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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Web-based Visualization and Analytics of Petascale Data: Equity as a Tide that Lifts All Boats

Scientists generate petabytes of data daily to help uncover environmental trends or behaviors that are hard to predict. For example, understanding climate simulations based on the long-term average of temperature, precipitation, and other environmental variables is essential to predicting and establishing root causes of future undesirable scenarios and assessing possible mitigation strategies. While supercomputer centers provide a powerful infrastructure for generating petabytes of simulation output, accessing and analyzing these datasets interactively remains challenging on multiple fronts. This paper presents an approach to managing, visualizing, and analyzing petabytes of data within a browser on equipment ranging from the top NASA supercomputer to commodity hardware like a laptop. Our novel data fabric abstraction layer allows user-friendly querying of scientific information while hid-ing the complexities of dealing with file systems or cloud services.We also optimize network utilization while streaming from petas-cale repositories through state-of-the-art progressive compression algorithms. Based on this abstraction, we provide customizable dashboards that can be accessed from any device with any inter-net connection, enabling interactive visual analysis of vast amounts of data to a wide range of users - from top scientists with access to leadership-class computing environments to undergraduate students of disadvantaged backgrounds from minority-serving institutions. We focus on NASA’s use of petascale climate datasets as an example of particular societal impact and, therefore, a case where achieving equity in science participation is critical. We validate our approach by improving the ability of climate scientists to visually explore their data via two fully interactive dashboards. We further validate our approach by deploying the dashboards and simplified training materials in the classroom at a minority-serving institution.These dashboards, released in simplified form to the general public, contribute significantly to a broader push to democratize the access and use of climate data.

Data visualization↗
NASA NTRSDate not supplied

DEVELOPING AN EARTH-FIXED VISUAL REFERENCE TO AID STABILITY, READAPTATION, AND EGRESS AFTER A WATER LANDING

Water landings present the worst possible sensory conditions for crews trying to orient and stabilize themselves immediately after long-duration spaceflight. Of the three sensory feedback systems involved in maintaining stability (i.e., proprioceptive, vestibular, and visual), none will provide reliable orientation information under the current water landing scenarios. Although the visual system is likely not affected by the disuse and adaptation to microgravity that affect the proprioceptive and vestibular systems, the visual environment within an enclosed space that is subject to wave-induced rocking will prevent the crewmember from using vision to determine which direction is up. This is true whether enclosed in the capsule or in a room on the recovery ship. The result is an increased risk of fall-related injury. In a prior study, 70% (21 of 30) of nonimpaired subjects reported that the presence of an Earth-fixed horizontal line helped them stabilize when their visually enclosed environment was exposed to wave motion. In addition to aiding stability, an Earth-fixed visual reference also can assist in the readaptation process. Sensory re-adaptation occurs when the three sensory systems are synchronized with one another and aligned with Earth’s gravity. The earlier an Earth-fixed visual reference can be introduced the sooner the readaptation process can begin. The goal of this project is to identify the optimal features of a device that visually presents gravitational reference cues to support egress, stability and readaptation. **Remainder of abstract in document preview or downloadable version

B. T. Peters↗
NASA NTRS1994

Computational Approaches to Vestibular Research

The Biocomputation Center at NASA Ames Research Center is dedicated to a union between computational, experimental and theoretical approaches to the study of neuroscience and of life sciences in general. The current emphasis is on computer reconstruction and visualization of vestibular macular architecture in three-dimensions (3-D), and on mathematical modeling and computer simulation of neural activity in the functioning system. Our methods are being used to interpret the influence of spaceflight on mammalian vestibular maculas in a model system, that of the adult Sprague-Dawley rat. More than twenty 3-D reconstructions of type I and type II hair cells and their afferents have been completed by digitization of contours traced from serial sections photographed in a transmission electron microscope. This labor-intensive method has now been replace d by a semiautomated method developed in the Biocomputation Center in which conventional photography is eliminated. All viewing, storage and manipulation of original data is done using Silicon Graphics workstations. Recent improvements to the software include a new mesh generation method for connecting contours. This method will permit the investigator to describe any surface, regardless of complexity, including highly branched structures such as are routinely found in neurons. This same mesh can be used for 3-D, finite volume simulation of synapse activation and voltage spread on neuronal surfaces visualized via the reconstruction process. These simulations help the investigator interpret the relationship between neuroarchitecture and physiology, and are of assistance in determining which experiments will best test theoretical interpretations. Data are also used to develop abstract, 3-D models that dynamically display neuronal activity ongoing in the system. Finally, the same data can be used to visualize the neural tissue in a virtual environment. Our exhibit will depict capabilities of our computational approaches and some of our findings from their application. For example, our research has demonstrated that maculas of adult mammals retain the property of synaptic plasticity. Ribbon synapses increase numerically and undergo changes in type and distribution (p<0.0001) in type II hair cells after exposure to microgravity for as few as nine days. The finding of macular synaptic plasticity is pertinent to the clinic, and may help explain some. balance disorders in humans. The software used in our investigations will be demonstrated for those interested in applying it in their own research.

Ross, Muriel D.↗
DOE OSTI2025

Single-molecule live-cell RNA imaging with CRISPR–Csm

Abstract Understanding the diverse dynamic behaviors of individual RNA molecules in single cells requires visualizing them at high resolution in real time. However, single-molecule live-cell imaging of unmodified endogenous RNA has not yet been achieved in a generalizable manner. Here, we present single-molecule live-cell fluorescence in situ hybridization (smLiveFISH), a robust approach that combines the programmable RNA-guided, RNA-targeting CRISPR–Csm complex with multiplexed guide RNAs for direct and efficient visualization of single RNA molecules in a range of cell types, including primary cells. Using smLiveFISH, we track individual nativeNOTCH2andMAP1Btranscripts in living cells and identify two distinct localization mechanisms including the cotranslational translocation ofNOTCH2mRNA at the endoplasmic reticulum and directional transport ofMAP1BmRNA toward the cell periphery. This method has the potential to unlock principles governing the spatiotemporal organization of native transcripts in health and disease.

Biotechnology & Applied Microbiology↗
NASA NTRS1983

What does the eye see best?

The quantum efficiency of the human eye is measured for detecting a wide variety of spatiotemporal patterns using foveal vision in bright light. The performance of an ideal visual detector whose weighting function is matched to the signal is analyzed in the abstract, and the conditions of a two-interval forced-choice experiment are described. The best stimulus found is a small, briefly exposed circular patch of sinusoidal grating having a spatial frequency of about 7 c/deg, drifting at about 4 Hz. It is proposed that this is the weighting function of the most efficient human contrast detector. This function resembles the receptive field sensitivity profiles of many cortical neurons. The detectors resemble those derived from other recent experiments on both detection and discrimination and may account for a broad range of previous psychophysical results.

Watson, A. B.↗
DOE OSTI2026

Expanding Access to Science Participation: A FAIR Framework for Petascale Data Visualization and Analytics

The massive data generated by scientists daily serve as both a major catalyst for new discoveries and innovations, as well as a significant roadblock that restricts access to the data. Here, our paper introduces a new approach to removing Big Data barriers and democratizing access to petascale data for the broader scientific community. Our novel data fabric abstraction layer allows user-friendly querying of scientific information while hiding the complexities of dealing with file systems or cloud services. We enable FAIR (Findable, Accessible, Interoperable, and Reusable) access to datasets such as NASA’s petascale climate datasets. Our paper presents an approach to managing, visualizing, and analyzing petabytes of data within a browser on equipment ranging from the top NASA supercomputer to commodity hardware like a laptop. Our novel data fabric abstraction utilizes state-of-the art progressive compression algorithms and machine-learning insights to power scalable visualization dashboards for petascale data. The result provides users with the ability to identify extreme events or trends dynamically, expanding access to scientific data and further enabling discoveries. We validate our approach by improving the ability of climate scientists to visually explore their data via three fully interactive dashboards. We further validate our approach by deploying the dashboards and simplified training materials in the classroom at a minority-serving institution. These dashboards, released in simplified form to the general public, contribute significantly to a broader push to democratize the access and use of climate data.

Computer science↗
NASA NTRS1991

Analysis and representation of complex structures in separated flows

We discuss our recent work on extraction and visualization of topological information in separated fluid flow data sets. As with scene analysis, an abstract representation of a large data set can greatly facilitate the understanding of complex, high-level structures. When studying flow topology, such a representation can be produced by locating and characterizing critical points in the velocity field and generating the associated stream surfaces. In 3D flows, the surface topology serves as the starting point. The 2D tangential velocity field near the surface of the body is examined for critical points. The tangential velocity field is integrated out along the principal directions of certain classes of critical points to produce curves depicting the topology of the flow near the body. The points and curves are linked to form a skeleton representing the 2D vector field topology. This skeleton provides a basis for analyzing the 3D structures associated with the flow separation. The points along the separation curves in the skeleton are used to start tangent curve integrations. Integration origins are successively refined to produce stream surfaces. The map of the global topology is completed by generating those stream surfaces associated with 3D critical points.

Helman, James↗
NASA NTRS1995

Scientific Visualization and Computational Science: Natural Partners

Scientific visualization is developing rapidly, stimulated by computational science, which is gaining acceptance as a third alternative to theory and experiment. Computational science is based on numerical simulations of mathematical models derived from theory. But each individual simulation is like a hypothetical experiment; initial conditions are specified, and the result is a record of the observed conditions. Experiments can be simulated for situations that can not really be created or controlled. Results impossible to measure can be computed.. Even for observable values, computed samples are typically much denser. Numerical simulations also extend scientific exploration where the mathematics is analytically intractable. Numerical simulations are used to study phenomena from subatomic to intergalactic scales and from abstract mathematical structures to pragmatic engineering of everyday objects. But computational science methods would be almost useless without visualization. The obvious reason is that the huge amounts of data produced require the high bandwidth of the human visual system, and interactivity adds to the power. Visualization systems also provide a single context for all the activities involved from debugging the simulations, to exploring the data, to communicating the results. Most of the presentations today have their roots in image processing, where the fundamental task is: Given an image, extract information about the scene. Visualization has developed from computer graphics, and the inverse task: Given a scene description, make an image. Visualization extends the graphics paradigm by expanding the possible input. The goal is still to produce images; the difficulty is that the input is not a scene description displayable by standard graphics methods. Visualization techniques must either transform the data into a scene description or extend graphics techniques to display this odd input. Computational science is a fertile field for visualization research because the results vary so widely and include things that have no known appearance. The amount of data creates additional challenges for both hardware and software systems. Evaluations of visualization should ultimately reflect the insight gained into the scientific phenomena. So making good visualizations requires consideration of characteristics of the user and the purpose of the visualization. Knowledge about human perception and graphic design is also relevant. It is this breadth of knowledge that stimulates proposals for multidisciplinary visualization teams and intelligent visualization assistant software. Visualization is an immature field, but computational science is stimulating research on a broad front.

Uselton, Samuel P.↗
DOE OSTI2024

FatPlants: a comprehensive information system for lipid-related genes and metabolic pathways in plants

Abstract FatPlants, an open-access, web-based database, consolidates data, annotations, analysis results, and visualizations of lipid-related genes, proteins, and metabolic pathways in plants. Serving as a minable resource, FatPlants offers a user-friendly interface for facilitating studies into the regulation of plant lipid metabolism and supporting breeding efforts aimed at increasing crop oil content. This web resource, developed using data derived from our own research, curated from public resources, and gleaned from academic literature, comprises information on known fatty-acid-related proteins, genes, and pathways in multiple plants, with an emphasis on Glycine max, Arabidopsis thaliana, and Camelina sativa. Furthermore, the platform includes machine-learning based methods and navigation tools designed to aid in characterizing metabolic pathways and protein interactions. Comprehensive gene and protein information cards, a Basic Local Alignment Search Tool search function, similar structure search capacities from AphaFold, and ChatGPT-based query for protein information are additional features. Database URL: https://www.fatplants.net/

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1998

Automated Fluid Feature Extraction from Transient Simulations

In the past, feature extraction and identification were interesting concepts, but not required to understand the underlying physics of a steady flow field. This is because the results of the more traditional tools like iso-surfaces, cuts and streamlines were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of much interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one 'snap-shot' of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for co-processing environments like pV3). And methods must be developed to abstract the feature and display it in a manner that physically makes sense. The following is a list of the important physical phenomena found in transient (and steady-state) fluid flow: Shocks; Vortex ores; Regions of Recirculation; Boundary Layers; Wakes.

Haimes, Robert↗
NASA NTRS1999

Automated Fluid Feature Extraction from Transient Simulations

In the past, feature extraction and identification were interesting concepts, but not required to understand the underlying physics of a steady flow field. This is because the results of the more traditional tools like iso-surfaces, cuts and streamlines were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of much interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one "snap-shot" of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for co-processing environments like pV3). And methods must be developed to abstract the feature and display it in a manner that physically makes sense. The following is a list of the important physical phenomena found in transient (and steady-state) fluid flow: (1) Shocks, (2) Vortex cores, (3) Regions of recirculation, (4) Boundary layers, (5) Wakes. Three papers and an initial specification for the (The Fluid eXtraction tool kit) FX Programmer's guide were included. The papers, submitted to the AIAA Computational Fluid Dynamics Conference, are entitled : (1) Using Residence Time for the Extraction of Recirculation Regions, (2) Shock Detection from Computational Fluid Dynamics results and (3) On the Velocity Gradient Tensor and Fluid Feature Extraction.

Haimes, Robert↗
NASA NTRS2000

Automated Fluid Feature Extraction from Transient Simulations

In the past, feature extraction and identification were interesting concepts, but not required in understanding the physics of a steady flow field. This is because the results of the more traditional tools like iso-surfaces, cuts and streamlines, were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of a great deal of interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one 'snap-shot' of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for co-processing environments like pV3). And methods must be developed to abstract the feature and display it in a manner that physically makes sense.

Haimes, Robert↗
NASA NTRS2020

Automatic Feature Tracking on Small Bodies for Autonomous Approach

Abstract—The autonomous approach of a spacecraft to an asteroid or comet (a small body) relies heavily on visual feature tracking to aid in estimating relative trajectories and the properties of the small body. Feature tracking for small bodies brings several challenges, including changing lighting, poor visual texture, and a concentration of features in a small part of an image. Six existing, open-source algorithms for feature tracking were tested on a simulated dataset and compared to the ground truth in the path of features. The main finding is that none of the algorithms provide all of the desired characteristics of long feature tracks with low errors and few outliers. Instead, there is a trade-off between long feature tracks and low error. The feature-matching algorithms SIFT, and BRISK provide good error characteristics, but short feature tracks, whereas the optical flow algorithm KLT provides long feature tracks, but with many features of large error. Given the challenges in feature tracking, it is recommended to focus development on each component of a feature tracking system: detection, description, and outlier rejection.

Morrell, Benjamin J↗
DOE OSTI2025

Extremely Scalable Distributed Computation of Contour Trees via Pre-Simplification

Contour trees offer an abstract representation of the level set topology in scalar fields and are widely used in topological data analysis and visualization. However, applying contour trees to large-scale scientific datasets remains challenging due to scalability limitations. Recent developments in distributed hierarchical contour trees have addressed these challenges by enabling scalable computation across distributed systems. Building on these structures, advanced analytical tasks—such as volumetric branch decomposition and contour extraction—have been introduced to facilitate large-scale scientific analysis. Despite these advancements, such analytical tasks substantially increase memory usage, which hampers scalability. In this paper, we propose a pre-simplification strategy to significantly reduce the memory overhead associated with analytical tasks on distributed hierarchical contour trees. We demonstrate enhanced scalability through strong scaling experiments, constructing the largest known contour tree—comprising over half a trillion nodes with complex topology—in under 15 minutes on a dataset containing 550 billion elements.

Li, Mingzhe [University of Utah]↗
NASA NTRS2018

T-infinity: The Dependency Inversion Principle for Rapid and Sustainable Multidisciplinary Software Development

The CFD Vision 2030 Study recommends that, “NASA should develop and maintain an integrated simulation and software development infrastructure to enable rapid CFD technology maturation.... [S]oftware standards and interfaces must be emphasized and supported whenever possible, and open source models for noncritical technology components should be adopted.” The current paper presents an approach to an open source development architecture, named T-infinity, for accelerated research in CFD leveraging the Dependency Inversion Principle to realize plugins that communicate through collections of functions without exposing internal data structures. Steady state flow visualization, mesh adaptation, fluid-structure interaction, and overset domain capabilities are demonstrated through compositions of plugins via standardized abstract interfaces without the need for source code dependencies between disciplines. Plugins interact through abstract interfaces thereby avoiding N 2 direct code-to-code data structure coupling where N is the number of codes. This plugin architecture enhances sustainable development by controlling the interaction between components to limit software complexity growth. The use of T-infinity abstract interfaces enables multidisciplinary application developers to leverage legacy applications alongside newly-developed capabilities. While rein, a description of interface details is deferred until the are more thoroughly tested and can be closed to modification.

O'Connell, Matthew D.↗