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At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

User Needs and Assessing the Impact of Low Latency NASA Earth Observation Data Availability on Societal Benefit

Since the advent of NASA's Earth Observing System, knowledge of the practical benefits of Earth science data has grown considerably. The community using NASA Earth science observations in applications has grown significantly, with increasing sophistication to serve national interests. Data latency, or how quickly communities receive science observations after acquisition, can have a direct impact on the applications and usability of the information. This study was conducted to determine how users are incorporating NASA data into applications and operational processes to benefit society beyond scientific research, as well as to determine the need for data latency of less than 12 h. The results of the analysis clearly show the significant benefit to society of serving the needs of the agricultural, emergency response, environmental monitoring and weather communities who use rapidly delivered, accurate Earth science data. The study also showed the potential of expanding the communities who use low latency NASA science data products to provide new ways of transforming data into information. These benefits can be achieved with a clear and consistent NASA policy on product latency.

NASA↗
NASA NTRS2014

Preparing Earth Data Scientists for 'The Sexiest Job of the 21st Century'

What Exactly do Earth Data Scientists do, and What do They Need to Know, to do It? There is not one simple answer, but there are many complex answers. Data Science, and data analytics, are new and nebulas, and takes on different characteristics depending on: The subject matter being analyzed, the maturity of the research, and whether the employed subject specific analytics is descriptive, diagnostic, discoveritive, predictive, or prescriptive, in nature. In addition, in a, thus far, business driven paradigm shift, university curriculums teaching data analytics pertaining to Earth science have, as a whole, lagged behind, andor have varied in approach.This presentation attempts to breakdown and identify the many activities that Earth Data Scientists, as a profession, encounter, as well as provide case studies of specific Earth Data Scientist and data analytics efforts. I will also address the educational preparation, that best equips future Earth Data Scientists, needed to further Earth science heterogeneous data research and applications analysis. The goal of this presentation is to describe the actual need for Earth Data Scientists and the practical skills to perform Earth science data analytics, thus hoping to initiate discussion addressing a baseline set of needed expertise for educating future Earth Data Scientists.

data analytics↗
NASA NTRS2008

Mars Interoperability 2008-2015: Options for Relay Orbiter Support to Mars Bound Assets

The current relay orbiter infrastructure at Mars, in support of the user assets presently at Mars and those scheduled for the 2008 to 2015 time frame, only have a need to store-and-forward the returned data collected by an asset to Earth as a single non-prioritized data file. In the forward direction, the relay orbiters are only required to relay the forward link data, i.e., command sequences, software and configuration information assembled on the ground, to the Asset. There are currently no requirements for status/control messages or files to be sent in the return direction from an Asset to an application located on the Relay, nor are there requirements in the forward direction to send status/control messages or files originating on a Relay to an Asset. In addition there are currently no networking requirements at Mars where data originally sent by an Asset is to be delivered to another user asset. However, we foresee the day when standard services for 1) on-board file prioritization of user asset data by a Relay, 2) control/status message transfer between assets and a Relay, and 3) networking between assets i.e., Asset to Asset message/file transfer via a Relay will be required. Each of these services will require the Relay to be capable of understanding the data type and routing needs of the user asset data and be capable of processing it for these purposes. This paper will focus on the innovative enhancements required to the existing communications infrastructure at Mars to enable these future services.

File Transfer↗
NASA NTRS1982

Data vs. information: A system paradigm

The data system designer requires data parameters, and is dependent on the user to convert information needs to these data parameters. This conversion will be done with more or less accuracy, beginning a chain of inaccuracies which propagate through the system, and which, in the end, may prevent the user from converting the data received into the information required. The concept to be pursued is that errors occur in various parts of the system, and, having occurred, propagate to the end. Modeling of the system may allow an estimation of the effects at any point and the final accumulated effect, and may prove a method of allocating an error budget among the system components. The selection of the various technical parameters which a data system must meet must be done in relation to the ability of the user to turn the cold, impersonal data into a live, personal decision or piece of information.

Billingsley, F. C.↗
NASA NTRS1982

Information Science Panel joint meeting with Imaging Science Panel

Specific activity in information extraction science (taken to include data handling) is needed to: help identify the bounds of practical missions; identify potential data handling and analysis scenarios; identify the required enabling technology; and identify the requirements for a design data base to be used by the disciplines in determining potential parameters for future missions. It was defined that specific analysis topics were a function of the discipline involved, and therefore no attempt was made to define any specific analysis developments required. Rather, it was recognized that a number of generic data handling requirements exist whose solutions cannot be typically supported by the disciplines. The areas of concern were therefore defined as: data handling aspects of system design considerations; enabling technology for data handling, with specific attention to rectification and registration; and enabling technology for analysis. Within each of these areas, the following topics were addressed: state of the art (current status and contributing factors); critical issues; and recommendations for research and/or development.

Source record↗
NASA NTRS2000

Coronal Physics and the Chandra Emission Line Project

With the launch of the Chandra X-ray Observatory, high resolution X-ray spectroscopy of cosmic sources has begun. Early, deep observations of three stellar coronal sources Capella, Procyon, and HR 1099 are providing not only invaluable calibration data, but also benchmarks for plasma spectral models. These models are needed to interpret data from stellar coronae, galaxies and clusters of galaxies, supernova, remnants and other astrophysical sources. They have been called into question in recent years as problems with understanding low resolution ASCA and moderate resolution Extreme Ultraviolet Explorer Satellite (EUVE) data have arisen. The Emission Line Project is a collaborative effort, to improve the models, with Phase I being the comparison of models with observed spectra of Capella, Procyon, and HR 1099. Goals of these comparisons are (1) to determine and verify accurate and robust diagnostics and (2) to identify and prioritize issues in fundamental spectroscopy which will require further theoretical and/or laboratory work. A critical issue in exploiting the coronal data for these purposes is to understand the extent, to which common simplifying assumptions (coronal equilibrium, negligible optical depth) apply. We will discuss recent, advances in our understanding of stellar coronae, in this context.

Brickhouse, N. S.↗
NASA NTRS2019

Big Data, Cloud, and Earth Science

Given the reality of a Big Data future, we need to reevaluate our ability to quickly process immense amounts of data while maintaining our responsibility of stewarding our archives. At National Aeronautics and Space Administration (NASA), our Science Missions Directorate and Earth Science Data Systems have been exploring the commercial cloud as a potential mechanism for data ingest, archive, and distribution since 2015. This talk will discuss our timeline and strategies being employed and will discuss the process of introducing commercial cloud entities into a largely on-premise hardware-reliant approach to ingest, archive, and distribution. We will address topics such as vendor lock-in, varying compute and costing strategies, and end-user adoption. Please join us for an open and authentic conversation about the opportunities we are embracing and the risks we are undertaking as a part of this evolution.

Informatics↗
NASA NTRS2005

NASA Earth Sciences Data Support System and Services for the Northern Eurasia Earth Science Partnership Initiative

The presentation describes data management of NASA remote sensing data for Northern Eurasia Earth Science Partnership Initiative (NEESPI). Many types of ground and integrative (e.g., satellite, GIs) data will be needed and many models must be applied, adapted or developed for properly understanding the functioning of Northern Eurasia cold and diverse regional system. Mechanisms for obtaining the requisite data sets and models and sharing them among the participating scientists are essential. The proposed project targets integration of remote sensing data from AVHRR, MODIS, and other NASA instruments on board US- satellites (with potential expansion to data from non-US satellites), customized data products from climatology data sets (e.g., ISCCP, ISLSCP) and model data (e.g., NCEPNCAR) into a single, well-architected data management system. It will utilize two existing components developed by the Goddard Earth Sciences Data & Information Services Center (GES DISC) at the NASA Goddard Space Flight Center: (1) online archiving and distribution system, that allows collection, processing and ingest of data from various sources into the online archive, and (2) user-friendly intelligent web-based online visualization and analysis system, also known as Giovanni. The former includes various kinds of data preparation for seamless interoperability between measurements by different instruments. The latter provides convenient access to various geophysical parameters measured in the Northern Eurasia region without any need to learn complicated remote sensing data formats, or retrieve and process large volumes of NASA data. Initial implementation of this data management system will concentrate on atmospheric data and surface data aggregated to coarse resolution to support collaborative environment and climate change studies and modeling, while at later stages, data from NASA and non-NASA satellites at higher resolution will be integrated into the system.

Leptoukh, Gregory↗
NASA NTRS1988

Wide band data collection system

The Incorporated Research Institutes for Seismology (IRIS) approached NASA Headquarters in 1986 about the need to collect data daily from seismic stations around the world as part of the Earth Observing System (EOS) mission. A typical IRIS Seismic Station generates 16 Megabytes of data per day when there is seismic activity. The Preliminary Design Parameters of the Wide Band Data Collection System are summarized.

Turkiewicz, J. M.↗
NASA NTRS1984

CAD/CAM data management

The role of data base management in CAD/CAM, particularly for geometric data is described. First, long term and short term objectives for CAD/CAM data management are identified. Second, the benefits of the data base management approach are explained. Third, some of the additional work needed in the data base area is discussed.

Bray, O. H.↗
NASA NTRS1988

The IBM PC at NASA Ames

Like many large companies, Ames relies very much on its computing power to get work done. And, like many other large companies, finding the IBM PC a reliable tool, Ames uses it for many of the same types of functions as other companies. Presentation and clarification needs demand much of graphics packages. Programming and text editing needs require simpler, more-powerful packages. The storage space needed by NASA's scientists and users for the monumental amounts of data that Ames needs to keep demand the best database packages that are large and easy to use. Availability to the Micom Switching Network combines the powers of the IBM PC with the capabilities of other computers and mainframes and allows users to communicate electronically. These four primary capabilities of the PC are vital to the needs of NASA's users and help to continue and support the vast amounts of work done by the NASA employees.

Peredo, James P.↗
NASA NTRS1992

Data Distribution Satellite

The Data Distribution Satellite (DDS) is described in terms of its role in providing space-data and communication services for the National Research and Education Network. The DDS is envisioned as a processing link in the microwave network that would connect academic, industrial, and government institutions to a high-data-rate service of space data. The general need for science communications is assessed, and it is shown that the data potential exceeds the available spectrum. The DDS could act as a bridge between terrestrial facilities the space network, and other space platforms to provide efficient access to space science data. Government demand for this type of data is high suggesting that the DDS could make use of hopping beams to provide more data at reduced costs.

Stevens, Grady H.↗
NASA NTRS2001

Large Engine Technology (LET) Task XXXVII Low-Bypass Ratio Mixed Turbofan Engine Subsonic Jet Noise Reduction Program Test Report

NASA Glenn Research Center supported a three year effort to develop the technology for reducing jet noise from low-bypass ratio engines. This effort concentrated on both analytical and experimental approaches using various mixer designs. CFD and MGB predictions are compared with LDV and noise data, respectively. While former predictions matched well with data, experiment shows a need for improving the latter predictions. Data also show that mixing noise can be sensitive to engine hardware upstream of the mixing exit plane.

Hauser, Joseph R.↗
NASA NTRS2011

Improving Data Collection and Analysis Interface for the Data Acquisition Software of the Spin Laboratory at NASA Glenn Research Center

In jet engines, turbines spin at high rotational speeds. The forces generated from these high speeds make the rotating components of the turbines susceptible to developing cracks that can lead to major engine failures. The current inspection technologies only allow periodic examinations to check for cracks and other anomalies due to the requirements involved, which often necessitate entire engine disassembly. Also, many of these technologies cannot detect cracks that are below the surface or closed when the crack is at rest. Therefore, to overcome these limitations, efforts at NASA Glenn Research Center are underway to develop techniques and algorithms to detect cracks in rotating engine components. As a part of these activities, a high-precision spin laboratory is being utilized to expand and conduct highly specialized tests to develop methodologies that can assist in detecting predetermined cracks in a rotating turbine engine rotor. This paper discusses the various features involved in the ongoing testing at the spin laboratory and elaborates on its functionality and on the supporting data system tools needed to enable successfully running optimal tests and collecting accurate results. The data acquisition system and the associated software were updated and customized to adapt to the changes implemented on the test rig system and to accommodate the data produced by various sensor technologies. Discussion and presentation of these updates and the new attributes implemented are herein reported

Abdul-Aziz, Ali↗
NASA NTRS2012

Continental-Scale Validation of Modis-Based and LEDAPS Landsat ETM + Atmospheric Correction Methods

The potential of Landsat data processing to provide systematic continental scale products has been demonstratedby several projects including the NASA Web-enabled Landsat Data (WELD) project. The recent freeavailability of Landsat data increases the need for robust and efficient atmospheric correction algorithms applicableto large volume Landsat data sets. This paper compares the accuracy of two Landsat atmospheric correctionmethods: a MODIS-based method and the Landsat Ecosystem Disturbance Adaptive ProcessingSystem (LEDAPS) method. Both methods are based on the 6SV radiative transfer code but have different atmosphericcharacterization approaches. The MODIS-based method uses the MODIS Terra derived dynamicaerosol type, aerosol optical thickness, and water vapor to atmospherically correct ETM+ acquisitions ineach coincident orbit. The LEDAPS method uses aerosol characterizations derived independently from eachLandsat acquisition and assumes a fixed continental aerosol type and uses ancillary water vapor. Validationresults are presented comparing ETM+ atmospherically corrected data generated using these two methodswith AERONET corrected ETM+ data for 95 10 km10 km 30 m subsets, a total of nearly 8 million 30 mpixels, located across the conterminous United States. The results indicate that the MODIS-based methodhas better accuracy than the LEDAPS method for the ETM+ red and longer wavelength bands.

Atmospheric correction↗