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At least 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Development of data processing interpretation and analysis system for the remote sensing of trace atmospheric gas species

Problems associated with the development of the measurement of air pollution from satellites (MAPS) experiment program are addressed. The primary thrust of this research was the utilization of the MAPS experiment data in three application areas: low altitude aircraft flights (one to six km); mid altitude aircraft flights (eight to 12 km); and orbiting space platforms. Extensive research work in four major areas of data management was the framework for implementation of the MAPS experiment technique. These areas are: (1) data acquisition; (2) data processing, analysis and interpretation algorithms; (3) data display techniques; and (4) information production.

Casas, J. C.↗
NASA NTRS1985

Multisensor Data Integration Techniques

The availability of data from sensors operating in several different wavelength regions had led to the development of new techniques and strategies for both data management and image analysis. Work is ongoing to develop computer techniques for analysis of integrated data sets. These techniques include coregistration of multisensor images, rectification of radar images in areas of topographic relief to ensure pixel to pixel registration with planimetric data sets, calibration of data so that signatures can be applied to remote areas, normalization of data acquired with disparate sensors and determination of extended spectral signatures of surface units. In addition, software is being developed to analyze coregistrated digital terrain and image data so that automated stratigraphic and structural analyses can be performed. These software procedures include: strike and dip determination, terrain profile generation, stratigraphic column generation, stratigraphic thickness measurements, structural cross-section generation, and creation of 3-D block diagrams. These techniques were applied to coregistered LANDSAT 4 Thematic Mapper (TM), Thermal Infrared Multispectral Scanner (TIMS), and multipolarization synthetic aperture radar (SAR) data of the Wind River Basin in Wyoming.

Evans, D. L.↗
NASA NTRS1993

A new technology for manufacturing scheduling derived from space system operations

A new technology for producing finite capacity schedules has been developed in response to complex requirements for operating space systems such as the Space Shuttle, the Space Station, and the Deep Space Network for telecommunications. This technology has proven its effectiveness in manufacturing environments where popular scheduling techniques associated with Materials Resources Planning (MRPII) and with factory simulation are not adequate for shop-floor work planning and control. The technology has three components. The first is a set of data structures that accommodate an extremely general description of a factory's resources, its manufacturing activities, and the constraints imposed by the environment. The second component is a language and set of software utilities that enable a rapid synthesis of functional capabilities. The third component is an algorithmic architecture called the Five Ruleset Model which accommodates the unique needs of each factory. Using the new technology, systems can model activities that generate, consume, and/or obligate resources. This allows work-in-process (WIP) to be generated and used; it permits constraints to be imposed or intermediate as well as finished goods inventories. It is also possible to match as closely as possible both the current factory state and future conditions such as promise dates. Schedule revisions can be accommodated without impacting the entire production schedule. Applications have been successful in both discrete and process manufacturing environments. The availability of a high-quality finite capacity production planning capability enhances the data management capabilities of MRP II systems. These schedules can be integrated with shop-floor data collection systems and accounting systems. Using the new technology, semi-custom systems can be developed at costs that are comparable to products that do not have equivalent functional capabilities and/or extensibility.

Hornstein, R. S.↗
NASA NTRS1993

NCDC mass storage systems and technologies

National Climatic Data Center (NCDC) data management issues are discussed, such as nature of holdings, history of the site, popularity of data sets, media/technology used for storage, volume distributed per month, mode of distribution, most frequently encountered problems, type of media requested/used, and evolution of media. Current holdings at NCDC are 107.8 terabytes of digital data and about 0.3 terabytes of manuscript data. The nexrad radar system is expected to generate approximately 88 terabytes per year by 1996.

Davis, Dick↗
NASA NTRS2006

Recent Project Experience Mars Reconnaissance Orbiter (MRO)

This viewgraph presentation reviews the experiences of the Mars Reconnaissance Orbiter (MRO). It includes an overview of the MRO mission; the challenges of data Management and Transport; a representation of the end-to-end flow for the telemetry data; a review of the data issues, and Coherent File Distribution Protocol (CFDP) uses and issues.

Mars Exploration Rover (MER)↗
NASA NTRS2010

Mercury Toolset for Spatiotemporal Metadata

Mercury (http://mercury.ornl.gov) is a set of tools for federated harvesting, searching, and retrieving metadata, particularly spatiotemporal metadata. Version 3.0 of the Mercury toolset provides orders of magnitude improvements in search speed, support for additional metadata formats, integration with Google Maps for spatial queries, facetted type search, support for RSS (Really Simple Syndication) delivery of search results, and enhanced customization to meet the needs of the multiple projects that use Mercury. It provides a single portal to very quickly search for data and information contained in disparate data management systems, each of which may use different metadata formats. Mercury harvests metadata and key data from contributing project servers distributed around the world and builds a centralized index. The search interfaces then allow the users to perform a variety of fielded, spatial, and temporal searches across these metadata sources. This centralized repository of metadata with distributed data sources provides extremely fast search results to the user, while allowing data providers to advertise the availability of their data and maintain complete control and ownership of that data. Mercury periodically (typically daily) harvests metadata sources through a collection of interfaces and re-indexes these metadata to provide extremely rapid search capabilities, even over collections with tens of millions of metadata records. A number of both graphical and application interfaces have been constructed within Mercury, to enable both human users and other computer programs to perform queries. Mercury was also designed to support multiple different projects, so that the particular fields that can be queried and used with search filters are easy to configure for each different project.

Wilson, Bruce E.↗
NASA NTRS2016

Earth Science Data Analytics: Preparing for Extracting Knowledge from Information

Data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information. Data analytics is a broad term that includes data analysis, as well as an understanding of the cognitive processes an analyst uses to understand problems and explore data in meaningful ways. Analytics also include data extraction, transformation, and reduction, utilizing specific tools, techniques, and methods. Turning to data science, definitions of data science sound very similar to those of data analytics (which leads to a lot of the confusion between the two). But the skills needed for both, co-analyzing large amounts of heterogeneous data, understanding and utilizing relevant tools and techniques, and subject matter expertise, although similar, serve different purposes. Data Analytics takes on a practitioners approach to applying expertise and skills to solve issues and gain subject knowledge. Data Science, is more theoretical (research in itself) in nature, providing strategic actionable insights and new innovative methodologies. Earth Science Data Analytics (ESDA) is the process of examining, preparing, reducing, and analyzing large amounts of spatial (multi-dimensional), temporal, or spectral data using a variety of data types to uncover patterns, correlations and other information, to better understand our Earth. The large variety of datasets (temporal spatial differences, data types, formats, etc.) invite the need for data analytics skills that understand the science domain, and data preparation, reduction, and analysis techniques, from a practitioners point of view. The application of these skills to ESDA is the focus of this presentation. The Earth Science Information Partners (ESIP) Federation Earth Science Data Analytics (ESDA) Cluster was created in recognition of the practical need to facilitate the co-analysis of large amounts of data and information for Earth science. Thus, from a to advance science point of view: On the continuum of ever evolving data management systems, we need to understand and develop ways that allow for the variety of data relationships to be examined, and information to be manipulated, such that knowledge can be enhanced, to facilitate science. Recognizing the importance and potential impacts of the unlimited ways to co-analyze heterogeneous datasets, now and especially in the future, one of the objectives of the ESDA cluster is to facilitate the preparation of individuals to understand and apply needed skills to Earth science data analytics. Pinpointing and communicating the needed skills and expertise is new, and not easy. Information technology is just beginning to provide the tools for advancing the analysis of heterogeneous datasets in a big way, thus, providing opportunity to discover unobvious scientific relationships, previously invisible to the science eye. And it is not easy It takes individuals, or teams of individuals, with just the right combination of skills to understand the data and develop the methods to glean knowledge out of data and information. In addition, whereas definitions of data science and big data are (more or less) available (summarized in Reference 5), Earth science data analytics is virtually ignored in the literature, (barring a few excellent sources).

data analytics↗
DOE OSTI2021

ECAR-1930 BASELINE CHARACTERIZATION DATABASE VERIFICATION REPORT - NBG-18 BILLET 635-14

The purpose of this Engineering Calculations and Analysis Report is to present the data being collected in the Baseline Graphite Characterization program, which is directly tasked with supporting the Idaho National Laboratory’s (INL’s) research and development efforts on the Next Generation Nuclear Plant (NGNP)/Very High Temperature Reactor (VHTR). This program is populating a comprehensive database that will reflect the baseline properties of nuclear-grade graphite with regard to individual grade, billet, and position within individual billets. The physical and mechanical property information being collected will be transferred to the NGNP Data Management and Analysis System (NDMAS), and from that database will help populate handbook of property data available to member nations of the Generation IV International Forum (GIF). The transfer of this data from the applicable technical lead to the dissemination databases available to other end users requires a full review of the test procedures and data collection efforts through an analysis of the multiple summary spreadsheets and values being collected. This report represents that analysis for a single billet of nuclear grade graphite (NBG-18 billet 635-14) and facilitates the release of the associated data to the NDMAS custodians.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Baseline Characterization Database Verification Report - PCEA Billet 02S8-5

The purpose of this engineering calculations and analysis report (ECAR) is to present data collected in the Baseline Graphite Characterization Program, which is directly tasked with supporting the Idaho National Laboratory's (INL's) research and development efforts on the Advanced Reactor Technologies (ART) Program. This program populates a comprehensive database that reflects the baseline properties of nuclear-grade graphite regarding individual grade, billet, and position within individual billets. The physical- and mechanical-property information being collected will be transferred to the Nuclear Data Management and Analysis System (NDMAS), and that database will help populate the handbook of property data available to member nations of the Generation-IV International Forum. Transfer of these data from the applicable technical lead to the dissemination databases available to other end users requires a full review of the test procedures and data-collection efforts through an analysis of the multiple summary spreadsheets and values being collected. This report represents the analysis for PCEA Billet 02S8-5 and facilitates release of associated data to the NDMAS custodians.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Baseline Characterization Database Verification Report - PCEA Billet 01S8-9

The purpose of this engineering calculations and analysis report (ECAR) is to present data collected in the Baseline Graphite Characterization Program, which is directly tasked with supporting the Idaho National Laboratory's (INL's) research and development efforts on the Advanced Reactor Technologies (ART) Program. This program populates a comprehensive database that reflects the baseline properties of nuclear-grade graphite with regard to individual grade, billet, and position within individual billets. The physical- and mechanical-property information being collected will be transferred to the Nuclear Data Management and Analysis System (NDMAS), and that database will help populate the handbook of property data available to member nations of the Generation-IV International Forum. Transfer of these data from the applicable technical lead to the dissemination databases available to other end users requires a full review of the test procedures and data-collection efforts through an analysis of the multiple summary spreadsheets and values being collected. This report represents the analysis for PCEA Billet 01S8-9 and facilitates release of associated data to the NDMAS custodians.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Baseline Characterization Database Verification Report ? NBG-17 Billet V104

The purpose of this report is to present data collected in the Baseline Graphite Characterization Program, which is directly tasked with supporting the Idaho National Laboratory’s (INL’s) research and development efforts on the Advanced Reactor Technologies (ART) Program. This program populates a comprehensive database that reflects the baseline properties of nuclear-grade graphite regarding individual grade, billet, and position within individual billets. The physical- and mechanical-property information being collected will be transferred to the Nuclear Data Management and Analysis System (NDMAS), and that database will help populate the handbook of property data available to member nations of the Generation-IV International Forum. Transfer of these data from the applicable technical lead to the dissemination databases available to other end users requires a full review of the test procedures and data-collection efforts through an analysis of the multiple summary spreadsheets and values being collected. This report represents the analysis for NBG-17 Billet V104 and facilitates release of associated data to the NDMAS custodians. Millions of raw data points have been collected during testing and quantification analyses for these billets. The summary scalar property values and supplementary traceability data are collected into comprehensive spreadsheets. Data sets are composed of single billets of graphite for any given grade, organized by mechanical test-specimen type, and further subdivided into individual spreadsheet tabs according to the specific test or evaluation being performed. A direct analysis of properties was not conducted, and this report does not provide information on the validity or performance characteristics of the graphite itself. Rather, this report is intended as a verification of the completeness of actual data collected in accordance with PLN-3467, “Baseline Graphite Characterization Plan: Electromechanical Testing,” [1] and PLN-3348 “Graphite Mechanical Testing” [2] and their representation of the measurement and test results with sole regard to the graphite billets under evaluation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

ECAR: Baseline Characterization Database Verification Report – PCEA Billet 01D3-35

The purpose of this engineering calculations and analysis report (ECAR) is to present data collected in the Baseline Graphite Characterization Program, which is directly tasked with supporting the Idaho National Laboratory’s (INL’s) research and development efforts on the Advanced Reactor Technologies (ART) Program. This program populates a comprehensive database that reflects the baseline properties of nuclear-grade graphite with regard to individual grade, billet, and position within individual billets. The physical- and mechanical-property information collected will be transferred to the Nuclear Data Management and Analysis System (NDMAS), and that database will help populate the handbook of property data available to member nations of the Generation-IV International Forum. Transfer of these data from the applicable technical lead to the dissemination databases available to other end users requires a full review of the test procedures and data-collection efforts through an analysis of the multiple summary spreadsheets and values being collected. This report represents the analysis for PCEA Billet 01D3-35 and facilitates release of associated data to the NDMAS custodians.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1982

Geographic Information Systems for Assessing Existing and Potential Bio-energy Resources: Their Use in Determining Land Use and Management Options which Minimize Ecological and Landscape Impacts in Rural Areas

A management construct is described which forms part of an overall landscape ecological planning model which has as a principal objective the extension of the traditional descriptive land use mapping capabilities of geographic information systems into land management realms. It is noted that geographic information systems appear to be moving to more comprehensive methods of data handling and storage, such as relational and hierarchical data management systems, and a clear need has simultaneously arisen therefore for planning assessment techniques and methodologies which can actually use such complex levels of data in a systematic, yet flexible and scenario dependent way. The descriptive of mapping method proposed broaches such issues and utilizes a current New England bioenergy scenario, stimulated by the use of hardwoods for household heating purposes established in the post oil crisis era and the increased awareness of the possible landscape and ecological ramifications of the continued increasing use of the resource.

Jackman, A. E.↗
NASA NTRS1983

The Network Information Management System (NIMS) in the Deep Space Network

In an effort to better manage enormous amounts of administrative, engineering, and management data that is distributed worldwide, a study was conducted which identified the need for a network support system. The Network Information Management System (NIMS) will provide the Deep Space Network with the tools to provide an easily accessible source of valid information to support management activities and provide a more cost-effective method of acquiring, maintaining, and retrieval data.

Wales, K. J.↗
DOE OSTI2025

A2SD: Accelerating Scientific Innovation Through Autonomous Discovery Systems

The 2025 Advancing Autonomous Scientific Discovery (A2SD) workshop convened researchers from academia, national laboratories, and industry to explore the transformative role of autonomy in scientific discovery. The workshop highlighted a convergence of artificial intelligence, robotics, and computational workflows into autonomous systems capable of accelerating the scientific process. Presentations and discussions spanned autonomous experimentation, intelligent workflow orchestration, digital twins, and agent-based systems for managing complex research ecosystems. Key challenges discussed included interoperability across heterogeneous infrastructures, near real-time data management under FAIR principles, reproducibility, and the integration of human oversight. The workshop also emphasized the need for modular software interfaces, federated learning models, and education initiatives to support a next-generation scientific workforce.

Taufer, Michela [University of Tennessee, Knoxvill↗
DOE OSTI2024

Towards Cross-Facility Workflows Orchestration through Distributed Automation

Modern science relies on end-to-end workflows that incorporate experimental instruments and utilize edge, cloud, or high-performance computing and storage resources. These components are geographically dispersed across various user facilities and interconnected through high-speed networks. In this paper, we present Zambeze, an automated distributed framework designed to facilitate this new class of cross-facility workflows. Utilizing swarm intelligence principles, Zambeze orchestrates science campaigns by managing distributed autonomous agents. These agents can offer a suite of services, including computing, storage, and data management. We demonstrate the feasibility of Zambeze through a real-world application involving electron microscopy, enhanced with Artificial Intelligence capabilities.

Skluzacek, Tyler↗
DOE OSTI2020

Experiences with a Flexible User Research Process to Build Data Change Tools

Scientific software development processes are understood to be distinct from commercial software development practices due to uncertain and evolving states of scientific knowledge. Sustaining these software products is a recognized challenge, but under-examined is the usability and usefulness of such tools to their scientific end users. User research is a well-established set of techniques (e.g., interviews, mockups, usability tests) applied in commercial software projects to develop foundational, generative, and evaluative insights about products and the people who use them. Currently these approaches are not commonly applied and discussed in scientific software development work. The use of user research techniques in scientific environments can be challenging due to the nascent, fluid problem spaces of scientific work, varying scope of projects and their user communities, and funding/economic constraints on projects.In this paper, we reflect on our experiences undertaking a multi-method user research process in the Deduce project. The Deduce project is investigating data change to develop metrics, methods, and tools that will help scientists make decisions around data change. There is a lack of common terminology since the concept of systematically measuring and managing data change is under explored in scientific environments. To bridge this gap we conducted user research that focuses on user practices, needs, and motivations to help us design and develop metrics and tools for data change. This paper contributes reflections and the lessons we have learned from our experiences. We offer key takeaways for scientific software project teams to effectively and flexibly incorporate similar processes into their projects.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

Simulation Of Failures And Repairs

Automated Reliability/Availability/Maintainability (ARAM) computer program one of software tools designed to assess candidate architectures of data-management system of the Space Station. Evaluates reliability, availability, and maintainability characteristcs of conceptual system. Uses data representing redundancy and maintainability characteristics of system, and reliability parameters of components of equipment. Design based upon simulation of failures and possible subsequent repairs of each unit of equipment included in system. Analyzes effects of failures and repairs on system and maintains statistics of behavior of system from which results of simulation obtained. Written for IBM PC XT/AT or compatible computer.

Vallone, Antonio↗