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Lexicon visualization Library and JavaScript for scientific data visualization

COMPUTING IN SCIENCE & ENGINEERING 2018年第1期20卷 50-65页

作者： Tanyalcin, Ibrahim Al Assaf, Carla Ferte, Julien Ancien, Francois Khan, Taushif Smits, Guillaume Rooman, Marianne Vranken, Wim VUB IB2 Brussels Belgium Katholieke Univ Leuven Essential Thrombocythemia Leuven Belgium ULB IB2 Brussels Belgium

It is becoming increasingly challenging to efficiently visualize and extract useful insight from complex and big datasets. JavaScript stands out as a suitable programming choice that offers mature libraries, easy implementation, and extensive customization, all of which stay in the shadow of new and rapid developments in the language. To illustrate the use of JavaScript in a scientific context, this article elaborates on Lexicon, a collection of JavaScript libraries for generating interactive visualizations in bioinformatics and other custom libraries.

关键词： Big data Bioinformatics data Visualisation Interactive Systems Java Custom Libraries Bioinformatics Interactive visualizations scientific Context Extensive Customization Big data Sets scientific data visualization Java Script Lexicon visualization Library Libraries data visualization Genomics Proteins Bioinformatics Big data visualization Computer Languages Java scientific Computing Java Script ES 6 Genetics Medicine data visualization Object Oriented Programming Bioinformatics ES 5

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Multiuser collaborative illustration and visualization for volumetric scientific data

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SOFTWARE-PRACTICE & EXPERIENCE 2021年第5期51卷 1080-1096页

作者： Liu, Richen Wen, Xiaodong Jiang, Meng Yang, Guang Zhang, Chuyu Chen, Xiaojian Nanjing Normal Univ Sch Comp & Elect Informat Sch Artificial Intelligence 1 Wenyuan Rd Nanjing 210023 Peoples R China

Multiuser can collaboratively complete complex visualization tasks that cannot be completed by a single user. Although multiuser collaboration system has made great progress, there are many challenges in the collaborative visualization of 3D volumetric scientific data due to the difficulties in multiuser collaboration, and collaborative slice analysis. This article proposes a client-server based collaborative visualization system, which consists of a 3D volume explorer and a 2D slice analyzer, to help domain experts to fully utilize their background domain knowledge to illustrate different parts of the data. For example, the brain surgeon expert, pulmonologist, and cardiologist can visualize and analyze the different subsets of the volumetric scientific data, that is, the corresponding subvolumes of the brain, heart, lungs, and blood vessels. It also allows taking full advantage of the hardware resources, because all the computation intensive tasks especially for the whole data rendering can be allocated to the powerful server while the light-weight tasks can be allocated to the portable clients. Besides, we design a seed point tracing algorithm based on flood fill algorithm to illustrate the slice more efficiently. We evaluate the system by collecting the feedback from domain experts and the people who are unfamiliar with data computation or visualization. The evaluation shows that the 3D volume explorer and the 2D slice analyzer are capable of supporting peer-expert discussion and medical case teaching, respectively.

关键词： collaborative visualization scientific data visualization visualization software

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Collaborative virtual reality platform for visualizing space data and mission planning

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MULTIMEDIA TOOLS AND APPLICATIONS 2019年第23期78卷 33191-33220页

作者： Garcia, Arturo S. Fernando, Terrence Roberts, David J. Bar, Christian Cencetti, Michele Engelke, Wito Gerndt, Andreas Univ Salford Salford M5 4WT Lancs England Univ Salford Telepresence Salford M5 4WT Lancs England Thales Alenia Space Turin Italy ALTEC Spa Permanent Multipurpose Module Int Space Stn Progr Turin Italy German Aerosp Ctr DLR Virtual Real & Sci Visualizat Grp Lilienthalpl 7 D-38108 Braunschweig Germany German Aerosp Ctr DLR Dept Software Space Syst & Interact Visualizat Lilienthalpl 7 D-38108 Braunschweig Germany

This paper presents the system architecture of a collaborative virtual environment in which distributed multidisciplinary teams involved in space exploration activities come together and explore areas of scientific interest of a planet for future missions. The aim is to reduce the current challenges of distributed scientific and engineering meetings that prevent the exploitation of their collaborative potential, as, at present, expertise, tools and datasets are fragmented. This paper investigates the functional characteristics of a software framework that addresses these challenges following the design science research methodology in the context of the space industry and research. An implementation of the proposed architecture and a validation process with end users, based on the execution of different use cases, are described. These use cases cover relevant aspects of real science analysis and operation, including planetary data visualization, as the system aims at being used in future European missions. This validation suggests that the system has the potential to enhance the way space scientists will conduct space science research in the future.

关键词： Distributed meetings Design science research methodology Collaborative virtual Environments Telepresence Space mission planning scientific data visualization

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The Development and Testing of a Digital ITER-Type Mock-Up Based on Virtual Reality Technology

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FUSION SCIENCE AND TECHNOLOGY 2021年第5期77卷 350-358页

作者： Li, Jin-Yang Gu, Long Xu, Hu-Shan Zhang, You-Peng Yao, Cun-Feng Fan, Da-Jun Wang, Guan Su, Xin-Kang Chinese Acad Sci Inst Modern Phys Lanzhou 730000 Peoples R China Adv Energy Sci & Technol Guangdong Lab Huizhou 516002 Peoples R China Univ Chinese Acad Sci Sch Nucl Sci & Technol Beijing 100049 Peoples R China Lanzhou Univ Sch Nucl Sci & Technol Lanzhou 730000 Peoples R China Fudan Univ Inst Modern Phys Shanghai 200433 Peoples R China

ITER is an experimental tokamak device that has many collaborators from different countries and aims to produce energy from nuclear fusion inside a reactor with magnetic confinement. Corresponding scientific data and structure visualization are important factors in connecting qualitative information from human intuition and quantitative content of physical-based datasets. Therefore, building an integrated platform with the interaction of scientific data visualization is inevitable for engineers and researchers in geographically distributed groups to effectively promote consistent design work, and it is also a key part in research and training processes for operators and students to better understand the ITER structure with analysis results. In this context, a digital ITER-type mock-up has been developed at the Institute of Modern Physics, Chinese Academy of Sciences based on an immersive virtual reality platform that is designed using client/server hybrid heterogeneous cloud architecture with many user-friendly and flexible features. Detailed ITER-type models have been developed and optimized in low-poly style to increase rendering speed, and scientific data in the scalar field have been represented by means of the view-dependent ray-casting method with topological texture images, which can fulfill real-time roaming and inspecting tasks for research purposes and provide an efficient and effective tool for fusion technology education at the University of Chinese Academy of Sciences.

关键词： Real time low-poly-style model rendering speed scientific data visualization immersive virtual reality

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Motivations, design, and preliminary testing for a 360° vision simulator

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VIRTUAL REALITY 2021年第1期25卷 247-255页

作者： Cook, Matt Grime, John Harvard Lib 1 Harvard Yard Cambridge MA 02138 USA Univ Oklahoma Lib 401 West Brooks St Norman OK 73019 USA

Contemporary virtual reality systems enable academics to more efficiently explore and analyze complex three-dimensional (3D) content, but their utility is limited by visual short-term memory. Janus, a geometry agnostic shader script, circumvents this cognitive limitation by automatically rendering complex object meshes to fit entirely within the field-of-view of consumer head-mounted displays. The resulting 360 degrees vision experience represents an advantage over existing scientific data visualization tools, which have sought to replicate real-world viewing experiences but have inadvertently replicated associated limitations as well. By presenting data in such a way so as to effectively circumvent cognitive loads associated with body (or object) movement, academics can use the Janus shader to more readily engage in the exploratory analysis of complex 3D data sets, thereby facilitating scientific insight. This paper explores the motivations and design of the Janus shader and describes preliminary results from user testing conducted under controlled conditions. For the 24 study participants (N = 24), statistically significant time-to-completion decreases were observed for spatial analysis tasks taking place in intervention (Janus-enabled) VR scenes of low-to-moderate complexity.

关键词： Virtual reality Cognitive load scientific data visualization Academic technologies

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visualization of randomly ordered numeric data sets using spherical self-organizing feature maps

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COMPUTERS & GRAPHICS-UK 2003年第6期27卷 963-976页

作者： Sangole, A Knopf, GK Univ Western Ontario Dept Mech & Mat Engn Fac Engn London ON N6A 5B9 Canada

scientific data visualization requires a variety of mathematical techniques to transform multivariate data sets into simple graphical objects, or glyphs, that provide scientists and engineers with a clearer understanding of the underlying system behaviour. The spherical self-organizing feature map (SOFM) described in this paper exploits an unsupervised clustering algorithm to map randomly organized N-dimensional data into a lower three-dimensional (3D) space for visual pattern analysis. Each node on the spherical lattice corresponds to a cluster of input vectors that lie in close spatial proximity within the original feature space, and neighbouring nodes on the lattice represent cluster centres with a high degree of vector similarity. Simple metrics are used to extract associations between the cluster units and the input vectors assigned to them. These are then graphically displayed on the spherical SOFM as either surface elevations or colourized facets. The resulting colourized graphical objects are displayed and manipulated within 3D immersive virtual reality (IVR) environments for interactive data analysis. The ability of the proposed algorithm to transform arbitrarily arranged numeric strings into unique, reproducible shapes is illustrated using chaotic data generated by the Lozi, Henon, Rossler, and Lorenz attractor functions under varying initial conditions. Implementation of the basic data visualization technique is further demonstrated using the more common Wisconsin breast cancer data and multispectral satellite data. (C) 2003 Elsevier Ltd. All rights reserved.

关键词： interactive data analysis scientific data visualization spherical self-organizing feature map feature clustering pattern recognition data mining

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Instrumenting and tuning dataView -: a networked application for navigating through large scientific datasets

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SOFTWARE-PRACTICE & EXPERIENCE 2002年第2期32卷 165-190页

作者： Slottow, J Shahriari, A Stein, M Chen, X Thomas, C Ender, PB Univ Calif Los Angeles Acad Technol Serv Los Angeles CA 90095 USA

dataView is an application that allows scientists to fly visually through large, regularly-gridded, time-varying 3D datasets from their desktop computers. dataView works with data that has been divided into cubes and sub-cubes (which we call 'tiles' and 'subtiles'), sampled at three levels of detail and written to a terabyte data server built on a PC cluster. dataView is a networked application. The dataView client component that runs on the scientist's computer is used only for user interaction and rendering. The selection of data subtiles for any given scene, and the geometry computation performed on those subtiles to create the virtual world, are performed by dataView components run in parallel on nodes of the PC cluster. This paper describes how we instrumented and tuned the code for improved performance in a networked environment. We report on how we measured network performance, first by inducing network delay and then by running the dataView client component in Washington DC and the compute components in Los Angeles. We report on the effect that the size, level of detail, and client CPU speed have on performance. We analyze what happens when the geometry computation is performed in parallel using MPI (Message Passing Interface) vs. in serial, and discuss the effect on performance of adding additional computational nodes. Copyright (C) 2001 John Wiley Sons, Ltd.

关键词： parallel visualization scientific data visualization virtual world tuning network performance cluster MPI master slave parallel code performance

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Domain-specific visualization system based on automatic multiseed recommendations: Extracting stratigraphic structures

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SOFTWARE-PRACTICE & EXPERIENCE 2020年第2期50卷 98-115页

作者： Liu, Richen Ji, Genlin Su, Mingjun Nanjing Normal Univ Sch Comp Sci & Technol 1Wenyuan Rd Nanjing 210023 Jiangsu Peoples R China PetroChina Res Inst Explorat & Dev Lanzhou Gansu Peoples R China

Underground flow path (UFP) is one of the most significant stratigraphic structures in revealing the distribution of oil or gas from seismic data. We design a domain-specific visualization system to extract the stratigraphic structures by seed point tracing and explore the seismic data by graph interactions. The seeds are automatically generated by kernel function-based density gradients computation. Users are allowed to adjust the recommended seeds by fine-tuning them with visual interactions. The seeds are further merged by a weighted quick-union algorithm to get the link information to construct a graph. Different types of nodes in the graph are designed to enable users to explore the extracted UFP structures intuitively. Finally, we evaluated the proposed approach by performance tests, sensitivity tests, and ground truth tests. The feedback from the domain experts demonstrates that the proposed visualization tool improved the capability of revealing the distribution and geostructures of UFPs compared with the existing methods.

关键词： domain-specific system scientific data visualization seismic visualization visualization tool

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Flexible formulation of value for experiment interpretation and design

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MATTER 2024年第2期7卷 P685-696页

作者： Carbone, Matthew R. Kim, Hyeong Jin Fernando, Chandima Yoo, Shinjae Olds, Daniel Joress, Howie DeCost, Brian Ravel, Bruce Zhang, Yugang Maffettone, Phillip M. Brookhaven Natl Lab Computat Sci Initiat Upton NY 11973 USA Ctr Funct Nanomat Brookhaven Natl Lab Upton NY 11973 USA Brookhaven Natl Lab Natl Synchroton Light Source 2 Upton NY 11973 USA Natl Inst Stand & Technol Mat Measurement Sci Div Gaithersburg MD 20899 USA

The challenge of optimal design of experiments pervades materials science, physics, chemistry, and biology. Bayesian optimization has been used to address this challenge but requires framing experimental campaigns through the lens of maximizing some observable. However, this framing is insufficient for epistemic research goals that seek to comprehensively analyze a sample space, without an explicit scalar objective. In this work, we propose a flexible formulation of scientific value that recasts a dataset of input conditions and higher -dimensional observable data into a continuous, scalar metric. Intuitively, the function measures where observables change significantly, emulating the perspective of experts driving an experiment. We demonstrate this as a collaborative analysis tool and objective for optimization technique using two simulated and two experimental examples. The method is flexible, easily deployed, seamlessly compatible with existing optimization tools, can be extended to multi -modal and multi -fidelity experiments, and can integrate existing models of an experimental system.

关键词： optimal experimental design Bayesian optimization scientific data visualization design of experiments autonomous experiments

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uPy: A Ubiquitous CG Python API with Biological-Modeling Applications

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IEEE COMPUTER GRAPHICS AND APPLICATIONS 2012年第5期32卷 50-61页

作者： Autin, Ludovic Johnson, Graham Hake, Johan Olson, Arthur Sanner, Michel Scripps Res Inst Mol Graph Lab La Jolla CA 92037 USA Univ Calif San Diego Dept Bioengn San Diego CA 92103 USA Scripps Res Inst Dept Mol Biol La Jolla CA 92037 USA

The uPy Python extension module provides a uniform abstraction of the APIs of several 3D computer graphics programs (called hosts), including Blender, Maya, Cinema 4D, and DejaVu. A plug-in written with uPy can run in all uPy-supported hosts. Using uPy, researchers have created complex plug-ins for molecular and cellular modeling and visualization. uPy can simplify programming for many types of projects (not solely science applications) intended for multihost distribution. It's available at http://***. The first featured Web extra is a video that shows interactive analysis of a calcium dynamics simulation. YouTube URL: http://***/wvs-nWE6ypo. The second featured Web extra is a video that shows rotation of the HIV virus. YouTube URL: http://***/vEOybMaRoKc.

关键词： 3D molecular visualization Adaptation models Biomedical image processing Blender Cinema 4D Computational modeling computer graphics data visualization Graphical user interfaces Maya Molecular biophysics Python scientific data visualization software plug-ins Three dimensional displays uPy

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