Search NASA⌕ Search

SEARCH · Search NASA

Results for “host data”

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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

The Solar-B Mission: First Light, Future Plans and Community Participation

The Solar-B spacecraft was launched from the Uchinoura Space Center into a circular, sun-synchronous, polar orbit by the Japanese Aerospace Exploration Agency in late September 2006. The spacecraft carries thee scientific instruments designed to follow the flow of magnetic energy from the photosphere to the corona to improve our understanding of both steady state and transient energy release. This goal will be achieved through coordinated observations of three highly advanced solar telescopes developed cooperatively by teams from Japan, the United States and the United Kingdom. The three telescopes are a 0.5m aperture, diffraction limited, solar optical telescope (SOT), an X-ray telescope (XRT) designed for full sun imaging with 1.0 arcsec pixels and an EUV imaging spectrometer (EIS) with an order of magnitude improvement in sensitivity over past instruments. The SOT focal plane contains three instruments, a spectropolarimeter for measuring vector magnetic fields, a broadband filter imager for recording images of the photosphere and chromosphere at the highest resolution the telescope is capable of, and a narrow band filter imager that will record Doppler grams and vector magnetograms. The XRT has broad temperature coverage and a spatial a resolution three times as high as Yohkoh. EIS covers a broad range of transition region and coronal temperatures in two spectral bands. Both XRT and EIS have 2 arcsec spatial resolution (1 arcsec pixels). Instrument first light occurred after five weeks on orbit to allow for out gassing and the opening of the telescopes doors. The initial observation sequences are designed to test the functionality of the different operating modes and for calibration. After this commissioning phase is complete a series of observations are planned to demonstrate the ability of the instruments to meet NASA's mission minimum success criteria. Data is downloaded every orbit to the Norwegian high latitude ground station at Svalbard. The data are transmitted to ISAS where they are reformatted into FITS files and archived as Level 0 data on the ISAS DARTS system. Once the initial observation period is complete, approximately six months after launch, the mission data will be open and freely available to researchers shortly after receipt at the DARTS data archive hosted in Japan and at NASA s Solar Data Analysis Center at the Goddard Space Flight Center. Scientific operations will be conducted from the ISAS facility in Sagamihara, Japan and the observatory will become available for performing joint operations with both ground and space based instruments and for conducting observing programs proposed by non-team members. This process will be described together with a status report from the initial operation of the observatory, showing examples of the first observations.

Davis, John M.↗
NASA NTRS2018

Advanced Analytics and Big Earth Data

NASA's Earth Science Data Systems process, archive and distribute petabytes of Earth Observation data to a variety of end users. These end users will face dramatically increased data size in the near future, bringing about new challenges and opportunities in analyzing those data. One area of particular ferment currently is Machine Learning. Many Machine Learning methods are black boxes, limiting direct insight into the data's properties. However, they can be used for a variety of data enhancement purposes, such as parameter retrieval, data fusion and image classification and segmentation. The Earth Observing System Data and Information System is also evolving to host large data volumes in the cloud, enabling data proximal analysis. As part of this effort, an Analytics framework is being developed to support and enhance user analysis of the data. By using standards based services in the framework, diverse user communities can be served, while also allowing inter-system collaboration in the analysis process.

Cloud Computing↗
NASA NTRS2019

Federated Cloud Challenges in NASA's Earth Science Data Systems (Why So Difficult?)

NASA is presented with a number of opportunities and challenges in federating its Earth Science Data Systems in the burgeoning world of cloud computing. Cloud hosting of Earth Science data provides a new way of bringing data together, at least from a virtual location sense, and is one of the main motives for NASA to host data there. However, NASA is also faced with a Big Data Variety challenge, brought on by the variety of the EO datasets in its archives. This diversity requires many diverse science archives to service the different science communities. As a result, nearly every major function in the Earth Observing System Data and Information System (EOSDIS) must also be federated across its data centers. This pattern is repeated with many of the outside agencies and organizations that EOSDIS federates with, such as the Committee for Earth Observing Satellites, leading to pioneering work on "deep federation" in a joint project with the European Space Agency to develop a Multi-Mission Algorithm and Analysis Platform.

Lynnes, Christopher↗
NASA NTRS1993

Lunar Scout Two spacecraft gravity experiment

Measurement of the gravity field of the Moon has a high science priority because of its implications for the internal structure and thermal history of the Moon, and it has a high priority for future exploration activities because of the influence of lunar gravity on spacecraft navigation and orbit maintenance. The current state of knowledge in the lunar gravity field (and the uncertainty in the knowledge) is based primarily on data accumulated from the Lunar Orbiter and Apollo programs. Data are sparse and emphasize the equatorial band (+/- 30 deg) on the near side of the Moon. There are no tracking data on the far side and only the Lunar Orbiter 5 provides a small amount of high inclination data. A host of gravity models developed from different combinations of tracking data have large discrepancies in their predictions of spacecraft motion and orbit lifetimes. There are also large disagreements in the Mercator projections of the gravity acceleration from each model, especially on the far side, where the contours tend to have no obvious relationship with the local topography. The science and engineering requirements for global gravity field mapping will be satisfied with continuous radio metric tracking of Lunar Scout 1 in a low polar orbit using the Deep Space Network and Lunar Scout 2 in a high elliptical orbit. The gravity field of the Moon will be mapped during the Scout Program using a two spacecraft concept. In the two spacecraft concept, one spacecraft is placed in a high altitude eccentric orbit while the second spacecraft is in a low altitude polar orbit. The gravity experiment requires a radio frequency that will permit two-way Doppler tracking between the spacecraft and the Deep Space Network (DSN). Both spacecraft carry NASA standard transponder systems for data transmission to Earth as well as for tracking and orbit determination. Data sufficient to produce a gravity field map could be acquired within one month with this system.

Cheng, Andrew F.↗
NASA NTRS2013

Cloud Absorption Radiometer Autonomous Navigation System - CANS

CAR (cloud absorption radiometer) acquires spatial reference data from host aircraft navigation systems. This poses various problems during CAR data reduction, including navigation data format, accuracy of position data, accuracy of airframe inertial data, and navigation data rate. Incorporating its own navigation system, which included GPS (Global Positioning System), roll axis inertia and rates, and three axis acceleration, CANS expedites data reduction and increases the accuracy of the CAR end data product. CANS provides a self-contained navigation system for the CAR, using inertial reference and GPS positional information. The intent of the software application was to correct the sensor with respect to aircraft roll in real time based upon inputs from a precision navigation sensor. In addition, the navigation information (including GPS position), attitude data, and sensor position details are all streamed to a remote system for recording and later analysis. CANS comprises a commercially available inertial navigation system with integral GPS capability (Attitude Heading Reference System AHRS) integrated into the CAR support structure and data system. The unit is attached to the bottom of the tripod support structure. The related GPS antenna is located on the P-3 radome immediately above the CAR. The AHRS unit provides a RS-232 data stream containing global position and inertial attitude and velocity data to the CAR, which is recorded concurrently with the CAR data. This independence from aircraft navigation input provides for position and inertial state data that accounts for very small changes in aircraft attitude and position, sensed at the CAR location as opposed to aircraft state sensors typically installed close to the aircraft center of gravity. More accurate positional data enables quicker CAR data reduction with better resolution. The CANS software operates in two modes: initialization/calibration and operational. In the initialization/calibration mode, the software aligns the precision navigation sensors and initializes the communications interfaces with the sensor and the remote computing system. It also monitors the navigation data state for quality and ensures that the system maintains the required fidelity for attitude and positional information. In the operational mode, the software runs at 12.5 Hz and gathers the required navigation/attitude data, computes the required sensor correction values, and then commands the sensor to the required roll correction. In this manner, the sensor will stay very near to vertical at all times, greatly improving the resulting collected data and imagery. CANS greatly improves quality of resulting imagery and data collected. In addition, the software component of the system outputs a concisely formatted, high-speed data stream that can be used for further science data processing. This precision, time-stamped data also can benefit other instruments on the same aircraft platform by providing extra information from the mission flight.

Kahle, Duncan↗
NASA NTRS2018

Lessons Learned and Cost Analysis of Hosting a Full Stack Open Data Cube (ODC) Application on the Amazon Web Services (AWS)

The Open Data Cube (ODC) initiative, with support from the Committee on Earth Observation Satellites (CEOS) System Engineering Office (SEO) has developed a state-of-the-art suite of software tools and products to facilitate the analysis of Earth Observation data. This paper presents a short summary and cost analysis of our experience using Amazon Web Services (AWS) to host one such software product, the CEOS Data Cube (CDC) web-based User Interface (UI). In order to provide adaptability, flexibility, scalability, and robustness, we leverage widely-adopted and well-supported technologies such as the Django web framework and the AWS Cloud platform. The UI has empowered users by providing features that assist with streamlining data preparation, data processing, data visualization, and the sub-setting of Analysis Ready Data (ARD) products in order to achieve a wide variety of Earth imaging objectives.

Rizvi, Syed R.↗
NASA NTRS2012

Security Data Warehouse Application

The Security Data Warehouse (SDW) is used to aggregate and correlate all JSC IT security data. This includes IT asset inventory such as operating systems and patch levels, users, user logins, remote access dial-in and VPN, and vulnerability tracking and reporting. The correlation of this data allows for an integrated understanding of current security issues and systems by providing this data in a format that associates it to an individual host. The cornerstone of the SDW is its unique host-mapping algorithm that has undergone extensive field tests, and provides a high degree of accuracy. The algorithm comprises two parts. The first part employs fuzzy logic to derive a best-guess host assignment using incomplete sensor data. The second part is logic to identify and correct errors in the database, based on subsequent, more complete data. Host records are automatically split or merged, as appropriate. The process had to be refined and thoroughly tested before the SDW deployment was feasible. Complexity was increased by adding the dimension of time. The SDW correlates all data with its relationship to time. This lends support to forensic investigations, audits, and overall situational awareness. Another important feature of the SDW architecture is that all of the underlying complexities of the data model and host-mapping algorithm are encapsulated in an easy-to-use and understandable Perl language Application Programming Interface (API). This allows the SDW to be quickly augmented with additional sensors using minimal coding and testing. It also supports rapid generation of ad hoc reports and integration with other information systems.

Vernon, Lynn R.↗
NASA NTRS1990

General-Purpose Serial Interface For Remote Control

Computer controls remote television camera. General-purpose controller developed to serve as interface between host computer and pan/tilt/zoom/focus functions on series of automated video cameras. Interface port based on 8251 programmable communications-interface circuit configured for tristated outputs, and connects controller system to any host computer with RS-232 input/output (I/O) port. Accepts byte-coded data from host, compares them with prestored codes in read-only memory (ROM), and closes or opens appropriate switches. Six output ports control opening and closing of as many as 48 switches. Operator controls remote television camera by speaking commands, in system including general-purpose controller.

Busquets, Anthony M.↗
DOE OSTI2023

Comparative genomics of Mollicutes-related endobacteria supports a late invasion into Mucoromycota fungi

Abstract Diverse members of early-diverging Mucoromycota, including mycorrhizal taxa and soil-associated Mortierellaceae, are known to harbor Mollicutes-related endobacteria (MRE). It has been hypothesized that MRE were acquired by a common ancestor and transmitted vertically. Alternatively, MRE endosymbionts could have invaded after the divergence of Mucoromycota lineages and subsequently spread to new hosts horizontally. To better understand the evolutionary history of MRE symbionts, we generated and analyzed four complete MRE genomes from two Mortierellaceae genera: Linnemannia (MRE-L) and Benniella (MRE-B). These genomes include the smallest known of fungal endosymbionts and showed signals of a tight relationship with hosts including a reduced functional capacity and genes transferred from fungal hosts to MRE. Phylogenetic reconstruction including nine MRE from mycorrhizal fungi revealed that MRE-B genomes are more closely related to MRE from Glomeromycotina than MRE-L from the same host family. We posit that reductions in genome size, GC content, pseudogene content, and repeat content in MRE-L may reflect a longer-term relationship with their fungal hosts. These data indicate Linnemannia and Benniella MRE were likely acquired independently after their fungal hosts diverged from a common ancestor. This work expands upon foundational knowledge on minimal genomes and provides insights into the evolution of bacterial endosymbionts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The Role of Mobility Data Hubs in an Integrated Decarbonized Transportation Future

The landscape for connected mobility ecosystems is evolving rapidly as information and communication technologies lower the cost and complexity of connecting people to places, integrating transportation modes and collecting data regarding such movements. These developments have been key to unlocking new business opportunities, particularly through mobility services. While the mechanisms for data collection, processing, and transfer have made significant advances in the past decade, the broader landscape of mobility data architectures and data users remains largely unresolved. It is unclear as to whether the result will converge towards a framework that resembles a coherent quilt or a disjointed patchwork of competing visions. Initial approaches to mobility data collection and provisioning have been largely siloed - by mode or software - or held for exclusive use, however several key players are quickly realizing the need and opportunities enabled through integrated mobility data eco-systems, or mobility data hubs as referred to in this paper. As the business case for hosting mobility data hubs evolves, there is great uncertainty regarding their impact to either advance or exacerbate sustainable mobility (e.g., seamless connectivity across modes, decreased energy consumption and greenhouse gas emissions, etc.). Groups such as the United Nations and World Bank have identified data platforms as a key enabler of realizing environmental and social benefits. If designed with decarbonization in mind, we hypothesize that enhanced observability provided by these ever-expanding mobility data hubs can facilitate energy and emissions reductions that are otherwise limited by transactional barriers and knowledge asymmetry that is inherent to a more siloed approach. In this sense, integration of mobility data can help to create a competitive playing field where value is not determined by exclusivity of data, but rather the quality and uniqueness of a given service. The goals of this paper are to 1) identify key players and data architectures that are emerging in a service-based mobility market, 2) explore several use cases where mobility data hubs have enabled greater sustainability outcomes, and 3) discuss key issues that will need to be resolved to fully leverage emerging mobility data hubs towards a sustainable transportation future.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗
DOE OSTI2024

Antarctic lake viromes reveal potential virus associated influences on nutrient cycling in ice-covered lakes

The McMurdo Dry Valleys (MDVs) of Antarctica are a mosaic of extreme habitats which are dominated by microbial life. The MDVs include glacial melt holes, streams, lakes, and soils, which are interconnected through the transfer of energy and flux of inorganic and organic material via wind and hydrology. For the first time, we provide new data on the viral community structure and function in the MDVs through metagenomics of the planktonic and benthic mat communities of Lakes Bonney and Fryxell. Viral taxonomic diversity was compared across lakes and ecological function was investigated by characterizing auxiliary metabolic genes (AMGs) and predicting viral hosts. Our data suggest that viral communities differed between the lakes and among sites: these differences were connected to microbial host communities. AMGs were associated with the potential augmentation of multiple biogeochemical processes in host, most notably with phosphorus acquisition, organic nitrogen acquisition, sulfur oxidation, and photosynthesis. Viral genome abundances containing AMGs differed between the lakes and microbial mats, indicating site specialization. Using procrustes analysis, we also identified significant coupling between viral and bacterial communities (p = 0.001). Finally, host predictions indicate viral host preference among the assembled viromes. Collectively, our data show that: (i) viruses are uniquely distributed through the McMurdo Dry Valley lakes, (ii) their AMGs can contribute to overcoming host nutrient limitation and, (iii) viral and bacterial MDV communities are tightly coupled.

Microbiology↗
NASA NTRS2015

International Observe the Moon Night: An Effective Model for Public Engagement with NASA Content

International Observe the Moon Night (InOMN) is an annual world-wide public engagement event designed with the goal of inspiring the public to want to learn more about NASAs contributions to planetary science and exploration, using the Earths Moon as an entryway, and to provide connections to do so [1,2,3]. InOMN will celebrate its 6th anniversary on September 19, 2015.Registration statistics from the past five years show an average of 500 InOMN events are held in 50 countries and 45 U.S. states per year (Figure 1), with over half of the events occurring outside the U.S. Host survey data indicate that approximately 55,000 to 75,000people participate in InOMN events each year. The consistent hosting of InOMN events across the U.S. and around the world indicates an interest by hosts in sharing lunar and planetary science with their local communities, as well as connecting with a larger international group of fellow space enthusiasts on an annual basis.

K-12-Schools↗
DOE OSTI2023

Metagenomic stable isotope probing reveals bacteriophage participation in soil carbon cycling

Soil viruses are important components of the carbon (C) cycle, yet we still know little about viral ecology in soils. We added diverse 13 C-labelled carbon sources to soil and we used metagenomic-SIP to detect 13 C assimilation by viruses and their putative bacterial hosts. These data allowed us to link a 13 C-labelled bacteriophage to its 13 C-labelled Streptomyces putative host, and we used qPCR to track the dynamics of the putative host and phage in response to C inputs. Following C addition, putative host numbers increased rapidly for 3 days, and then more gradually, reaching maximal abundance on Day 6. Viral abundance and virus:host ratio increased dramatically over 6 days, and remained high thereafter (8.42 ± 2.94). From Days 6 to 30, virus:host ratio remained high, while putative host numbers declined more than 50%. Putative host populations were 13 C-labelled on Days 3–30, while 13 C-labelling of phage was detected on Days 14 and 30. This dynamic suggests rapid growth and 13 C-labelling of the host fueled by new C inputs, followed by extensive host mortality driven by phage lysis. Furthermore, these findings indicate that the viral shunt promotes microbial turnover in soil following new C inputs, thereby altering microbial community dynamics, and facilitating soil organic matter production.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

TESS Science Processing Operations Center Pipeline and Data Products

TESS launched 18-4-2018 to conduct a two-year, near all-sky survey for at least 50 nearby exoplanets for which masses can be. TESS just completed surveying the southern hemisphere, identifying hundreds of candidate exoplanet systems and unveiling a plethora of exciting non-exoplanet astrophysics results, such as asteroseismology, asteroids, and supernova. The TESS Science Processing Operations Center (SPOC) at NASA Ames Research Center processes the image data downlinked from TESS every two weeks to generate a variety of data products hosted at the Mikulski Archive for Space Telescopes (MAST). For each ~1 month sector, the SPOC calibrates the image data for both 30-min Full Frame Images (FFIs) and up to 20,000 pre-selected 2-min target star postage stamps. Simple aperture photometry and systematic error-corrected flux time series are generated for the 2-min data. The data products also include co-trending basis vectors (CBVs) and calibration files, such as the Pixel Response Functions (PRF). The archival files are modeled after Kepler's for ease of use, and include Target Pixel Files (TPFs) containing original and calibrated 2-min image data, Light Curve files (LCs) containing the photometric time series for each 2-min target, as well as the Data Validation products. New products derived from the FFIs include light curves for the 2-min targets and CBVs. The TESS Mission is funded by NASA's Science Mission Directorate as an Astrophysics Explorer Mission.

Jenkins, Jon M.↗
DOE OSTI2020

Utah FORGE: Microseismic Monitoring Geophone Data from Well 78-32

This submission includes geophone data collected by Schlumberger from Utah FORGE Phase 2C seismic monitoring well 78-32 during stimulation testing of well 58-32. The data are hosted by the Center for High Performance Computing (CHPC) at the University of Utah, and a script for downloading the data is attached. Additional survey info and tips for running the script are included in the document below.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

IDB Database Tables

The International Database of Reference Gamma-Ray Spectra of Various Nuclear Matter is designed to hold curated gamma spectral data is hosted by the International Atomic Energy Agency on its public facing web site. The database used to hold the spectral data was designed by Sandia National Labs under the auspices of the State Department’s Support Program. This document describes the tables and entity relationships that make up the database.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2019

TESS Science Processing Operations Center Pipeline and Data Products

TESS (Transiting Exoplanet Survey Satellite) launched on 18-4-2018 to conduct a two-year, near all-sky survey for at least 50 nearby exoplanets for which masses can be obtained. TESS just completed surveying the southern hemisphere, identifying hundreds of candidate exoplanet systems and unveiling a plethora of exciting non-exoplanet astrophysics results, such as asteroseismology, asteroids, and supernova. The TESS Science Processing Operations Center (SPOC) at NASA Ames Research Center processes the image data downlinked from TESS every two weeks to generate a variety of data products hosted at the Mikulski Archive for Space Telescopes (MAST). For each approximately 1-month sector, the SPOC calibrates the image data for both 30-minute Full Frame Images (FFIs) and up to 20,000 pre-selected 2-minute target star postage stamps. Simple aperture photometry and systematic error-corrected flux-time series are generated for the 2-minute data. The data products also include co-trending basis vectors (CBVs) and calibration files, such as the Pixel Response Functions (PRF). The archival files are modeled after Kepler's for ease of use, and include Target Pixel Files (TPFs) containing original and calibrated 2-minute image data, Light Curve files (LCs) containing the photometric time series for each 2-minute target, as well as the Data Validation products. New products derived from the FFIs include light curves for the 2-minute targets and CBVs. The TESS Mission is funded by NASA's Science Mission Directorate as an Astrophysics Explorer Mission.

Science Pipeline↗
NASA NTRS2019

TESS Science Processing Operations Center Pipeline and Data Products

TESS launched 18 April 2018 to conduct a two-year, near all-sky survey for at least 50 small, nearby exoplanets for which masses can be ascertained and whose atmospheres can be characterized by ground- and space-based follow-on observations. TESS just completed its survey of the southern hemisphere, identifying >600 candidate exoplanets and unveiling a plethora of exciting non-exoplanet astrophysics results, such as asteroseismology, asteroids, and supernova. The TESS Science Processing Operations Center (SPOC) processes the data downlinked every two weeks to generate a range of data products hosted at the Mikulski Archive for Space Telescopes (MAST). For each sector (~1 month) of observations, the SPOC calibrates the image data for both 30-min Full Frame Images (FFIs) and up to 20,000 pre-selected 2-min target star postage stamps. Data products for the 2-min targets include simple aperture photometry and systematic error-corrected flux time series. The SPOC also conducts searches for transiting exoplanets in the 2-min data for each sector and generates Data Validation time series and associated reports for each transit-like feature identified in the search. Multi-sector searches for exoplanets are conducted periodically to discover longer period planets, including those in the James Webb Continuous Viewing Zone (CVZ), which are observed for up to one year. Data products also include co-trending basis vectors (CBVs) and calibration files, such as the Pixel Response Functions across the field of view of each of TESS's four cameras. To maximize the usability, the TESS science data products are modeled after those for Kepler, including Target Pixel Files and Light Curve files.In this talk, I describe the SPOC pipeline and the chief differences between the TESS and the Kepler pipelines, and the major updates to the SPOC pipeline (4.0) available now to the community at MAST. I also discuss the documentation available to the community to help them in properly interpreting and analyzing the TESS data products.The TESS Mission is funded by NASA's Science Mission Directorate as an Astrophysics Explorer Mission.

Jenkins, Jon M.↗