SEARCH · Search NASA

Results for “Data archiving software”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13

All sources NASA NTRS DOE OSTI

NASA NTRS2011

PDS4: Developing the Next Generation Planetary Data System

The Planetary Data System (PDS) is in the midst of a major upgrade to its system. This upgrade is a critical modernization of the PDS as it prepares to support the future needs of both the mission and scientific community. It entails improvements to the software system and the data standards, capitalizing on newer, data system approaches. The upgrade is important not only for the purpose of capturing results from NASA planetary science missions, but also for improving standards and interoperability among international planetary science data archives. As the demands of the missions and science community increase, PDS is positioning itself to evolve and meet those demands.

Crichton, D.↗

NASA NTRS1992

System of Experts for Intelligent Data Management (SEIDAM)

It is proposed to conduct research and development on a system of expert systems for intelligent data management (SEIDAM). CCRS has much expertise in developing systems for integrating geographic information with space and aircraft remote sensing data and in managing large archives of remotely sensed data. SEIDAM will be composed of expert systems grouped in three levels. At the lowest level, the expert systems will manage and integrate data from diverse sources, taking account of symbolic representation differences and varying accuracies. Existing software can be controlled by these expert systems, without rewriting existing software into an Artificial Intelligence (AI) language. At the second level, SEIDAM will take the interpreted data (symbolic and numerical) and combine these with data models. At the top level, SEIDAM will respond to user goals for predictive outcomes given existing data. The SEIDAM Project will address the research areas of expert systems, data management, storage and retrieval, and user access and interfaces.

Goodenough, David G.↗

NASA NTRS1993

System of experts for intelligent data management (SEIDAM)

A proposal to conduct research and development on a system of expert systems for intelligent data management (SEIDAM) is being developed. CCRS has much expertise in developing systems for integrating geographic information with space and aircraft remote sensing data and in managing large archives of remotely sensed data. SEIDAM will be composed of expert systems grouped in three levels. At the lowest level, the expert systems will manage and integrate data from diverse sources, taking account of symbolic representation differences and varying accuracies. Existing software can be controlled by these expert systems, without rewriting existing software into an Artificial Intelligence (AI) language. At the second level, SEIDAM will take the interpreted data (symbolic and numerical) and combine these with data models. at the top level, SEIDAM will respond to user goals for predictive outcomes given existing data. The SEIDAM Project will address the research areas of expert systems, data management, storage and retrieval, and user access and interfaces.

Goodenough, David G.↗

NASA NTRS2016

EVA Wiki - Transforming Knowledge Management for EVA Flight Controllers and Instructors

The EVA (Extravehicular Activity) Wiki was recently implemented as the primary knowledge database to retain critical knowledge and skills in the EVA Operations group at NASA's Johnson Space Center by ensuring that information is recorded in a common, searchable repository. Prior to the EVA Wiki, information required for EVA flight controllers and instructors was scattered across different sources, including multiple file share directories, SharePoint, individual computers, and paper archives. Many documents were outdated, and data was often difficult to find and distribute. In 2011, a team recognized that these knowledge management problems could be solved by creating an EVA Wiki using MediaWiki, a free and open-source software developed by the Wikimedia Foundation. The EVA Wiki developed into an EVA-specific Wikipedia on an internal NASA server. While the technical implementation of the wiki had many challenges, the one of the biggest hurdles came from a cultural shift. Like many enterprise organizations, the EVA Operations group was accustomed to hierarchical data structures and individually-owned documents. Instead of sorting files into various folders, the wiki searches content. Rather than having a single document owner, the wiki harmonized the efforts of many contributors and established an automated revision control system. As the group adapted to the wiki, the usefulness of this single portal for information became apparent. It transformed into a useful data mining tool for EVA flight controllers and instructors, and also for hundreds of other NASA and contract employees. Program managers, engineers, astronauts, flight directors, and flight controllers in differing disciplines now have an easier-to-use, searchable system to find EVA data. This paper presents the benefits the EVA Wiki has brought to NASA's EVA community, as well as the cultural challenges it had to overcome.

Johnston, Stephanie↗

NASA NTRS2016

EVA Wiki - Transforming Knowledge Management for EVA Flight Controllers and Instructors

The EVA Wiki was recently implemented as the primary knowledge database to retain critical knowledge and skills in the EVA Operations group at NASA's Johnson Space Center by ensuring that information is recorded in a common, easy to search repository. Prior to the EVA Wiki, information required for EVA flight controllers and instructors was scattered across different sources, including multiple file share directories, SharePoint, individual computers, and paper archives. Many documents were outdated, and data was often difficult to find and distribute. In 2011, a team recognized that these knowledge management problems could be solved by creating an EVA Wiki using MediaWiki, a free and open-source software developed by the Wikimedia Foundation. The EVA Wiki developed into an EVA-specific Wikipedia on an internal NASA server. While the technical implementation of the wiki had many challenges, one of the biggest hurdles came from a cultural shift. Like many enterprise organizations, the EVA Operations group was accustomed to hierarchical data structures and individually-owned documents. Instead of sorting files into various folders, the wiki searches content. Rather than having a single document owner, the wiki harmonized the efforts of many contributors and established an automated revision controlled system. As the group adapted to the wiki, the usefulness of this single portal for information became apparent. It transformed into a useful data mining tool for EVA flight controllers and instructors, as well as hundreds of others that support the EVA. Program managers, engineers, astronauts, flight directors, and flight controllers in differing disciplines now have an easier-to-use, searchable system to find EVA data. This paper presents the benefits the EVA Wiki has brought to NASA's EVA community, as well as the cultural challenges it had to overcome.

Johnston, Stephanie S.↗

NASA NTRS2016

EVA Wiki - Transforming Knowledge Management for EVA Flight Controllers and Instructors

The EVA Wiki was recently implemented as the primary knowledge database to retain critical knowledge and skills in the EVA Operations group at NASA's Johnson Space Center by ensuring that information is recorded in a common, easy to search repository. Prior to the EVA Wiki, information required for EVA flight controllers and instructors was scattered across different sources, including multiple file share directories, SharePoint, individual computers, and paper archives. Many documents were outdated, and data was often difficult to find and distribute. In 2011, a team recognized that these knowledge management problems could be solved by creating an EVA Wiki using MediaWiki, a free and open-source software developed by the Wikimedia Foundation. The EVA Wiki developed into an EVA-specific Wikipedia on an internal NASA server. While the technical implementation of the wiki had many challenges, one of the biggest hurdles came from a cultural shift. Like many enterprise organizations, the EVA Operations group was accustomed to hierarchical data structures and individually-owned documents. Instead of sorting files into various folders, the wiki searches content. Rather than having a single document owner, the wiki harmonized the efforts of many contributors and established an automated revision controlled system. As the group adapted to the wiki, the usefulness of this single portal for information became apparent. It transformed into a useful data mining tool for EVA flight controllers and instructors, as well as hundreds of others that support EVA. Program managers, engineers, astronauts, flight directors, and flight controllers in differing disciplines now have an easier-to-use, searchable system to find EVA data. This paper presents the benefits the EVA Wiki has brought to NASA's EVA community, as well as the cultural challenges it had to overcome.

Johnston, Stephanie S.↗

NASA NTRS1992

Archiving the FIFE data on CD-ROM

FIFE (first ISLSCP field experiment) is a land surface climatology project consisting of a series of field compaigns conducted in Kansas from 1987 to 1989. The authors describe the process of designing the FIFE prototype CD-ROM including data file structure and directory structure, the image compression and expansion software used, and the user interface software developed.

Landis, David R.↗

NASA NTRS1984

ERB master archival tape specification no. T 134081 ERB MAT, revision 1

The Earth radiation budget (ERB)MAT tapes are generated by the ERB MATGEN software using the IBM 3081 computer system operated by the Science and Applications Computer Center at Goddard Space Flight Center. All MAT's are 9-track and MAT data are in ascending time order. The gross tape format for NIMBUS year-1 and year-2 MAT's is different from the format of MAT's starting with year-3. The MATs from the first two years are to contain one day's worth of data while all other MATs are to contain multiple day's worth of data stacked onto the tapes.

Source record↗

NASA NTRS2000

NASA Goddard Space Flight Center

The NASA SLR Operational Center is responsible for: 1) NASA SLR network control, sustaining engineering, and logistics; 2) ILRS mission operations; and 3) ILRS and NASA SLR data operations. NASA SLR network control and sustaining engineering tasks include technical support, daily system performance monitoring, system scheduling, operator training, station status reporting, system relocation, logistics and support of the ILRS Networks and Engineering Working Group. These activities ensure the NASA SLR systems are meeting ILRS and NASA mission support requirements. ILRS mission operations tasks include mission planning, mission analysis, mission coordination, development of mission support plans, and support of the ILRS Missions Working Group. These activities ensure than new mission and campaign requirements are coordinated with the ILRS. Global Normal Points (NP) data, NASA SLR FullRate (FR) data, and satellite predictions are managed as part of data operations. Part of this operation includes supporting the ILRS Data Formats and Procedures Working Group. Global NP data operations consist of receipt, format and data integrity verification, archiving and merging. This activity culminates in the daily electronic transmission of NP files to the CDDIS. Currently of all these functions are automated. However, to ensure the timely and accurate flow of data, regular monitoring and maintenance of the operational software systems, computer systems and computer networking are performed. Tracking statistics between the stations and the data centers are compared periodically to eliminate lost data. Future activities in this area include sub-daily (i.e., hourly) NP data management, more stringent data integrity tests, and automatic station notification of format and data integrity issues.

Carter, David↗

NASA NTRS1998

Incorporating the APS Catalog of the POSS I and Image Archive in ADS

The primary purpose of this contract was to develop the software to both create and access an on-line database of images from digital scans of the Palomar Sky Survey. This required modifying our DBMS (called Star Base) to create an image database from the actual raw pixel data from the scans. The digitized images are processed into a set of coordinate-reference index and pixel files that are stored in run-length files, thus achieving an efficient lossless compression. For efficiency and ease of referencing, each digitized POSS I plate is then divided into 900 subplates. Our custom DBMS maps each query into the corresponding POSS plate(s) and subplate(s). All images from the appropriate subplates are retrieved from disk with byte-offsets taken from the index files. These are assembled on-the-fly into a GIF image file for browser display, and a FITS format image file for retrieval. The FITS images have a pixel size of 0.33 arcseconds. The FITS header contains astrometric and photometric information. This method keeps the disk requirements manageable while allowing for future improvements. When complete, the APS Image Database will contain over 130 Gb of data. A set of web pages query forms are available on-line, as well as an on-line tutorial and documentation. The database is distributed to the Internet by a high-speed SGI server and a high-bandwidth disk system. URL is http://aps.umn.edu/IDB/. The image database software is written in perl and C and has been compiled on SGI computers with MIX5.3. A copy of the written documentation is included and the software is on the accompanying exabyte tape.

Humphreys, Roberta M.↗

NASA NTRS1992

Deep near-infrared survey of the Southern Sky (DENIS)

DENIS (Deep Near-Infrared Survey of the Southern Sky) will be the first complete census of astronomical sources in the near-infrared spectral range. The challenges of this novel survey are both scientific and technical. Phenomena radiating in the near-infrared range from brown dwarfs to galaxies in the early stages of cosmological evolution, the scientific exploitation of data relevant over such a wide range requires pooling expertise from several of the leading European astronomical centers. The technical challenges of a project which will provide an order of magnitude more sources than given by the IRAS space mission, and which will involve advanced data-handling and image-processing techniques, likewise require pooling of hardware and software resources, as well as of human expertise. The DENIS project team is composed of some 40 scientists, computer specialists, and engineers located in 5 European Community countries (France, Germany, Italy, The Netherlands, and Spain), with important contributions from specialists in Australia, Brazil, Chile, and Hungary. DENIS will survey the entire southern sky in 3 colors, namely in the I band at a wavelength of 0.8 micron, in the 1.25 micron J band, and in the 2.15 micron K' band. The sensitivity limits will be 18th magnitude in the I band, 16th in the J band, and 14.5th in the K' band. The angular resolution achieved will be 1 arcsecond in the I band, and 3.0 arcseconds in the J and K' bands. The European Southern Observatory 1 m telescope on La Silla will be dedicated to survey use during operations expected to last four years, commencing in late 1993. DENIS aims to provide the astronomical community with complete digitized infrared images of the full southern sky and a catalogue of extracted objects, both of the best quality and in readily accessible form. This will be achieved through dedicated software packages and specialized catalogues, and with assistance from the Leiden and Paris Data Analysis Centers. The data will be mailed on DAT tapes from La Silla to the two Data Analysis Centers for further processing. Two centers are necessary because of the shear quantity of data and because of the complementary roles the Centers will develop, each exploiting its own particular expertise. The Leiden Data Analysis Center (LDAC) will extract objects, establish their parameters, and archive them into a source catalogue. The LDAC will collaborate with the Groningen Space Research group that has gained experience in infrared image handling from the IRAS satellite. The Paris Data Analysis Center (PDAC) will be responsible for archiving and preprocessing the raw data to provide a homogeneous set of data suitable for further reduction in both the Leiden and Paris data analysis streams. The PDAC will also extract and archive images for the sources flagged by the LDAC as extended, and create a catalogue of galaxies. In exploiting the DENIS data we foresee the collaboration with other data analysis centers, such as the Observatoire de Lyon where the relevant DENIS catalogue of galaxies can be incorporated into their extragalactic database. The Point Sources and the Small Extended Sources catalogues could be incorporated in the Late Type Star database at Montpellier, and in the SIMBAD database as CDS. At Groningen the IRAS Point Source catalogue and/or image data can be merged with the DENIS catalogues. At Meudon algorithms and software will be developed with main goal assessing the limits reachable for the homogeneity and intrinsic consistency between the ensemble of the images in the data base (flat-fielding, relative positioning of the fields, bootstrapped flux calibration) but also for the data analysis.

Deul, E.↗

NASA NTRS2012

Rotorcraft Diagnostics

Health management (HM) in any engineering systems requires adequate understanding about the system s functioning; a sufficient amount of monitored data; the capability to extract, analyze, and collate information; and the capability to combine understanding and information for HM-related estimation and decision-making. Rotorcraft systems are, in general, highly complex. Obtaining adequate understanding about functioning of such systems is quite difficult, because of the proprietary (restricted access) nature of their designs and dynamic models. Development of an EIM (exact inverse map) solution for rotorcraft requires a process that can overcome the abovementioned difficulties and maximally utilize monitored information for HM facilitation via employing advanced analytic techniques. The goal was to develop a versatile HM solution for rotorcraft for facilitation of the Condition Based Maintenance Plus (CBM+) capabilities. The effort was geared towards developing analytic and reasoning techniques, and proving the ability to embed the required capabilities on a rotorcraft platform, paving the way for implementing the solution on an aircraft-level system for consolidation and reporting. The solution for rotorcraft can he used offboard or embedded directly onto a rotorcraft system. The envisioned solution utilizes available monitored and archived data for real-time fault detection and identification, failure precursor identification, and offline fault detection and diagnostics, health condition forecasting, optimal guided troubleshooting, and maintenance decision support. A variant of the onboard version is a self-contained hardware and software (HW+SW) package that can be embedded on rotorcraft systems. The HM solution comprises components that gather/ingest data and information, perform information/feature extraction, analyze information in conjunction with the dependency/diagnostic model of the target system, facilitate optimal guided troubleshooting, and offer decision support for optimal maintenance.

Haste, Deepak↗

NASA NTRS2013

Hyperspectral Microwave Atmospheric Sounder (HyMAS) Architecture and Design Accommodations

The Hyperspectral Microwave Atmospheric Sounder (HyMAS) is being developed at Lincoln Laboratories and accommodated by the Goddard Space Flight Center for a flight opportunity on a NASA research aircraft. The term "hyperspectral microwave" is used to indicate an all-weather sounding that performs equivalent to hyperspectral infrared sounders in clear air with vertical resolution of approximately 1 km. Deploying the HyMAS equipped scanhead with the existing Conical Scanning Microwave Imaging Radiometer (CoSMIR) shortens the path to a flight demonstration. Hyperspectral microwave is achieved through the use of independent RF antennas that sample the volume of the Earth s atmosphere through various levels of frequencies, thereby producing a set of dense, spaced vertical weighting functions. The simulations proposed for HyMAS 118/183-GHz system should yield surface precipitation rate and water path retrievals for small hail, soft hail, or snow pellets, snow, rainwater, etc. with accuracies comparable to those of the Advanced Technology Microwave Sounder. Further improvements in retrieval methodology (for example, polarization exploitation) are expected. The CoSMIR instrument is a packaging concept re-used on HyMAS to ease the integration features of the scanhead. The HyMAS scanhead will include an ultra-compact Intermediate Frequency Processor (IFP) module that is mounted inside the door to improve thermal management. The IFP is fabricated with materials made of Low-Temperature Co-fired Ceramic (LTCC) technology integrated with detectors, amplifiers, A/D conversion and data aggregation. The IFP will put out 52 channels of 16 bit data comprised of 4-9 channel data streams for temperature profiles and 2-8 channel streams for water vapor. With the limited volume of the existing CoSMIR scanhead and new HyMAS front end components, the HyMAS team at Goddard began preliminary layout work inside the new drum. Importing and re-using models of the shell, the scan head computer, and the slip rings developed for CoSMIR was the starting point. The next step was to modify the antenna faceplate to accommodate the dimensions of the three dual polarization Gaussian Optics Antenna (GOA) assemblies. Two mechanical concepts for the core technology, the hyperspectral IFP, were captured in a design tradeoff. Connector models considered minimum bend radii for the IFP analog connectors. Hyperspectral imaging is accomplished by strategically using a short wavelength intermediate frequency of 18-29 GHz, and thus reducing the size of components in the connection of the front end to the IFP. The SMK (2.92mm) Series connector will lay near the hinge line to minimize its flexing. The digital output of the IFP will use a Serial Peripheral Interface (SPI) that must be accommodated by the scan head computer. To make that computer more reliable, maintainable, and forward compatible with the 52 HyMAS channels, a testbed of the scan head, calibration, and archive computers and the PIC24 microprocessor that resides on the IFP is in development. The computers will be programmed using a new framework application called Interoperable Remote Component (IRC). This software allows flexibility to program computers that communicate with each other and can adapt easily to the emerging HyMAS requirements for data format, algorithms, and graphical user interface (GUI). It is expected that the CoSMIR instrument will cut over to the IRC after it is adapted on an updated CoSMIR testbed.

Hilliard, Lawrence↗

NASA NTRS2001

Simple, Scalable, Script-Based Science Processor (S4P)

The development and deployment of data processing systems to process Earth Observing System (EOS) data has proven to be costly and prone to technical and schedule risk. Integration of science algorithms into a robust operational system has been difficult. The core processing system, based on commercial tools, has demonstrated limitations at the rates needed to produce the several terabytes per day for EOS, primarily due to job management overhead. This has motivated an evolution in the EOS Data Information System toward a more distributed one incorporating Science Investigator-led Processing Systems (SIPS). As part of this evolution, the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC) has developed a simplified processing system to accommodate the increased load expected with the advent of reprocessing and launch of a second satellite. This system, the Simple, Scalable, Script-based Science Processor (S42) may also serve as a resource for future SIPS. The current EOSDIS Core System was designed to be general, resulting in a large, complex mix of commercial and custom software. In contrast, many simpler systems, such as the EROS Data Center AVHRR IKM system, rely on a simple directory structure to drive processing, with directories representing different stages of production. The system passes input data to a directory, and the output data is placed in a "downstream" directory. The GES DAAC's Simple Scalable Script-based Science Processing System is based on the latter concept, but with modifications to allow varied science algorithms and improve portability. It uses a factory assembly-line paradigm: when work orders arrive at a station, an executable is run, and output work orders are sent to downstream stations. The stations are implemented as UNIX directories, while work orders are simple ASCII files. The core S4P infrastructure consists of a Perl program called stationmaster, which detects newly arrived work orders and forks a job to run the appropriate executable (registered in a configuration file for that station). Although S4P is written in Perl, the executables associated with a station can be any program that can be run from the command line, i.e., non-interactively. An S4P instance is typically monitored using a simple Graphical User Interface. However, the reliance of S4P on UNIX files and directories also allows visibility into the state of stations and jobs using standard operating system commands, permitting remote monitor/control over low-bandwidth connections. S4P is being used as the foundation for several small- to medium-size systems for data mining, on-demand subsetting, processing of direct broadcast Moderate Resolution Imaging Spectroradiometer (MODIS) data, and Quick-Response MODIS processing. It has also been used to implement a large-scale system to process MODIS Level 1 and Level 2 Standard Products, which will ultimately process close to 2 TB/day.

Lynnes, Christopher↗

NASA NTRS1994

Managing People's Data

Just imagine a mass storage system that consists of a machine with 2 CPUs, 1 Gigabyte (GB) of memory, 400 GB of disk space, 16800 cartridge tapes in the automated tape silos, 88,000 tapes located in the vault, and the software to manage the system. This system is designed to be a data repository; it will always have disk space to store all the incoming data. Currently 9.14 GB of new data per day enters the system with this rate doubling each year. To assure there is always disk space available for new data, the system. has to move data reside from the expensive disk to a much less expensive medium such as the 3480 cartridge tapes. Once the data is archived to tape, it should be able to move back to disk when someone wants to access it and the data movement should be transparent to the user. Now imagine all the tasks that a system administrator must perform to keep this system running 24 hour a day, 7 days a week. Since the filesystem maintains the illusion of unlimited disk space, data that comes to the system must get moved to tapes in an efficient manner. This paper will describe the mass storage system running at the Numerical Aerodynamic Simulation (NAS) at NASA Ames Research Center in both software and hardware aspects, then it will describe all of the tasks the system administrator has to perform on this system.

Le, Diana↗

NASA NTRS1993

LDEF materials special investigation group's data bases

The Long Duration Exposure Facility (LDEF) was composed of and contained a wide array of materials, representing the largest collection of materials flown for space exposure and returned for ground-based analyses to date. The results and implications of the data from these materials are the foundation on which future space missions will be built. The LDEF Materials Special Investigation Group (MSIG) has been tasked with establishing and developing data bases to document these materials and their performance to assure not only that the data are archived for future generations but also that the data are available to the space user community in an easily accessed, user-friendly form. The format and content of the data bases developed or being developed to accomplish this task are discussed. The hardware and software requirements for each of the three data bases are discussed along with current availability of the data bases.

Strickland, John W.↗

NASA NTRS1989

A programmable image compression system

A programmable image compression system which has the necessary flexibility to address diverse imaging needs is described. It can compress and expand single frame video images (monochrome or color) as well as documents and graphics (black and white or color) for archival or transmission applications. Through software control, the compression mode can be set for lossless or controlled quality coding; the image size and bit depth can be varied; and the image source and destination devices can be readily changed. Despite the large combination of image data types, image sources, and algorithms, the system provides a simple consistent interface to the programmer. This system (OPTIPAC) is based on the TITMS320C25 digital signal processing (DSP) chip and has been implemented as a co-processor board for an IBM PC-AT compatible computer. The underlying philosophy can readily be applied to different hardware platforms. By using multiple DSP chips or incorporating algorithm specific chips, the compression and expansion times can be significantly reduced to meet performance requirements.

Farrelle, Paul M.↗

NASA NTRS1991

Data systems and computer science programs: Overview

An external review of the Integrated Technology Plan for the Civil Space Program is presented. The topics are presented in viewgraph form and include the following: onboard memory and storage technology; advanced flight computers; special purpose flight processors; onboard networking and testbeds; information archive, access, and retrieval; visualization; neural networks; software engineering; and flight control and operations.

Smith, Paul H.↗