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All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

The SPASE Data Model for Heliophysics Data: Is it Working?

The Space Physics Archive Search and Extract (SPASE) Data Model was developed to provide a metadata standard for describing Heliophysics (Space and Solar Physics) data within that science discipline. The SPASE Data Model has matured over the many years of its creation and is presently represented by Version 2.2.1. Information about SPASE can be obtained from the website group.org. The Data Model defines terms and values as well as the relationships between them in order to describe the data resources in the Heliophysics data environment. This data environment is quite complex, consisting of Virtual Observatories, Resident Archives, Data Providers, Partnering Data Centers, Services, Final Archives, and a Deep Archive. SPASE is the metadata language standard intended to permeate the complexity and provide a common method of obtaining and understanding data. Is it working in this capacity? SPASE has been used to describe a wide range of data. Examples range from ground-based magnetometer data to interplanetary satellite measurements to space weather model results. Has it achieved the goal of making the data easier to find and use? To find data of interest it is necessary that all the data of importance be described using the SPASE Data Model. Within the part of the data community associated with NASA (supported through NASA funding) there are obligations to use SPASE and (0 describe the old and new data using the SPASE XML schema. Although this pan of the community is not near 100% compliance with the mandate, there is good progress being made and the goal should be reachable in the future. Outside of the NASA data community there is still work to be done to convince the international community that SPASE descriptions are w011h the cost of their generation. Some of these groups such as Cluster, HELlO, GAIA, NOAA/NGDe. CSSDP, VSTO, SuperMAG, and IUGONET have agreed to use SPASE. but there are still other groups of importance that need (0 be reached. It is also assumed that the terminology is sufficiently broad and the descriptions are sufficiently complete that researchers needing data of a specific type or from a specific period can find and acquire what they need. A valid SPASE description can be very brief or very thorough depending on the willingness of the author to spend the time necessary to make the description useful. There is evidence that users are finding what they need through the SPASE descriptions, and this standard is a big step forward in Heliophysics data location. Does SPASE make it easier to use the data once they are found,) Thorough descriptions of data using SPASE can describe the data down to the level of individual parameters and exactly how the data are organized and stored. Should the SPASE data descriptions be written in such a way that they can be automatically ingested and understood by software tools'? Heliophysics instruments are becoming morc versatile all the time and the complexity of the data makes it tedious and time consuming to write SPASE descriptions with this level of sophistication even with the improvement of the tools used to generate the descriptions. Is it better to just write human-readable descriptions of the data at the parameter level or to refer to references that provide this information? This is a debate that is presently taking place and software is being developed to test what is possible.

Thieman, James↗
NASA NTRS1998

Parallel PAB3D: Experiences with a Prototype in MPI

PAB3D is a three-dimensional Navier Stokes solver that has gained acceptance in the research and industrial communities. It takes as computational domain, a set disjoint blocks covering the physical domain. This is the first report on the implementation of PAB3D using the Message Passing Interface (MPI), a standard for parallel processing. We discuss briefly the characteristics of tile code and define a prototype for testing. The principal data structure used for communication is derived from preprocessing "patching". We describe a simple interface (COMMSYS) for MPI communication, and some general techniques likely to be encountered when working on problems of this nature. Last, we identify levels of improvement from the current version and outline future work.

Guerinoni, Fabio↗
NASA NTRS2001

XML Based Scientific Data Management Facility

The World Wide Web consortium has developed an Extensible Markup Language (XML) to support the building of better information management infrastructures. The scientific computing community realizing the benefits of HTML has designed markup languages for scientific data. In this paper, we propose a XML based scientific data management facility, XDMF. The project is motivated by the fact that even though a lot of scientific data is being generated, it is not being shared because of lack of standards and infrastructure support for discovering and transforming the data. The proposed data management facility can be used to discover the scientific data itself, the transformation functions, and also for applying the required transformations. We have built a prototype system of the proposed data management facility that can work on different platforms. We have implemented the system using Java, and Apache XSLT engine Xalan. To support remote data and transformation functions, we had to extend the XSLT specification and the Xalan package.

Mehrotra, Piyush↗
NASA NTRS2002

XML Based Scientific Data Management Facility

The World Wide Web consortium has developed an Extensible Markup Language (XML) to support the building of better information management infrastructures. The scientific computing community realizing the benefits of XML has designed markup languages for scientific data. In this paper, we propose a XML based scientific data management ,facility, XDMF. The project is motivated by the fact that even though a lot of scientific data is being generated, it is not being shared because of lack of standards and infrastructure support for discovering and transforming the data. The proposed data management facility can be used to discover the scientific data itself, the transformation functions, and also for applying the required transformations. We have built a prototype system of the proposed data management facility that can work on different platforms. We have implemented the system using Java, and Apache XSLT engine Xalan. To support remote data and transformation functions, we had to extend the XSLT specification and the Xalan package.

Mehrotra, P.↗
NASA NTRS2009

Evolution of Web Services in EOSDIS: Search and Order Metadata Registry (ECHO)

During 2005 through 2008, NASA defined and implemented a major evolutionary change in it Earth Observing system Data and Information System (EOSDIS) to modernize its capabilities. This implementation was based on a vision for 2015 developed during 2005. The EOSDIS 2015 Vision emphasizes increased end-to-end data system efficiency and operability; increased data usability; improved support for end users; and decreased operations costs. One key feature of the Evolution plan was achieving higher operational maturity (ingest, reconciliation, search and order, performance, error handling) for the NASA s Earth Observing System Clearinghouse (ECHO). The ECHO system is an operational metadata registry through which the scientific community can easily discover and exchange NASA's Earth science data and services. ECHO contains metadata for 2,726 data collections comprising over 87 million individual data granules and 34 million browse images, consisting of NASA s EOSDIS Data Centers and the United States Geological Survey's Landsat Project holdings. ECHO is a middleware component based on a Service Oriented Architecture (SOA). The system is comprised of a set of infrastructure services that enable the fundamental SOA functions: publish, discover, and access Earth science resources. It also provides additional services such as user management, data access control, and order management. The ECHO system has a data registry and a services registry. The data registry enables organizations to publish EOS and other Earth-science related data holdings to a common metadata model. These holdings are described through metadata in terms of datasets (types of data) and granules (specific data items of those types). ECHO also supports browse images, which provide a visual representation of the data. The published metadata can be mapped to and from existing standards (e.g., FGDC, ISO 19115). With ECHO, users can find the metadata stored in the data registry and then access the data either directly online or through a brokered order to the data archive organization. ECHO stores metadata from a variety of science disciplines and domains, including Climate Variability and Change, Carbon Cycle and Ecosystems, Earth Surface and Interior, Atmospheric Composition, Weather, and Water and Energy Cycle. ECHO also has a services registry for community-developed search services and data services. ECHO provides a platform for the publication, discovery, understanding and access to NASA s Earth Observation resources (data, service and clients). In their native state, these data, service and client resources are not necessarily targeted for use beyond their original mission. However, with the proper interoperability mechanisms, users of these resources can expand their value, by accessing, combining and applying them in unforeseen ways.

Mitchell, Andrew↗
NASA NTRS2016

Developing the Next Generation of Science Data System Engineers

At Goddard, engineers and scientists with a range of experience in science data systems are needed to employ new technologies and develop advances in capabilities for supporting new Earth and Space science research. Engineers with extensive experience in science data, software engineering and computer-information architectures are needed to lead and perform these activities. The increasing types and complexity of instrument data and emerging computer technologies coupled with the current shortage of computer engineers with backgrounds in science has led the need to develop a career path for science data systems engineers and architects.The current career path, in which undergraduate students studying various disciplines such as Computer Engineering or Physical Scientist, generally begins with serving on a development team in any of the disciplines where they can work in depth on existing Goddard data systems or serve with a specific NASA science team. There they begin to understand the data, infuse technologies, and begin to know the architectures of science data systems. From here the typical career involves peermentoring, on-the-job training or graduate level studies in analytics, computational science and applied science and mathematics. At the most senior level, engineers become subject matter experts and system architect experts, leading discipline-specific data centers and large software development projects. They are recognized as a subject matter expert in a science domain, they have project management expertise, lead standards efforts and lead international projects. A long career development remains necessary not only because of the breadth of knowledge required across physical sciences and engineering disciplines, but also because of the diversity of instrument data being developed today both by NASA and international partner agencies and because multidiscipline science and practitioner communities expect to have access to all types of observational data.This paper describes an approach to defining career-path guidance for college-bound high school and undergraduate engineering students, junior and senior engineers from various disciplines.

Next Generation of Science↗
DOE OSTI2025

Remote Sensing and Fluxes Upscaling for Real-world Impact (Workshop Report)

The "Remote Sensing and Fluxes Upscaling for Real-world Impact" workshop, held on July 9-10, 2024, at Lawrence Berkeley National Lab, was a collaborative effort led by the AmeriFlux Management Project, NEON, and the Carbon Dew Community of Practice. The event brought together over 200 registrants and approximately 100 attendees each day, including leading experts, researchers, and practitioners. The primary focus was on bridging the gap between cutting-edge research and practical applications in environmental monitoring by integrating remote sensing and flux data. Key themes included the importance of site-level measurements for validating remote sensing products, providing nature-based climate solutions, and addressing challenges such as instrument costs and the need for standardized methods. At the regional scale, discussions centered on addressing spatial heterogeneity and using high-resolution remote sensing and machine learning methods to enhance data interpretation. Global scale challenges included data consistency, gap filling, and accurate emission source identification, with opportunities for international collaboration and standardized practices to improve global carbon budget assessments. The workshop emphasized the critical need for integrating data across local, regional, and global scales through explicit scale-matching and developed a workflow for scaling flux data using "straight shot" and "explicit nesting" approaches. The event highlighted the importance of connecting scientific research with real-world applications in carbon, energy, and water management, ensuring that advancements translate into tangible societal benefits. These insights will guide future research, technology transfer, and collaboration, maximizing the potential of environmental fluxes to address real-world challenges.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2009

One NASA PEM qualification standard : comparison of JPL and GSFC standards

Although use of Plastic Encapsulated Microelectronics (PEMs) in space applications is discouraged, their use is mandatory for selected applications involving the need for advanced technology and small packages. Various space systems designers and manufacturers have developed methods to qualify and screen PEMs. In general, each procedure is different. The purpose of this fiscal year’s investigation is to initiate a process to coordinate the efforts at various NASA centers to eventually develop a One NASA method. Part of this activity includes sharing of test data and PEM qualification methodologies. Various experts in the NASA community were identified and contacted to support this effort. We were successful in finding such experts at GSFC, APL and the Constellation office (Orion and Ares). All these experts provided typical qualification program plans. Since funding was severely restricted, it was decided to concentrate on coordination activity with GSFC. GSFC is planning a new version of IEEE-INST-002 section applying to PEMs. The GSFC expert (Dr. Alexander Teverovsky) provided a detailed assessment of the differences between the planned new version of IEEE-INST-002 and the JPL-D-19426 (JPL guideline) as well as a summary rationale for the decisions within the IEEE-INST-002. It should be noted that GSFC’s assessment of IEEE-INST-002 in the area of PEMs is not finalized. JPL is also considering changes in PEM qualification methodologies based on test data from recent qualification testing for their newer Projects (MSL, Grail, Juno). A spreadsheet delineating the differences between the JPL standard and the GSFC standard is presented.

Cooper, Mark↗
DOE OSTI2023

A Power Application Developer’s Guide to the Common Information Model: An Introduction for Power Systems Engineers and Application Developers – CIM17v40

A key issue in creating the next generation of energy management system (EMS) and advanced distribution management system (ADMS) platforms will be the ability to represent and exchange power system network model data in a consistent manner. To this end, the Common Information Model (CIM) stands out as the only standardized vocabulary (or ontology) for defining power system network models and asset data in a comprehensive, consistent manner across the generation-transmission-distribution boundary. The CIM is freely available to use and extend. The CIM is maintained by the UCAiug (informally known as the CIM User’s Group) under an Apache 2.0 license. The CIM Users Group collaborates with the IEC and other standards communities for the development of technical and informative specifications. Although portions of the information model are referred to by the corresponding IEC standards naming, it is not necessary to purchase any of the IEC standards to use the CIM information model. This document provides a roadmap for power system engineers and application developers not familiar with semantic modeling to start using the CIM for modeling, simulation, optimization, and development of advanced power applications. The key classes needed for defining power system topology and equipment are explained systematically. Key focus areas include modeling of lines, transformers, generators, switching equipment, loads, and distributed energy resources (DERs).

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1996

Experimental Characterization of Gas Turbine Emissions at Simulated Flight Altitude Conditions

NASA's Atmospheric Effects of Aviation Project (AEAP) is developing a scientific basis for assessment of the atmospheric impact of subsonic and supersonic aviation. A primary goal is to assist assessments of United Nations scientific organizations and hence, consideration of emissions standards by the International Civil Aviation Organization (ICAO). Engine tests have been conducted at AEDC to fulfill the need of AEAP. The purpose of these tests is to obtain a comprehensive database to be used for supplying critical information to the atmospheric research community. It includes: (1) simulated sea-level-static test data as well as simulated altitude data; and (2) intrusive (extractive probe) data as well as non-intrusive (optical techniques) data. A commercial-type bypass engine with aviation fuel was used in this test series. The test matrix was set by parametrically selecting the temperature, pressure, and flow rate at sea-level-static and different altitudes to obtain a parametric set of data.

GAS TURBINES↗
NASA NTRS2020

NASA ESDS Citizen Science Data Working Group

This document provides guidelines for legal, policy, and ethical issues; standards for citizen science data collection and management; information on ensuring usability of citizen science data and communication regarding its use; and best practices for long-term archival of citizen science data.Section1 contains a detailed discussion of policy, ethical, and legal considerations influencing citizen science data collection. Section 2 considers standards for documentation, including documentation of instrumentation, procedures, and the data itself. It concludes with a discussion of how citizen science data should be attributed. Section 3 provides guidance about how to ensure citizen science data are collected and stored in a useable way. It also considers how NASA and data producers should notify the scientific community, including citizen scientists and the public, about citizen science datasets and the scientific conclusions reached using them. Finally, Section 4 provides detailed information regarding what should be archived from projects using a citizen science approach, including data and code. It provides guidance about archive location, process, and timeframe, as well as information about data access and distribution services provided by NASA that may be relevant to data producers working with citizen scientists.

Citizen Science↗
NASA NTRS2019

Lunar Ice Cube: ongoing development of first generation deep space cubesat mission with compact broadband IR spectrometer

Lunar Ice Cube (LIC) is one of 13 6U cubesats that will be deployed by EM1 in cislunar space. LIC along with Lunar Flashlight and LunaH-Map, all focused on the search for volatiles but with very different payloads, will be the first deep space cubesats designed to address goals for both demonstrating new technologies and collecting scientific data. Effectively, as their developments are occurring in parallel, they are acting as prototypes for future deep space cubesats missions. One useful outcome of this experiment is to evolve a working paradigm for the development and operation of compact, cost-capped, standardized (supporting subsystems) spacecraft to serve the needs of diverse user communities.

Mason, Paul↗
NASA NTRSDate not supplied

RadLab: A Comprehensive Database and Graphical and Programming Interfaces for Biologically Relevant Space Radiation Data

RadLab, a new component of the NASA Open Science Data Repository (OSDR), comprises a database of radiation measurements relevant to space biology, and visual and programmatic interfaces for interrogation and retrieval of these data. The attributes of data available through RadLab include spacecraft, types of radiation sensing instruments, locations within the spacecraft (e.g. modules of the ISS), associated celestial bodies, trajectories, and spacecraft coordinates. The application programming interface (API) implements a request syntax for retrieval of timestamped data filtered by various combinations of such attributes; the graphical user interface (GUI) extends this functionality with visualizations, such as spacecraft schematics, time series plots, geospatial visualizations, and provides easy means to iteratively refine search parameters, inspect the data on the fly, and download target subsets of these data. The release of RadLab currently available to the public contains datasets provided by US and international collaborators and focuses on data recorded on the ISS. Investigators from multiple countries, including the US, Canada, Germany, Bulgaria, Hungary, Italy, Japan, Russia and the Czech Republic, have committed to provide data from their instruments in and beyond low Earth orbit; RadLab will also soon expand to include past (e.g. Shuttle and Mir) and future (e.g. Artemis) data. RadLab will provide a comprehensive, dynamic compendium of space radiation data, enabling the scientific community to perform analyses of data from multiple detectors and to determine the radiation environment of research missions and experiments, both via programmatic retrieval of these data and through the graphical analysis toolkit. The RadLab Working Group has been formed to foster collaborations among data contributors and users, to identify data sources, to put in place standards for data harmonization, and to guide the development of the platform, with the goal to establish the use of RadLab in space radiation research and to advance our understanding of the space radiation environment in human habitats.

radiation↗
NASA NTRS1994

Improved small satellite access of the space network

This report contains the results of a study performed under the sponsorship of the National Aeronautics and Space Administration (NASA) made as a grant to the Center for Space Telemetering and Telecommunication Systems at New Mexico State University. The purpose of this phase of the grant is to increase user access to the Space Network (SN) run by NASA for supplying space-to-ground communications for satellites and associated control centers. The identified need is to bring more users into the community of those accessing the SN, especially those in the small satellite class of users. The initial phase of the study concerned the potential for modifications to the standard transponder used in the SN. The results of that investigation are summarized in Section 4. As the hardware modifications were being investigated, a second option was developed, namely to consider changes to the operational mode for the small satellites. This operational concept was to use a single, fixed-pointing antenna in a spin-stabilized satellite and let the antenna pattern sweep past the Tracking and Data Relay Satellites (TDRS) in the SN. The question to be answered by this phase of the study was twofold: could enough contact time per day be made available using this simple operating mode and could the data rate be high enough to allow for sufficient data throughput to satisfy the user community using existing components. Section 2 outlines the methodology and simulation results to answer these questions. Section 3 contains a summary of an operational simulation of a simple satellite payload using these contact scenarios. The simulation is not all inclusive but shows how a payload simulation could be configured to utilize variable contact times. The answer to both of the questions desired to be answered is affirmative. By carefully choosing the correct system transmission power and antenna pattern, the system will allow support to the 50th percentile of expected systems. It is recommended that based on this initial study, further work be done to quantify the exact parameters for transmission through the space network and to optimize usage of the contact time to maximize throughput.

Horan, Stephen↗
NASA NTRS2022

NASA System-Wide Safety Wildland Firefighting Operations Workshop Report

On March 9-11, 2022, NASA’s System-Wide Safety Wildland Firefighting Operations Workshop engaged the broader wildland firefighting management ecosystem in a safety-oriented discussion via a virtual platform. This enabled a better understanding of how NASA and community expertise can be leveraged in the safe development of current and future firefighting systems and operations. The goals of the workshop were to: (1) identify and prioritize the top safety-oriented risks, gaps in capabilities, and emerging technologies to enhance wildland firefighting for both near-term and far-term concepts, with a specific focus on aviation operations and (2) engage the stakeholder community in defining emergent safety-oriented scope, roles, responsibilities, and procedures for agents undergoing increasingly complex wildland firefighting operations in information-rich, but uncertain environments. Workshop participants were solicited from wildland firefighting stakeholders across government, industry, and academia. All levels of government were engaged, as NASA sought attendees from federal, state, local, and tribal government agencies. Industry participants from traditional wildland firefighting domains such as data visualization and equipment manufacturers were invited, and corporate attendees from novel application domains such as aerial robotics and autonomous systems were present as well. The top three findings were as follows: (1) Enhancing situation awareness is a safety priority, especially in the use of aerial assets; (2) Timely access to information along with data fusion and integrated displays will enhance safety-critical decision-making both inside and outside aviation contexts; and (3) Tailorable standards and common operating pictures in the field will enhance inter-agency cooperation in the wildland firefighting lifecycle and enable the optimal use of limited resources such as aerial assets. The workshop helped inform NASA of the relevant safety-related wildland firefighting concerns and aided the broader ecosystem in understanding the potential safety-oriented role NASA might play in this community. Increased engagement with crucial governmental stakeholders (e.g., U.S. Forest Service, CAL FIRE, etc.) along with industry partners in cutting- edge information -centric domains is a fundamental next step. Additionally, the workshop findings will help define the first of a series of operationally challenging demonstrations, held in concert with strategic ecosystem partners, known as the Safety Demonstrator Series for NASA’s System-Wide Safety project. The first demonstration is set in the wildland firefighting application domain and will: (1) examine high risk operational scenarios to reduce their overall risk via services, functions or capabilities that act as risk mitigators (or transfer that risk to automated systems better able to tolerate it) and (2) explore novel tools and technologies that will enhance safety margins by enabling non-traditional or neoteric operational paradigms.

wildland firefighting↗
DOE OSTI2025

Stable Simulation of the Community Atmosphere Model Using Machine‐Learning Physical Parameterization Trained With Experience Replay

In recent years, machine learning (ML) models have been used to improve physical parameterizations of general circulation models (GCMs). A significant challenge of integrating ML models into GCMs is the online instability when they are coupled for long‐term simulation. We present a new strategy that demonstrates robust online stability when the physical parameterization package of an atmospheric GCM is replaced by a deep ML model. The method uses experience replay with a multistep training scheme of the ML model in which the model's own output at the previous time step is used in the training. Predicted physics tendencies in the replay buffer with the most recent errors in the training iterations are reused, making the ML model learn from its own errors. The training method reduces the gap between the offline and online environments of the ML model. The method is used to train the ML model as the physical parameterization of the Community Atmosphere Model (CAM5) with training data from the Multi‐scale Modeling Framework high resolution simulations. Three 6‐year online simulations of the CAM5 are carried out by using the ML physics package. The simulated spatial distributions of precipitation, surface temperature and zonally averaged atmospheric fields demonstrate overall better accuracy than that of the standard CAM5 and benchmark model even without the use of additional physical constraints or tuning. This work is the first to demonstrate a solution to address the online instability problem in climate modeling with ML physics by using experience replay.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

Globally Gridded Satellite (GridSat) Observations for Climate Studies

Geostationary satellites have provided routine, high temporal resolution Earth observations since the 1970s. Despite the long period of record, use of these data in climate studies has been limited for numerous reasons, among them: there is no central archive of geostationary data for all international satellites, full temporal and spatial resolution data are voluminous, and diverse calibration and navigation formats encumber the uniform processing needed for multi-satellite climate studies. The International Satellite Cloud Climatology Project set the stage for overcoming these issues by archiving a subset of the full resolution geostationary data at approx.10 km resolution at 3 hourly intervals since 1983. Recent efforts at NOAA s National Climatic Data Center to provide convenient access to these data include remapping the data to a standard map projection, recalibrating the data to optimize temporal homogeneity, extending the record of observations back to 1980, and reformatting the data for broad public distribution. The Gridded Satellite (GridSat) dataset includes observations from the visible, infrared window, and infrared water vapor channels. Data are stored in the netCDF format using standards that permit a wide variety of tools and libraries to quickly and easily process the data. A novel data layering approach, together with appropriate satellite and file metadata, allows users to access GridSat data at varying levels of complexity based on their needs. The result is a climate data record already in use by the meteorological community. Examples include reanalysis of tropical cyclones, studies of global precipitation, and detection and tracking of the intertropical convergence zone.

Knapp, Kenneth R.↗
NASA NTRS1993

EOSDIS - Its role in the EOS program and its importance to the scientific community

In order to manage the global data sets required to understand the earth as a system, the EOS Data and Information System (EOSDIS) will collect and store satellite, aircraft, and in situ measurements and their resultant data products, and will distribute the data conveniently. EOSDIS will also provide product generation and science computing facilities to support the development, processing, and validation of standard EOS science data products. The overall architecture of EOSDIS, and how the Distributed Active Archive Centers fit into that structure, are shown. EOSDIS will enable users to query data bases nationally, make use of keywords and other mnemonic identifiers, and see graphic images of subsets of available data prior to ordering full (or selected pieces of) data sets for use in their 'home' environment.

Price, Robert D.↗