Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “data management”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A standards perspective on genomic data reusability and reproducibility

Genomic and metagenomic sequence data provides an unprecedented ability to re-examine findings, offering a transformative potential for advancing research, developing computational tools, enhancing clinical applications, and fostering scientific collaboration. However, effective and ethical reuse of genomics data is hampered by numerous technical and social challenges. The International Microbiome and Multi’Omics Standards Alliance (IMMSA, https://www.microbialstandards.org/) and the Genomic Standards Consortium (GSC, https://gensc.org) hosted a 5-part seminar series “A Year of Data Reuse” in 2024 to explore challenges and opportunities of data reuse and reproducibility across disparate domains of the genomic sciences. Addressing these challenges will require a multifaceted approach, including common metadata reporting, clear communication, standardized protocols, improved data management infrastructure, ethical guidelines, and collaborative policies that prioritize transparency and accessibility. We offer strategies to enable responsible and technically feasible data reuse, recognition of data reproducibility challenges, and emphasizing the importance of cross-disciplinary efforts in the pursuit of open science and data-driven innovation.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2002

Operational Limitations of the High Rate Frame Multiplexer (HRFM) Onboard the International Space Station(ISS)-and How These Limitations Affect Payload Developers (PDs) and International Partners (IPs)

The data system onboard the United States Operating Segment (USOS) of the ISS is currently used to capture, route, record and downlink high-rate science data from experiments inside the US Lab. Once NASDA's Japanese Experiment Module (JEM) and ESA's Attached Pressurized Module (APM) are launched - in the 2004 to 2005 timeframe - data from these facilities will also be routed to the ground using the USOS data system. A critical component of the USOS data system is the High Rate Frame Multiplexer (HRFM). The HRFM combines multiple data/video inputs and combines them into one data stream. This Ku-band data stream is then routed through the Tracking and Data Relay Satellite (TDRS) system to the ground. The Data Management Coordinator (DMC) - located at the Marshall Space Flight Center's Payload Operations Center (POC) - is responsible for commanding and controlling the HRFM. The HRFM can multiplex a maximum of eight digital data sources and four digital video sources. Thus far, this limitation has not been constraining to operations. However, once the JEM and APM are integrated, the HRFM limitations will become a major constraint to science operations onboard. The purpose of this paper is to characterize the limitations of the HRFM and to explain how these limitations can be successfully managed. With this information, Payload Developers and International Partners will be able to more effectively utilize the data systems onboard the ISS. Ultimately, more science data can be captured and downlinked to Flight Controllers and Scientists on the ground.

Mixson, Charles D.↗
NASA NTRS1982

A modular data system for Spacelab experiments

This overview describes a flexible system of electronic and mechanical building blocks with characteristics and capabilities suitable for construction of a flight-capable experiment data management system. The initial space application of this modular system, called the Spacelab Payload System Modular Electronics (SPSME), is the data system for the Nuclear Radiation Monitor (NRM) on Spacelab Mission 2.

Frost, W. O.↗
NASA NTRS1992

Automated in situ observations of upper ocean biogeochemistry, bio-optics, and physics and their potential use for global studies

The processes controlling the flux of carbon in the upper ocean have dynamic ranges in space and time of at least nine orders of magnitude. These processes depend on a broad suite of inter-related biogeochemical, bio-optical, and physical variables. These variables should be sampled on scales matching the relevant phenomena. Traditional ship-based sampling, while critical for detailed and more comprehensive observations, can span only limited portions of these ranges because of logistical and financial constraints. Further, remote observations from satellite platforms enable broad horizontal coverage which is restricted to the upper few meters of the ocean. For these main reasons, automated subsurface measurement systems are important for the fulfillment of research goals related to the regional and global estimation and modeling of time varying biogeochemical fluxes. Within the past few years, new sensors and systems capable of autonomously measuring several of the critical variables have been developed. The platforms for deploying these systems now include moorings and drifters and it is likely that autonomous underwater vehicles (AUV's) will become available for use in the future. Each of these platforms satisfies particular sampling needs and can be used to complement both shipboard and satellite observations. In the present review, (1) sampling considerations will be summarized, (2) examples of data obtained from some of the existing automated in situ sampling systems will be highlighted, (3) future sensors and systems will be discussed, (4) data management issues for present and future automated systems will be considered, and (5) the status of near real-time data telemetry will be outlined. Finally, we wish to make it clear at the outset that the perspectives presented here are those of the authors and are not intended to represent those of the United States JGOFS program, the International JGOFS program, NOAA's C&GC program, or other global ocean programs.

Dickey, Tommy D.↗
NASA NTRS1994

Automatic cataloguing and characterization of Earth science data using SE-trees

In the future, NASA's Earth Observing System (EOS) platforms will produce enormous amounts of remote sensing image data that will be stored in the EOS Data Information System. For the past several years, the Intelligent Data Management group at Goddard's Information Science and Technology Office has been researching techniques for automatically cataloguing and characterizing image data (ADCC) from EOS into a distributed database. At the core of the approach, scientists will be able to retrieve data based upon the contents of the imagery. The ability to automatically classify imagery is key to the success of contents-based search. We report results from experiments applying a novel machine learning framework, based on Set-Enumeration (SE) trees, to the ADCC domain. We experiment with two images: one taken from the Blackhills region in South Dakota; and the other from the Washington DC area. In a classical machine learning experimentation approach, an image's pixels are randomly partitioned into training (i.e. including ground truth or survey data) and testing sets. The prediction model is built using the pixels in the training set, and its performance is estimated using the testing set. With the first Blackhills image, we perform various experiments achieving an accuracy level of 83.2 percent, compared to 72.7 percent using a Back Propagation Neural Network (BPNN) and 65.3 percent using a Gaussain Maximum Likelihood Classifier (GMLC). However, with the Washington DC image, we were only able to achieve 71.4 percent, compared with 67.7 percent reported for the BPNN model and 62.3 percent for the GMLC.

Rymon, Ron↗
NASA NTRS2003

Airborne Oceanographic Lidar (AOL) (Global Carbon Cycle)

This bimonthly contractor progress report covers the operation, maintenance and data management of the Airborne Oceanographic Lidar and the Airborne Topographic Mapper. Monthly activities included: mission planning, sensor operation and calibration, data processing, data analysis, network development and maintenance and instrument maintenance engineering and fabrication.

Source record↗
NASA NTRS2004

SCDM in a Distributed Environment

The Software Configuration Management (SCM) of the Space Launch Initiative (SLI) Advanced Engineering Environment (AEE) products is performed in a distributed environment-meaning the activities performed during the project lifecycle are across numerous NASA Centers, facilities, organizations, colleges and industry. SCM is the glue that holds the project and products together-especially in a distributed environment. It identifies, controls, accounts, and verified the details of the products; the schedule of activities; the assigned responsibilities; and the required resources, including staff, tools, and computer facilities. Data/document management (DM) captures and conveys the SCM and project efforts. SCM and DM are integrally linked; hence, Software Configuration and Data Management (SCDM). This paper discusses one team's challenges in implementing SCDM in a distributed environment. The distributed nature of the project introduces new opportunities for moving SCDM to the next level of usefulness in today's high-tech development arena. The lessons learned from the implementation of distributed SCDM in support of the SLI AEE Project provide valuable information for future implementations of SCM and DM.

Crowley, Sandra L.↗
NASA NTRS2011

Extensions to the Dynamic Aerospace Vehicle Exchange Markup Language

The Dynamic Aerospace Vehicle Exchange Markup Language (DAVE-ML) is a syntactical language for exchanging flight vehicle dynamic model data. It provides a framework for encoding entire flight vehicle dynamic model data packages for exchange and/or long-term archiving. Version 2.0.1 of DAVE-ML provides much of the functionality envisioned for exchanging aerospace vehicle data; however, it is limited in only supporting scalar time-independent data. Additional functionality is required to support vector and matrix data, abstracting sub-system models, detailing dynamics system models (both discrete and continuous), and defining a dynamic data format (such as time sequenced data) for validation of dynamics system models and vehicle simulation packages. Extensions to DAVE-ML have been proposed to manage data as vectors and n-dimensional matrices, and record dynamic data in a compatible form. These capabilities will improve the clarity of data being exchanged, simplify the naming of parameters, and permit static and dynamic data to be stored using a common syntax within a single file; thereby enhancing the framework provided by DAVE-ML for exchanging entire flight vehicle dynamic simulation models.

Brian, Geoffrey J.↗
DOE OSTI2025

HP-MDR: High-performance and Portable Data Refactoring and Progressive Retrieval with Advanced GPUs

Scientific applications produce vast amounts of data, posing grand challenges in the underlying data management and analytic tasks. Progressive compression is a promising way to address this problem, as it allows for on-demand data retrieval with significantly reduced data movement cost. However, most existing progressive methods are designed for CPUs, leaving a gap for them to unleash the power of today’s heterogeneous computing systems with GPUs.In this work, we propose HP-MDR, a high-performance and portable data refactoring and progressive retrieval framework for GPUs. Our contributions are four-fold: (1) We carefully optimize the bitplane encoding and lossless encoding, two key stages in progressive methods, to achieve high performance on GPUs; (2) We propose pipeline optimization and incorporate it with data refactoring and progressive retrieval workflows to further enhance the performance for large data process; (3) We leverage our framework to enable high-performance data retrieval with guaranteed error control for common Quantities of Interest; (4) We evaluate HP-MDR and compare it with state of the arts using five real-world datasets. Experimental results demonstrate that HP-MDR delivers an average 13.68 × and 6.31 × throughput in data refactoring and progressive retrieval tasks, respectively. It also leads to 11.22 × throughput for recomposing required data representations under Quantity-of-Interest error control and 6.04 × performance for the corresponding end-to-end data retrieval, when compared with state-of-the-art solutions.

Li, Yanliang [University of Oregon]↗
NASA NTRS1974

Skylab report - Man's role in space research

Some of the early results reported by several investigators in the solar physics discipline are described, as well as a subjective response to long-term zero-gravity exposure in several areas related to medical studies. Many of the roles in which man has participated in research aboard Skylab will again be important in future space activities such as the Space Shuttle. Examples are pointing, alignment, transient identification and response, and assurance of data quality. These tasks can be extended to include a greater role in data management and interpretation, so that some selectivity or processing, or both, might be appropriate onboard the spacecraft, prior to transmission of data to the ground.

Garriott, O. K.↗
NASA NTRS1984

Aerothermodynamic Data Base

Space shuttle aerothermodynamic data, collected from a continuing series of wind tunnel tests, are permanently stored with the Data Management Services (DMS) system. Information pertaining to current baseline configuration definition is also stored. A list of documentation of DMS processed data arranged sequentially and by space shuttle configuration is presented. The listing provides an up to date record of all applicable aerothermodynamic data collected, processed, or summarized during the space shuttle program. Tables are designed to provide survey information to the various space shuttle managerial and technical levels.

Source record↗
NASA NTRS1999

A Flight/Ground/Test Event Logging Facility

The onboard control software for spacecraft such as Mars Pathfinder and Cassini is composed of many subsystems including executive control, navigation, attitude control, imaging, data management, and telecommunications. The software in all of these subsystems needs to be instrumented for several purposes: to report required telemetry data, to report warning and error events, to verify internal behavior during system testing, and to provide ground operators with detailed data when investigating in-flight anomalies. Events can range in importance from purely informational events to major errors. It is desirable to provide a uniform mechanism for reporting such events and controlling their subsequent processing. Since radiation-hardened flight processors are several years behind the speed and memory of their commercial cousins, and since most subsystems require real-time control, and since downlink rates to earth can be very low from deep space, there are limits to how much of the data can be saved and transmitted. Some kinds of events are more important than others and should therefore be preferentially retained when memory is low. Some faults can cause an event to recur at a high rate, but this must not be allowed to consume the memory pool. Some event occurrences may be of low importance when reported but suddenly become more important when a subsequent error event gets reported. Some events may be so low-level that they need not be saved and reported unless specifically requested by ground operators.

Dvorak, Daniel↗
NASA NTRS2017

How Accurately Do Maize Crop Models Simulate the Interactions of Atmospheric CO2 Concentration Levels With Limited Water Supply on Water Use and Yield?

This study assesses the ability of 21 crop models to capture the impact of elevated CO2 concentration [CO2] on maize yield and water use as measured in a 2-year Free Air Carbon dioxide Enrichment experiment conducted at the Thunen Institute in Braunschweig, Germany (Manderscheid et al. 2014). Data for ambient [CO2] and irrigated treatments were provided to the 21 models for calibrating plant traits, including weather, soil and management data as well as yield, grain number, above ground biomass, leaf area index, nitrogen concentration in biomass and grain, water use and soil water content. Models differed in their representation of carbon assimilation and evapotranspiration processes. The models reproduced the absence of yield response to elevated [CO2] under well-watered conditions, as well as the impact of water deficit at ambient [CO2], with 50 percent of models within a range of plus/minus 1 Mg ha(exp. -1) around the mean. The bias of the median of the 21 models was less than 1 Mg ha(exp. -1). However under water deficit in one of the two years, the models captured only 30 percent of the exceptionally high [CO2] enhancement on yield observed. Furthermore the ensemble of models was unable to simulate the very low soil water content at anthesis and the increase of soil water and grain number brought about by the elevated [CO2] under dry conditions. Overall, we found models with explicit stomatal control on transpiration tended to perform better. Our results highlight the need for model improvement with respect to simulating transpirational water use and its impact on water status during the kernel-set phase.

grain number↗
NASA NTRSDate not supplied

ICARTT File Format Enhancements: Supporting FAIRness and Data Discovery of Suborbital Campaign Data

Suborbital campaigns aim to accomplish a wide variety of goals and can include a variety of platforms, instruments, and parameters measured. In 2004, the ICARTT (International Consortium for Atmospheric Research on Transport and Transformation) standards were developed to fulfill data management needs for the ICARTT campaign. The ICARTT file format is text-based and composed of a header with important data description information and the data section. Built on the NASA Ames and GTE data formats, the ICARTT format was created to facilitate data exchange and promote collaborations among the science teams for achieving the ICARTT campaign goals. Due to its success and adaptation for use in many other field campaigns, the ICARTT file format became a NASA standard in 2010 and was amended in January 2017. These changes provided many enhancements, including the requirement for variable standard names. Primarily designed for airborne field studies, ICARTT has been further utilized for ground-based studies. NASA has made a commitment to build an inclusive open science community over the next decade. Open-source science strives to make publicly funded scientific research transparent, inclusive, accessible, and reproducible. The ICARTT format can host metadata that is critical for proper use of the data, particularly for in-situ measurements, and can enhance data discovery and accessibility. However, the required fields are often free text, meaning that the information is human readable, but not machine interpretable. Furthermore, the amount and type of information provided can vary significantly between principal investigators and campaigns. To support FAIR principles and interoperability, enhancements to the ICARTT standards are recommended. Possible recommendations include potential use of controlled and consistent vocabulary for variable standard name and certain common metadata elements; standardizing timestamps for easier data comparisons and analysis; and providing guidance on variable measurement units and how they are reported. Enhancing ICARTT metadata can further streamline the process to make suborbital data more readily available to the data user and improve variable-level metadata. Providing more variable-level metadata can enhance data searching and discovery, supporting NASA’s Open-Source Science Initiative (OSSI).

Megan Buzanowicz↗
NASA NTRS2005

Managed Development Environment Successes for MSFC's VIPA Team

This paper outlines the best practices of the Vehicle Design Team for VIPA. VIPA is the Vehicle Integrated Performance Analysis Team at MSFC. This team was created to reconnect the individual engineering disciplines to be able to perform system level technical assessments in support of program decisions. The functions of the VIPA Vehicle Design (VVD) discipline team are to maintain the controlled reference geometry and provide linked, simplified geometry for each of the other discipline analyses. The core of the VVD work, and the approach for VVD s first task of controlling the reference geometry, involves systems engineering, top-down, layout-based CAD modeling within a Product Data Manager (PDM) development environment. The topdown approach allcws for simple contrnl of very large, integrated assemblies and greatly enhances the ability to generate trade configurations and reuse data. The second W D task, model simplification for analysis, is handled within the managed environment through application of the master model concept. In this approach, there is a single controlling, or master, product definition dataset. Connected to this master model are reference datasets with live geometric and expression links. The referenced models can be for drawings, manufacturing, visualization, embedded analysis, or analysis simplification. A discussion of web based interaction, including visualization, between the design and other disciplines is included. Demonstrated examples are cited, including the Space Launch Initiative development cycle, the Saturn V systems integration and verification cycle, an Orbital Space Plane study, and NASA Exploration Office studies of Shuttle derived and clean sheet launch vehicles. The VIPA Team has brought an immense amount of detailed data to bear on program issues. A central piece of that success has been the Managed Development Environment and the VVD Team approach to modeling.

Finckenor, Jeff↗
NASA NTRS1994

The SAX Italian scientific satellite. The on-board implemented automation as a support to the ground control capability

This paper presents the capabilities implemented in the SAX system for an efficient operations management during its in-flight mission. SAX is an Italian scientific satellite for x-ray astronomy whose major mission objectives impose quite tight constraints on the implementation of both the space and ground segment. The most relevant mission characteristics require an operative lifetime of two years, performing scientific observations both in contact and in noncontact periods, with a low equatorial orbit supported by one ground station, so that only a few minutes of communications are available each orbit. This operational scenario determines the need to have a satellite capable of performing the scheduled mission automatically and reacting autonomously to contingency situations. The implementation approach of the on-board operations management, through which the necessary automation and autonomy are achieved, follows a hierarchical structure. This has been achieved adopting a distributed avionic architecture. Nine different on-board computers, in fact, constitute the on-board data management system. Each of them performs the local control and monitors its own functions while the system level control is performed at a higher level by the data handling applications software. The SAX on-board architecture provides the ground operators with different options of intervention by three classes of telecommands. The management of the scientific operations will be scheduled by the operation control center via dedicated operating plans. The SAX satellite flight mode is presently being integrated at Alenia Spazio premises in Turin for a launch scheduled for the end of 1995. Once in orbit, the SAX satellite will be subject to intensive check-out activities in order to verify the required mission performances. An overview of the envisaged procedure and of the necessary on-ground activities is therefore depicted as well.

Martelli, Andrea↗
NASA NTRS1989

Integrating NASA's Land Analysis System (LAS) image processing software with an appropriate Geographic Information System (GIS): A review of candidates in the public domain

A user requirements analysis (URA) was undertaken to determine and appropriate public domain Geographic Information System (GIS) software package for potential integration with NASA's LAS (Land Analysis System) 5.0 image processing system. The necessity for a public domain system was underscored due to the perceived need for source code access and flexibility in tailoring the GIS system to the needs of a heterogenous group of end-users, and to specific constraints imposed by LAS and its user interface, Transportable Applications Executive (TAE). Subsequently, a review was conducted of a variety of public domain GIS candidates, including GRASS 3.0, MOSS, IEMIS, and two university-based packages, IDRISI and KBGIS. The review method was a modified version of the GIS evaluation process, development by the Federal Interagency Coordinating Committee on Digital Cartography. One IEMIS-derivative product, the ALBE (AirLand Battlefield Environment) GIS, emerged as the most promising candidate for integration with LAS. IEMIS (Integrated Emergency Management Information System) was developed by the Federal Emergency Management Agency (FEMA). ALBE GIS is currently under development at the Pacific Northwest Laboratory under contract with the U.S. Army Corps of Engineers' Engineering Topographic Laboratory (ETL). Accordingly, recommendations are offered with respect to a potential LAS/ALBE GIS linkage and with respect to further system enhancements, including coordination with the development of the Spatial Analysis and Modeling System (SAMS) GIS in Goddard's IDM (Intelligent Data Management) developments in Goddard's National Space Science Data Center.

Rochon, Gilbert L.↗
DOE OSTI2024

Enhancing Discoverability and Management of Atmospheric Data at Scale: Solutions from the ARM Data Center

The Atmospheric Radiation Measurement (ARM) is a multi-laboratory and multi-institutional U.S. Department of Energy (DOE) Office of Science National User Facility. The ARM Data Center (ADC), located at Oak Ridge National Laboratory, collects, archives, and shares vast atmospheric data crucial for climate research. The ADC manages over 7 PB of data from 460 instruments worldwide, processing it into more than 11,000 diverse data products using the Network Common Data Form (NetCDF) for machine-independent accessibility. The primary challenge addressed in this paper is the efficient management and distribution of vast and diverse datasets essential for the climate research community, enhancing accessibility through advanced tools like Data Discovery. The ADC has developed advanced infrastructure and software architecture to handle the continuous influx of heterogeneous data to enhance data discoverability, resulting in increased scientific collaboration. In 2023, users from over 34 countries downloaded and utilized ARM data, resulting in 1,455 publications. The ADC’s efforts have significantly improved the discoverability and usability of atmospheric data, fostering extensive scientific research and collaboration. This paper details the solutions implemented by the ADC team for efficient data discovery and distribution, and it demonstrates ARM’s capability of staging processed data for scientific analysis.

Shah, Chirag [ORNL] (ORCID:0000000203145737)↗