scholarly journals Applying Graph Centrality Metrics in Visual Analytics of Scientific Standard Datasets

Symmetry ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 30 ◽  
Author(s):  
Jie Hua ◽  
Mao Lin Huang ◽  
Weidong Huang ◽  
Chenglin Zhao
Keyword(s):  
Visual Analytics ◽  
Graph Drawing ◽  
Graph Centrality ◽  
Standard Data ◽  
Link Diagrams ◽  
Centrality Metrics ◽  
Scientific Standard ◽  
Graph Layouts ◽  
Importance Ranking ◽  
Scientific Standards

Graphs are often used to model data with a relational structure and graphs are usually visualised into node-link diagrams for a better understanding of the underlying data. Node-link diagrams represent not only data entries in a graph, but also the relations among the data entries. Further, many graph drawing algorithms and graph centrality metrics have been successfully applied in visual analytics of various graph datasets, yet little attention has been paid to analytics of scientific standard data. This study attempts to adopt graph drawing methods (force-directed algorithms) to visualise scientific standard data and provide information with importance ‘ranking’ based on graph centrality metrics such as Weighted Degree, PageRank, Eigenvector, Betweenness and Closeness factors. The outcomes show that our method can produce clear graph layouts of scientific standard for visual analytics, along with the importance ‘ranking’ factors (represent via node colour, size etc.). Our method may assist users with tracking various relationships while understanding scientific standards with fewer relation issues (missing/wrong connection etc.) through focusing on higher priority standards.

scholarly journals An Information-Theoretic Framework for Evaluating Edge Bundling Visualization

Entropy ◽  
2018 ◽  
Vol 20 (9) ◽  
pp. 625 ◽  
Author(s):  
Jieting Wu ◽  
Feiyu Zhu ◽  
Xin Liu ◽  
Hongfeng Yu
Keyword(s):  
Information Theory ◽  
Graph Drawing ◽  
Evaluation Framework ◽  
Graph Visualization ◽  
Large Graphs ◽  
Information Theoretic ◽  
Underlying Network ◽  
Graph Layouts ◽  
Edge Bundling ◽  
Visual Results

Edge bundling is a promising graph visualization approach to simplifying the visual result of a graph drawing. Plenty of edge bundling methods have been developed to generate diverse graph layouts. However, it is difficult to defend an edge bundling method with its resulting layout against other edge bundling methods as a clear theoretic evaluation framework is absent in the literature. In this paper, we propose an information-theoretic framework to evaluate the visual results of edge bundling techniques. We first illustrate the advantage of edge bundling visualizations for large graphs, and pinpoint the ambiguity resulting from drawing results. Second, we define and quantify the amount of information delivered by edge bundling visualization from the underlying network using information theory. Third, we propose a new algorithm to evaluate the resulting layouts of edge bundling using the amount of the mutual information between a raw network dataset and its edge bundling visualization. Comparison examples based on the proposed framework between different edge bundling techniques are presented.

Edge v. Node Parallelism for Graph Centrality Metrics

2012 ◽  
pp. 15-28 ◽  
Author(s):  
Yuntao Jia ◽  
Victor Lu ◽  
Jared Hoberock ◽  
Michael Garland ◽  
John C. Hart
Keyword(s):  
Graph Centrality ◽  
Centrality Metrics

A Dynamic Multiscale Magnifying Tool for Exploring Large Sparse Graphs

2008 ◽  
Vol 7 (2) ◽  
pp. 105-117 ◽  
Author(s):  
Pak Chung Wong ◽  
Harlan Foote ◽  
Patrick Mackey ◽  
George Chin ◽  
Heidi Sofia ◽  
...  
Keyword(s):  
Information Visualization ◽  
Visual Analytics ◽  
Graph Drawing ◽  
Small World ◽  
Visualization Tool ◽  
Graph Visualization ◽  
Desktop Computer ◽  
Sparse Graphs ◽  
Small World Graphs ◽  
Unknown Unknown

We present an information visualization tool, known as GreenMax, to visually explore large small-world graphs with up to a million graph nodes on a desktop computer. A major motivation for scanning a small-world graph in such a dynamic fashion is the demanding goal of identifying not just the well-known features but also the unknown–known and unknown–unknown features of the graph. GreenMax uses a highly effective multilevel graph drawing approach to pre-process a large graph by generating a hierarchy of increasingly coarse layouts that later support the dynamic zooming of the graph. This paper describes the graph visualization challenges, elaborates our solution, and evaluates the contributions of GreenMax in the larger context of visual analytics on large small-world graphs. We report the results of two case studies using GreenMax and the results support our claim that we can use GreenMax to locate unexpected features or structures behind a graph.

scholarly journals Towards Standardization: A Participatory Framework for Scientific Standard-Making

2013 ◽  
Vol 8 (1) ◽  
pp. 157-172 ◽  
Author(s):  
Lynn Yarmey ◽  
Karen S. Baker
Keyword(s):  
Best Practices ◽  
Research Network ◽  
Hierarchical Framework ◽  
Metadata Standards ◽  
Scientific Standard ◽  
Long Term Ecological Research ◽  
Multiple Levels ◽  
Working Standards ◽  
Scientific Standards

In contemporary scientific research, standard-making and standardization are key processes for the sharing and reuse of data. The goals of this paper are twofold: 1) to stress that collaboration is crucial to standard-making, and 2) to urge recognition of metadata standardization as part of the scientific process. To achieve these goals, a participatory framework for developing and implementing scientific metadata standards is presented. We highlight the need for ongoing, open dialogue within and among research communities at multiple levels. Using the Long Term Ecological Research network adoption of the Ecological Metadata Language as a case example in the natural sciences, we illustrate how a participatory framework addresses the need for active coordination of the evolution of scientific metadata standards. The participatory framework is contrasted with a hierarchical framework to underscore how the development of scientific standards is a dynamic and continuing process. The roles played by ‘best practices’ and ‘working standards’ are identified in relation to the process of standardization.

A Parallel Algorithm for Planar Orthogonal Grid Drawings

2000 ◽  
Vol 10 (01) ◽  
pp. 141-150
Author(s):  
ROBERTO TAMASSIA ◽  
IOANNIS G. TOLLIS ◽  
JEFFREY SCOTT VITTER
Keyword(s):  
Graph Drawing ◽  
Edge Length ◽  
Optimal Time ◽  
Worst Case ◽  
Vlsi Layout ◽  
Orthogonal Grid ◽  
Graph Layouts ◽  
Crew Pram ◽  
Number Of Bends ◽  
Simply Connected

In this paper we consider the problem of constructing planar orthogonal grid drawings (or more simply, layouts) of graphs, with the goal of minimizing the number of bends along the edges. We present optimal parallel algorithms that construct graph layouts with O(n) maximum edge length, O(n2) area, and at most 2n+4 bends (for biconnected graphs) and 2.4n+2 bends (for simply connected graphs). All three of these quality measures for the layouts are optimal in the worst case for biconnected graphs. The algorithm runs on a CREW PRAM in O( log n) time with n/ log n processors, thus achieving optimal time and processor utilization. Applications include VLSI layout, graph drawing, and wireless communication.

scholarly journals Cognitive Measurements of Graph Aesthetics

2002 ◽  
Vol 1 (2) ◽  
pp. 103-110 ◽  
Author(s):  
Colin Ware ◽  
Helen Purchase ◽  
Linda Colpoys ◽  
Matthew McGill
Keyword(s):  
Large Class ◽  
Graph Drawing ◽  
Shortest Paths ◽  
Pattern Perception ◽  
Graph Layout ◽  
Detailed Understanding ◽  
Link Diagrams ◽  
Edge Crossings ◽  
Cognitive Cost ◽  
Number Of Branches

A large class of diagrams can be informally characterized as node–link diagrams. Typically nodes represent entities, and links represent relationships between them. The discipline of graph drawing is concerned with methods for drawing abstract versions of such diagrams. At the foundation of the discipline are a set of graph aesthetics (rules for graph layout) that, it is assumed, will produce graphs that can be clearly understood. Examples of aesthetics include minimizing edge crossings and minimizing the sum of the lengths of the edges. However, with a few notable exceptions, these aesthetics are taken as axiomatic, and have not been empirically tested. We argue that human pattern perception can tell us much that is relevant to the study of graph aesthetics including providing a more detailed understanding of aesthetics and suggesting new ones. In particular, we find the importance of good continuity (ie keeping multi-edge paths as straight as possible) has been neglected. We introduce a methodology for evaluating the cognitive cost of graph aesthetics and we apply it to the task of finding the shortest paths in spring layout graphs. The results suggest that after the length of the path the two most important factors are continuity and edge crossings, and we provide cognitive cost estimates for these parameters. Another important factor is the number of branches emanating from nodes on the path.

Using Personal Cell Phones for Ecological Momentary Assessment

2013 ◽  
Vol 18 (1) ◽  
pp. 3-11 ◽  
Author(s):  
Emmanuel Kuntsche ◽  
Florian Labhart
Keyword(s):  
Data Collection ◽  
Ecological Momentary Assessment ◽  
Communication Systems ◽  
Cell Phones ◽  
Personal Digital Assistants ◽  
Natural Environments ◽  
Mobility Patterns ◽  
Standard Data ◽  
Ecological Momentary ◽  
Momentary Assessment

Ecological Momentary Assessment (EMA) is a way of collecting data in people’s natural environments in real time and has become very popular in social and health sciences. The emergence of personal digital assistants has led to more complex and sophisticated EMA protocols but has also highlighted some important drawbacks. Modern cell phones combine the functionalities of advanced communication systems with those of a handheld computer and offer various additional features to capture and record sound, pictures, locations, and movements. Moreover, most people own a cell phone, are familiar with the different functions, and always carry it with them. This paper describes ways in which cell phones have been used for data collection purposes in the field of social sciences. This includes automated data capture techniques, for example, geolocation for the study of mobility patterns and the use of external sensors for remote health-monitoring research. The paper also describes cell phones as efficient and user-friendly tools for prompt manual data collection, that is, by asking participants to produce or to provide data. This can either be done by means of dedicated applications or by simply using the web browser. We conclude that cell phones offer a variety of advantages and have a great deal of potential for innovative research designs, suggesting they will be among the standard data collection devices for EMA in the coming years.

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