Interactive scientific visualization of fluid flow

Examples of scientific visualization techniques used for the interactive exploration of very large data sets from supercomputer simulations of fluid flow are presented. Interactive rendering of images from simulations of grids of 2 million or more computational zones are required to drive high-end graphics workstations to their limits with 2-D data. The author presents one such image and discusses interactive steering of 2-D flow simulations, a phenomenon now possible with grids of half a million computational zones. He uses a simulation of compressible turbulence on a grid of 134 million computational zones to set the scale for discussing interactive 3-D visualization techniques. A concept for a gigapixel-per-second video wall, or gigawall, which could be built with present technology to meet the demands of interactive visualization of the data sets that will be produced by the next generation of supercomputers, is discussed     

智能可视化与可视分析

可视化与可视分析已成为众多领域中结合人类智能与机器智能协同理解、分析数据的常见手段。人工智能可以通过对大数据的学习分析提高数据质量,捕捉关键信息,并选取最有效的视觉呈现方式,从而使用户更快、更准确、更全面地从可视化中理解数据。利用人工智能方法,交互式可视化系统也能更好地学习用户习惯及用户意图,推荐符合用户需求的可视化形式、交互操作和数据特征,从而降低用户探索的学习及时间成本,提高交互分析的效率。人工智能方法在可视化中的应用受到了极大关注,产生了大量学术成果。本文从最新工作出发,探讨人工智能在可视化流程的关键步骤中的作用。包括如何智能地表示和管理数据、如何辅助用户快速创建和定制可视化、如何通过人工智能扩展交互手段及提高交互效率、如何借助人工智能辅助数据的交互分析等。具体而言,本文详细梳理每个步骤中需要完成的任务及解决思路,介绍相应的人工智能方法（如深度网络结构）,并以图表数据为例介绍智能可视化与可视分析的应用,最后讨论智能可视化方法的发展趋势,展望未来的研究方向及应用场景。     

A Time Model for Time-Varying Visualization

The analysis of unsteady phenomena is an important topic for scientific visualization. Several time-dependent visualization techniques exist, as well as solutions for dealing with the enormous size of time-varying data in interactive visualization. Many current visualization toolkits support displaying time-varying data sets. However, for the interactive exploration of time-varying data in scientific visualization, no common time model that describes the temporal properties which occur in the visualization process has been established. In this work, we propose a general time model which classifies the time frames of simulation phenomena and the connections between different time scales in the analysis process. This model is designed for intuitive interaction with time in visualization applications for the domain expert as well as for the developer of visualization tools. We demonstrate the benefits of our model by applying it to two use cases with different temporal properties.     

3DIVE: An Immersive Environment for Interactive Volume Data Exploration

This paper describes an immersive system,called 3DIVE,for interactive volume data visualization and exploration inside the CAVE virtual environment.Combining interactive volume rendering and virtual reality provides a netural immersive environment for volumetric data visualization.More advanced data exploration operations,such as object level data manipulation,simulation and analysis ,are supported in 3DIVE by several new techniques,In particular,volume primitives and texture regions ae used for the rendering,manipulation,and collision detection of volumetric objects;and the region-based rendering pipeline is integrated with 3D image filters to provide an image-based mechanism for interactive transfer function design.The system has been recently released as public domain software for CAVE/ImmersaDesk users,and is currently being actively used by various scientific and biomedical visualization projects.     

Scalar field visualization via extraction of symmetric structures

Identifying symmetry in scalar fields is a recent area of research in scientific visualization and computer graphics communities. Symmetry detection techniques based on abstract representations of the scalar field use only limited geometric information in their analysis. Hence they may not be suited for applications that study the geometric properties of the regions in the domain. On the other hand, methods that accumulate local evidence of symmetry through a voting procedure have been successfully used for detecting geometric symmetry in shapes. We extend such a technique to scalar fields and use it to detect geometrically symmetric regions in synthetic as well as real-world datasets. Identifying symmetry in the scalar field can significantly improve visualization and interactive exploration of the data. We demonstrate different applications of the symmetry detection method to scientific visualization: query-based exploration of scalar fields, linked selection in symmetric regions for interactive visualization, and classification of geometrically symmetric regions and its application to anomaly detection.     

Local Exact Particle Tracing on Unstructured Grids

For analyzing and interpreting results of flow simulations, particle tracing is a well established visualization method. In addition, it is a preliminary step for more advanced techniques such as line integral convolution. For interactive exploration of large data sets, a very efficient and reliable particle tracing method is needed. For wind channel experiments or flight simulations, large unstructured computational grids have become common practice. Traditional approachs, based on numerical integration methods of ordinary differential equations however fail to deliver sufficiently accurate path calculation at the speed required for interactive use. In this paper we extend the local exact approach of Nielson and Jung in such a way that it can be used for interactive particle tracing in large data sets of steady flow simulation experiments. This will be achieved by sophisticated preprocessing using additional memory. For further visual enhancement of the streamline we construct an implicitly defined smooth Bézier curve that is used for ray tracing. This allows us to visualize additional scalar values of the simulation as attributes to the trajectory and enables the display of high‐quality smooth curves without creating any visualization geometry and providing a good impression of the spatial situation at the same time. ACM CSS: I.3.3 Computer Graphics—Line and curve generation; I .3.7 Computer Graphics—Raytracing; G.1.2 Numerical Analysis—Spline and piecewise polynomial approximation     

Visual data mining in large geospatial point sets

Visual data-mining techniques have proven valuable in exploratory data analysis, and they have strong potential in the exploration of large databases. Detecting interesting local patterns in large data sets is a key research challenge. Particularly challenging today is finding and deploying efficient and scalable visualization strategies for exploring large geospatial data sets. One way is to share ideas from the statistics and machine-learning disciplines with ideas and methods from the information and geo-visualization disciplines. PixelMaps in the Waldo system demonstrates how data mining can be successfully integrated with interactive visualization. The increasing scale and complexity of data analysis problems require tighter integration of interactive geospatial data visualization with statistical data-mining algorithms.     

Temporally Dense Exploration of Moving and Deforming Shapes

We present our approach for the dense visualization and temporal exploration of moving and deforming shapes from scientific experiments and simulations. Our image space representation is created by convolving a noise texture along shape contours (akin to LIC). Beyond indicating spatial structure via luminosity, we additionally use colour to depict time or classes of shapes via automatically customized maps. This representation summarizes temporal evolution, and provides the basis for interactive user navigation in the spatial and temporal domain in combination with traditional renderings. Our efficient implementation supports the quick and progressive generation of our representation in parallel as well as adaptive temporal splits to reduce overlap. We discuss and demonstrate the utility of our approach using 2D and 3D scalar fields from experiments and simulations.     

State‐of‐the‐Art in GPU‐Based Large‐Scale Volume Visualization

This survey gives an overview of the current state of the art in GPU techniques for interactive large‐scale volume visualization. Modern techniques in this field have brought about a sea change in how interactive visualization and analysis of giga‐, tera‐ and petabytes of volume data can be enabled on GPUs. In addition to combining the parallel processing power of GPUs with out‐of‐core methods and data streaming, a major enabler for interactivity is making both the computational and the visualization effort proportional to the amount and resolution of data that is actually visible on screen, i.e. ‘output‐sensitive’ algorithms and system designs. This leads to recent output‐sensitive approaches that are ‘ray‐guided’, ‘visualization‐driven’ or ‘display‐aware’. In this survey, we focus on these characteristics and propose a new categorization of GPU‐based large‐scale volume visualization techniques based on the notions of actual output‐resolution visibility and the current working set of volume bricks—the current subset of data that is minimally required to produce an output image of the desired display resolution. Furthermore, we discuss the differences and similarities of different rendering and data traversal strategies in volume rendering by putting them into a common context—the notion of address translation. For our purposes here, we view parallel (distributed) visualization using clusters as an orthogonal set of techniques that we do not discuss in detail but that can be used in conjunction with what we present in this survey.     

The city metaphor in software visualization: feelings,emotions, and thinking

Software visualization is a program comprehension technique used in the context of software maintenance, reverse engineering, and software evolution analysis. In the last decade, researchers have been exploring 3D representations for visualizing programs. Among these representations, one of the most popular is the city metaphor, which represents a target program as a city. Recently, this metaphor has been also implemented in interactive software visualization tools using Virtual Reality (VR) in an immersive 3D environment medium. We report the results of a study to assess the city metaphor implemented in a VR-based tool and in a 3D-based tool with respect to users’ feelings, emotions, and thinking. To this end, we contrasted these tools with a non-visual exploration tool (i.e., Eclipse). The main result of our study is: the use of the city metaphor implemented in a VR-based tool positively affects users’ feelings and emotions, while the thinking about this implementation is positive and comparable with that of a traditional 3D implementation of the city metaphor and it is slightly better than the thinking about a non-visual exploration tool (i.e., Eclipse).

     

Interactive Visualization with Programmable Graphics Hardware

One of the main scientific goals of visualization is the development of algorithms and appropriate data models which facilitate interactive visual analysis and direct manipulation of the increasingly large data sets which result from simulations running on massive parallel computer systems, from measurements employing fast high‐resolution sensors, or from large databases and hierarchical information spaces. This task can only be achieved with the optimization of all stages of the visualization pipeline: filtering, compression, and feature extraction of the raw data sets, adaptive visualization mappings which allow the users to choose between speed and accuracy, and exploiting new graphics hardware features for fast and high‐quality rendering. The recent introduction of advanced programmability in widely available graphics hardware has already led to impressive progress in the area of volume visualization. However, besides the acceleration of the final rendering, flexible graphics hardware is increasingly being used also for the mapping and filtering stages of the visualization pipeline, thus giving rise to new levels of interactivity in visualization applications. The talk will present recent results of applying programmable graphics hardware in various visualization algorithms covering volume data, flow data, terrains, NPR rendering, and distributed and remote applications.     

Network visualization for financial crime detection

Objective: We present a new software system, VisFAN, for the visual analysis of financial activity networks.MethodsWe combine enhanced graph drawing techniques to devise novel algorithms and interaction functionalities for the visual exploration of networked data sets, together with tools for SNA and for the automatic generation of reports.ResultsAn application example constructed on real data is presented. We also report the results of a study aimed at qualitatively understanding the satisfaction level of the analysts when using VisFAN.ConclusionVisFAN makes a strong use of visual interactive tools, combined with ad-hoc clustering techniques and customizable layout constraints management.ImplicationsAs this system confirms, information visualization can play a crucial role to face the discovery of financial crimes.     

Interactive multilevel focus+context visualization framework

In this article, we present the construction of an interactive multilevel focus+context visualization framework for the navigation and exploration of large-scale 2D and 3D images. The presented framework utilizes a balanced multiresolution technique supported by a balanced wavelet transform (BWT). It extends the mode of focus+context visualization, where spatially separate magnification of regions of interest (ROIs) is performed, as opposed to in-place magnification. Each resulting visualization scenario resembles a tree structure, where the root constitutes the main context, each non-root internal node plays the dual roles of both focus and context, and each leaf solely represents a focus. Our developed prototype supports interactive manipulation of the visualization hierarchy, such as addition and deletion of ROIs and desired changes in their resolutions at any level of the hierarchy on the fly. We describe the underlying data structure efficiently support such operations. Changes in the spatial locations of query windows defining the ROIs trigger on-demand reconstruction queries. We explain in detail how to efficiently process such reconstruction queries within the hierarchy of details (wavelet coefficients) contained in the BWT in order to ensure real-time feedback. As the BWT need only be constructed once in a preprocessing phase on the server-side and robust on-demand reconstruction queries require minimal data communication overhead, our presented framework is a suitable candidate for efficient web-based visualization of complex large-scale imagery. We also discuss the performance characteristics of our proposed framework from various aspects, such as time and space complexities and achieved frame rates.     

Interactive publication: The document as a research tool

The increasing prevalence of multimedia and research data generated by scientific work affords an opportunity to reformulate the idea of a scientific article from the traditional static document, or even one with links to supplemental material in remote databases, to a self-contained, multimedia-rich interactive publication. This paper describes our concept of such a document, and the design of tools for authoring (Forge) and visualization/analysis (Panorama). They are platform-independent applications written in Java, and developed in Eclipse¹ using its Rich Client Platform (RCP) framework. Both applications operate on PDF files with links to XML files that define the media type, location, and action to be performed. We also briefly cite the challenges posed by the potentially large size of interactive publications, the need for evaluating their value to improved comprehension and learning, and the need for their long-term preservation by the National Library of Medicine and other libraries.     

Interactive visual analysis of set-typed data

While it is quite typical to deal with attributes of different data types in the visualization of heterogeneous and multivariate datasets, most existing techniques still focus on the most usual data types such as numerical attributes or strings. In this paper we present a new approach to the interactive visual exploration and analysis of data that contains attributes which are of set type. A set-typed attribute of a data item--like one cell in a table--has a list of n > or = 0 elements as its value. We present the set'o'gram as a new visualization approach to represent data of set type and to enable interactive visual exploration and analysis. We also demonstrate how this approach is capable to help in dealing with datasets that have a larger number of dimensions (more than a dozen or more), especially also in the context of categorical data. To illustrate the effectiveness of our approach, we present the interactive visual analysis of a CRM dataset with data from a questionnaire on the education and shopping habits of about 90000 people.     

Extending interactive data language with higher-order functions

The interactive data language (IDL) is a dynamically typed array processing language widely used for the analysis of images and other scientific data. It operates in two basic modes. The first is a command line mode for interactive analysis and visualization of scientific data. The second is as a development platform for end-user applications which process scientific data. This paper details the introduction of higher-order functions to the core IDL. The purpose of these constructs is to increase the productivity of the interactive IDL user. Historically, interactive users of IDL have been scientists and engineers engaged in the exploration of new data. The addition of functional constructs aids these users by allowing them to accomplish, in a few lines of code, what might otherwise require writing a custom function which is then compiled and used. The constructs described were implemented as C language extensions to core IDL. The IDL extensions themselves are available for download at .     

Exploration of architectural spaces by blind people using auditory virtual reality for the construction of spatial knowledge

Navigation within a closed environment requires analysis of a variety of acoustic cues, a task that is well developed in many visually impaired individuals, and for which sighted individuals rely almost entirely on visual information. For blind people, the act of creating cognitive maps for spaces, such as home or office buildings, can be a long process, for which the individual may repeat various paths numerous times. While this action is typically performed by the individual on-site, it is of some interest to investigate at which point this task can be performed off-site, at the individual's discretion. In short, is it possible for an individual to learn an architectural environment without being physically present? If so, such a system could prove beneficial for navigation preparation in new and unknown environments. The main goal of the present research can therefore be summarized as investigating the possibilities of assisting blind individuals in learning a spatial environment configuration through the listening of audio events and their interactions with these events within a virtual reality experience. A comparison of two types of learning through auditory exploration has been performed: in situ real displacement and active navigation in a virtual architecture. The virtual navigation rendered only acoustic information. Results for two groups of five participants showed that interactive exploration of virtual acoustic room simulations can provide sufficient information for the construction of coherent spatial mental maps, although some variations were found between the two environments tested in the experiments. Furthermore, the mental representation of the virtually navigated environments preserved topological and metric properties, as was found through actual navigation.     

数值模拟并行程序的跟踪与可视化

采用并行计算的手段,数值模拟程序可以在高性能计算环境下获得数值求解加速,但在短时间内输出的大量、多块的计算结果,也为研究者的数据分析造成了困难。为此,本文介绍了一个针对并行计算程序的远程跟踪可视化系统,它适合运行于并行分布式计算环境,用户只需简单改造数值程序,即可通过远程终端对运行期的程序进行自动计算跟踪和交互可视化,而跟踪系统的优化设计则使数值程序的远程交互延迟得到有效控制。     

Volume-based large dynamic graph analysis supported by evolution provenance

We present an approach for the visualization and interactive analysis of dynamic graphs that contain a large number of time steps. A specific focus is put on the support of analyzing temporal aspects in the data. Central to our approach is a static, volumetric representation of the dynamic graph based on the concept of space-time cubes that we create by stacking the adjacency matrices of all time steps. The use of GPU-accelerated volume rendering techniques allows us to render this representation interactively. We identified four classes of analytics methods as being important for the analysis of large and complex graph data, which we discuss in detail: data views, aggregation and filtering, comparison, and evolution provenance. Implementations of the respective methods are presented in an integrated application, enabling interactive exploration and analysis of large graphs. We demonstrate the applicability, usefulness, and scalability of our approach by presenting two examples for analyzing dynamic graphs. Furthermore, we let visualization experts evaluate our analytics approach.

     

FI3D: direct-touch interaction for the exploration of 3D scientific visualization spaces

We present the design and evaluation of FI3D, a direct-touch data exploration technique for 3D visualization spaces. The exploration of three-dimensional data is core to many tasks and domains involving scientific visualizations. Thus, effective data navigation techniques are essential to enable comprehension, understanding, and analysis of the information space. While evidence exists that touch can provide higher-bandwidth input, somesthetic information that is valuable when interacting with virtual worlds, and awareness when working in collaboration, scientific data exploration in 3D poses unique challenges to the development of effective data manipulations. We present a technique that provides touch interaction with 3D scientific data spaces in 7 DOF. This interaction does not require the presence of dedicated objects to constrain the mapping, a design decision important for many scientific datasets such as particle simulations in astronomy or physics. We report on an evaluation that compares the technique to conventional mouse-based interaction. Our results show that touch interaction is competitive in interaction speed for translation and integrated interaction, is easy to learn and use, and is preferred for exploration and wayfinding tasks. To further explore the applicability of our basic technique for other types of scientific visualizations we present a second case study, adjusting the interaction to the illustrative visualization of fiber tracts of the brain and the manipulation of cutting planes in this context.