward
2017 ◽  
Vol 727 ◽  
pp. 919-924 ◽  
Author(s):  
Feng Li ◽  
Shiqi Liu ◽  
Ruiyan Qi ◽  
Hongren Li ◽  
Tianfang Cui

2019 ◽  
Vol 19 (2) ◽  
pp. e10
Author(s):  
Dana Urribarri ◽  
Martín L Larrea ◽  
Silvia M Castro

The visualization process is a very complex exploration activity and, even for skilled users, it can be difficult to produce an effective visualization. The result of such process depends on the user's decisions along it. One way to improve the probability of achieving a useful outcome is to assist the user in the configuration and preparation of the visualization. Our proposal consists in live suggestions on how to improve the visualization. These live suggestions are based on the user decisions, and achieved by the integration of semantic reasoning into the visualization process. In this paper, we present a case study for scatterplots visualization that combines ontologies with a semantic reasoner and helps the user in the generation of an effective visualization.


F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1651 ◽  
Author(s):  
Ajit Singh ◽  
Christopher J. Rawlings ◽  
Keywan Hassani-Pak

KnetMaps is a BioJS component for the interactive visualization of biological knowledge networks. It is well suited for applications that need to visualise complementary, connected and content-rich data in a single view in order to help users to traverse pathways linking entities of interest, for example to go from genotype to phenotype. KnetMaps loads data in JSON format, visualizes the structure and content of knowledge networks using lightweight JavaScript libraries, and supports interactive touch gestures. KnetMaps uses effective visualization techniques to prevent information overload and to allow researchers to progressively build their knowledge.


Leonardo ◽  
2013 ◽  
Vol 46 (3) ◽  
pp. 270-271 ◽  
Author(s):  
Miriah Meyer

Visualization is now a vital component of the biological discovery process. This article presents visualization design studies as a promising approach for creating effective, visualization tools for biological data.


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