Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Data Center”

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 775 records · Page 43

Preparing the DSN operations concepts

Operations concepts are prepared to support a specific application and can, therefore, be classified accordingly. Studies of NASA and military operations concepts suggest three major types: data services, customer services, and systems oriented. Data services concepts concentrate on data types (e.g., telemetry and command) and how these data are processed and delivered to the user. Such concepts are normally used by data-processing centers to describe data-coding schemes and data formats. Customer services concepts concentrate on the customers' requirements and describe how these requirements are met using the systems available to the operation. Project centers use such concepts to describe the various types of data as they flow from the source (e.g., a spacecraft) to the end user (i.e., the customer). Systems oriented concepts concentrate on the use of systems for processing and delivering customer data. This paper examines the latter type and the 'concepts' that are inherent within them.

Salazar, A. J.↗

Study of data entry requirements at Marshall Space Flight Computation Center

An economic and systems analysis of a data center was conducted. Current facilities for data storage of documentation are shown to be inadequate and outmoded for efficient data handling. Redesign of documents, condensation of the keypunching operation, upgrading of hardware, and retraining of personnel are the solutions proposed to improve the present data system.

Sherman, G. R.↗

Exploring and Analyzing Climate Variations Online by Using NASA MERRA-2 Data at GES DISC

NASA Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) (http:giovanni.sci.gsfc.nasa.govgiovanni) is a web-based data visualization and analysis system developed by the Goddard Earth Sciences Data and Information Services Center (GES DISC). Current data analysis functions include Lat-Lon map, time series, scatter plot, correlation map, difference, cross-section, vertical profile, and animation etc. The system enables basic statistical analysis and comparisons of multiple variables. This web-based tool facilitates data discovery, exploration and analysis of large amount of global and regional remote sensing and model data sets from a number of NASA data centers. Long term global assimilated atmospheric, land, and ocean data have been integrated into the system that enables quick exploration and analysis of climate data without downloading, preprocessing, and learning data. Example data include climate reanalysis data from NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) which provides data beginning in 1980 to present; land data from NASA Global Land Data Assimilation System (GLDAS), which assimilates data from 1948 to 2012; as well as ocean biological data from NASA Ocean Biogeochemical Model (NOBM), which provides data from 1998 to 2012. This presentation, using surface air temperature, precipitation, ozone, and aerosol, etc. from MERRA-2, demonstrates climate variation analysis with Giovanni at selected regions.

knowledge base↗

Regional agriculture surveys using ERTS-1 data

The Center for Remote Sensing Research has conducted studies designed to evaluate the potential application of ERTS data in performing agricultural inventories, and to develop efficient methods of data handling and analysis useful in the operational context for performing large area surveys. This work has resulted in the development of an integrated system utilizing both human and computer analysis of ground, aerial, and space imagery, which has been shown to be very efficient for regional crop acreage inventories. The technique involves: (1) the delineation of ERTS images into relatively homogeneous strata by human interpreters, (2) the point-by-point classification of the area within each strata on the basis of crop type using a human/machine interactive digital image processing system; and (3) a multistage sampling procedure for the collection of supporting aerial and ground data used in the adjustment and verification of the classification results.

Draeger, W. C.↗

Laser ranging data analysis

Center for Space Research efforts have focused on the near real-time analysis of Lageos laser ranging data and on the production of predictive ephemerides. The data are analyzed in terms of range bias, time bias, and internal precision, and estimates for the Earth orientation parameters X(sub p), Y(sub p) and UT1 are obtained. The results of these analyses are reported in a variety of formats. In addition several additional stations began sending not only quick-look observations but also normal points created on-site with new software. These normal points are transmitted in a new standard format different from either current quick-look or MERIT-II full-rate formats. Thus new preprocessing software was written and successfully tested on these data. Inspection of the Bendix produced Lageos full-rate normal points continued, with detailed analyses and filtering of all 1991 A and B release normal points for Lageos through the beginning of 1992. A summary of the combined full-rate and quick-look normal point data set created for 1991 is provided. New long-term ephemerides for Lageos satellite, as well as for Etalon-1 and Etalon-2 (the so-called high satellites used for laser ranging) were produced and distributed to the network stations in cooperation with the Crustal Dynamics Project and Eurolas. These predictions are used by essentially every laser ranging site obtaining regular returns from any of these three satellites.

Source record↗

International GPS Service for Geodynamics

This 1995 annual report of the IGS International GPS (Global Positioning System) Service for Geodynamics - describes the second operational year of the service. It provides the many IGS contributing agencies and the rapidly growing user community with essential information on current organizational and technical matters promoting the IGS standards and products (including organizational framework, data processing strategies, and statistics showing the remarkable expansion of the GPS monitoring network, the improvement of IGS performance, and product quality). It also introduces important practical concepts for network densification by integration of regional stations and the combination of station coordinate solutions. There are groups of articles describing general aspects of the IGS, the Associate Analysis Centers (AACs), Data Centers, and IGS stations.

Zumberge, J. F.↗

Tracking-station coordinates from Geos 1 and Geos 2 optical flash data.

Center-of-mass coordinates for 28 NASA MOTS and SAO Baker-Nunn camera sites have been obtained from optical flash data from Geos 1 (1965 89A) and Geos 2 (1968 002A). More than 25,000 observations in about 100 two-day arcs were used in dynamical solutions (SAO 1969 AGU gravity model). Comparison of results with local survey solutions and with solutions from deep-space vehicle tracking suggests accuracy of about 2 meters in longitude and height and 5 meters in latitude. The relatively larger error in latitude arose from propagation of gravity-model error largely along the track of these high-inclination satellites. The results have also been compared with the solutions of the SAO 1969 standard earth for station coordinates on the North American datum. The solution obtained in the present work is much closer to the survey results in chord length between stations.

Marsh, J. G.↗

Cyber Security: Big Data Think II Working Group Meeting

This presentation focuses on approaches that could be used by a data computation center to identify attacks and ensure malicious code and backdoors are identified if planted in system. The goal is to identify actionable security information from the mountain of data that flows into and out of an organization. The approaches are applicable to big data computational center and some must also use big data techniques to extract the actionable security information from the mountain of data that flows into and out of a data computational center. The briefing covers the detection of malicious delivery sites and techniques for reducing the mountain of data so that intrusion detection information can be useful, and not hidden in a plethora of false alerts. It also looks at the identification of possible unauthorized data exfiltration.

computer security↗

Scaling a Smart Sub-metered Electrical Data Solution for the Center

Currently, there is no single Center-level point solution that enables facility systems data to be collected and stored from buildings on-site, on-demand, and through a faceted search capability that would enable the cultivation of deeper insights into incipient facility-related issues that would otherwise be overlooked. Such insights would represent a powerful and very valuable tool to aid in data-driven decision making and informing actionable steps for remediation and resolution of these problems. Access to electrically sub-metered data via hardware upgrades is in the process of being restored for Building N232, Sustainability Base, but this is only the first step. The native software capabilities that were originally part of a proposed Agencywide Smart Center initiative project can unlock the ability to access actionable insights. This work would also nicely complement many initiatives that are actively being pursued, under consideration, or pending submission to this same call at the Center. This project is poised to support an NRSAA with Verdigris Technologies, as well as in support of an Agencywide Smart Center initiative. Monitoring electrical consumption usage at the most granular level in Bldg. N232 will be instrumental in accurately quantifying potential utility costs and investments, and monitoring usage trends, as it is being converted into hoteling spaces, to help. This will also help with determining how the capability can scale more broadly across the Center and Agency at large.

Rodney Alexander Martin↗

Scaling a Smart Sub-metered Electrical Data Solution for the Center

Currently, there is no single Center-level point solution that enables facility systems data to be collected and stored from buildings on-site, on-demand, and through a faceted search capability that would enable the cultivation of deeper insights into incipient facility-related issues that would otherwise be overlooked. Such insights would represent a powerful and very valuable tool to aid in data-driven decision making and informing actionable steps for remediation and resolution of these problems. Access to electrically sub-metered data via hardware upgrades is in the process of being restored for Building N232, Sustainability Base, but this is only the first step. The native software capabilities that were originally part of a proposed Agencywide Smart Center initiative project can unlock the ability to access actionable insights. This work would also nicely complement many initiatives that are actively being pursued, under consideration, or pending submission to this same call at the Center. This project is poised to support an NRSAA with Verdigris Technologies, as well as in support of an Agencywide Smart Center initiative. Monitoring electrical consumption usage at the most granular level in Bldg. N232 will be instrumental in accurately quantifying potential utility costs and investments, and monitoring usage trends, as it is being converted into hoteling spaces, to help. This will also help with determining how the capability can scale more broadly across the Center and Agency at large.

Rodney Alexander Martin↗

Terrestrial Hydrological Data from NASA's Hydrology Data and Information Services Center (HDISC): Products, Services, and Applications

Terrestrial hydrological variables are important in global hydrology, climate, and carbon cycle studies. The North American and Global Land Data Assimilation Systems (NLDAS and GLDAS, respectively) have been generating a series of land surface states (soil moisture, snow, and temperature) and fluxes (evapotranspiration, radiation, and heat flux) variables. These data, hosted at and available from NASA s Hydrology Data and Information Services Center (HDISC), include the NLDAS hourly 1/8 degree products and the GLDAS 3-hourly 0.25 and 1.0 degree products. HDISC provides easy access and visualization and analysis capabilities for these products, thus reducing the time and resources spent by scientists on data management and facilitating hydrological research. Users can perform spatial and parameter subsetting, data format transformation, and data analysis operations without needing to first download the data. HDISC is continually being developed as a data and services portal that supports weather and climate forecasts, and water and energy cycle research.

Fang, Hongliang↗

Data capture and processing

A systems concept developed in response to the specific requirements imposed by the Space Station and affiliated instrumentation is described. Particular attention is given to those subsystems associated with initial data capture, handling, routing, and distribution control for return link data via the Tracking and Data Relay Satellite System. The conceived approach, designated the Customer Data and Operations System, includes a data interface facility and a data handling center whose functions are data capture, demultiplexing and routing, early preprocessing, and ancillary data handling.

Lyon, John↗

The NASA NEESPI Data Portal: Products, Information, and Services

Studies have indicated that land cover and use changes in Northern Eurasia influence global climate system. However, the procedures are not fully understood and it is challenging to understand the interactions between the land changes in this region and the global climate. Having integrated data collections form multiple disciplines are important for studies of climate and environmental changes. Remote sensed and model data are particularly important die to sparse in situ measurements in many Eurasia regions especially in Siberia. The NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) NEESPI data portal has generated infrastructure to provide satellite remote sensing and numerical model data for atmospheric, land surface, and cryosphere. Data searching, subsetting, and downloading functions are available. ONe useful tool is the Web-based online data analysis and visualization system, Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure), which allows scientists to assess easily the state and dynamics of terrestrial ecosystems in Northern Eurasia and their interactions with global climate system. Recently, we have created a metadata database prototype to expand the NASA NEESPI data portal for providing a venue for NEESPI scientists fo find the desired data easily and leveraging data sharing within NEESPI projects. The database provides product level information. The desired data can be found through navigation and free text search and narrowed down by filtering with a number of constraints. In addition, we have developed a Web Map Service (WMS) prototype to allow access data and images from difference data resources.

Shen, Suhung↗

Distorted radio sources in Abell 2255 - Evidence of intergalactic gas 2.5 to 5 megaparsecs from the cluster center

Spectroscopic data are presented for radio galaxies in the A2255 region. The results indicate that the galaxies associated with distorted radio sources 2.5-5 Mpc projected radius from the cluster center are indeed cluster members. This implies the presence of substantial intergalactic gas 10-20 core radii from the cluster center. Reasonable assumptions concerning the gas distribution result in an estimated minimum mass for the A2255 intracluster gas of 4 x 10 to the 14th solar masses.

Hintzen, P.↗

Global Precipitation Products at NASA GES DISC for Supporting Agriculture Research and Applications

This presentation describes precipitation products available at the NASA GES DISC that support agricultural research. XXXX Key environmental variables for agriculture: precipitation, temperature, water (soil moisture), solar radiation, NDVI, etc. Rainfed agriculture - major farming practices that rely on rainfall for water. Rainfed agriculture: >95% of farmed land (sub- Saharan Africa); 90% (Latin America); 75% (Near East and North Africa); 65% (East Asia); 60% (South Asia). Precipitation is very important for rainfed agriculture. Droughts can cause severe damage. Precipitation information can be used to monitor the growing season. The Goddard Earth Sciences (GES) Data and Information Services Center (DISC), one of 12 NASA data centers, located in Greenbelt, Maryland, USA. The GES DISC is a major data archive center for global precipitation, water & energy cycles, atmospheric composition, and climate variability Global and regional precipitation datasets (satellite-based and data assimilation Data services (subsetting, format conversion, online visualization, etc.) User services are available FAQs, How to (recipes), Glossary, etc. Social media (Twitter, YouTube, User forum) Help desk (phone, email, online feedback) Training materials (ARSET => Applied Remote Sensing Training) Liu,

precipitation↗

Global Precipitation Measurement (GPM) Mission Products and Services at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC)

On February 27, 2014, the NASA Global Precipitation Measurement (GPM) mission was launched to provide the next-generation global observations of rain and snow (http:pmm.nasa.govGPM). The GPM mission consists of an international network of satellites in which a GPM Core Observatory satellite carries both active and passive microwave instruments to measure precipitation and serve as a reference standard, to unify precipitation measurements from a constellation of other research and operational satellites. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) hosts and distributes GPM data within the NASA Earth Observation System Data Information System (EOSDIS). The GES DISC is home to the data archive for the GPM predecessor, the Tropical Rainfall Measuring Mission (TRMM). Over the past 16 years, the GES DISC has served the scientific as well as other communities with TRMM data and user-friendly services. During the GPM era, the GES DISC will continue to provide user-friendly data services and customer support to users around the world. GPM products currently and to-be available include the following: 1. Level-1 GPM Microwave Imager (GMI) and partner radiometer products. 2. Goddard Profiling Algorithm (GPROF) GMI and partner products. 3. Integrated Multi-satellitE Retrievals for GPM (IMERG) products. (early, late, and final)A dedicated Web portal (including user guides, etc.) has been developed for GPM data (http:disc.sci.gsfc.nasa.govgpm). Data services that are currently and to-be available include Google-like Mirador (http:mirador.gsfc.nasa.gov) for data search and access; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion into various formats (e.g., netCDF, HDF, KML (for Google Earth), ASCII); exploration, visualization, and statistical online analysis through Giovanni (http:giovanni.gsfc.nasa.gov); generation of value-added products; parameter and spatial subsetting; time aggregation; regridding; data version control and provenance; documentation; science support for proper data usage, FAQ, help desk; monitoring services (e.g. Current Conditions) for applications.In this presentation, we will present GPM data products and services with examples.

NASA GES DISC↗

Global Precipitation Measurement (GPM) Mission Products and Services at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC)

On February 27, 2014, the NASA Global Precipitation Measurement (GPM) mission was launched to provide the next-generation global observations of rain and snow (http:pmm.nasa.govGPM). The GPM mission consists of an international network of satellites in which a GPM Core Observatory satellite carries both active and passive microwave instruments to measure precipitation and serve as a reference standard, to unify precipitation measurements from a constellation of other research and operational satellites. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) hosts and distributes GPM data within the NASA Earth Observation System Data Information System (EOSDIS). The GES DISC is home to the data archive for the GPM predecessor, the Tropical Rainfall Measuring Mission (TRMM). Over the past 16 years, the GES DISC has served the scientific as well as other communities with TRMM data and user-friendly services. During the GPM era, the GES DISC will continue to provide user-friendly data services and customer support to users around the world. GPM products currently and to-be available include the following:Level-1 GPM Microwave Imager (GMI) and partner radiometer productsLevel-2 Goddard Profiling Algorithm (GPROF) GMI and partner productsLevel-3 daily and monthly productsIntegrated Multi-satellitE Retrievals for GPM (IMERG) products (early, late, and final) A dedicated Web portal (including user guides, etc.) has been developed for GPM data (http:disc.sci.gsfc.nasa.govgpm). Data services that are currently and to-be available include Google-like Mirador (http:mirador.gsfc.nasa.gov) for data search and access; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion into various formats (e.g., netCDF, HDF, KML (for Google Earth), ASCII); exploration, visualization, and statistical online analysis through Giovanni (http:giovanni.gsfc.nasa.gov); generation of value-added products; parameter and spatial subsetting; time aggregation; regridding; data version control and provenance; documentation; science support for proper data usage, FAQ, help desk; monitoring services (e.g. Current Conditions) for applications.

precipitation↗

Proto-Examples of Data Access and Visualization Components of a Potential Cloud-Based GEOSS-AI System

Once a research or application problem has been identified, one logical next step is to search for available relevant data products. Thus, an early component of a potential GEOSS-AI system, in the continuum between observations and end point research, applications, and decision making, would be one that enables transparent data discovery and access by users. Such a component might be effected via the systems data agents. Presumably, some kind of data cataloging has already been implemented, e.g., in the GEOSS Common Infrastructure (GCI). Both the agents and cataloging could also leverage existing resources external to the system. The system would have some means to accept and integrate user-contributed agents. The need or desirability for some data format internal to the system should be evaluated. Another early component would be one that facilitates browsing visualization of the data, as well as some basic analyses.Three ongoing projects at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provide possible proto-examples of potential data access and visualization components of a cloud-based GEOSS-AI system. 1. Reorganizing data archived as time-step arrays to point-time series (data rods), as well as leveraging the NASA Simple Subset Wizard (SSW), to significantly increase the number of data products available, at multiple NASA data centers, for production as on-the-fly (virtual) data rods. SSWs data discovery is based on OpenSearch. Both pre-generated and virtual data rods are accessible via Web services. 2. Developing Web Feature Services to publish the metadata, and expose the locations, of pre-generated and virtual data rods in the GEOSS Portal and enable direct access of the data via Web services. SSW is also leveraged to increase the availability of both NASA and non-NASA data.3.Federating NASA Giovanni (Geospatial Interactive Online Visualization and Analysis Interface), for multi-sensor data exploration, that would allow each cooperating data center, currently the NASA Distributed Active Archive Centers (DAACs), to configure its own Giovanni deployment, while also allowing all the deployments to incorporate each others data. A federated Giovanni comprises Giovanni Virtual Machines, which can be run on local servers or in the cloud.

access↗