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All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Easy, Scalable Subsetting of GEDI Point Clouds

The GEDI Subsetter, a Python tool developed for NASA’s Multi-mission Algorithm and Analysis Platform (MAAP), optimizes the accessibility and visualization of GEDI point clouds by enabling users to efficiently subset data in a convenient, scalable manner. Complex science data often requires users to learn new software skills and handle many large files. Handling and cleaning large data sets is tedious and error-prone. These challenges significantly impede analysis. One of the goals of NASA's MAAP is to provide a platform that lowers the barrier to conducting research and analysis at scale. When a group of MAAP users wanted to conduct above-ground biomass estimation using GEDI data, we found that their existing workflow for leveraging GEDI data suffered from the barriers mentioned above. Furthermore, their workflow did not scale easily beyond a small number of granules. We found that existing tools related to GEDI data retrieval and subsetting were too limiting, so the GEDI Subsetter was written to support MAAP users’ needs. Being able to run many subsetting jobs simultaneously in the MAAP, and parallelizing the code itself, has led to significant speed improvements in obtaining relevant data, reducing subsetting time from hours to minutes. MAAP users can now more quickly and easily obtain only the data relevant to their research, by choosing which GEDI collection they want to work with (L1A, L2A, L2B, or L4A), and how they want to subset it, by specifying an area of interest, a temporal range, and relevant attributes. This has significantly reduced the feedback loop for users, allowing them to much more quickly subset GEDI data and begin their analysis. Although the GEDI Subsetter originally targeted users of the MAAP, it is generalized such that it can also be used outside of the MAAP and includes a command-line interface for convenience. Furthermore, with minor modifications, it should be possible to use it with non-GEDI data as the general pattern should be applicable to other sparse/track-based sensors.

Charles Daniels↗
NASA NTRS2012

TRMM Precipitation Application Examples Using Data Services at NASA GES DISC

Data services to support precipitation applications are important for maximizing the NASA TRMM (Tropical Rainfall Measuring Mission) and the future GPM (Global Precipitation Mission) mission's societal benefits. TRMM Application examples using data services at the NASA GES DISC, including samples from users around the world will be presented in this poster. Precipitation applications often require near-real-time support. The GES DISC provides such support through: 1) Providing near-real-time precipitation products through TOVAS; 2) Maps of current conditions for monitoring precipitation and its anomaly around the world; 3) A user friendly tool (TOVAS) to analyze and visualize near-real-time and historical precipitation products; and 4) The GES DISC Hurricane Portal that provides near-real-time monitoring services for the Atlantic basin. Since the launch of TRMM, the GES DISC has developed data services to support precipitation applications around the world. In addition to the near-real-time services, other services include: 1) User friendly TRMM Online Visualization and Analysis System (TOVAS; URL: http://disc2.nascom.nasa.gov/Giovanni/tovas/); 2) Mirador (http://mirador.gsfc.nasa.gov/), a simplified interface for searching, browsing, and ordering Earth science data at GES DISC. Mirador is designed to be fast and easy to learn; 3) Data via OPeNDAP (http://disc.sci.gsfc.nasa.gov/services/opendap/). The OPeNDAP provides remote access to individual variables within datasets in a form usable by many tools, such as IDV, McIDAS-V, Panoply, Ferret and GrADS; and 4) The Open Geospatial Consortium (OGC) Web Map Service (WMS) (http://disc.sci.gsfc.nasa.gov/services/wxs_ogc.shtml). The WMS is an interface that allows the use of data and enables clients to build customized maps with data coming from a different network.

Liu, Zhong↗
NASA NTRS2000

The Use of HDTV Format and the Electronic Theater in Presenting Earth Science

In order to maximize the public's awareness of earth science observations, earth science data must be available in multiple media formats. This talk will focus on the use High Definition TV format in presenting earth science data, The Television (HDTV) networks are mandated to completely switch over from the current TV standard (NTSC) to HDTV in the next seven years. Museums are also beginning to use HDTV format in their displays. The Visualization Analysis Laboratory at Goddard Space Flight Center has been experimenting with the use of HDTV to present earth science data. The experimental package we have developed is called the Electronic Theater (e-theater). The e-theater is a mobile presentation system used for displaying and teaching groups about earth science and the delicate interdependence between the various earth systems. The e-theater takes advantage of a double-wide screen to show the audiences high resolution data displays. The unique architecture used in this exhibit allows several data sets to be displayed at one time, demonstrating the connections between different earth systems. The data animations are manipulated in real-time during the presentation and can be paused, moved forward, backward, looped, or zoomed into, to maximize the flexibility of the presentation. Because HDTV format is used within the e-theater, the materials generated for the e-theater are made available to the news media and museums.

Summey, Barbara↗
DOE OSTI2012

AKUNA – INTEGRATED TOOLSETS SUPPORTING ADVANCED SUBSURFACE FLOW AND TRANSPORT SIMULATIONS FOR ENVIRONMETAL MANAGEMENT

A next generation open source subsurface simulator and user environment for environmental management is being developed through a collaborative effort across Department of Energy National Laboratories. The flow and transport simulator, Amanzi, will be capable of modeling complex subsurface environments and processes using both unstructured and adaptive meshes at very fine spatial resolutions that require supercomputing-scale resources. The user environment, Akuna, provides users with a range of tools to manage environmental and simulator data sets, create models, manage and share simulation data, and visualize results. Underlying the user interface are core toolsets that provide algorithms for sensitivity analysis, parameter estimation, and uncertainty quantification. Akuna is open-source, cross platform software that is initially being demonstrated on the Hanford BC Cribs remediation site. In this paper, we describe the emerging capabilities of Akuna and illustrate how these are being applied to the BC Cribs site.

user interface, data management, uncertainty quant↗
NASA NTRS1991

A study of high alpha dynamics and flow visualization for a 2.5-percent model of the F-18 HARV undergoing wing rock

Free-to-roll experiments and flow visualization studies have been conducted for a 2.5-percent model of the F-18 undergoing unsteady wing rock oscillations. Data have been acquired in the form of roll angle time histories as well as video recordings and 35 mm photography of the forebody and leading edge extension vortices. The time histories were differentiated to produce angular velocity and angular acceleration. From this the roll moment as a function of time and/or roll angle could be estimated. A thorough analysis of the data has revealed a genuine wing-rock phenomenon. Off-surface flow visualization was used to identiify the forebody and LEX vortex core positions and their interaction in both static and dynamic configurations. A direct correlation between the dynamic data and visualized vortex activity during the wing-rock motion has been made.

Quast, Thomas↗
DOE OSTI2015

SU-E-T-255: Development of a Michigan Quality Assurance (MQA) Database for Clinical Machine Operations

Purpose: A unified database system was developed to allow accumulation, review and analysis of quality assurance (QA) data for measurement, treatment, imaging and simulation equipment in our department. Recording these data in a database allows a unified and structured approach to review and analysis of data gathered using commercial database tools. Methods: A clinical database was developed to track records of quality assurance operations on linear accelerators, a computed tomography (CT) scanner, high dose rate (HDR) afterloader and imaging systems such as on-board imaging (OBI) and Calypso in our department. The database was developed using Microsoft Access database and visual basic for applications (VBA) programming interface. Separate modules were written for accumulation, review and analysis of daily, monthly and annual QA data. All modules were designed to use structured query language (SQL) as the basis of data accumulation and review. The SQL strings are dynamically re-written at run time. The database also features embedded documentation, storage of documents produced during QA activities and the ability to annotate all data within the database. Tests are defined in a set of tables that define test type, specific value, and schedule. Results: Daily, Monthly and Annual QA data has been taken in parallel with established procedures to test MQA. The database has been used to aggregate data across machines to examine the consistency of machine parameters and operations within the clinic for several months. Conclusion: The MQA application has been developed as an interface to a commercially available SQL engine (JET 5.0) and a standard database back-end. The MQA system has been used for several months for routine data collection.. The system is robust, relatively simple to extend and can be migrated to a commercial SQL server.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Information-Theoretic Exploration of Multivariate Time-Varying Image Databases

Modern scientific simulations produce very large datasets, making interactive exploration of such data computationally prohibitive. An increasingly common data reduction technique is to store visualizations and other data extracts in a database. The Cinema project is one such approach, storing visualizations in an image database for post hoc exploration and interactive image-based analysis. This work focuses on developing efficient algorithms that can quantify various types of multivariate dependencies existing within multi-variable datasets. It applies specific mutual information measures for the quantification of salient regions from multivariate image data. Here, using such information measures, the opacity of the images is modulated so that the salient regions are automatically highlighted and the domain scientists can interactively explore the most relevant regions for scientific discovery.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

GeneLab: The NASA System Biology Platform for Space Omics Repository, Analysis and Visualization

NASA’s GeneLab includes an open-access repository of some 250+ omics datasets generated by biological experiments relevant to spaceflight including simulated cosmic radiation and microgravity. In order to maximize the intelligibility of these data, particularly for users with limited bioinformatics background, GeneLab has become a knowledgebase platform converting raw genetic and proteomic signatures found in flight samples into biological and physiological meanings. A large community of more than 100 scientists has rallied behind GeneLab and organized into four Analysis Working Groups (AWGs: Animal, Plant, Microbe, and Multi-Omics). Together, the AWGs have gained scientific recognition worldwide by establishing a consortium in charge of adopting new complex standards for data analysis workflows and omics sample processing in a rapidly evolving field. We will demonstrate the usage of the repository with smart search capability, an online controlled-access toolshed "Galaxy" to process user data with vetted standard workflows, a workspace for data sharing and a data submission portal with ontology control for better metadata curation. The GeneLab visualization portal will also be demonstrated, showing how anyone without formal training in bioinformatics can now browse the space biology omics data to discover new biology and potential solutions to improve life in space.

GeneLab↗
DOE OSTI2014

Visual Analytics for Power Grid Contingency Analysis

Contingency analysis is the process of employing different measures to model scenarios, analyze them, and then derive the best response to remove the threats. This application paper focuses on a class of contingency analysis problems found in the power grid management system. A power grid is a geographically distributed interconnected transmission network that transmits and delivers electricity from generators to end users. The power grid contingency analysis problem is increasingly important because of both the growing size of the underlying raw data that need to be analyzed and the urgency to deliver working solutions in an aggressive timeframe. Failure to do so may bring significant financial, economic, and security impacts to all parties involved and the society at large. The paper presents a scalable visual analytics pipeline that transforms about 100 million contingency scenarios to a manageable size and form for grid operators to examine different scenarios and come up with preventive or mitigation strategies to address the problems in a predictive and timely manner. Great attention is given to the computational scalability, information scalability, visual scalability, and display scalability issues surrounding the data analytics pipeline. Most of the large-scale computation requirements of our work are conducted on a Cray XMT multi-threaded parallel computer. The paper demonstrates a number of examples using western North American power grid models and data.

contingency analysis↗
NASA NTRS1993

Scientific Visualization Using the Flow Analysis Software Toolkit (FAST)

Over the past few years the Flow Analysis Software Toolkit (FAST) has matured into a useful tool for visualizing and analyzing scientific data on high-performance graphics workstations. Originally designed for visualizing the results of fluid dynamics research, FAST has demonstrated its flexibility by being used in several other areas of scientific research. These research areas include earth and space sciences, acid rain and ozone modelling, and automotive design, just to name a few. This paper describes the current status of FAST, including the basic concepts, architecture, existing functionality and features, and some of the known applications for which FAST is being used. A few of the applications, by both NASA and non-NASA agencies, are outlined in more detail. Described in the Outlines are the goals of each visualization project, the techniques or 'tricks' used lo produce the desired results, and custom modifications to FAST, if any, done to further enhance the analysis. Some of the future directions for FAST are also described.

Bancroft, Gordon V.↗
NASA NTRS2001

Analysis and visualization of single-trial event-related potentials

In this study, a linear decomposition technique, independent component analysis (ICA), is applied to single-trial multichannel EEG data from event-related potential (ERP) experiments. Spatial filters derived by ICA blindly separate the input data into a sum of temporally independent and spatially fixed components arising from distinct or overlapping brain or extra-brain sources. Both the data and their decomposition are displayed using a new visualization tool, the "ERP image," that can clearly characterize single-trial variations in the amplitudes and latencies of evoked responses, particularly when sorted by a relevant behavioral or physiological variable. These tools were used to analyze data from a visual selective attention experiment on 28 control subjects plus 22 neurological patients whose EEG records were heavily contaminated with blink and other eye-movement artifacts. Results show that ICA can separate artifactual, stimulus-locked, response-locked, and non-event-related background EEG activities into separate components, a taxonomy not obtained from conventional signal averaging approaches. This method allows: (1) removal of pervasive artifacts of all types from single-trial EEG records, (2) identification and segregation of stimulus- and response-locked EEG components, (3) examination of differences in single-trial responses, and (4) separation of temporally distinct but spatially overlapping EEG oscillatory activities with distinct relationships to task events. The proposed methods also allow the interaction between ERPs and the ongoing EEG to be investigated directly. We studied the between-subject component stability of ICA decomposition of single-trial EEG epochs by clustering components with similar scalp maps and activation power spectra. Components accounting for blinks, eye movements, temporal muscle activity, event-related potentials, and event-modulated alpha activities were largely replicated across subjects. Applying ICA and ERP image visualization to the analysis of sets of single trials from event-related EEG (or MEG) experiments can increase the information available from ERP (or ERF) data. Copyright 2001 Wiley-Liss, Inc.

Non-NASA Center↗
DOE OSTI2012

Meta Parallel Coordinates For Visualizing Features in Large, High-Dimensional, Time-Varying Data

Managing computational complexity and designing effective visual representations are two important challenges for the visualization of large, complex, high-dimensional datasets. Parallel coordinates are an effective technique for visualizing high- dimensional data, but do not scale well to very large datasets. The addition of the temporal dimension leads to more uncertainty due to clutter on screen. Consequently, this poses a significant challenge for visually finding trends and patterns that maximize insight about the underlying time-varying properties of the data. To address these problems, we present meta parallel coordinates, a parallel coordinates display that is guided by perceptually mo- tivated visual metrics. These metrics describe the visual structures typically found in parallel coordinates and thus aid the user’s analysis by providing meaningful views of the data. Since they are computed in screen space, our metrics are computationally more efficient than data-based metrics. Our choice of metrics is driven by the different analytical tasks that a user typically wants to perform with time-varying multivariate data. In particular, we have worked with domain scientists who performed simulations of bioremediation experiments, and use their data and results to demonstrate the usefulness of our approach

Dasgupta, Aritra↗
DOE OSTI2012

Akuna - Integrated Toolsets Supporting Advanced Subsurface Flow and Transport Simulations for Environmental Management

A next generation open source subsurface simulator and user environment for environmental management is being developed through a collaborative effort across Department of Energy National Laboratories. The flow and transport simulator, Amanzi, will be capable of modeling complex subsurface environments and processes using both unstructured and adaptive meshes at very fine spatial resolutions that require supercomputing-scale resources. The user environment, Akuna, provides users with a range of tools to manage environmental and simulator data sets, create models, manage and share simulation data, and visualize results. Underlying the user interface are core toolsets that provide algorithms for sensitivity analysis, parameter estimation, and uncertainty quantification. Akuna is open-source, cross platform software that is initially being demonstrated on the Hanford BC Cribs remediation site. In this paper, we describe the emerging capabilities of Akuna and illustrate how these are being applied to the BC Cribs site.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Enabling the democratization of the genomics revolution with a fully integrated web-based bioinformatics platform

Continued advancements in sequencing technologies have fueled the development of new sequencing applications and promise to flood current databases with raw data. A number of factors prevent the seamless and easy use of these data, including the breadth of project goals, the wide array of tools that individually perform fractions of any given analysis, the large number of associated software/hardware dependencies, and the detailed expertise required to perform these analyses. To address these issues, we have developed an intuitive web-based environment with a wide assortment of integrated and cutting-edge bioinformatics tools in pre-configured workflows. These workflows, coupled with the ease of use of the environment, provide even novice next-generation sequencing users with the ability to perform many complex analyses with only a few mouse clicks and, within the context of the same environment, to visualize and further interrogate their results. As a result, this bioinformatics platform is an initial attempt at Empowering the Development of Genomics Expertise (EDGE) in a wide range of applications for microbial research.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

BactoGeNIE: A large-scale comparative genome visualization for big displays

The volume of complete bacterial genome sequence data available to comparative genomics researchers is rapidly increasing. However, visualizations in comparative genomics--which aim to enable analysis tasks across collections of genomes--suffer from visual scalability issues. While large, multi-tiled and high-resolution displays have the potential to address scalability issues, new approaches are needed to take advantage of such environments, in order to enable the effective visual analysis of large genomics datasets. In this paper, we present Bacterial Gene Neighborhood Investigation Environment, or BactoGeNIE, a novel and visually scalable design for comparative gene neighborhood analysis on large display environments. We evaluate BactoGeNIE through a case study on close to 700 draft Escherichia coli genomes, and present lessons learned from our design process. In conclusion, BactoGeNIE accommodates comparative tasks over substantially larger collections of neighborhoods than existing tools and explicitly addresses visual scalability. Given current trends in data generation, scalable designs of this type may inform visualization design for large-scale comparative research problems in genomics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Scalable Volume Visualization for Big Scientific Data Modeled by Functional Approximation

Considering the challenges posed by the space and time complexities in handling extensive scientific volumetric data, various data representations have been developed for the analysis of large-scale scientific data. Multivariate functional approximation (MFA) is an innovative data model designed to tackle substantial challenges in scientific data analysis. It computes values and derivatives with high-order accuracy throughout the spatial domain, mitigating artifacts associated with zero- or first-order interpolation. However, the slow query time through MFA makes it less suitable for interactively visualizing a large MFA model. In this work, we develop the first scalable interactive volume visualization pipeline, MFA-DVV, for the MFA model encoded from large-scale datasets. Our method achieves low input latency through distributed architecture, and its performance can be further enhanced by utilizing a compressed MFA model while still maintaining a high-quality rendering result for scientific datasets. We conduct comprehensive experiments to show that MFA-DVV can decrease the input latency and achieve superior visualization results for big scientific data compared with existing approaches.

big scientific dataset↗
DOE OSTI2014

3D Imaging of Microbial Biofilms: Integration of Synchrotron Imaging and an Interactive Visualization Interface

Understanding the interactions of structured communities known as “biofilms” and other complex matrixes is possible through the X-ray micro tomography imaging of the biofilms. Feature detection and image processing for this type of data focuses on efficiently identifying and segmenting biofilms and bacteria in the datasets. The datasets are very large and often require manual interventions due to low contrast between objects and high noise levels. Thus new software is required for the effectual interpretation and analysis of the data. This work specifies the evolution and application of the ability to analyze and visualize high resolution X-ray micro tomography datasets.

Biofilm Viewer↗