Density Displays for Data Stream Monitoring

In many business applications, large data workloads such as sales figures or process performance measures need to be monitored in real‐time. The data analysts want to catch problems in flight to reveal the root cause of anomalies. Immediate actions need to be taken before the problems become too expensive or consume too many resources. In the meantime, analysts need to have the “big picture” of what the information is about. In this paper, we derive and analyze two real‐time visualization techniques for managing density displays: (1) circular overlay d isplays which visualize large volumes of data without data shift movements after the display is full, thus freeing the analyst from adjusting the mental picture of the data after each data shift; and (2) variable resolution density displays which allow users to get the entire view without cluttering. We evaluate these techniques with respect to a number of evaluation measures, such as constancy of the display and usage of display space, and compare them to conventional d isplays with periodic shifts. Our real time data monitoring system also provides advanced interactions such as a local root cause analysis for further exploration. The applications using a number of real‐world data sets show the wide applicability and usefulness of our ideas.     

Visual Inspection of Multivariate Graphs

Most graph visualization techniques focus on the structure of graphs and do not offer support for dealing with node attributes and edge labels. To enable users to detect relations and patterns in terms of data associated with nodes and edges, we present a technique where this data plays a more central role. Nodes and edges are clustered based on associated data. Via direct manipulation users can interactively inspect and query the graph. Questions that can be answered include, “which edge types are activated by specific node attributes?” and, “how and from where can I reach specific types of nodes?” To validate our approach we contrast it with current practice. We also provide several examples where our method was used to study transition graphs that model real‐world systems.     

Calculation of phase equilibria for an alloy nanoparticle in contact with a solid nanowire

Phase equilibria in a system constituted of an alloy nanoparticle in contact with a solid nanowire have been modelled based on the minimization of a Gibbs free energy function. The Gibbs free energy consists of a bulk, surface and interface contribution. The bulk contribution is taken from CALPHAD thermodynamic databases and the surface properties from the literature. The effect of particle size and surface and interfacial properties on the liquidus line of the Au-Ge and In-Si systems has been studied. The results are compared to the bulk phase diagram and phase equilibria calculated for nano-systems with different geometries.     

Visualizing Waypoints‐Constrained Origin‐Destination Patterns for Massive Transportation Data

Origin‐destination (OD) pattern is a highly useful means for transportation research since it summarizes urban dynamics and human mobility. However, existing visual analytics are insufficient for certain OD analytical tasks needed in transport research. For example, transport researchers are interested in path‐related movements across congested roads, besides global patterns over the entire domain. Driven by this need, we propose waypoints‐constrained OD visual analytics, a new approach for exploring path‐related OD patterns in an urban transportation network. First, we use hashing‐based query to support interactive filtering of trajectories through user‐specified waypoints. Second, we elaborate a set of design principles and rules, and derive a novel unified visual representation called the waypoints‐constrained OD view by carefully considering the OD flow presentation, the temporal variation, spatial layout and user interaction. Finally, we demonstrate the effectiveness of our interface with two case studies and expert interviews with five transportation experts.     

BubbleNet: A Cyber Security Dashboard for Visualizing Patterns

The field of cyber security is faced with ever‐expanding amounts of data and a constant barrage of cyber attacks. Within this space, we have designed BubbleNet as a cyber security dashboard to help network analysts identify and summarize patterns within the data. This design study faced a range of interesting constraints from limited time with various expert users and working with users beyond the network analyst, such as network managers. To overcome these constraints, the design study employed a user‐centered design process and a variety of methods to incorporate user feedback throughout the design of BubbleNet. This approach resulted in a successfully evaluated dashboard with users and further deployments of these ideas in both research and operational environments. By explaining these methods and the process, it can benefit future visualization designers to help overcome similar challenges in cyber security or alternative domains.     

Using Visualization to Explore Original and Anonymized LBSN Data

We present GSUVis, a visualization tool designed to provide better understanding of location‐based social network (LBSN) data. LBSN data is one of the most important sources of information for transportation, marketing, health, and public safety. LBSN data consumers are interested in accessing and analysing data that is as complete and as accurate as possible. However, LBSN data contains sensitive information about individuals. Consequently, data anonymization is of critical importance if this data is to be made available to consumers. However, anonymization commonly reduces the utility of information available. Working with privacy experts, we designed GSUVis a visual analytic tool to help experts better understand the effects of anonymization techniques on LBSN data utility. One of GSUVis's primary goals is to make it possible for people to use LBSN data, without requiring them to gain deep knowledge about data anonymization. To inform the design of GSUVis, we interviewed privacy experts, and collected their tasks and system requirements. Based on this understanding, we designed and implemented GSUVis. It applies two anonymization algorithms for social and location trajectory data to a real‐world LBSN dataset and visualizes the data both before and after anonymization. Through feedback from domain experts, we reflect on the effectiveness of GSUVis and the impact of anonymization using visualization.     

An overview of the model integration process: From pre-integration assessment to testing

Integration of models requires linking models which can be developed using different tools, methodologies, and assumptions. We performed a literature review with the aim of improving our understanding of model integration process, and also presenting better strategies for building integrated modeling systems. We identified five different phases to characterize integration process: pre-integration assessment, preparation of models for integration, orchestration of models during simulation, data interoperability, and testing. Commonly, there is little reuse of existing frameworks beyond the development teams and not much sharing of science components across frameworks. We believe this must change to enable researchers and assessors to form complex workflows that leverage the current environmental science available. In this paper, we characterize the model integration process and compare integration practices of different groups. We highlight key strategies, features, standards, and practices that can be employed by developers to increase reuse and interoperability of science software components and systems.     

Visualising Errors in Animal Pedigree Genotype Data

Genetic analysis of a breeding animal population involves determining the inheritance pattern of genotypes for multiple genetic markers across the individuals in the population pedigree structure. However, experimental pedigree genotype data invariably contains errors in both the pedigree structure and in the associated individual genotypes, introducing inconsistencies into the dataset, rendering them useless for further analysis. The resolution of these errors requires consideration of genotype inheritance patterns in the context of the pedigree structure. Existing pedigree visualisations are typically more suited to human pedigrees and are less suitable for large complex animal pedigrees which may exhibit cross generational inbreeding. Similarly, table‐based viewers of genotype marker data can highlight where errors become apparent but lack the functionality and interactive visual feedback to allow users to locate the origin of errors within the pedigree. In this paper, we detail a design study steered by biologists who work with pedigree data, and describe successive iterations through approaches and prototypes for viewing genotyping errors in the context of a displayed pedigree. We describe how each approach performs with real pedigree genotype data and why eventually we deemed them unsuitable. Finally, a novel prototype visualisation for pedigrees, which we term the ‘sandwich view’, is detailed and we demonstrate how the approach effectively communicates errors in the pedigree context, supporting the biologist in the error identification task.     

3D Video Billboard Clouds

3D video billboard clouds reconstruct and represent a dynamic three-dimensional scene using displacement-mapped billboards. They consist of geometric proxy planes augmented with detailed displacement maps and combine the generality of geometry-based 3D video with the regularization properties of image-based 3D video. 3D video billboards are an image-based representation placed in the disparity space of the acquisition cameras and thus provide a regular sampling of the scene with a uniform error model. We propose a general geometry filtering framework which generates time-coherent models and removes reconstruction and quantization noise as well as calibration errors. This replaces the complex and time-consuming sub-pixel matching process in stereo reconstruction with a bilateral filter. Rendering is performed using a GPU-accelerated algorithm which generates consistent view-dependent geometry and textures for each individual frame. In addition, we present a semi-automatic approach for modeling dynamic three-dimensional scenes with a set of multiple 3D video billboards clouds.     

Dynamic Spar Elements and Discrete Element Methods in Two Dimensions for the Modeling of Soil-Inclusion Problems

Discrete element methods (DEMs) provide new numerical means to study the behavior of soil-inclusion systems. In some cases, however, the classic DEM fails to model specific aspects of the inclusions. That is why a model based on spar elements is introduced, designed specifically for inclusions. In this model, the movement of the inclusion is considered as a dynamic process and is computed step by step in the same way as in the DEM. The model can be coupled with a DEM code, thus enabling one to simulate the interaction between an inclusion and a disk assembly. Contact laws at the contacts between disks and spar elements describe the interface constitutive behavior. Finally, the results obtained by simulating a geosynthetic anchorage in two different ways are reported. In the first case the inclusion is represented by disks, while in the last case it is represented by spar elements. The comparison shows that spar elements are much more versatile and can simplify the calibration of the discrete models used to simulate soil-inclusion systems.