NOODLES: Introducing Collaborative Visualization in a Flavorful Package
In this talk, we introduce NOODLES, describe it's design, use cases, and how to get started with the protocol.
collaborative analysis↗
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The Art and Science of Statistical Visualization and Collaboration
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Peter A Parker↗
NOODLES Grid [SWR-25-93]
NOODLES Grid is a real-time visualization server for power system simulation data. It loads precomputed datasets, builds optimized instance renderings, and streams live interactive scenes to connected clients. It is built for high scalability, flexible visualization, and fast interaction. NOODLES is a cross-platform/device/tool protocol for collaborative visualization. NOODLES was Developed at the National Renewable Energy Laboratory (NREL) as a capability of the Insight Center https://www.nrel.gov/computational-science/insight-center.html
Brunhart-Lupo, Nicholas [National Renewable Energy↗
PowerSystemsData Specification [SWR-25-92]
This repository defines a standardized data format for representing power system datasets, with a focus on supporting time-series visualizations and 3D visualization tools. By providing a consistent and extensible structure, this format aims to streamline the development and interoperability of visualization codebases in the power systems domain. NOODLES is a cross-platform/device/tool protocol for collaborative visualization. NOODLES was Developed at the National Renewable Energy Laboratory (NREL) as a capability of the Insight Center https://www.nrel.gov/computational-science/insight-center.html
Brunhart-Lupo, Nicholas [National Renewable Energy↗
Data Communications Requirements for CAS Applications
This paper discusses the long-haul data communications requirements needed to support visualization of Computational Aeroscience (CAS) simulations. A scientific computing model is presented, from which current communications requirements are derived. This model is then expanded to describe the CAS Collaborative Visualization Environment, in which scientists from multiple NASA centers will collaborate on multidisciplinary, time-accurate simulations. An analysis of this model, along with data from the TFCC Workload Model, shows that CAS data communications requirements will increase to 10-100 megabytes/second by 1996.
McCabe, James D.↗
A Graph Based Interface for Representing Volume Visualization Results
This paper discusses a graph based user interface for representing the results of the volume visualization process. As images are rendered, they are connected to other images in a graph based on their rendering parameters. The user can take advantage of the information in this graph to understand how certain rendering parameter changes affect a dataset, making the visualization process more efficient. Because the graph contains more information than is contained in an unstructured history of images, the image graph is also helpful for collaborative visualization and animation.
Patten, James M.↗
The NAS Computational Aerosciences Archive
In order to further the state-of-the-art in computational aerosciences (CAS) technology, researchers must be able to gather and understand existing work in the field. One aspect of this information gathering is studying published work available in scientific journals and conference proceedings. However, current scientific publications are very limited in the type and amount of information that they can disseminate. Information is typically restricted to text, a few images, and a bibliography list. Additional information that might be useful to the researcher, such as additional visual results, referenced papers, and datasets, are not available. New forms of electronic publication, such as the World Wide Web (WWW), limit publication size only by available disk space and data transmission bandwidth, both of which are improving rapidly. The Numerical Aerodynamic Simulation (NAS) Systems Division at NASA Ames Research Center is in the process of creating an archive of CAS information on the WWW. This archive will be based on the large amount of information produced by researchers associated with the NAS facility. The archive will contain technical summaries and reports of research performed on NAS supercomputers, visual results (images, animations, visualization system scripts), datasets, and any other supporting meta-information. This information will be available via the WWW through the NAS homepage, located at http://www.nas.nasa.gov/, fully indexed for searching. The main components of the archive are technical summaries and reports, visual results, and datasets. Technical summaries are gathered every year by researchers who have been allotted resources on NAS supercomputers. These summaries, together with supporting visual results and references, are browsable by interested researchers. Referenced papers made available by researchers can be accessed through hypertext links. Technical reports are in-depth accounts of tools and applications research projects performed by NAS staff members and collaborators. Visual results, which may be available in the form of images, animations, and/or visualization scripts, are generated by researchers with respect to a certain research project, depicting dataset features that were determined important by the investigating researcher. For example, script files for visualization systems (e.g. FAST, PLOT3D, AVS) are provided to create visualizations on the user's local workstation to elucidate the key points of the numerical study. Users can then interact with the data starting where the investigator left off. Datasets are intended to give researchers an opportunity to understand previous work, 'mine' solutions for new information (for example, have you ever read a paper thinking "I wonder what the helicity density looks like?"), compare new techniques with older results, collaborate with remote colleagues, and perform validation. Supporting meta-information associated with the research projects is also important to provide additional context for research projects. This may include information such as the software used in the simulation (e.g. grid generators, flow solvers, visualization). In addition to serving the CAS research community, the information archive will also be helpful to students, visualization system developers and researchers, and management. Students (of any age) can use the data to study fluid dynamics, compare results from different flow solvers, learn about meshing techniques, etc., leading to better informed individuals. For these users it is particularly important that visualization be integrated into dataset archives. Visualization researchers can use dataset archives to test algorithms and techniques, leading to better visualization systems, Management can use the data to figure what is really going on behind the viewgraphs. All users will benefit from fast, easy, and convenient access to CFD datasets. The CAS information archive hopes to serve as a useful resource to those interested in computational sciences. At present, only information that may be distributed internationally is made available via the archive. Studies are underway to determine security requirements and solutions to make additional information available. By providing access to the archive via the WWW, the process of information gathering can be more productive and fruitful due to ease of access and ability to manage many different types of information. As the archive grows, additional resources from outside NAS will be added, providing a dynamic source of research results.
Miceli, Kristina D.↗
Scalable Adaptive Graphics Environment (SAGE) Software for the Visualization of Large Data Sets on a Video Wall
The use of collaborative scientific visualization systems for the analysis, visualization, and sharing of "big data" available from new high resolution remote sensing satellite sensors or four‐dimensional numerical model simulations is propelling the wider adoption of ultra‐resolution tiled display walls interconnected by high speed networks. These systems require a globally connected and well‐integrated operating environment that provides persistent visualization and collaboration services. This abstract and subsequent presentation describes a new collaborative visualization system installed for NASA's Shortterm Prediction Research and Transition (SPoRT) program at Marshall Space Flight Center and its use for Earth science applications. The system consists of a 3 x 4 array of 1920 x 1080 pixel thin bezel video monitors mounted on a wall in a scientific collaboration lab. The monitors are physically and virtually integrated into a 14' x 7' for video display. The display of scientific data on the video wall is controlled by a single Alienware Aurora PC with a 2nd Generation Intel Core 4.1 GHz processor, 32 GB memory, and an AMD Fire Pro W600 video card with 6 mini display port connections. Six mini display‐to‐dual DVI cables are used to connect the 12 individual video monitors. The open source Scalable Adaptive Graphics Environment (SAGE) windowing and media control framework, running on top of the Ubuntu 12 Linux operating system, allows several users to simultaneously control the display and storage of high resolution still and moving graphics in a variety of formats, on tiled display walls of any size. The Ubuntu operating system supports the open source Scalable Adaptive Graphics Environment (SAGE) software which provides a common environment, or framework, enabling its users to access, display and share a variety of data‐intensive information. This information can be digital‐cinema animations, high‐resolution images, high‐definition video‐teleconferences, presentation slides, documents, spreadsheets or laptop screens. SAGE is cross‐platform, community‐driven, open‐source visualization and collaboration middleware that utilizes shared national and international cyberinfrastructure for the advancement of scientific research and education.
Jedlovec, Gary↗
Rover Sequencing and Visualization Program
The Rover Sequencing and Visualization Program (RSVP) is the software tool for use in the Mars Exploration Rover (MER) mission for planning rover operations and generating command sequences for accomplishing those operations. RSVP combines three-dimensional (3D) visualization for immersive exploration of the operations area, stereoscopic image display for high-resolution examination of the downlinked imagery, and a sophisticated command-sequence editing tool for analysis and completion of the sequences. RSVP is linked with actual flight-code modules for operations rehearsal to provide feedback on the expected behavior of the rover prior to committing to a particular sequence. Playback tools allow for review of both rehearsed rover behavior and downlinked results of actual rover operations. These can be displayed simultaneously for comparison of rehearsed and actual activities for verification. The primary inputs to RSVP are downlink data products from the Operations Storage Server (OSS) and activity plans generated by the science team. The activity plans are high-level goals for the next day s activities. The downlink data products include imagery, terrain models, and telemetered engineering data on rover activities and state. The Rover Sequence Editor (RoSE) component of RSVP performs activity expansion to command sequences, command creation and editing with setting of command parameters, and viewing and management of rover resources. The HyperDrive component of RSVP performs 2D and 3D visualization of the rover s environment, graphical and animated review of rover-predicted and telemetered state, and creation and editing of command sequences related to mobility and Instrument Deployment Device (IDD) operations. Additionally, RoSE and HyperDrive together evaluate command sequences for potential violations of flight and safety rules. The products of RSVP include command sequences for uplink that are stored in the Distributed Object Manager (DOM) and predicted rover state histories stored in the OSS for comparison and validation of downlinked telemetry. The majority of components comprising RSVP utilize the MER command and activity dictionaries to automatically customize the system for MER activities. Thus, RSVP, being highly data driven, may be tailored to other missions with minimal effort. In addition, RSVP uses a distributed, message-passing architecture to allow multitasking, and collaborative visualization and sequence development by scattered team members.
Cooper, Brian↗
Ziti (Ziti Client) [SWR-25-91]
Ziti is a NOODLES client application for RealityKit-powered devices (specifically the Apple Vision Pro). NOODLES is a cross-platform/device/tool protocol for collaborative visualization. NOODLES was Developed at the National Renewable Energy Laboratory (NREL) as a capability of the Insight Center https://www.nrel.gov/computational-science/insight-center.html
Brunhart-Lupo, Nicholas [National Renewable Energy↗
Visualizing Progress
Reality Capture Technologies, Inc. is a spinoff company from Ames Research Center. Offering e-business solutions for optimizing management, design and production processes, RCT uses visual collaboration environments (VCEs) such as those used to prepare the Mars Pathfinder mission.The product, 4-D Reality Framework, allows multiple users from different locations to manage and share data. The insurance industry is one targeted commercial application for this technology.
Source record↗
Summary of ADTT Website Functionality and Features
This report summarizes development of the ADTT web-based design environment by the ELORET team in 2000. The Advanced Design Technology Testbed had been in development for several years, with demonstration applications restricted to aerodynamic analyses of subsonic aircraft. The key changes achieved this year were improvements in Web-based accessibility, evaluation of collaborative visualization, remote invocation of geometry updates and performance analysis, and application to aerospace system analysis. Significant effort was also devoted to post-processing of data, chiefly through comparison of similar data for alternative vehicle concepts. Such comparison is an essential requirement for designers to make informed choices between alternatives. The next section of this report provides more discussion of the goals for ADTT development. Section 3 provides screen shots from a sample session in the ADTT environment, including Login and navigation to the project of interest, data inspection, analysis execution and output evaluation. The following section provides discussion of implementation details and recommendations for future development of the software and information technologies that provide the key functionality of the ADTT system. Section 5 discusses the integration architecture for the system, which links machines running different operating systems and provides unified access to data stored in distributed locations. Security is a significant issue for this system, especially for remote access to NAS machines, so Section 6 discusses several architectural considerations with respect to security. Additional details of some aspects of ADTT development are included in Appendices.
Hawke, Veronica↗
Presentation Extensions of the SOAP
A set of extensions of the Satellite Orbit Analysis Program (SOAP) enables simultaneous and/or sequential presentation of information from multiple sources. SOAP is used in the aerospace community as a means of collaborative visualization and analysis of data on planned spacecraft missions. The following definitions of terms also describe the display modalities of SOAP as now extended: In SOAP terminology, View signifies an animated three-dimensional (3D) scene, two-dimensional still image, plot of numerical data, or any other visible display derived from a computational simulation or other data source; a) "Viewport" signifies a rectangular portion of a computer-display window containing a view; b) "Palette" signifies a collection of one or more viewports configured for simultaneous (split-screen) display in the same window; c) "Slide" signifies a palette with a beginning and ending time and an animation time step; and d) "Presentation" signifies a prescribed sequence of slides. For example, multiple 3D views from different locations can be crafted for simultaneous display and combined with numerical plots and other representations of data for both qualitative and quantitative analysis. The resulting sets of views can be temporally sequenced to convey visual impressions of a sequence of events for a planned mission.
Carnright, Robert↗
Training Astronauts using Hardware-in-the-Loop Simulations and Virtual Reality
The commercial market has recently started giving significant attention to virtual and augmented reality, even though the technology has been around for many years. The Virtual Reality Training Lab (VRL) at the NASA Johnson Space Center has been using virtual reality to train astronauts for decades. This paper will focus on describing three major Hardware-in-the-Loop VR simulation systems, the Simplified Aid for EVA Rescue (SAFER) system known as the "jetpack", the Mass Handling System nicknamed Charlotte, and a simulated robotics environment for collaborative mission evaluation. Two of these systems are critical for astronaut training. Crew must certify on SAFER and go through the Charlotte Mass Handling training prior to flying to the International Space Station (ISS). Typically, they also complete at least one collaborative visualization session to review any planned Extra Vehicular Activities (EVAs), or spacewalks, before an assigned flight. Given the volatility of new technologies, the graphics and simulation environments used are maintained to be hardware agnostic to preserve a high level of fidelity. Utilizing VR for astronaut training has proved to be effective and essential for these specific systems.
Angelica D. Garcia↗
MBSE (SysML) and Digital Twin Integration to Support Engineering Analysis & Design
Problem Statement: The complexity of Gateway systems and of managing the integrated safety analysis have made traditional methods of engineering analysis and design increasingly challenging. To address these challenges, a prototype that integrate Model-Based Systems Engineering (MBSE) with Digital Twin technology has been developed to demonstrate the utilities and functions. Project Goal: Develop a prototype of a Digital Twin Of Gateway ECLSS IMV system to enhance fault management analysis through collaboration, visualization, and simulation. Overall Project Results / Accomplishments: - Developed extension to streamline the integration of SysML models with the Digital Twin platform - Demonstrated the capability to aggregate any relevant information and provide simulation integration within the DT prototype. - Generated digital twin simulation using SysML Activity Diagrams - Implemented a complex trade study use case based on the integrated SysML-Digital Twin infrastructure
MBSE↗
Remote Visualization and Remote Collaboration On Computational Fluid Dynamics
A new technology has been developed for remote visualization that provides remote, 3D, high resolution, dynamic, interactive viewing of scientific data (such as fluid dynamics simulations or measurements). Based on this technology, some World Wide Web sites on the Internet are providing fluid dynamics data for educational or testing purposes. This technology is also being used for remote collaboration in joint university, industry, and NASA projects in computational fluid dynamics and wind tunnel testing. Previously, remote visualization of dynamic data was done using video format (transmitting pixel information) such as video conferencing or MPEG movies on the Internet. The concept for this new technology is to send the raw data (e.g., grids, vectors, and scalars) along with viewing scripts over the Internet and have the pixels generated by a visualization tool running on the viewer's local workstation. The visualization tool that is currently used is FAST (Flow Analysis Software Toolkit).
Watson, Val↗
An open-source data storage and visualization platform for collaborative qubit control
Developing collaborative research platforms for quantum bit control is crucial for driving innovation in the field, as they enable the exchange of ideas, data, and implementation to achieve more impactful outcomes. Furthermore, considering the high costs associated with quantum experimental setups, collaborative environments are vital for maximizing resource utilization efficiently. However, the lack of dedicated data management platforms presents a significant obstacle to progress, highlighting the necessity for essential assistive tools tailored for this purpose. Current qubit control systems are unable to handle complicated management of extensive calibration data and do not support effectively visualizing intricate quantum experiment outcomes. In this paper, we introduce Qubit Control Storage and Visualization ( QubiCSV ), a platform specifically designed to meet the demands of quantum computing research, focusing on the storage and analysis of calibration and characterization data in qubit control systems. As an open-source tool, QubiCSV facilitates efficient data management of quantum computing, providing data versioning capabilities for data storage and allowing researchers and programmers to interact with qubits in real time. The insightful visualization are developed to interpret complex quantum experiments and optimize qubit performance. QubiCSV not only streamlines the handling of qubit control system data but also improves the user experience with intuitive visualization features, making it a valuable asset for researchers in the quantum computing domain.
97 MATHEMATICS AND COMPUTING↗
Collaborative: in situ visual analytics technologies for extreme scale combustion simulations
This project aims to drastically enhance the usability of in situ analysis and visualization for extreme-scale scientific simulations. Current exascale computing capabilities promise to offer greater predictive ability of simulations and to further push the frontiers of science and technology. However, to validate the simulation output at extreme scale, examine the modeled phenomena, and discover previously unknowns from the output data, the output must be reduced or transformed in situ as it is being generated during the simulation such that the amount of data to examine and store is kept to a minimum. Such in situ approaches allow us to process and analyze the data and any embedded geometry to an extent that would be prohibitively expensive, if not impossible, to perform as a post hoc task. While in situ processing has been demonstrated to be a feasible and promising approach, its full potential has not yet been leveraged. In this project, we have developed comprehensive enhancements to in situ technology based on probability distributions in data. Our research focuses on jointly developing new ways of interacting with massive statistical samples while creatively utilizing new state-of-the-art computational resources to push the boundaries of in situ exploration. Moreover, we have developed new time-dependent techniques to enable previously unattainable capabilities in areas such as intelligent simulation steering and precise feature identification. We have experimentally studied our design and implementation at NERSC and OLCF, and are able to leverage existing in situ infrastructures whenever possible. While the exemplar in this project is combustion, many other fields for which turbulent transport is important, e.g., fusion, climate, astrophysics among others, encounter similar issues as simulations scale up to the exascale. This project shows its potential to generate high impact on DOE missions since the resulting technology promises to improve scientists’ ability to rapidly and correctly interpret and tune extreme-scale simulations, leading to new scientific understanding and advancements.
97 MATHEMATICS AND COMPUTING↗