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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.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Data systems

The Data Systems Program consists of research and technology devoted to controlling, processing, storing, manipulating, and analyzing space-derived data. The objectives are to provide the technology advancements needed to enable affordable utilization of space-derived data, to increase substantially the capability for future missions of on-board processing and recording and to provide high speed and high volume computational systems anticipated for missions such as the evolutionary Space Station and Earth Observing System. The Data Systems Program supports fundamental research in such areas as laser diodes, supports work to select and provide the appropriate on-board processor technology for future NASA missions, and also supports the development of two flight processors with special architectures.

Smith, Paul H.↗
NASA NTRSDate not supplied

FAIR-ness Assessment of NASA’s Earth Observation System Data and Information System (EOSDIS)

This presentation addresses the challenge of evaluating a multi-disciplinary institutional network of data repositories in operation since 1994 against the relatively recent criteria that constitute FAIR (Findable, Accessible, Interoperable, Reusable) data. NASA’s Earth Observation System Data and Information System (EOSDIS), with its 12 discipline-based Distributed Active Archive Centers (DAACs), preceded the definition and popularization of FAIR by over two decades. An assessment is very useful to describe how well the FAIR principles are met and to identify any improvements needed. In 2020, A “self-assessment” of EOSDIS and DAACs was performed by the ESDIS Project staff and the DAACs from the points of view of human actionability and machine actionability. More recently, a draft of a Science Mission Directorate (SMP) Program Directive (SPD-41a) has been released by NASA Headquarters for comment, where it is recommended that all SMD-funded data should follow the FAIR principles. This presentation is timely to initiate community discussion within the Information Quality Cluster (IQC) of the Earth Science Information Partners (ESIP) and help strategize and develop implementation guidelines for EOSDIS and DAACs to conform to FAIR principles.

Remote sensing↗
NASA NTRS2001

Global Gridded Data from the Goddard Earth Observing System Data Assimilation System (GEOS-DAS)

The Goddard Earth Observing System Data Assimilation System (GEOS-DAS) timeseries is a globally gridded atmospheric data set for use in climate research. This near real-time data set is produced by the Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center in direct support of the operational EOS instrument product generation from the Terra (12/1999 launch), Aqua (05/2002 launch) and Aura (01/2004 launch) spacecrafts. The data is archived in the EOS Core System (ECS) at the Goddard Earth Sciences Data and Information Services Center/Distributed Active Archive Center (GES DISC DAAC). The data is only a selection of the products available from the GEOS-DAS. The data is organized chronologically in timeseries format to facilitate the computation of statistics. GEOS-DAS data will be available for the time period January 1, 2000, through present.

Source record↗
NASA NTRS2018

FAIRness and Usability for Open-Access Omics Data Systems

Omics data sharing is especially crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the "FAIRness" of NASA's GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. 14 metrics. The range of Pass ratings was 29-79% of the 14 metrics, Partial Pass 0-21%, and Fail 7-50%. The range of overall FAIRness scores was 5-12 (out of 14). The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. We propose two new principles that Big Data systems, in particular, should consider for increasing data accessibility. We relate our experiences implementing semantic integration of omics data from several systems for the federated querying and retrieval functions of the GLDS, given the shortcomings in data interoperability of these systems.

Berrios, Daniel C.↗
NASA NTRS1981

Algorithms for onboard orbit estimation with Tracking and Data Relay Satellite System data

An investigation is carried out to determine an appropriate estimation technique for onboard orbit determination using simulated Tracking and Data Relay Satellite System (TDRSS) data. Results are presented from studies done using three estimation techniques: an extended Kalman filter, a consider filter, and a sliding batch differential corrector. These estimators are evaluated when used with both baseline and worst-case TDRSS measurement errors and with tracking configurations for two types of orbits: a high-inclination, near-circular orbit with an altitude of 700 km and a moderately inclined, lower altitude orbit. Each estimation result is evaluated by comparing the true with the estimated ephemeris.

Dunham, J. B.↗
NASA NTRS2018

FAIRness and Usability for Open-access Omics Data Systems

Omics data sharing is crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the "FAIRness" of NASA's GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. The range of overall FAIRness scores was 6-12 (out of 14), average 10.1, and standard deviation 2.4. The range of Pass ratings for the metrics was 29-79%, Partial Pass 0-21%, and Fail 7-50%. The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. Reusability of metadata, in particular, was frequently not well supported. We relate our experiences implementing semantic integration of omics data from some of the assessed systems for federated querying and retrieval functions, given their shortcomings in data interoperability. Finally, we propose two new principles that Big Data system developers, in particular, should consider for maximizing data accessibility.

Berrios, Daniel C.↗
NASA NTRS2018

FAIRness and Usability for Open-access Omics Data Systems

Omics data sharing is crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the “FAIRness” of NASA’s GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. The range of overall FAIRness scores was 6-12 (out of 14), average 10.1, and standard deviation 2.4. The range of Pass ratings for the metrics was 29-79%, Partial Pass 0-21%, and Fail 7-50%. The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. Reusability of metadata, in particular, was frequently not well supported. We relate our experiences implementing semantic integration of omics data from some of the assessed systems for federated querying and retrieval functions, given their shortcomings in data interoperability. Finally, we propose two new principles that Big Data system developers, in particular, should consider for maximizing data accessibility.

Berrios, Daniel C.↗
NASA NTRSDate not supplied

Open-Source Science-led Development of the Atmosphere Observing System (AOS) Mission Science Data System (SDS)

The Earth System Observatory (ESO) Atmosphere Observing System (AOS) mission will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The AOS Science Data System (SDS) will be a system of systems developed within the Cloud to manage the research and operational processing of AOS mission orbital and suborbital sensors and curate these data for reprocessing (e.g., in near real-time or by collection) and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage. Further, AOS SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The AOS mission follows NASA’s lead in making a commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the AOS SDS system components will be developed with open-source concepts including components of SDS itself as well as AOS mission algorithms. Further, the AOS SDS assumes the role to lead and facilitate OSS activities for the AOS mission. This presentation describes the framework of the AOS SDS and its integral part in facilitating OSS within the AOS mission.

David Giles↗
NASA NTRS1990

The Planetary Data System - A solution to data management for the planetary science community

An overview of the first release of the Planetary Data System (PDS) is presented, and some of the challenges encountered during development of the system are described. The principal goals of the PDS are to distribute planetary science data and information about these data to NASA, to provide scientific knowledge to users of these data, and to provide for permanent storage. The current architecture and capabilities of the PDS (Version 1.0) are examined, and some of the special challenges encountered and lessons learned during the application are highlighted. Finally, implications for future versions of the PDS as well as for other science data systems are discussed.

Dobinson, Elaine R.↗
NASA NTRS2002

An Overview of the Earth Observing System MODIS Instrument Performance, Data Systems Performance, and Data Products Status and Availability

The Moderate Resolution Imaging Spectroradiometer (MODIS) on the Earth Observing System (EOS) Terra Mission began to produce data in February 2000. Now, approximately 2 years from that time, the instrument is operating well. All subsystems of the instrument are performing as expected, the signal-to-noise (S/N) performance meets or exceeds specifications, band-to-band registration meets specifications, geodetic registration of observations is nearing 50 meters (one sigma) and the spectral bands are located where they were intended to be pre-launch and attendant gains and offsets are stable to date. The data systems have performed well and are producing a wide variety of data products useful for scientific and applications studies in relatively consistent fashion extending from November 2000 to the present. Within the approximately 40 MODIS data products, several are new and represent powerful and exciting capabilities. The remainder of the MODIS products exceed or, at a minimum, match the capabilities of products from heritage sensors such as, for example, the Advanced Very High Resolution Radiometer (AVHRR). Efforts are underway to provide data sets for the greater Earth science community and to improve access to these products at the various Distributed Active Archive Centers (DAAC's) or through Direct Broadcast (DB) stations. The MODIS instrument on the EOS Aqua mission should also be expected to be in orbit and functioning in the Spring of 2002.

Salomonson, Vincent V.↗
NASA NTRS1989

The Earth Observing System (EOS) SAR ground data system

NASA, in association with ESA and NASDA, will launch the Space Station Freedom in 1993. As a complement to the Space Station, several unmanned Polar-Orbit Platforms (POPs) will be developed, built and launched with suites of instruments devoted to remote-sensing for earth surface and atmosphere observations or to planetary and deep-space studies. Attention is presently given to the POPs-associated Earth Observing System SAR Ground Data System, which encompasses a SAR processor, a postprocessing subsystem, a geophysical processor, and a data management and control subsystem.

Curlander, John C.↗
NASA NTRS1969

Why data system standards?

Data systems coordinating standards developed from experience with STADAN, discussing operating environment and administrative decisions influence on implementation

Coates, R. J.↗
NASA NTRS1980

Systems analysis - Key to NASA's data system planning

Critical steps in the systems analysis process for NASA's data system planning are: (1) compilation of future user/mission requirements, (2) development of alternative overall data system concepts which satisfy requirements, (3) assessment of future development and availability of data system technology, and (4) cost/performance tradeoff studies of the alternative concepts for systems optimization. Tasks within the NEEDS (NASA End-to-End Data System) Program, which correspond to the critical steps in this systems analysis process are examined.

Nelson, R. W.↗