scholarly journals Toward automatic comparison of visualization techniques: Application to graph visualization

2020 ◽  
Vol 4 (2) ◽  
pp. 86-98
Author(s):  
L. Giovannangeli ◽  
R. Bourqui ◽  
R. Giot ◽  
D. Auber
2014 ◽  
Author(s):  
Kevin Boyack ◽  
Mei-Ching Chen ◽  
George Chacko

The National Institutes of Health (NIH) is the largest source of funding for biomedical research in the world. This funding is largely effected through a competitive grants process. Each year the Center for Scientific Review (CSR) at NIH manages the evaluation, by peer review, of more than 55,000 grant applications. A relevant management question is how this scientific evaluation system, supported by finite resources, could be continuously evaluated and improved for maximal benefit to the scientific community and the taxpaying public. Towards this purpose, we have created the first system-level description of peer review at CSR by applying text analysis, bibliometric, and graph visualization techniques to administrative records. We identify otherwise latent relationships across scientific clusters, which in turn suggest opportunities for structural reorganization of the system based on expert evaluation. Such studies support the creation of monitoring tools and provide transparency and knowledge to stakeholders


2004 ◽  
Vol 3 (3) ◽  
pp. 209-222 ◽  
Author(s):  
Kenneth L. Summers ◽  
Thomas Preston Caudell ◽  
Kathryn Berkbigler ◽  
Brian Bush ◽  
Kei Davis ◽  
...  

We are exploring the development and application of information visualization techniques for the analysis of new massively parallel supercomputer architectures. Modern supercomputers typically comprise very large clusters of commodity SMPs interconnected by possibly dense and often non-standard networks. The scale, complexity, and inherent non-locality of the structure and dynamics of this hardware, and the operating systems and applications distributed over them, challenge traditional analysis methods. As part of the á la carte (A Los Alamos Computer Architecture Toolkit for Extreme-Scale Architecture Simulation) team at Los Alamos National Laboratory, who are simulating these new architectures, we are exploring advanced visualization techniques and creating tools to enhance analysis of these simulations with intuitive three-dimensional representations and interfaces. This work complements existing and emerging algorithmic analysis tools. In this paper, we give background on the problem domain, a description of a prototypical computer architecture of interest (on the order of 10,000 processors connected by a quaternary fat-tree communications network), and a presentation of three classes of visualizations that clearly display the switching fabric and the flow of information in the interconnecting network.


2006 ◽  
pp. 154-171 ◽  
Author(s):  
Flavius Frasincar ◽  
Alexandru Telea ◽  
Geert-Jan Houben

2007 ◽  
Vol 13 (2) ◽  
pp. 294-304 ◽  
Author(s):  
Emilio Di Giacomo ◽  
Walter Didimo ◽  
Luca Grilli ◽  
Giuseppe Liotta

Author(s):  
G. Jacobs ◽  
F. Theunissen

In order to understand how the algorithms underlying neural computation are implemented within any neural system, it is necessary to understand details of the anatomy, physiology and global organization of the neurons from which the system is constructed. Information is represented in neural systems by patterns of activity that vary in both their spatial extent and in the time domain. One of the great challenges to microscopists is to devise methods for imaging these patterns of activity and to correlate them with the underlying neuroanatomy and physiology. We have addressed this problem by using a combination of three dimensional reconstruction techniques, quantitative analysis and computer visualization techniques to build a probabilistic atlas of a neural map in an insect sensory system. The principal goal of this study was to derive a quantitative representation of the map, based on a uniform sample of afferents that was of sufficient size to allow statistically meaningful analyses of the relationships between structure and function.


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