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At least 271 records · Page 15
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NASA NTRS1991

NASA-SETI microwave observing project: Targeted Search Element (TSE)

The Targeted Search Element (TSE) performs one of two complimentary search strategies of the NASA-SETI Microwave Observing Project (MOP): the targeted search. The principle objective of the targeted search strategy is to scan the microwave window between the frequencies of one and three gigahertz for narrowband microwave emissions eminating from the direction of 773 specifically targeted stars. The scanning process is accomplished at a minimum resolution of one or two Hertz at very high sensitivity. Detectable signals will be of a continuous wave or pulsed form and may also drift in frequency. The TSE will possess extensive radio frequency interference (RFI) mitigation and verification capability as the majority of signals detected by the TSE will be of local origin. Any signal passing through RFI classification and classifiable as an extraterrestrial intelligence (ETI) candidate will be further validated at non-MOP observatories using established protocol. The targeted search will be conducted using the capability provided by the TSE. The TSE provides six Targeted Search Systems (TSS) which independently or cooperatively perform automated collection, analysis, storage, and archive of signal data. Data is collected in 10 megahertz chunks and signal processing is performed at a rate of 160 megabits per second. Signal data is obtained utilizing the largest radio telescopes available for the Targeted Search such as those at Arecibo and Nancay or at the dedicated NASA-SETI facility. This latter facility will allow continuous collection of data. The TSE also provides for TSS utilization planning, logistics, remote operation, and for off-line data analysis and permanent archive of both the Targeted Search and Sky Survey data.

Webster, L. D.↗
NASA NTRSDate not supplied

High Performance Access to Archival Data Stored in HDF4 and HDF5 on Cloud Object Stores Without Reformatting the Files

Cloud computing offers numerous advantages for users of extensive Earth science data collections. These benefits encompass direct online access to data files and granules from any location, scalable access supporting parallel computing workflows, and flexible computing tools enabling innovative experimentation with processing techniques. However, older archival file formats designed for distinct computing systems hinder efficient access to decade-long time-series data when compared to data stored in modern cloud-optimized formats like Web Object Stores (WOS), exemplified by Amazon Web Services’ Simple Storage Service (S3). We describe DMR++ (Dataset Metadata Response plus plus), a technology facilitating efficient access to HDF5 (Hierarchical Data Format, version 5) and HDF4 files stored on WOS systems without requiring data reformatting. DMR++ achieves performance comparable to technologies like Zarr while preserving the original file structure, a substantial benefit considering the vast quantity of archival files held by organizations such as NASA. Moreover, DMR++ typically outperforms cloud-optimized versions of HDF5. Essentially an XML (Extensible Markup Language) document usually stored alongside the described data, DMR++ can also be generated on-the-fly but is generally created during data staging to the WOS. Archival files that use HDF4/5 often store large arrays of numerical data. The data in these files is often compressed, typically reducing their size by a factor of four or more. To achieve efficient access to portions of those arrays, they are 'chunked' into smaller sub-arrays, each individually compressed. The chunk size is a compromise, where spinning disks can efficiently access data in smaller chunks while S3 favors larger chunks. A simple optimization of aggregating smaller chunks that are stored adjacently, transferring them in a single access and then individually decompressing them will improve performance. NASA data pose an additional challenge: special Application Programmer Interface (API) libraries are often needed to compute some variables. These libraries are incompatible with WOS environments. Our solution involves storing computed values in the DMR++ document or a companion file, making them accessible like other variables and eliminating the need for specialized APIs. We outline specific optimizations for both satellite grid and swath data stored in HDF4-EOS2 (Earth Observing System).

James Gallagher↗
NASA NTRS1992

Recommendations for a service framework to access astronomical archives

There are a large number of astronomical archives and catalogs on-line for network access, with many different user interfaces and features. Some systems are moving towards distributed access, supplying users with client software for their home sites which connects to servers at the archive site. Many of the issues involved in defining a standard framework of services that archive/catalog suppliers can use to achieve a basic level of interoperability are described. Such a framework would simplify the development of client and server programs to access the wide variety of astronomical archive systems. The primary services that are supplied by current systems include: catalog browsing, dataset retrieval, name resolution, and data analysis. The following issues (and probably more) need to be considered in establishing a standard set of client/server interfaces and protocols: Archive Access - dataset retrieval, delivery, file formats, data browsing, analysis, etc.; Catalog Access - database management systems, query languages, data formats, synchronous/asynchronous mode of operation, etc.; Interoperability - transaction/message protocols, distributed processing mechanisms (DCE, ONC/SunRPC, etc), networking protocols, etc.; Security - user registration, authorization/authentication mechanisms, etc.; Service Directory - service registration, lookup, port/task mapping, parameters, etc.; Software - public vs proprietary, client/server software, standard interfaces to client/server functions, software distribution, operating system portability, data portability, etc. Several archive/catalog groups, notably the Astrophysics Data System (ADS), are already working in many of these areas. In the process of developing StarView, which is the user interface to the Space Telescope Data Archive and Distribution Service (ST-DADS), these issues and the work of others were analyzed. A framework of standard interfaces for accessing services on any archive system which would benefit archive user and supplier alike is proposed.

Travisano, J. J.↗
NASA NTRS2019

Developing a Machine-Learning-Based Processing Framework for Twitter and Other Crowdsourced Data

Crowdsourced data streams such as Twitter and other social media are important sources of real-time and historical global information for Earth science applications. At the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), we have been exploring the Twitter data stream for its potential in augmenting the validation program of NASA's Global Precipitation Measurement (GPM) mission. To realize this potential, we need to increase the information density and enhance the quality of filtered precipitation tweets. We have implemented various components of a machine learning (ML)-based processing infrastructure for crowdsourced data that outputs, in this instance, useful and usable information derived from precipitation tweets. We have test enriched the Twitter stream with higher quality active tweets from those knowingly contributing to our effort and from existing crowdsourced programs (e.g., mPING, CoCoRaHS). We have experimented with various algorithms for processing tweets, including Naà ve Bayes, Convolutional Neural Network (CNN), Hierarchical Attention Network (HAN), and semi-supervised learning (with tri-training). Our current work focuses on (1) automated review of Earth science-related publications to determine relationships between discipline research needs and ML algorithms; (2) investigating Sequential Generative Adversarial Network (SeqGAN) for processing precipitation tweets for anomaly detection; and (3) managing crowdsourced data in a way that is compatible with existing NASA satellite data archives and using the data for ML applications. Key results include (1) network visualization of NLP-processed publications in various Earth science disciplines; (2) difference between GPM-linked, generated tweets and collected actual tweets that is small for GPM-determined light to moderate rain cases and high for GPM-determined heavy rain cases; and (3) identification of MongoDB for storing raw tweets and Zarr format for gridded tweets (compatible with GPM data). Our results have taken us a step closer to an operational ML-based tweet processing infrastructure and have already demonstrated that tweet-derived precipitation information is potentially useful for validation of Earth science satellite data.

Teng, William↗
NASA NTRS1977

Phase fluctuation spectra: New radio science information to become available in the DSN tracking system Mark III-77

An algorithm was developed for the continuous and automatic computation of Doppler noise concurrently at four sample rate intervals, evenly spanning three orders of magnitude. Average temporal Doppler phase fluctuation spectra will be routinely available in the DSN tracking system Mark III-77 and require little additional processing. The basic (noise) data will be extracted from the archival tracking data file (ATDF) of the tracking data management system.

Berman, A. L.↗
NASA NTRS1985

Trajectory reconstruction and aerodynamic results from the first Discovery flight, STS-14(41-D)

Trajectory reconstruction results for the first Discovery flight are presented. Spacecraft dynamic measurements from IMU2 were utilized in conjunction with the ground based tracking data from two S-band stations, eight C-band, and five cameras at Edwards Air Force Base to determine the spacecraft trajectory from epoch through roll-out on Runway 17. Specifics as to the trajectory reconstruction are discussed in Section 1. The final inertial profile is BT14NO2/UN=169750N. Merging of this file with the final LAIRS atmosphere is discussed in Section 2. The final Extended BET is ST14BET/UN=274885C. Section 3 presents plots of relevant parameters from the AEROBET as well as aerodynamic performance comparison results. High frequency files for maneuver extraction were also generated as discussed in Section 4. Appendices are attached which contain: (1) spacecraft and physical parameters utilized, (2) final residuals obtained from the data fitting process, (3) listing of trajectory parameters, and (4) archival information.

Kelly, G. M.↗
NASA NTRS1993

The HYDICE instrument design and its application to planetary instruments

The Hyperspectral Digital Imagery Collection Experiment (HYDICE) instrument represents a significant advance in the state of the art in hyperspectral sensors. It combines a higher signal-to-noise ratio (SNR) and significantly better spatial and spectral resolution and radio metric accuracy than systems flying on aircraft today. The need for 'clean' data, i.e., data free of sampling artifacts and excessive spatial or spectral noise, is a key driver behind the difficult combination of performance requirements laid out for HYDICE. Most of these involve the sensor optics and detector. This paper presents an optimized approach to those requirements, one that comprises push broom scanning, a single, mechanically cooled focal plane, a double-pass prism spectrometer, and an easily fabricated yet wide-field telescope. Central to the approach is a detector array that covers the entire spectrum from 0.4 to 2.5 microns. Among the major benefits conferred by such a design are optical and mechanical simplicity, low polarization sensitivity, and coverage of the entire spectrum without suffering the spectral gaps caused by beam splitters. The overall system minimizes interfaces to the C-141 aircraft on which it will be flown, can be calibrated on the ground and in flight to accuracies better than those required, and is designed for simple, push-button operation. Only unprocessed data are recorded during flight. A ground data processing station provides quick-look, calibration correction, and archiving capabilities, with a throughput better than the requirements. Overall performance of the system is expected to provide the solid database required to evaluate the potential of hyperspectral imagery in a wide variety of applications. HYDICE can be regarded as a test bed for future planetary instruments. The ability to spectrally image a wide field of view over multiple spectral octaves offers obvious advantages and is expected to maximize science return for the required cost and weight.

Basedow, R.↗
NASA NTRS1994

Generic trending and analysis system

The Generic Trending and Analysis System (GTAS) is a generic spacecraft performance monitoring tool developed by NASA Code 511 and Loral Aerosys. It is designed to facilitate quick anomaly resolution and trend analysis. Traditionally, the job of off-line analysis has been performed using hardware and software systems developed for real-time spacecraft contacts; then, the systems were supplemented with a collection of tools developed by Flight Operations Team (FOT) members. Since the number of upcoming missions is increasing, NASA can no longer afford to operate in this manner. GTAS improves control center productivity and effectiveness because it provides a generic solution across multiple missions. Thus, GTAS eliminates the need for each individual mission to develop duplicate capabilities. It also allows for more sophisticated tools to be developed because it draws resources from several projects. In addition, the GTAS software system incorporates commercial off-the-shelf tools software (COTS) packages and reuses components of other NASA-developed systems wherever possible. GTAS has incorporated lessons learned from previous missions by involving the users early in the development process. GTAS users took a proactive role in requirements analysis, design, development, and testing. Because of user involvement, several special tools were designed and are now being developed. GTAS users expressed considerable interest in facilitating data collection for long term trending and analysis. As a result, GTAS provides easy access to large volumes of processed telemetry data directly in the control center. The GTAS archival and retrieval capabilities are supported by the integration of optical disk technology and a COTS relational database management system.

Keehan, Lori↗
NASA NTRS2016

Stewardship of NASA's Earth Science Data and Ensuring Long-Term Active Archives

Program, NASA has followed an open data policy, with non-discriminatory access to data with no period of exclusive access. NASA has well-established processes for assigning and or accepting datasets into one of 12 Distributed Active Archive Centers (DAACs) that are parts of EOSDIS. EOSDIS has been evolving through several information technology cycles, adapting to hardware and software changes in the commercial sector. NASA is responsible for maintaining Earth science data as long as users are interested in using them for research and applications, which is well beyond the life of the data gathering missions. For science data to remain useful over long periods of time, steps must be taken to preserve: (1) Data bits with no corruption, (2) Discoverability and access, (3) Readability, (4) Understandability, (5) Usability' and (6). Reproducibility of results. NASAs Earth Science data and Information System (ESDIS) Project, along with the 12 EOSDIS Distributed Active Archive Centers (DAACs), has made significant progress in each of these areas over the last decade, and continues to evolve its active archive capabilities. Particular attention is being paid in recent years to ensure that the datasets are published in an easily accessible and citable manner through a unified metadata model, a common metadata repository (CMR), a coherent view through the earthdata.gov website, and assignment of Digital Object Identifiers (DOI) with well-designed landing product information pages.

Data Management↗
NASA NTRS2020

Recovery, Restoration and Archiving of Previously Lost Data and Metadata from the Apollo Lunar Surface Experiments Package (ALSEP)

The Apollo Lunar Surface Experiments Package (ALSEP) is the name used to collectively represent the geophysical instruments deployed on the lunar surface by the astronauts on Apollo 12, 14, 15, 16, and 17. These instruments were active from the times of their deployment (November 1969 – December 1972) to September 1977. During that time, fourteen types of experiments were conducted, and their data were transmitted to Earth. The experiment PIs processed them. At the conclusion of the experiments, some of these data were submitted to the NASA Space Science Data Coordinated Archive (NSSDCA) for archiving, while others were not. The raw instrument data received from the Moon prior to March 1976 were not archived, either. The unarchived data, resided on open-reel magnetic tapes, became lost in the decades since, along with much of the metadata (the information necessary/useful in properly processing/analyzing the data). This article retraces the history of the ALSEP data archiving efforts in the 1970s, the subsequent loss of the data tapes, and the search, recovery, and restoration of the lost data by contemporary researchers in the 21st century. In 2006, NSSDCA began reformatting some of the ALSEP data archived in the 1970s to conform with the current Planetary Data System (PDS). In 2010, 440 of the previously lost magnetic tapes containing the raw ALSEP data were recovered. From these tapes, the data were extracted, re-packaged for individual experiments, and, for those with sufficient metadata, processed into higher order data readily usable by researchers. All of these data products have been recently archived with either PDS or NSSDCA. These newly restored data fill a number of gaps in the previously existing archive of the ALSEP data. In addition, tens of thousands of pages of Apollo era documents have been optically scanned and compiled into an online searchable catalog. This article also describes the content, organization, and usage of the restored raw ALSEP data and metadata.

S Nagihara↗
NASA NTRS1997

The Imaging Node for the Planetary Data System

The Planetary Data System Imaging Node maintains and distributes the archives of planetary image data acquired from NASA's flight projects with the primary goal of enabling the science community to perform image processing and analysis on the data. The Node provides direct and easy access to the digital image archives through wide distribution of the data on CD-ROM media and on-line remote-access tools by way of Internet services.

Imaging Node remote sensing↗
NASA NTRS1993

The SSABLE system - Automated archive, catalog, browse and distribution of satellite data in near-real time

Historically, locating and browsing satellite data has been a cumbersome and expensive process. This has impeded the efficient and effective use of satellite data in the geosciences. SSABLE is a new interactive tool for the archive, browse, order, and distribution of satellite date based upon X Window, high bandwidth networks, and digital image rendering techniques. SSABLE provides for automatically constructing relational database queries to archived image datasets based on time, data, geographical location, and other selection criteria. SSABLE also provides a visual representation of the selected archived data for viewing on the user's X terminal. SSABLE is a near real-time system; for example, data are added to SSABLE's database within 10 min after capture. SSABLE is network and machine independent; it will run identically on any machine which satisfies the following three requirements: 1) has a bitmapped display (monochrome or greater); 2) is running the X Window system; and 3) is on a network directly reachable by the SSABLE system. SSABLE has been evaluated at over 100 international sites. Network response time in the United States and Canada varies between 4 and 7 s for browse image updates; reported transmission times to Europe and Australia typically are 20-25 s.

Simpson, James J.↗
NASA NTRS2009

NASA's Earth Observing Data and Information System

NASA's Earth Observing System Data and Information System (EOSDIS) has been a central component of NASA Earth observation program for over 10 years. It is one of the largest civilian science information system in the US, performing ingest, archive and distribution of over 3 terabytes of data per day much of which is from NASA s flagship missions Terra, Aqua and Aura. The system supports a variety of science disciplines including polar processes, land cover change, radiation budget, and most especially global climate change. The EOSDIS data centers, collocated with centers of science discipline expertise, archive and distribute standard data products produced by science investigator-led processing systems. Key to the success of EOSDIS is the concept of core versus community requirements. EOSDIS supports a core set of services to meet specific NASA needs and relies on community-developed services to meet specific user needs. EOSDIS offers a metadata registry, ECHO (Earth Observing System Clearinghouse), through which the scientific community can easily discover and exchange NASA s Earth science data and services. Users can search, manage, and access the contents of ECHO s registries (data and services) through user-developed and community-tailored interfaces or clients. The ECHO framework has become the primary access point for cross-Data Center search-and-order of EOSDIS and other Earth Science data holdings archived at the EOSDIS data centers. ECHO s Warehouse Inventory Search Tool (WIST) is the primary web-based client for discovering and ordering cross-discipline data from the EOSDIS data centers. The architecture of the EOSDIS provides a platform for the publication, discovery, understanding and access to NASA s Earth Observation resources and allows for easy integration of new datasets. The EOSDIS also has developed several methods for incorporating socioeconomic data into its data collection. Over the years, we have developed several methods for determining needs of the user community including use of the American Customer Satisfaction Index and a broad metrics program.

Mitchell, Andrew E.↗
NASA NTRS1981

Satellite and correlative measurements of the stratospheric aerosol. I An optical model for data conversions

A description is presented of an empirically based model of stratospheric aerosol optical properties (size distributions and refractive indices) and their variations. The need for such a model arose in the data validation and archival programs for two satellite sensors, SAM II and SAGE. These programs require the ability to convert measurements of a given aerosol macroproperty (e.g., volume extinction coefficient, volume backscatter coefficient, particle number or mass per unit volume) to best estimates of other aerosol macroproperties, and to assess quantitatively the uncertainties in the conversion process. The described model provides the information on size distributions, refractive indices and their variations necessary for these tasks, and also defines a procedure for combining the model information with empirical data in a way that facilitates automatic data processing. Although the model was developed for use in the satellite validation and archival programs, it also has proven useful in other studies of stratospheric aerosol.

Russell, P. B.↗
NASA NTRS2017

Kepler: A Search for Terrestrial Planets. K2 Handbook

The Kepler spacecraft was repurposed for the K2 mission a year after the failure of the second of Kepler's four reaction wheels in 2013 May. The purpose of this document, the K2 Handbook (K2H), is to describe features of K2 operations, performance, data analysis, and archive products which are common to most K2 campaigns, but different in degree or kind from the corresponding features of the Kepler mission.The K2 Handbook is meant to be read with the following companion documents, which are all publicly available:1. Kepler Instrument Handbook (KSCI-19033) provides information about the design, performance and operational constraints of the instrument and an overview of the types of pixel data that are available.2. Kepler Data Processing Handbook (KSCI-19081) describes how pixels downloaded from the spacecraft are converted by the Kepler Data Processing Pipeline into the data products available at the MAST archive3. Kepler Archive Manual (KDMC-100008) describes the format and content of the data products and how to search for them.4. Kepler Data Characteristics Handbook (KSCI-19040) describes recurring non-astrophysical features of the Kepler data due to instrument signatures, spacecraft events or solar activity and explains how these characteristics are handled by the Kepler pipeline.5. The Ecliptic Plane Input Catalog describes the provenance of the positions and Kepler magnitudes used for target management and aperature photometry.6. K2 Data Release Notes (DRN) are on-line documents available on the K2 science website which describe the data inventory, instrumental signatures and events peculiar to individual observing campaigns.

K2↗
NASA NTRS2018

Generalizing a Data Analysis Pipeline in the Cloud to Handle Diverse Use Cases in NASA's EOSDIS

NASA's Earth Observing System Data and Information System (EOSDIS) is tasked with archiving and distributing Earth Observation data across a range of disciplines, including atmospheric science, oceanography, land processes, natural hazards, solar radiance and even socioeconomic aspects relating to the environment. Driven by rapidly rising data volumes, EOSDIS is migrating to a cloud computing based archive over the next few years. Although this simplifies data management somewhat, the main aim is to provide the data in an environment where end users can bring their analysis to the data rather than attempting to download and manage ever-increasing volumes. To that end, a cloud-based analysis platform is being constructed to enable data transformations, analyses and visualization without egressing the data from the cloud. In this endeavor, we expect a wide variety of users, algorithms and use cases. Consequently, the architecture of this cloud analytics platform is expressly designed to be based on open services, thus fostering an ecosystem that enables the efficient combination of common components with data-specific or analysis-specific components. Reviewed and approved by Andrew Mitchell, ESDIS project manager.

Cloud computing↗
NASA NTRS1987

Mining the IUE archive

The IUE archives are described as well as their applications and possible future developments. The data for each image is archived as a set usually containing a raw image, a processed image, and one or more extracted spectra. A cumulative plot of the number of images which have been retrieved from the IUE archives is provided, indicating that interest in the data continues to grow in all of the astronomical communities served.

Giaretta, David↗
NASA NTRS1996

Incorporating Oracle on-line space management with long-term archival technology

The storage requirements of today's organizations are exploding. As computers continue to escalate in processing power, applications grow in complexity and data files grow in size and in number. As a result, organizations are forced to procure more and more megabytes of storage space. This paper focuses on how to expand the storage capacity of a Very Large Database (VLDB) cost-effectively within a Oracle7 data warehouse system by integrating long term archival storage sub-systems with traditional magnetic media. The Oracle architecture described in this paper was based on an actual proof of concept for a customer looking to store archived data on optical disks yet still have access to this data without user intervention. The customer had a requirement to maintain 10 years worth of data on-line. Data less than a year old still had the potential to be updated thus will reside on conventional magnetic disks. Data older than a year will be considered archived and will be placed on optical disks. The ability to archive data to optical disk and still have access to that data provides the system a means to retain large amounts of data that is readily accessible yet significantly reduces the cost of total system storage. Therefore, the cost benefits of archival storage devices can be incorporated into the Oracle storage medium and I/O subsystem without loosing any of the functionality of transaction processing, yet at the same time providing an organization access to all their data.

Moran, Steven M.↗