scholarly journals Methods and Tools for Visualization of Graphs and Graph Algorithms

Author(s):  
V.N. Kasyanov

Graphs are the most common abstract structure encountered in computer science and are widely used for structural information visualization. In the paper, we consider practical and general graph formalism of so called hierarchical graphs and present the Higres and ALVIS systems aimed at supporting of structural information visualization on the base of hierarchical graph models.

2021 ◽  
Vol 2099 (1) ◽  
pp. 012051
Author(s):  
V N Kasyanov ◽  
A M Merculov ◽  
T A Zolotuhin

Abstract Information visualization based on graph models is a key component of support tools for many applications in science and engineering. The Visual Graph system is intended for visualization of big amounts of complex information on the basis of attributed hierarchical graph models. In this paper, a circular layout algorithm for attributed hierarchical graphs with ports and its effective implementation in the Visual Graph system are presented.


2003 ◽  
Vol 2 (2) ◽  
pp. 126-139 ◽  
Author(s):  
Sanjay Rana ◽  
Jason Dykes

Animated sequences of raster images that represent continuously varying surfaces, such as a temporal series of an evolving landform or an attribute series of socio-economic variation, are often used in an attempt to gain insight from ordered sequences of raster spatial data. Despite their aesthetic appeal and condensed nature, such representations are limited in terms of their suitability for prompting ideas and offering insight due to their poor information delivery and the lack of the levels of interactivity that are required to support visualization. Cartographic techniques aim to assist users of geographic information through processes of abstraction, by selecting, simplifying, smoothing and exaggerating when representing an underlying spatial data set graphically. Here we suggest a number of transformations and abstractions that take advantage of these techniques in a specific context–that of addressing the limitations associated with using animated raster surfaces for visualization, and propose them in the context of a framework that can be used to inform practice. The five techniques proposed are spatial and attribute smoothing, temporal interpolation, transformation of the surfaces into a network of morphometric features, the use of a graphic lag or fading and the employment of techniques for conditional interactivity that are appropriate for visualization. These efforts allow us to generate graphical environments that support visualization when using animated sequences of images representing continuous surfaces and are analogous to traditional cartographic techniques, namely, smoothing and exaggeration, simplification, enhancement and the various issues of design. By developing a framework for considering cartography in support of visualization from this particular type of data and phenomenon we aim to highlight the utility of a generically cartographic approach to information visualization. A number of particular techniques originating from computer science and conventional cartography are used in an application of the framework. A suitably interactive software tool is offered for evaluation–to establish the results of applying the framework and demonstrate ways in which we may augment the visualization of dynamic raster surfaces through animation and more generally aim to offer opportunity for insight through cartographic design.


Author(s):  
Mark D. Lee ◽  
Lena Mamykina ◽  
Chandra Harrison

Diabetes requires continual monitoring of diet, glucose level, and other personal data so that a balance may be achieved between a desired lifestyle and one that is healthy and sustainable. While ubiquitous computing technologies can capture data necessary to make judgments, individuals need to be able to easily comprehend the data to draw conclusions. To help individuals with diabetis with this task, we designed two types of visualizations, a relational visualization using traditional graph-based techniques for presenting data, and a metaphorical visualization that conveys data using familiar, domain-specific imagery in an aesthetically pleasing composition. This paper presents a comparative analysis of these visualizations which indicated that older individuals with lower general graph-interpretation skills perform superior data analysis when using a visualization based on a familiar metaphor. These findings suggest that metaphorical visualizations constitute a viable alternative when designing informational displays for the elderly.


2020 ◽  
Vol 63 (4) ◽  
pp. 1071-1091
Author(s):  
Luke Morgan ◽  
Cheryl E. Praeger ◽  
Kyle Rosa

AbstractIn this paper, we study finite semiprimitive permutation groups, that is, groups in which each normal subgroup is transitive or semiregular. These groups have recently been investigated in terms of their abstract structure, in a similar way to the O'Nan–Scott Theorem for primitive groups. Our goal here is to explore aspects of such groups which may be useful in place of precise structural information. We give bounds on the order, base size, minimal degree, fixed point ratio, and chief length of an arbitrary finite semiprimitive group in terms of its degree. To establish these bounds, we study the structure of a finite semiprimitive group that induces the alternating or symmetric group on the set of orbits of an intransitive minimal normal subgroup.


2007 ◽  
Vol 6 (3) ◽  
pp. 189-196 ◽  
Author(s):  
Andreas Kerren ◽  
John T. Stasko ◽  
Jean-Daniel Fekete ◽  
Chris North

From 28 May to 1 June 2007, a seminar on ‘Information Visualization–Human-Centered Issues in Visual Representation, Interaction, and Evaluation’ took place at the International Conference and Research Center for Computer Science, Dagstuhl Castle, Germany. One important aim of this seminar was to bring together researchers and practitioners from Information Visualization and related fields, as well as from application areas, for lively discussion and interaction. The seminar allowed critical reflection on actual research efforts, the state of field, evaluation challenges, and other important topics. This report summarizes the event.


2009 ◽  
Vol 9 (1) ◽  
pp. 70-81 ◽  
Author(s):  
Meredith Skeels ◽  
Bongshin Lee ◽  
Greg Smith ◽  
George G. Robertson

Uncertainty in data occurs in domains ranging from natural science to medicine to computer science. By developing ways to include uncertainty in our information visualizations, we can provide more accurate depictions of critical data sets so that people can make more informed decisions. One hindrance to visualizing uncertainty is that we must first understand what uncertainty is and how it is expressed. We reviewed existing work from several domains on uncertainty and created a classification of uncertainty based on the literature. We empirically evaluated and improved upon our classification by conducting interviews with 18 people from several domains, who self-identified as working with uncertainty. Participants described what uncertainty looks like in their data and how they deal with it. We found commonalities in uncertainty across domains and believe our refined classification will help us in developing appropriate visualizations for each category of uncertainty.


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