Walter Didimo

Drawing Graphs with Right Angle Crossings

Cognitive experiments show that humans can read graph drawings in which all edge crossings are at right angles equally well as they can read planar drawings; they also show that the readability of a drawing is heavily affected by the number of bends along the edges. A graph visualization whose edges can only cross perpendicularly is called a RAC (Right Angle Crossing) drawing . This paper initiates the study of combinatorial and algorithmic questions related with the problem of computing RAC drawings with few bends per edge. Namely, we study the interplay between number of bends per edge and total number of edges in RAC drawings. We establish upper and lower bounds on these quantities by considering two classical graph drawing scenarios: The one where the algorithm can choose the combinatorial embedding of the input graph and the one where this embedding is fixed.

Computing orthogonal drawings with the minimum number of bends

We describe a branch-and-bound algorithm for computing an orthogonal grid drawing with the minimum number of bends of a biconnected planar graph. Such an algorithm is based on an efficient enumeration schema of the embeddings of a planar graph and on several new methods for computing lower bounds of the number of bends. We experiment with such algorithm on a large test suite and compare the results with the state of the art. The experiments show the feasibility of the approach and also its limitations. Further, the experiments show how minimizing the number of bends has positive effects on other quality measures of the effectiveness of the drawing. We also present a new method for dealing with vertices of degree larger than four.

Graph Visualization Techniques for Web Clustering Engines

One of the most challenging issues in mining information from the World Wide Web is the design of systems that present the data to the end user by clustering them into meaningful semantic categories. We show that the analysis of the results of a clustering engine can significantly take advantage of enhanced graph drawing and visualization techniques. We propose a graph-based user interface for Web clustering engines that makes it possible for the user to explore and visualize the different semantic categories and their relationships at the desired level of detail

Curve-constrained drawings of planar graphs

Let C be the family of 2D curves described by concave functions, let G be a planar graph, and let L be a linear ordering of the vertices of G. L is a curve embedding of G if for any given curve Λ ∈ C there exists a planar drawing of G such that: (i) the vertices are constrained to be on Λ with the same ordering as in L, and (ii) the edges are polylines with at most one bend. Informally speaking, a curve embedding can be regarded as a two-page book embedding in which the spine is bent. Although deciding whether a graph has a two-page book embedding is an NP-hard problem, in this paper it is proven that every planar graph has a curve embedding which can be computed in linear time. Applications of the concept of curve embedding to upward drawability and point-set embeddability problems are also presented.

The Crossing-Angle Resolution in Graph Drawing

The crossing-angle resolution of a drawing of a graph measures the smallest angle formed by any pair of crossing edges. In this chapter, we survey some of the most recent results and discuss the current research agenda on drawings of graphs with good crossing-angle resolution.

Visual analysis of large graphs using (X,Y)-clustering and hybrid visualizations

Many different approaches have been proposed for the challenging problem of visually analyzing large networks. Clustering is one of the most promising. In this paper, we propose a new clustering technique whose goal is that of producing both intracluster graphs and intercluster graph with desired topological properties. We formalize this concept in the (X,Y) -clustering framework, where Y is the class that defines the desired topological properties of intracluster graphs and X is the class that defines the desired topological properties of the intercluster graph. By exploiting this approach, hybrid visualization tools can effectively combine different node-link and matrix-based representations, allowing users to interactively explore the graph by expansion/contraction of clusters without loosing their mental map. As a proof of concept, we describe the system Visual Hybrid (X,Y)-clustering (VHYXY) that implements our approach and we present the results of case studies to the visual analysis of social networks.

Area, Curve Complexity, and Crossing Resolution of Non-Planar Graph Drawings

In this paper we study non-planar drawings of graphs, and study trade-offs between the crossing resolution (i.e., the minimum angle formed by two crossing segments), the curve complexity (i.e., maximum number of bends per edge), the total number of bends, and the area.

Planarization of Clustered Graphs

We propose a planarization algorithm for clustered graphs and experimentally test its efficiency and effectiveness. Further, we integrate our planarization strategy into a complete topology-shape-metrics algorithm for drawing clustered graphs in the orthogonal drawing convention.

Orthogonal and Quasi-upward Drawings with Vertices of Prescribed Size

We consider the problem of computing orthogonal drawings and quasi-upward drawings with vertices of prescribed size. For both types of drawings we present algorithms based on network flow techniques and show that the produced drawings are optimal within a wide class. Further, we present the results of an experimentation conducted on the algorithms that we propose for orthogonal drawings. The experiments show the effectiveness of the approach.

Density of straight-line 1-planar graph drawings

A 1-planar drawing of a graph is such that each edge is crossed at most once. In 1997, Pach and Toth showed that any 1-planar drawing with n vertices has at most 4n-8 edges and that this bound is tight for n>=12. We show that, in fact, 1-planar drawings with n vertices have at most 4n-9 edges, if we require that the edges are straight-line segments. We also prove that this bound is tight for infinitely many values of n>=8. Furthermore, we investigate the density of 1-planar straight-line drawings with additional constraints on the vertex positions. We show that 1-planar drawings of bipartite graphs whose vertices lie on two distinct horizontal layers have at most 1.5n-2 edges, and we prove that 1-planar drawings such that all vertices lie on a circumference have at most 2.5n-4 edges; both these bounds are also tight.