Among recent graph drawing (GD) methods, tsNET creates high quality layouts but suffers from a very high runtime due to its underlying reliance on the t-SNE projection technique. We address this problem by presenting NNP-NET, a method that adapts NNP, a projection technique that can project high-dimensional datasets linearly in the data size, to handle both unweighted and weighted graphs, with layout quality being very close to the ground-truth tsNET. We also exploit NNP's built-in out-of-sample ability to enable NNP-NET to project time-dependent (dynamic) graphs while striking a good balance between layout stability and good layout quality. We show experiments that outline how NNP-NET can handle very large graphs - up to 50 million nodes and 108 million edges faster than all other comparable methods we are aware of while also yielding good quality metric values.

tsNET is a recent graph drawing (GD) method that creates high quality layouts but suffers from a very high runtime. We present a new GD method, NNP-NET, which reduces tsNET’s time complexity to generate layouts for very large graphs in seconds. Additionally, we extend tsNET to support drawing graphs with edge weights. We accomplish this by replacing tsNET’s t-SNE projection with Neural Network Projection (NNP), a fast dimensionality reduction (DR) method that can imitate any given DR method. Our experiments show that NNP-NET gets good quality results when compared to other state-of-the art GD methods while yielding a better computational scalability.

Metaphorical maps or contact representations are visual representations of vertex-weighted graphs that rely on the geographic map metaphor. The vertices are represented by countries, the weights by the areas of the countries, and the edges by contacts/boundaries among them. The accuracy with which the weights are mapped to areas and the simplicity of the polygons representing the countries are the two classical optimization goals for metaphorical maps. Mchedlidze & Schnorr [Mchedlidze and Schnorr, 2022] presented a force-based algorithm that creates metaphorical maps that balance between these two optimization goals. Their maps look visually simple, but the accuracy of the maps is far from optimal - the countries' areas can vary up to 30% compared to required. In this paper, we provide a multi-fold extension of the algorithm in [Mchedlidze and Schnorr, 2022]. More specifically: 1) Towards improving accuracy: We introduce the notion of region stiffness and suggest a technique for varying the stiffness based on the current pressure of map regions. 2) Towards maintaining simplicity: We introduce a weight coefficient to the pressure force exerted on each polygon point based on whether the corresponding point appears along a narrow passage. 3) Towards generality: We cover, in contrast to [Mchedlidze and Schnorr, 2022], non-triangulated graphs. This is done by either generating points where more than three regions meet or by introducing holes in the metaphorical map. We perform an extended experimental evaluation that, among other results, reveals that our algorithm is able to construct metaphorical maps with nearly perfect area accuracy with a little sacrifice in their simplicity.

Graph drawings are commonly used to visualize relational data. User understanding and performance are linked to the quality of such drawings, which is measured by quality metrics. The tacit knowledge in the graph drawing community about these quality metrics is that they are not always able to accurately capture the quality of graph drawings. In particular, such metrics may rate drawings with very poor quality as very good. In this work we make this tacit knowledge explicit by showing that we can modify existing graph drawings into arbitrary target shapes while keeping one or more quality metrics almost identical. This supports the claim that more advanced quality metrics are needed to capture the "goodness" of a graph drawing and that we cannot confidently rely on the value of a single (or several) certain quality metrics.

Abstract Graph drawings using a node‐link metaphor and straight edges are widely used to represent and understand relational data. While such drawings are typically created in 2D, 3D representations have also gained popularity. When exploring 3D drawings, finding viewpoints that help understanding the graph's structure is crucial. Finding good viewpoints also allows using the 3D drawings to generate good 2D graph drawings. In this work, we tackle the problem of automatically finding high‐quality viewpoints for 3D graph drawings. We propose and evaluate strategies based on sampling, gradient descent, and evolutionary‐inspired meta‐heuristics. Our results show that most strategies quickly converge to high‐quality viewpoints within a few dozen function evaluations, with meta‐heuristic approaches showing robust performance regardless of the quality metric.

Abstract Node‐link diagrams are a widely used metaphor for creating visualizations of relational data. Most frequently, such techniques address creating 2D graph drawings, which are easy to use on computer screens and in print. In contrast, 3D node‐link graph visualizations are far less used, as they have many known limitations and comparatively few well‐understood advantages. A key issue here is that such 3D visualizations require users to select suitable viewpoints. We address this limitation by studying the ability of layout techniques to produce high‐quality views of 3D graph drawings. For this, we perform a thorough experimental evaluation, comparing 3D graph drawings, rendered from a covering sampling of all viewpoints, with their 2D counterparts across various state‐of‐the‐art node‐link drawing algorithms, graph families, and quality metrics. Our results show that, depending on the graph family, 3D node‐link diagrams can contain a many viewpoints that yield 2D visualizations that are of higher quality than those created by directly using 2D node‐link diagrams. This not only sheds light on the potential of 3D node‐link diagrams but also gives a simple approach to produce high‐quality 2D node‐link diagrams.

Abstract A k-page upward book embedding (kUBE) of a directed acyclic graph G is a book embeddings of G on k pages with the additional requirement that the vertices appear in a topological ordering along the spine of the book. The kUBE Testing problem, which asks whether a graph admits a kUBE, was introduced in 1999 by Heath, Pemmaraju, and Trenk (SIAM J Comput 28(4), 1999). In a companion paper, Heath and Pemmaraju (SIAM J Comput 28(5), 1999) proved that the problem is linear-time solvable for $$k=1$$ k = 1 and NP-complete for $$k = 6$$ k = 6 . Closing this gap has been a central question in algorithmic graph theory since then. In this paper, we make a major contribution towards a definitive answer to the above question by showing that kUBE Testing is NP-complete for $$k\ge 3$$ k ≥ 3 , even for st-graphs, i.e., acyclic directed graphs with a single source and a single sink. Indeed, our result, together with a recent work of Bekos et al. (Theor Comput Sci 946, 2023) that proves the NP-completeness of 2UBE for planar st-graphs, closes the question about the complexity of the kUBE problem for any k. Motivated by this hardness result, we then focus on the 2UBE Testing for planar st-graphs. On the algorithmic side, we present an $$O(f(\beta )\cdot n+n^3)$$ O ( f ( β ) · n + n 3 ) -time algorithm for 2UBE Testing, where $$\beta $$ β is the branchwidth of the input graph and f is a singly-exponential function on $$\beta $$ β . Since the treewidth and the branchwidth of a graph are within a constant factor from each other, this result immediately yields an FPT algorithm for st-graphs of bounded treewidth. Furthermore, we describe an O(n)-time algorithm to test whether a plane st-graph whose faces have a special structure admits a 2UBE that additionally preserves the plane embedding of the input st-graph. On the combinatorial side, we present two notable families of plane st-graphs that always admit an embedding-preserving $$2$$ 2 UBE.

The page-number of a directed acyclic graph (a DAG, for short) is the minimum k for which the DAG has a topological order and a k-coloring of its edges such that no two edges of the same color cross, i.e., have alternating endpoints along the topological order. In 1999, Heath and Pemmaraju conjectured that the recognition of DAGs with page-number 2 is NP-complete and proved that recognizing DAGs with page-number 6 is NP-complete (Heath and Pemmaraju (1999) [15]). Binucci et al. recently strengthened this result by proving that recognizing DAGs with page-number k is NP-complete, for every k≥3 (Binucci et al. (2019) [6]). In this paper, we finally resolve Heath and Pemmaraju's conjecture in the affirmative. In particular, our NP-completeness result holds even for st-planar graphs and planar posets.

Abstract In geographic data analysis, one is often given point data of different categories (such as facilities of a university categorized by department). Drawing upon recent research on set visualization, we want to visualize category membership by connecting points of the same category with visual links. Existing approaches that follow this path usually insist on connecting all members of a category, which may lead to many crossings and visual clutter. We propose an approach that avoids crossings between connections of different categories completely. Instead of connecting all data points of the same category, we subdivide categories into smaller, local clusters where needed. We do a case study comparing the legibility of drawings produced by our approach and those by existing approaches. In our problem formulation, we are additionally given a graph G on the data points whose edges express some sort of proximity. Our aim is to find a subgraph G′ of G with the following properties: (i) edges connect only data points of the same category, (ii) no two edges cross, and (iii) the number of connected components (clusters) is minimized. We then visualize the clusters in G′. For arbitrary graphs, the resulting optimization problem, Cluster Minimization, is NP‐hard (even to approximate). Therefore, we introduce two heuristics. We do an extensive benchmark test on real‐world data. Comparisons with exact solutions indicate that our heuristics do astonishing well for certain relative‐neighborhood graphs.

We study $k$-page upward book embeddings ($k$UBEs) of $st$-graphs, that is, book embeddings of single-source single-sink directed acyclic graphs on $k$ pages with the additional requirement that the vertices of the graph appear in a topological ordering along the spine of the book. We show that testing whether a graph admits a $k$UBE is NP-complete for $k\geq 3$. A hardness result for this problem was previously known only for $k = 6$ [Heath and Pemmaraju, 1999]. Motivated by this negative result, we focus our attention on $k=2$. On the algorithmic side, we present polynomial-time algorithms for testing the existence of $2$UBEs of planar $st$-graphs with branchwidth $β$ and of plane $st$-graphs whose faces have a special structure. These algorithms run in $O(f(β)\cdot n+n^3)$ time and $O(n)$ time, respectively, where $f$ is a singly-exponential function on $β$. Moreover, on the combinatorial side, we present two notable families of plane $st$-graphs that always admit an embedding-preserving $2$UBE.

Abstract We introduce and study level-planar straight-line drawings with a fixed number $$\lambda $$ λ of slopes. For proper level graphs (all edges connect vertices of adjacent levels), we give an $$O(n \log ^2 n / \log \log n)$$ O ( n log 2 n / log log n ) -time algorithm that either finds such a drawing or determines that no such drawing exists. Moreover, we consider the partial drawing extension problem, where we seek to extend an immutable drawing of a subgraph to a drawing of the whole graph, and the simultaneous drawing problem, which asks about the existence of drawings of two graphs whose restrictions to their shared subgraph coincide. We present $$O(n^{4/3} \log n)$$ O ( n 4 / 3 log n ) -time and $$O(\lambda n^{10/3} \log n)$$ O ( λ n 10 / 3 log n ) -time algorithms for these respective problems on proper level-planar graphs. We complement these positive results by showing that testing whether non-proper level graphs admit level-planar drawings with $$\lambda $$ λ slopes is -hard even in restricted cases.

A queue layout of a graph consists of a linear order of its vertices and a partition of its edges into queues, so that no two independent edges of the same queue are nested. The queue number of a graph is the minimum number of queues required by any of its queue layouts. A long-standing conjecture by Heath, Leighton and Rosenberg states that the queue number of planar graphs is bounded.This conjecture has been partially settled in the positive for several sub- families of planar graphs (most of which have bounded treewidth).

A queue layout of a graph consists of a linear order of its vertices and a partition of its edges into queues, so that no two independent edges of the same queue are nested. The queue number of a graph is the minimum number of queues required by any of its queue layouts. A long-standing conjecture by Heath, Leighton and Rosenberg [ SIAM J. Discrete Math., 5 (1992), pp. 398--412] states that the queue number of planar graphs is bounded. This conjecture has been partially settled in the positive for several subfamilies of planar graphs (most of which have bounded treewidth). In this paper, we make a further important step towards settling this conjecture. We prove that planar graphs of bounded degree (which may have unbounded treewidth) have bounded queue number. A notable implication of this result is that every planar graph of bounded degree admits a three-dimensional straight-line grid drawing in linear volume. Further implications are that every planar graph of bounded degree has bounded track number, and that every $k$-planar graph (i.e., every graph that can be drawn in the plane with at most $k$ crossings per edge) of bounded degree has bounded queue number.

A straight-line drawing of a graph is a monotone drawing if for each pair of vertices there is a path which is monotonically increasing in some direction, and it is called a strongly monotone drawing if the direction of monotonicity is given by the direction of the line segment connecting the two vertices. We present algorithms to compute crossing-free strongly monotone drawings for some classes of planar graphs; namely, 3-connected planar graphs, outerplanar graphs, and 2-trees. The drawings of 3-connected planar graphs are based on primal-dual circle packings. Our drawings of outerplanar graphs depend on a new algorithm that constructs strongly monotone drawings of trees which are also convex. For irreducible trees, these drawings are strictly convex.