54 research outputs found
Visual Similarity Perception of Directed Acyclic Graphs: A Study on Influencing Factors
While visual comparison of directed acyclic graphs (DAGs) is commonly
encountered in various disciplines (e.g., finance, biology), knowledge about
humans' perception of graph similarity is currently quite limited. By graph
similarity perception we mean how humans perceive commonalities and differences
in graphs and herewith come to a similarity judgment. As a step toward filling
this gap the study reported in this paper strives to identify factors which
influence the similarity perception of DAGs. In particular, we conducted a
card-sorting study employing a qualitative and quantitative analysis approach
to identify 1) groups of DAGs that are perceived as similar by the participants
and 2) the reasons behind their choice of groups. Our results suggest that
similarity is mainly influenced by the number of levels, the number of nodes on
a level, and the overall shape of the graph.Comment: Graph Drawing 2017 - arXiv Version; Keywords: Graphs, Perception,
Similarity, Comparison, Visualizatio
Convexity-Increasing Morphs of Planar Graphs
We study the problem of convexifying drawings of planar graphs. Given any
planar straight-line drawing of an internally 3-connected graph, we show how to
morph the drawing to one with strictly convex faces while maintaining planarity
at all times. Our morph is convexity-increasing, meaning that once an angle is
convex, it remains convex. We give an efficient algorithm that constructs such
a morph as a composition of a linear number of steps where each step either
moves vertices along horizontal lines or moves vertices along vertical lines.
Moreover, we show that a linear number of steps is worst-case optimal.
To obtain our result, we use a well-known technique by Hong and Nagamochi for
finding redrawings with convex faces while preserving y-coordinates. Using a
variant of Tutte's graph drawing algorithm, we obtain a new proof of Hong and
Nagamochi's result which comes with a better running time. This is of
independent interest, as Hong and Nagamochi's technique serves as a building
block in existing morphing algorithms.Comment: Preliminary version in Proc. WG 201
A Symmetry Metric for Graphs and Line Diagrams
Symmetry is often considered a desirable feature of diagrams. However, quantifying the exact amount of symmetry present is often difficult. We propose a novel symmetry metric that can score the amount of rotational, translational, and reflective symmetry present in a graph or line diagram
GiViP: A Visual Profiler for Distributed Graph Processing Systems
Analyzing large-scale graphs provides valuable insights in different
application scenarios. While many graph processing systems working on top of
distributed infrastructures have been proposed to deal with big graphs, the
tasks of profiling and debugging their massive computations remain time
consuming and error-prone. This paper presents GiViP, a visual profiler for
distributed graph processing systems based on a Pregel-like computation model.
GiViP captures the huge amount of messages exchanged throughout a computation
and provides an interactive user interface for the visual analysis of the
collected data. We show how to take advantage of GiViP to detect anomalies
related to the computation and to the infrastructure, such as slow computing
units and anomalous message patterns.Comment: Appears in the Proceedings of the 25th International Symposium on
Graph Drawing and Network Visualization (GD 2017
Perception of Symmetries in Drawings of Graphs
Symmetry is an important factor in human perception in general, as well as in
the visualization of graphs in particular. There are three main types of
symmetry: reflective, translational, and rotational. We report the results of a
human subjects experiment to determine what types of symmetries are more
salient in drawings of graphs. We found statistically significant evidence that
vertical reflective symmetry is the most dominant (when selecting among
vertical reflective, horizontal reflective, and translational). We also found
statistically significant evidence that rotational symmetry is affected by the
number of radial axes (the more, the better), with a notable exception at four
axes.Comment: Appears in the Proceedings of the 26th International Symposium on
Graph Drawing and Network Visualization (GD 2018
Planar Drawings of Fixed-Mobile Bigraphs
A fixed-mobile bigraph G is a bipartite graph such that the vertices of one
partition set are given with fixed positions in the plane and the mobile
vertices of the other part, together with the edges, must be added to the
drawing. We assume that G is planar and study the problem of finding, for a
given k >= 0, a planar poly-line drawing of G with at most k bends per edge. In
the most general case, we show NP-hardness. For k=0 and under additional
constraints on the positions of the fixed or mobile vertices, we either prove
that the problem is polynomial-time solvable or prove that it belongs to NP.
Finally, we present a polynomial-time testing algorithm for a certain type of
"layered" 1-bend drawings
Evaluation of two interaction techniques for visualization of dynamic graphs
Several techniques for visualization of dynamic graphs are based on different
spatial arrangements of a temporal sequence of node-link diagrams. Many studies
in the literature have investigated the importance of maintaining the user's
mental map across this temporal sequence, but usually each layout is considered
as a static graph drawing and the effect of user interaction is disregarded. We
conducted a task-based controlled experiment to assess the effectiveness of two
basic interaction techniques: the adjustment of the layout stability and the
highlighting of adjacent nodes and edges. We found that generally both
interaction techniques increase accuracy, sometimes at the cost of longer
completion times, and that the highlighting outclasses the stability adjustment
for many tasks except the most complex ones.Comment: Appears in the Proceedings of the 24th International Symposium on
Graph Drawing and Network Visualization (GD 2016
Revisited experimental comparison of node-link and matrix representations
Visualizing network data is applicable in domains such as biology, engineering, and social sciences. We report the results of a study comparing the effectiveness of the two primary techniques for showing network data: node-link diagrams and adjacency matrices. Specifically, an evaluation with a large number of online participants revealed statistically significant differences between the two visualizations. Our work adds to existing research in several ways. First, we explore a broad spectrum of network tasks, many of which had not been previously evaluated. Second, our study uses a large dataset, typical of many real-life networks not explored by previous studies. Third, we leverage crowdsourcing to evaluate many tasks with many participants
Visual Causality: Investigating Graph Layouts for Understanding Causal Processes
Causal diagrams provide a graphical formalism indicating how statistical models can be used to study causal processes. Despite the extensive research on the efficacy of aesthetic graphic layouts, the causal inference domain has not benefited from the results of this research. In this paper, we investigate the performance of graph visualisations for supporting users’ understanding of causal graphs. Two studies were conducted to compare graph visualisations for understanding causation and identifying confounding variables in a causal graph. The first study results suggest that while adjacency matrix layouts are better for understanding direct causation, node-link diagrams are better for understanding mediated causation along causal paths. The second study revealed that node-link layouts, and in particular layouts created by a radial algorithm, are more effective for identifying confounder and collider variables
- …