An important approach for scientific inquiry across many disciplines involves using observational time series data to understand the relationships between key variables to gain mechanistic insights into the underlying rules that govern the given system. In real systems, such as those found in ecology, the relationships between time series variables are generally not static; instead, these relationships are dynamical and change in a nonlinear or state-dependent manner. To further understand such systems, we investigate integrating methods that appropriately characterize these dynamics (i.e., methods that measure interactions as they change with time-varying system states) with visualization techniques that can help analyze the behavior of the system. Here, we focus on empirical dynamic modeling (EDM) as a state-of-the-art method that specifically identifies causal variables and measures changing state-dependent relationships between time series variables. Instead of using approaches centered on parametric equations, EDM is an equation-free approach that studies systems based on their dynamic attractors. We propose a visual analytics system to support the identification and mechanistic interpretation of system states using an EDM-constructed dynamic graph. This work, as detailed in four analysis tasks and demonstrated with a GUI, provides a novel synthesis of EDM and visualization techniques such as brush-link visualization and visual summarization to interpret dynamic graphs representing ecosystem dynamics. We applied our proposed system to ecological simulation data and real data from a marine mesocosm study as two key use cases. Our case studies show that our visual analytics tools support the identification and interpretation of the system state by the user, and enable us to discover both confirmatory and new findings in ecosystem dynamics. Overall, we demonstrated that our system can facilitate an understanding of how systems function beyond the intuitive analysis of high-dimensional information based on specific domain knowledge.

Group-in-a-box (GIB) is a graph-drawing method designed to facilitate the visualization of the group structure of a graph. GIB allows the user to simultaneously view group sizes and inter-and intra-group structures. Several GIB variants have been proposed in the literature; however, their advantages and disadvantages have not been studied from the perspective of human cognition. Therefore, herein, we used eye tracking analysis and user surveys to evaluate the user experience of four GIB variants: Squarified-Treemap GIB(ST-GIB), Croissant-and-Doughnut GIB (CD-GIB), Force-Directed GIB (FD-GIB), and Tree-Reordered GIB (TR-GIB). We found some trade-offs among the methods for each type of user task and that FD-GIB and TR-GIB are superior than the other variants. Although ST-GIB's results were good, links were difficult to read in this graph layout. Eye-tracking data was gathered to determine which elements in each visualization significantly affected user experience. The results of this study will promote the effective use of GIB to analyze networks such as social networks or web graphs.

To improve visualization, it is necessary to optimize the design by analyzing the behavior of users as well as improving the evaluation index of the computational experiment and the task performance (e.g., the correct answer rate and completion time) in the user experiment. Although various studies have investigated the influence of user behavior on the evaluation of visualization, majority of these studies focused on simple visualization tasks. A simple task does not indicate a simple visualization comprising a few visualization elements but a task in which the information obtained from visualization is the only clue for completing the task. However, a few studies have targeted complicated tasks in which multiple information obtained from visualization is considered to be a clue for completing the task regardless of the number of elements that are contained in the visualization. Therefore, in this study, we investigated the behavior of the participants who have performed complicated tasks. We selected two types of group-in-a-box (GIB) layouts, which can be considered to be a complicated visualization method , as the target of the user experiment. In the user experiment, participants were asked to perform an exploration task specific to GIB layouts; which group has the maximum number of intra-edges? We also collected the eye-tracking data in addition to task performance. The results showed that the correct answer rate is considerably affected by the visualization factor; whether the correct answer, the box with maximum number of intra-edges, is the box with the largest area. Furthermore, an analysis of the collected eye-tracking data revealed that this visualization factor affected the exploration behavior of the participants; however, it did not affect the location at which the participants were focused on. The obtained results indicated that the visualization elements that were not considered by the visualization designer can influence the task of extracting information from the data. Therefore, designers have to configure the visualization by considering the visual cognitive behavior of the users.

Wet and dry biological data are potentially complementary. By visually integrating the initiation and developmental processes of organisms, we might reveal new causalities in biological data. Here we present an integrated visualization system for a causality network constructed from phenotypic developmental characters and their related scientific literature. To obtain the phenotypic characters, we applied bio-imaging informatics techniques to the data of wet experiments. The phenotypic character network was visually rendered in the CausalNet system, which provides both explanatory and verification visualization functions. Statistical analysis and scientific literature mining proved useful for determining the mechanisms underlying the phenotypic trait network. The validity of the system was confirmed in an application example and expert feedback on the developmental process of the nematode Caenorhabditis elegans. The discussed methodology is applicable to other multicellular organisms.

The four papers in this special section were presented at the 2018 IEEE Pacific Visualization Symposium (IEEE PacificVis’18), which was held at the Integrated Research Center of Kobe University, Kobe,Japan from April 10 to 13, 2018.

In most species, calcium waves in the oocyte are considered common phenomena in the activation of eggs. However, the mechanism of calcium waves has not yet been clarified. By collaborating with biologists studying Caenorhabditis elegans ( C. elegans ), which is widely used as a model organism, we observed that the following requirements must be satisfied to form a useful hypothesis based on calcium waves captured using high-speed in vivo imaging: (1) the ability to obtain an overview of how the calcium waves are propagated and (2) the ability to understand the propagation of waves in a narrow region. However, conventional visualization methods cannot satisfy these requirements simultaneously. Therefore, we propose a visual analytics system that allows users to understand and explore calcium wave images using cross-correlation analysis of the time-series data of the Ca 2+ fluorescence intensity at each point. The interface of this system comprises an overview visualization, a detail visualization, and user interactions to satisfy these requirements and realize exploratory visualization. Some views present an overview visualization that displays the clustering results of a directed graph calculated using cross-correlation analysis. These views enable the users to understand the overview of wave propagation, thereby helping users find a region of interest. The detail visualization shows the relationship between the region of interest and other areas. Furthermore, users can use the proposed system with overview-detail and brush-link exploration to assign meaning to the region of interest and construct a hypothesis for its role. In this paper, we demonstrate how the proposed visual analytics approach works and how new hypotheses can be formed using the analysis of C. elegans calcium waves.

Biclustering is a well-known approach for data mining, and it is applied in many fields, such as genome analyses, security services, and social network analyses. Biclustering finds bicliques contained in a bipartite graph. However, in real data, a biclique may lack several edges because of various reasons, such as errors. In this situation, traditional biclustering methods cannot find correct biclusters. A novel biclustering method that can analyze real data under uncertainty is needed. Quasi-biclique is a mathematical concept that represents incomplete bicliques. We propose the quasi-biclique edge concentration (QBEC) method, which is a visual analysis method for biclustering using quasi-biclique mining. QBEC includes visual representations and user interactions for quasi-bicliques. Quasi-bicliques contained in a bipartite graph are represented based on edge concentration. The incompleteness of a quasi-biclique is reflected in edge opacity. Users can interactively explore data by adjusting the incompleteness parameter of the quasi-biclique. We demonstrate the effectiveness of QBEC using real-world data.

The primary challenge in the visualization of a large-scale unstructured volume data with mixed cell types is to dissolve a bottleneck caused by visibility sorting of unstructured cells. In this paper, we implement an interactive particle-based rendering method to solve this complex visualization problem. This technique uses opaque particles as the proxy geometry of the mixed unstructured cells so that the visibility sorting process is not needed. This characteristic makes the rendering of mixed-cell unstructured volume efficient. We also construct a resizing function to adjust the particle radius depending on the assigned transfer function so that the transfer function can be adjusted in real time. Furthermore, we develop a time-varying level-of-detail (LOD) rendering to efficiently handle the large-scale time-varying data. This LOD rendering can provide high-speed rendering for animation rendering and high-quality rendering when the animation is stopped at any time step of interest. These features facilitate the detailed analysis of the temporal features of the data.

Edge concentration in dense bipartite graphs is a technique for reducing the numbers of edges and edge crossings in graph drawings. The conventional method proposed by Newbery is designed to reduce the number of edge crossings; however, it does not always reduce the number of edges. Reducing the number of edges is also an important factor for improving the readability of graphs. However, no edge concentration method with the explicit purpose of minimizing the number of edges has previously been studied. In this study, we propose a novel, efficient heuristic method for minimizing the number of edges during edge concentration. We demonstrate the efficiency of the proposed method via a comparison using randomly generated graphs. We find that Newbery's method fails to reduce the number of edges when the number of vertices is large. By contrast, the proposed method achieves an average compression ratio of 47 to 82 percent for all generated graph groups. We also present a real-world application of the proposed method using a causality network of biological data.

In this talk, we will clarify roles of visualization techniques which are mandatory to employ a scientific method in policy-making. Currently, many countries are investing heavily in policy-making process development through the ICT for this purpose. In the policy cycle, there are many opportunities in which a scientific method can be effectively applied especially in the agenda setting. In the phase, it is important to visualize a cognitive structure in a citizen. We focus on the evaluation grid method to figure out the citizen's requirement. Once we construct the cognitive structure represented by a graph in which nodes and arcs are represented as constructs and relationships between them, respectively, we can develop a predictive cognitive model which will be useful in the agenda setting. For this purpose we employ multivariate visualization techniques which can figure out meaningful relationships in the cognitive model.

In this paper, we propose a technique for rendering multiple irregular volumes using a stochastic approach. In this approach, we extend our stochastic projected tetrahedral (SPT) algorithm to treat irregular volumes. The SPT algorithm is a sorting-free volume rendering algorithm that projects a tetrahedral cell onto an image plane and controls the particle rendering using the opacity as the probability in the rasterization process. In the rasterization process, the particle depth is determined as that of a pre-defined location, which may be the front, back or middle point on a ray segment in the SPT algorithm. This determination causes a prominent artifact when treating multiple volumes, although it does not cause any problem when treating a single volume. The artifact occurs because the SPT algorithm controls the particle stochastically in the image plane but not in the depth direction. In the volume rendering process, it is assumed that the number of particles follows a Poisson distribution along the segment of the viewing ray that intersects the tetrahedral cell. The particle spacing follows the exponential distribution. In this case, we construct a cumulative distribution function of the particle spacing and develop a technique for calculating the nearest particle along the interval. We apply this technique to multiple volumes to confirm its effectiveness.

We propose a new application of stochastic point-based rendering, which was recently proposed for implicit surfaces, to large-scale laser-scanned 3D point data. Specifically, we propose a scheme to apply the rendering to transparent and fused visualization of recent large and complex laser-scanned data from cultural assets. Our scheme uses 3D points that are directly acquired using a laser scanner as the rendering primitives. For laser-scanned data that consist of more than 107 or 108 3D points, the pre-processing stage takes only a few minutes, and the rendering stage is executable at interactive frame rates. We do not encounter rendering artifacts originating from the indefiniteness of depth-sorted orders of rendering primitives. Fused visualization with various visual assistants is also possible. We demonstrate the effectiveness of our scheme by visualizing a campus building and a culturally important festival float.

In this study, we propose a novel integrated visualization system that enables interactive visual development of a Habitat Suitability Index (HSI) model for predicting the locations of fishing grounds. Our system enables the interactive selection of variables that are highly correlated to fish catches recorded by fishermen on their vessels. We illustrate the use of this system using a real-world simulation of the Pacific Ocean. Vortex structures, such as those used for fishing grounds exploration, are crucial for exploring fishing ground because they can drive nutrients from the ocean floor to the sea surface. The ability to locate fishing grounds therefore depends on accurate ocean forecasting systems for calculating ocean model variables such as temperature, salinity, velocity etc. Currently, these forecasts are based on multiple spatio-temporal simulations that produce multidimensional and multivariate results. Critical points in the ocean model are good indicators of the likelihood of finding microscale vortices, and our visualization approach enables the interactive exploration and analysis of these critical points. The proposed system makes it possible to analyze the vortex structure in the spatial domain, and explore fishing grounds on the sea surface in detail.

We report the system that collects the data from the sensor network and visualizes the data on real time by three dimensions on a computer. It becomes possible for this system to make a user make the measurement data on space intuitive.

We consider that eye-to-eye contact during face-to-face communication is important to understand each other in everyday communication. However, 3D display usually requires deflection glasses and a head mount display (HMD), and it is difficult to carry out eye-to-eye contact in such a condition. To support face-to-face communication by group in tele-immersive environment, we constructed 3D display environment using a merged video image obtained from the multi-viewpoint videos merging system set up in the actual space. In this paper, we have conducted experiments on the possibility of eye-to-eye contact by the multi-viewpoint videos merging system with auto-stereoscopic display. From experimental results, we have proved that two estimators could realize eye-to-eye contact at each direction for a gazer on auto-stereoscopic display. In addition, we have showed that it is effective to locate cameras at the center or at the lower half of display in order to feel eye-to-eye contact.

Recently, immersive projection technology (IPT) systems such as CAVE and CABIN have attracted great attention. In IPT systems, since we can experience virtual environments with whole body, these can provide high immersive virtual environments. To interact with virtual environments easily, IPT systems often adopt one-handed input systems. However, by using bimanual input systems, their operationality, e.g., walking-through and pointing, can be improved. Although there are several bimanual input systems for virtual environments, these have not been used for IPT systems. In this paper, we propose a bimanual input system for IPT systems. In our proposed system, users wear compact joysticks on both hands and their hands' positions are detected by magnetic sensors. By using the system, users can interact with the virtual environment in the IPT system. From our evaluations, we confirmed that our proposed system provides fast and easy operations in virtual environments.

In the present paper, we introduce a novel point-based volume rendering technique based on particle generation from user-specified transfer function. In the proposed technique, a set of tiny particles is generated from a given 3D scalar field. This particle generation process is based on a user-specified transfer function and rejection method. These particles are then projected onto the image plane to generate the final image. The main characteristic of the proposed technique is that the particle projection order is independent and unfixed because the transparency values of the particles are not taken into account. Therefore, only the depth-order comparison between the particles is required during the projection stage, which can greatly facilitate the distributed processing. When the quantity of projected particles is small, for instance, a maximum of one per pixel area, it becomes difficult to achieve semi-transparency, which is the main characteristic of volume rendering. To overcome this problem, sub-pixel processing is applied in order to allow the projection of multiple particles onto each of the pixel areas. The final pixel value is then obtained by averaging the contribution from each of these projected particles. The use of the Metropolis method for particle generation is also investigated as an alternative method for further improving the image quality

One of the most effective techniques for developing efficient isosurfacing algorithms is the reduction of visits to nonisosurface cells. Recent algorithms have drastically reduced the unnecessary cost of visiting nonisosurface cells. The experimental results show almost optimal performance in their isosurfacing processes. However, most of them have a bottleneck in that they require more than O(n) computation time for their preprocessing, where n denotes the total number of cells. We propose an efficient isosurfacing technique, which can be applied to unstructured as well as structured volumes and which does not require more than O(n) computation time for its preprocessing. A preprocessing step generates an extrema skeleton, which consists of cells and connects all extremum points, by the volume thinning algorithm. All disjoint parts of every isosurface intersect at least one cell in the extrema skeleton. Our implementation generates isosurfaces by searching for isosurface cells in the extrema skeleton and then recursively visiting their adjacent isosurface cells, while it skips most of the nonisosurface cells. The computation time of the preprocessing is estimated as O(n). The computation time of the isosurfacing process is estimated as O(n/sup 1/3/m+k), where k denotes the number of isosurface cells and m denotes the number of extremum points since the number of cells in an extrema skeleton is estimated as O(n/sup 1/3/m).

Proposes an effective technique for searching for critical points, which are points at which the velocity vector is zero. The previous method, using tetrahedral-cell subdivision, often generates multiple critical points in a hexahedral cell, and this causes several defects in flow visualization. First, we propose a new criterion for differences between interpolation functions, and investigate the reasons for the generation of multiple critical points in a hexahedral cell. Next, to prevent the generation of multiple critical points, we propose an improved method using both tetrahedral-cell subdivision and a trilinear interpolation function. Our method finds critical points by using a linear interpolation function, and, when multiple critical points are found in a hexahedral cell, a numerical integration scheme (Newton's method) is applied and a more precise position is calculated. We apply our approach to several sets of velocity data and evaluate it in several ways.

An isosurface can be efficiently generated by visiting adjacent intersected cells in order, as if the isosurface were propagating itself. We previously proposed an extrema graph method (T. Itoh and K. Koyamada, 1995), which generates a graph connecting extremum points. The isosurface propagation starts from some of the intersected cells that are found both by visiting the cells through which arcs of the graph pass and by visiting the cells on the boundary of a volume. We propose an efficient method of searching for cells intersected by an isosurface. This method generates a volumetric skeleton. consisting of cells, like an extrema graph, by applying a thinning algorithm used in the image recognition area. Since it preserves the topological features of the volume and the connectivity of the extremum points, it necessarily intersects every isosurface. The method is more efficient than the extrema graph method, since it does not require that cells on the boundary be visited.

A high-performance algorithm for generating isosurfaces is presented. In our method, guides to searching for cells intersected by an isosurface are generated as a pre-process. These guides are two kinds of cell lists: an extrema graph, and sorted lists of boundary cells. In an extrema graph, extremum points are connected by arcs, and each arc has a list of cells through which it passes. At the same time, all boundary cells are sorted according to their minimum and maximum values, and two sorted lists are then generated. Isosurfaces are generated by visiting adjacent intersected cells in order. Here, the starting cells for this process are found by searching in an extrema graph and in sorted boundary cell lists. In this process, isosurfaces appear to propagate themselves. Our algorithm is efficient, since it visits only cells that are intersected by an isosurface and cells whose IDs are included in the guides. It is especially efficient when many isosurfaces are interactively generated in a huge volume. Some benchmark tests described in this paper show the efficiency of the algorithm.

A high-performance algorithm for generating isosurfaces is presented. In this algorithm, extrema points in a scalar field are first extracted. A graph is then generated in which the extrema points are taken as nodes. Each arc of the graph has a list of IDs of the cells that are intersected by the arc. A boundary cell list ordered according to cells' values is also generated. The graph and the list generated in this pre-process are used as a guide in searching for seed cells. Isosurfaces are generated from seed cells that are found in arcs of the graph. In this process, isosurfaces appear to propagate themselves. The algorithm visits only cells that are intersected by an isosurface and cells whose IDs an included in cell lists. It is especially efficient when many isosurfaces are interactively generated in a huge volume. Some benchmark tests described show the efficiency of the algorithm.>

Techniques for visualizing a simulated air flow in a clean room are developed by using an efficient cell traverse of tetrahedral cells generated from irregular volumes. The proposed techniques, probing and stream line display, are related to the measurement techniques used in actual clean rooms. The efficient traverse makes it possible to move freely around a given irregular volume and to spawn off stream lines. A successful application of these techniques to a problem in a clean room is also described.>

Abstract This paper proposes an integrated rendering algorithm for visualizing 3D volumetric and geometric data, such as surfaces, lines and points, simultaneously with depth information, and other algorithms for improving the performance of the rendering process of the first. The first algorithm extends a volume rendering algorithm based on ray‐tracing so that it can handle both 3D volumetric and geometric data. It processes these data in accordance with their original representation formats to eliminate conversion artefacts such as spurious or missing surfaces, and also gives special treatment to volume segments so as to avoid errors in visibility at the intersections between volume segments and geometric data. The other algorithms employ adaptive termination of ray‐tracing, elimination of rays that do not intersect the volume, and adaptive undersampling over an image plane. These improve the performance by three to seven times over the brute‐force approach. The cost and versatility of the algorithm are evaluated by using data from the results of 3D computational fluid dynamics.