A linear layout of a graph defines a total order of the vertices and partitions the edges into either stacks or queues, i.e., crossing-free and non-nested sets of edges along the order, respectively. In this work, we study defective linear layouts that allow forbidden patterns among edges of the same set. Our focus is on k-defective stack layouts and k-defective queue layouts, in which the conflict graph representing the forbidden patterns among the edges of each stack or queue has maximum degree at most k.

We present TReView, the first visual analytics system for the exploration of the European Union (EU) Transparency Register, a large repository that aims to enhance transparency around lobbying activities within the EU, by enabling public oversight of meetings between lobbyists and EU officials.

We study the following question, which has been considered since the 90’s: Does every st-planar graph admit a planar straight-line dominance drawing? We show concrete evidence for the difficulty of this question, by proving that, unlike upward planar straight-line drawings, planar straight-line dominance drawings with prescribed y-coordinates do not always exist and planar straight-line dominance drawings cannot always be constructed via a contract-draw-expand inductive approach. We also show several classes of st-planar graphs that always admit a planar straight-line dominance drawing. These include st-planar 3-trees in which every stacking operation introduces two edges incoming into the new vertex, st-planar graphs in which every vertex is adjacent to the sink, and st-planar graphs in which no face has the left boundary that is a single edge.

A 2-layer drawing of a bipartite graph G is a drawing such that the vertices of each partition set are drawn as points of a distinct horizontal line (called a layer) and the edges are drawn as straight-line segments. We study 2-layer drawings where edges can cross only at right angles; these drawings are called 2-layer right angle crossing drawings (2-layer RAC drawings for short). We focus on the following problem, which we call the maximum 2-layer RAC subgraph (M2LRacS) problem. Given a bipartite graph G, compute a subgraph H of G such that: (i) H admits a 2-layer RAC drawing and (ii) H has the maximum number of edges among the subgraphs of G that satisfy (i). We study this problem both in the no-fixed-layer setting, where no restriction is given on the vertex ordering on each layer, and in the 1-fixed-layer setting, where the ordering of the vertices of one of the two layers is given as part of the input and cannot be changed. The M2LRacS problem is known to be 𝒩𝒫-hard in the no-fixed-layer setting (Di Giacomo, E., Didimo, W., Eades, P. and Liotta, G. (2011) 2-Layer Right Angle Crossing Drawings. Proc. IWOCA 2011, Lecturer Notes in Computer Science 7056, pp. 156–169; Di Giacomo, E., Didimo, W., Eades, P. and Liotta, G. (2014) 2-layer right angle crossing drawings. Algorithmica, 68, 954–997), but no algorithm has been proposed so far to solve it. We prove that the M2LRacS problem remains 𝒩𝒫-hard even in the 1-fixed-layer setting, and provide different heuristics to solve it in the two settings; one of these heuristics is a 3-approximation algorithm for the no-fixed-layer setting. Also, we present the results of an experimental study that compares our heuristics and shows the effectiveness of the 3-approximation algorithm in practice.

The paper describes WhatsOnWeb+, a search clustering engine that allows users to browse and analyze the results of a query by means of enhanced graph visualization techniques. WhatsOnWeb+ integrates a wide array of visual interfaces, animation and interaction functionalities, and clustering technologies. The effectiveness of the different visual interfaces and of the different clustering algorithms implemented in the system has been measured by means of an extensive experimental analysis. The described system represents a significant evolution of a previous clustering engine for the Web.

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.