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All sources NASA NTRS DOE OSTI

NASA NTRS2007

Accident/Mishap Investigation System

InvestigationOrganizer (IO) is a Web-based collaborative information system that integrates the generic functionality of a database, a document repository, a semantic hypermedia browser, and a rule-based inference system with specialized modeling and visualization functionality to support accident/mishap investigation teams. This accessible, online structure is designed to support investigators by allowing them to make explicit, shared, and meaningful links among evidence, causal models, findings, and recommendations.

Keller, Richard↗

NASA NTRS2013

Real-Time Multimission Event Notification System for Mars Relay

As the Mars Relay Network is in constant flux (missions and teams going through their daily workflow), it is imperative that users are aware of such state changes. For example, a change by an orbiter team can affect operations on a lander team. This software provides an ambient view of the real-time status of the Mars network. The Mars Relay Operations Service (MaROS) comprises a number of tools to coordinate, plan, and visualize various aspects of the Mars Relay Network. As part of MaROS, a feature set was developed that operates on several levels of the software architecture. These levels include a Web-based user interface, a back-end "ReSTlet" built in Java, and databases that store the data as it is received from the network. The result is a real-time event notification and management system, so mission teams can track and act upon events on a moment-by-moment basis. This software retrieves events from MaROS and displays them to the end user. Updates happen in real time, i.e., messages are pushed to the user while logged into the system, and queued when the user is not online for later viewing. The software does not do away with the email notifications, but augments them with in-line notifications. Further, this software expands the events that can generate a notification, and allows user-generated notifications. Existing software sends a smaller subset of mission-generated notifications via email. A common complaint of users was that the system-generated e-mails often "get lost" with other e-mail that comes in. This software allows for an expanded set (including user-generated) of notifications displayed in-line of the program. By separating notifications, this can improve a user's workflow.

Wallick, Michael N.↗

NASA NTRSDate not supplied

Langley Automated Sensor Inter-calibration System (LASICS): Open Access Tools for Satellite Imager Inter-Calibration

Satellite imager calibration teams are tasked with maintaining stable measurement records to facilitate reliable monitoring of geophysical parameters and ensure dependable input for weather forecast models. Satellite imagers are neither uniformly calibrated nor radiometrically scaled to a common reference. Consistent inter-calibration between various earth-orbiting satellite imager pairs is a critical step in the creation of seamless earth-scene reflectance data records over time for input to higher level algorithms that retrieve earth system climate-sensitive properties. Each imager inherently by virtue of its optics (and associated properties like Spectral Response etc.) will have a unique measurement of the same earth-scene reflected signal. A key part of this is the identification and prediction of events where the imager pairs from their respective earth-orbits view the same stable terrestrial targets with nearly identical viewing and solar geometry. Langley Automated Sensor Inter-calibration System (LASICS) will provide the Earth remote sensing community with a foundation for the harmonization of these remote sensing records by the development of an intuitive, user-friendly, interactive web-based open access service that will leverage, an existing extensive and ever-growing database of earth-imager channel spectral response functions, on-demand capabilities for computation and visualization of spectral band adjustment factors using a variety of external hyper-spectral earth observation sources (e.g. SCIAMACHY, GOME-2 for VIS and IASI, AIRS for IR) and a variety of Solar Irradiance Spectra.

Arun Gopalan↗

NASA NTRS2005

Advanced Weather Awareness and Reporting Enhancements

AWARE (Aviation Weather Awareness and Reporting Enhancements) was a NASA Cooperative Research and Development program conducted jointly by Rockwell Scientific, Rockwell Collins, and NASA. The effort culminated in an enhanced weather briefing and reporting tool prototype designed to integrate graphical and text-based aviation weather data to provide clear situational awareness in the context of a specific pilot, flight and equipment profile. The initial implementation of AWARE was as a web-based preflight planning tool, specifically for general aviation pilots, who do not have access to support such as the dispatchers available for commercial airlines. Initial usability tests showed that for VFR (Visual Flight Rules) pilots, AWARE provided faster and more effective weather evaluation. In a subsequent formal usability test for IFR (Instrument Flight Rules) pilots, all users finished the AWARE tests faster than the parallel DUAT tests, and all subjects graded AWARE higher for effectiveness, efficiency, and usability. The decision analysis basis of AWARE differentiates it from other aviation safety programs, providing analysis of context-sensitive data in a personalized graphical format to aid pilots/dispatchers in their complex flight requirements.

Busquets, Anthony M.↗

NASA NTRS2006

Integrated Modeling Environment

The Integrated Modeling Environment (IME) is a software system that establishes a centralized Web-based interface for integrating people (who may be geographically dispersed), processes, and data involved in a common engineering project. The IME includes software tools for life-cycle management, configuration management, visualization, and collaboration.

Mosier, Gary↗

DOE OSTI2022

RCSB Protein Data bank: Tools for visualizing and understanding biological macromolecules in 3D

Abstract Now in its 52nd year of continuous operations, the Protein Data Bank (PDB) is the premiere open‐access global archive housing three‐dimensional (3D) biomolecular structure data. It is jointly managed by the Worldwide Protein Data Bank (wwPDB) partnership. The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) is funded by the National Science Foundation, National Institutes of Health, and US Department of Energy and serves as the US data center for the wwPDB. RCSB PDB is also responsible for the security of PDB data in its role as wwPDB‐designated Archive Keeper. Every year, RCSB PDB serves tens of thousands of depositors of 3D macromolecular structure data (coming from macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro‐electron diffraction). The RCSB PDB research‐focused web portal ( RCSB.org ) makes PDB data available at no charge and without usage restrictions to many millions of PDB data consumers around the world. The RCSB PDB training, outreach, and education web portal ( PDB101.RCSB.org ) serves nearly 700 K educators, students, and members of the public worldwide. This invited Tools Issue contribution describes how RCSB PDB (i) is organized; (ii) works with wwPDB partners to process new depositions; (iii) serves as the wwPDB‐designated Archive Keeper; (iv) enables exploration and 3D visualization of PDB data via RCSB.org ; and (v) supports training, outreach, and education via PDB101.RCSB.org . New tools and features at RCSB.org are presented using examples drawn from high‐resolution structural studies of proteins relevant to treatment of human cancers by targeting immune checkpoints.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Noodles: Cooking Up Collaborative Visualization

NOODLES is a new cross-domain collaborative visualization and analysis capability being developed at NREL. The NOODLES specification is a minimal protocol that can tie different software packages and platforms together. As an example, a simulation code that speaks this protocol could stream iso-surfaces to an immersive VR space and a web browser. Another example is a team (with some members across the country) classifying and discovering features in a statistical data plot, driven from a researcher's existing Python-based workflow. In this talk, we will discuss some background on the problems that this protocol intends to solve, basic principles of the specification, the current state of supporting libraries, and some demonstrations of the protocol in action.

3D↗

DOE OSTI2016

MSAViewer: interactive JavaScript visualization of multiple sequence alignments

The MSAViewer is a quick and easy visualization and analysis JavaScript component for Multiple Sequence Alignment data of any size. Core features include interactive navigation through the alignment, application of popular color schemes, sorting, selecting and filtering. The MSAViewer is ‘web ready’: written entirely in JavaScript, compatible with modern web browsers and does not require any specialized software. The MSAViewer is part of the BioJS collection of components.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2014

MO-E-18C-06: Enriching Medical Physics Education By Visualizing The Invisible

Purpose: To enhance the understanding of medical physics concepts and develop higher levels of learning relating to invisible physics phenomena such as radiation. To provide medical physics educators in all countries of the world with understanding of knowledge structures in the human brain, the different levels of learning, and the types of knowledge required for higher level functions such as problem solving, creative innovations, and applied clinical applications. To provide medical physics educators with an open access resource (tool) that they can use in their teaching activities to enrich and elevate the level of learning for their students, residents, etc. with respect to the invisible realm of medical physics. Methods: An experienced clinical medical physicist and educator has created and provided with open access three complementary web-based resources to achieve the purposes described above. One is a module focusing on the medical physics learning process with respect to mental knowledge structures, how they relate to outcomes and applications, and learning activities that are required to develop the required knowledge structures. The second is an extensive set of visuals that educators can use in their activities (classes, small group discussions, etc.) to visualize the invisible. The third is an interactive online simulation where learners can adjust factors and visually observe changes in x-radiation.These resources are available online at www.BLINDED FOR REVIEW . Results: Medical physics education, especially for non-physicists, is becoming much more interesting and useful especially with respect to invisible radiation. The global impact is that medical imaging professionals can be more effective in optimizing x-ray imaging procedures and risk management when they have knowledge levels that enhance problem solving, innovation, and creativity. Conclusion: Medical physics educators in all institutions can be much more effective and efficient in the sharing of their knowledge and experience when enhanced with high-quality visuals.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2026

An interactive machine learning platform for analyzing multi-particle coincidence data from cold target recoil ion momentum spectroscopy

We present SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training), a comprehensive software platform for analyzing tabulated high-dimensional multi-particle coincidence data from Cold Target Recoil Ion Momentum Spectroscopy (COLTRIMS) experiments. The software addresses critical challenges in modern momentum spectroscopy by integrating advanced machine learning techniques with physics-informed analysis in an interactive web-based environment. SCULPT implements uniform manifold approximation and projection for non-linear dimensionality reduction to reveal correlations in high-dimensional data. We also discuss potential extensions to deep autoencoders for feature learning and genetic programming for automated discovery of physically meaningful observables. A novel adaptive confidence scoring system provides quantitative reliability assessments by evaluating user-selected clustering quality metrics with predefined weights that reflect each metric’s robustness. The platform features configurable molecular profiles for different experimental systems, interactive visualization with selection tools, and comprehensive data filtering capabilities. Utilizing a subset of SCULPT’s capabilities, we analyze photo-double-ionization data measured using the COLTRIMS method for three-body dissociation of the D 2 O molecule, revealing distinct fragmentation channels and their correlations with physics parameters. The software’s modular architecture and web-based implementation make it accessible to the broader atomic and molecular physics community, significantly reducing the time required for complex multi-dimensional analyses. This opens the door to finding and isolating rare events exhibiting non-linear correlations on the fly during experimental measurements, which can help steer exploration and improve the efficiency of experiments.

Artificial neural networks↗

DOE OSTI2025

Extraction and Analysis of Time Series Data from Building Automation Systems Using Large Language Models

Semantic schemas like Haystack 4, Brick and ASHRAE standard 223 enable the structured, standardized, and machine-readable representation of building data, facilitating interoperability, data integration, and advanced analytics. However, extracting information from these models requires specialized expertise in SPARQL and other programming languages, skills that are not commonly found among building professionals. Recent advancements in Large Language Models (LLMs), such as ChatGPT, enable the construction of queries using natural language, making it easier for individuals to interact with these systems in a manner that resembles everyday speech. However, these methods have not yet been tested on building semantic ontologies. This paper introduces a novel workflow and tool for enabling users to ask questions about a specific building's data, using natural language and receive answers automatically generated by GPT-4o. Our approach integrates semantic ontologies with advanced LLM capabilities to automate three critical steps: (1) generating SPARQL queries to retrieve time series references from ontological models, (2) extracting the corresponding time series data from the Building Automation System, and (3) performing computations and visualizations tailored to the user's query. The proposed method simplifies access to BAS data, allowing both domain experts and non-specialists to conduct sophisticated analyses without needing extensive technical knowledge of semantic web technologies. By demonstrating this pipeline, we facilitate more accessible and scalable data-driven decision-making in building operations and management.

Mulayim, Ozan Baris↗

DOE OSTI2024

Dynamic CCS-EJ-SJ Database and Web Application - What's New

At the 2024 FECM/NETL Carbon Management Research Project Review Meeting, within the Carbon Transport and Storage Breakout Session 3, the presentation "Dynamic CCS-EJ-SJ Database and Web Application - What's New" highlights the critical tool designed to integrate environmental and social justice considerations into Carbon Capture and Storage (CCS) projects. Key features include an interactive dashboard for data access and visualization, which supports stakeholders in making informed decisions regarding CCS implementation, and updated data layers. The latest version enhances data integration and usability, providing a comprehensive resource for assessing the social and environmental impacts of CCS projects. There are 7 categories in the CCS EJSJ v2 database (released 03/31/2024): environmental justice, energy justice, economic justice, social justice, ecosystem assets, clean energy, and infrastructure. Most of the layers within each category have been updated in this version. As compared to the old database, there are 3 new categories in the v2 database: ecosystem assets, clean energy, and infrastructure.

Sharma, Maneesh↗

DOE OSTI2025

Extraction and Analysis of Time Series Data from Building Automation Systems Using Large Language Models

Mulayim, Ozan Baris↗

NASA NTRS2004

GRIDVIEW: Recent Improvements in Research and Education Software for Exploring Mars Topography

GRIDVIEW is being developed by the GEODYNAMICS Branch at NASA's Goddard Space Flight Center and can be downloaded on the web at http://geodynamics.gsfc.nasa.gov/gridview/. The program is very mature and has been successfully used for more than four years, but is still under development as we add new features for data analysis and visualization. The software can run on any computer supported by the IDL virtual machine application supplied by RSI. The virtual machine application is currently available for recent versions of MS Windows, MacOS X, Red Hat Linux and UNIX. Minimum system memory requirement is 32 MB, however loading large data sets may require larger amounts of RAM to function adequately.

Roark, J. H.↗

NASA NTRS2019

GeoNEX: A Cloud Gateway for Near Real-time Processing of Geostationary Satellite Products

The emergence of a new generation of geostationary satellite sensors provides land andatmosphere monitoring capabilities similar to MODIS and VIIRS with far greater temporal resolution (5-15 minutes). However, processing such large volume, highly dynamic datasets requires computing capabilities that (1) better support data access and knowledge discovery for scientists; (2) provide resources to enable real-time processing for emergency response (wildfire, smoke, dust, etc.); and (3) provide reliable and scalable services for the broader user community. This paper presents an implementation of GeoNEX (Geostationary NASA-NOAA Earth Exchange) services that integrate scientific algorithms with Amazon Web Services (AWS) to provide near realtime monitoring (~5 minute latency) capability in a hybrid cloud-computing environment. It offers a user-friendly, manageable and extendable interface and benefits from the scalability provided by Amazon Web Services. Four use cases are presented to illustrate how to (1) search and access geostationary data; (2) configure computing infrastructure to enable near real-time processing; (3) disseminate and utilize research results, visualizations, and animations to concurrent users; and (4) use a Jupyter Notebook-like interface for data exploration and rapid prototyping. As an example of (3), the Wildfire Automated Biomass Burning Algorithm (WF_ABBA) was implemented on GOES-16 and -17 data to produce an active fire map every 5 minutes over the conterminous US. Details of the implementation strategies, architectures, and challenges of the use cases are discussed.

GeoNEX↗

DOE OSTI2014

Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 2.

More information: http://daymet.ornl.gov Presenter: Ranjeet Devarakonda Environmental Sciences Division Oak Ridge National Laboratory (ORNL) Daymet: Daily Surface Weather Data and Climatological Summaries provides gridded estimates of daily weather parameters for North America, including daily continuous surfaces of minimum and maximum temperature, precipitation occurrence and amount, humidity, shortwave radiation, snow water equivalent, and day length. The current data product (Version 2) covers the period January 1, 1980 to December 31, 2013 [1]. The prior product (Version 1) only covered from 1980-2008. Data are available on a daily time step at a 1-km x 1-km spatial resolution in Lambert Conformal Conic projection with a spatial extent that covers the conterminous United States, Mexico, and Southern Canada as meteorological station density allows. Daymet data can be downloaded from 1) the ORNL Distributed Active Archive Center (DAAC) search and order tools (http://daac.ornl.gov/cgi-bin/cart/add2cart.pl?add=1219) or directly from the DAAC FTP site (http://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1219) and 2) the Single Pixel Tool [2] and THREDDS (Thematic Real-time Environmental Data Services) Data Server [3]. The Single Pixel Data Extraction Tool allows users to enter a single geographic point by latitude and longitude in decimal degrees. A routine is executed that translates the (lon, lat) coordinates into projected Daymet (x,y) coordinates. These coordinates are used to access the Daymet database of daily-interpolated surface weather variables. Daily data from the nearest 1 km x 1 km Daymet grid cell are extracted from the database and formatted as a table with one column for each Daymet variable and one row for each day. All daily data for selected years are returned as a single (long) table, formatted for display in the browser window. At the top of this table is a link to the same data in a simple comma-separated text format, suitable for import into a spreadsheet or other data analysis software. The Single Pixel Data Extraction Tool also provides the option to download multiple coordinates programmatically. A multiple extractor script is freely available to download at http://daymet.ornl.gov/files/daymet.zip. The ORNL DAAC s THREDDS data server (TDS) provides customized visualization and access to Daymet time series of North American mosaics. Users can subset and download Daymet data via a variety of community standards, including OPeNDAP, NetCDF Subset service, and Open Geospatial Consortium (OGC) Web Map/Coverage Service. The ORNL DAAC TDS also exposes Daymet metadata through its ncISO service to facilitate harvesting Daymet metadata records into 3rd party catalogs. References: [1] Thornton, P.E., M.M. Thornton, B.W. Mayer, N. Wilhelmi, Y. Wei, R. Devarakonda, and R.B. Cook. 2014. Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 2. Data set. Available on-line [http://daac.ornl.gov] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, USA. [2] Devarakonda R., et al. 2012. Daymet: Single Pixel Data Extraction Tool. Available on-line [http://daymet.ornl.go/singlepixel.html]. [3] Wei Y., et al. 2014. Daymet: Thematic Real-time Environmental Data Services. Available on-line [http://daymet.ornl.gov/thredds_tiles.html].

Thornton, Peter E↗

NASA NTRS1994

A distributed analysis and visualization system for model and observational data

Software was developed with NASA support to aid in the analysis and display of the massive amounts of data generated from satellites, observational field programs, and from model simulations. This software was developed in the context of the PATHFINDER (Probing ATmospHeric Flows in an Interactive and Distributed EnviRonment) Project. The overall aim of this project is to create a flexible, modular, and distributed environment for data handling, modeling simulations, data analysis, and visualization of atmospheric and fluid flows. Software completed with NASA support includes GEMPAK analysis, data handling, and display modules for which collaborators at NASA had primary responsibility, and prototype software modules for three-dimensional interactive and distributed control and display as well as data handling, for which NSCA was responsible. Overall process control was handled through a scientific and visualization application builder from Silicon Graphics known as the Iris Explorer. In addition, the GEMPAK related work (GEMVIS) was also ported to the Advanced Visualization System (AVS) application builder. Many modules were developed to enhance those already available in Iris Explorer including HDF file support, improved visualization and display, simple lattice math, and the handling of metadata through development of a new grid datatype. Complete source and runtime binaries along with on-line documentation is available via the World Wide Web at: http://redrock.ncsa.uiuc.edu/ PATHFINDER/pathre12/top/top.html.

Wilhelmson, Robert B.↗

NASA NTRS2003

Multi-Disciplinary Analysis for Future Launch Systems Using NASA's Advanced Engineering Environment (AEE)

A new engineering environment constructed for the purposes of analyzing and designing Reusable Launch Vehicles (RLVs) is presented. The new environment has been developed to allow NASA to perform independent analysis and design of emerging RLV architectures and technologies. The new Advanced Engineering Environment (AEE) is both collaborative and distributed. It facilitates integration of the analyses by both vehicle performance disciplines and life-cycle disciplines. Current performance disciplines supported include: weights and sizing, aerodynamics, trajectories, propulsion, structural loads, and CAD-based geometries. Current life-cycle disciplines supported include: DDT&E cost, production costs, operations costs, flight rates, safety and reliability, and system economics. Involving six NASA centers (ARC, LaRC, MSFC, KSC, GRC and JSC), AEE has been tailored to serve as a web-accessed agency-wide source for all of NASA's future launch vehicle systems engineering functions. Thus, it is configured to facilitate (a) data management, (b) automated tool/process integration and execution, and (c) data visualization and presentation. The core components of the integrated framework are a customized PTC Windchill product data management server, a set of RLV analysis and design tools integrated using Phoenix Integration's Model Center, and an XML-based data capture and transfer protocol. The AEE system has seen production use during the Initial Architecture and Technology Review for the NASA 2nd Generation RLV program, and it continues to undergo development and enhancements in support of its current main customer, the NASA Next Generation Launch Technology (NGLT) program.

Monell, D.↗