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At least 73 records · Page 4

Spacecraft Orbit Design and Analysis (SODA), version 1.0 user's guide

The Spacecraft Orbit Design and Analysis (SODA) computer program, Version 1.0 is described. SODA is a spaceflight mission planning system which consists of five program modules integrated around a common database and user interface. SODA runs on a VAX/VMS computer with an EVANS & SUTHERLAND PS300 graphics workstation. BOEING RIM-Version 7 relational database management system performs transparent database services. In the current version three program modules produce an interactive three dimensional (3D) animation of one or more satellites in planetary orbit. Satellite visibility and sensor coverage capabilities are also provided. One module produces an interactive 3D animation of the solar system. Another module calculates cumulative satellite sensor coverage and revisit time for one or more satellites. Currently Earth, Moon, and Mars systems are supported for all modules except the solar system module.

Stallcup, Scott S.↗

Querying Semi-Structured Data

The amount of data of all kinds available electronically has increased dramatically in recent years. The data resides in different forms, ranging from unstructured data in the systems to highly structured in relational database systems. Data is accessible through a variety of interfaces including Web browsers, database query languages, application-specic interfaces, or data exchange formats. Some of this data is raw data, e.g., images or sound. Some of it has structure even if the structure is often implicit, and not as rigid or regular as that found in standard database systems. Sometimes the structure exists but has to be extracted from the data. Sometimes also it exists but we prefer to ignore it for certain purposes such as browsing. We call here semi-structured data this data that is (from a particular viewpoint) neither raw data nor strictly typed, i.e., not table-oriented as in a relational model or sorted-graph as in object databases. As will seen later when the notion of semi-structured data is more precisely de ned, the need for semi-structured data arises naturally in the context of data integration, even when the data sources are themselves well-structured. Although data integration is an old topic, the need to integrate a wider variety of data- formats (e.g., SGML or ASN.1 data) and data found on the Web has brought the topic of semi-structured data to the forefront of research. The main purpose of the paper is to isolate the essential aspects of semi- structured data. We also survey some proposals of models and query languages for semi-structured data. In particular, we consider recent works at Stanford U. and U. Penn on semi-structured data. In both cases, the motivation is found in the integration of heterogeneous data.

DATA MANAGEMENT↗

A relational data-knowledge base system and its potential in developing a distributed data-knowledge system

A new approach used in constructing a rational data knowledge base system is described. The relational database is well suited for distribution due to its property of allowing data fragmentation and fragmentation transparency. An example is formulated of a simple relational data knowledge base which may be generalized for use in developing a relational distributed data knowledge base system. The efficiency and ease of application of such a data knowledge base management system is briefly discussed. Also discussed are the potentials of the developed model for sharing the data knowledge base as well as the possible areas of difficulty in implementing the relational data knowledge base management system.

Rahimian, Eric N.↗

FJET Database Project: Extract, Transform, and Load

The Data Mining & Knowledge Management team at Kennedy Space Center is providing data management services to the Frangible Joint Empirical Test (FJET) project at Langley Research Center (LARC). FJET is a project under the NASA Engineering and Safety Center (NESC). The purpose of FJET is to conduct an assessment of mild detonating fuse (MDF) frangible joints (FJs) for human spacecraft separation tasks in support of the NASA Commercial Crew Program. The Data Mining & Knowledge Management team has been tasked with creating and managing a database for the efficient storage and retrieval of FJET test data. This paper details the Extract, Transform, and Load (ETL) process as it is related to gathering FJET test data into a Microsoft SQL relational database, and making that data available to the data users. Lessons learned, procedures implemented, and programming code samples are discussed to help detail the learning experienced as the Data Mining & Knowledge Management team adapted to changing requirements and new technology while maintaining flexibility of design in various aspects of the data management project.

excel vba↗

Databases for LDEF results

One of the objectives of the team supporting the LDEF Systems and Materials Special Investigative Groups is to develop databases of experimental findings. These databases identify the hardware flown, summarize results and conclusions, and provide a system for acknowledging investigators, tracing sources of data, and future design suggestions. To date, databases covering the optical experiments, and thermal control materials (chromic acid anodized aluminum, silverized Teflon blankets, and paints) have been developed at Boeing. We used the Filemaker Pro software, the database manager for the Macintosh computer produced by the Claris Corporation. It is a flat, text-retrievable database that provides access to the data via an intuitive user interface, without tedious programming. Though this software is available only for the Macintosh computer at this time, copies of the databases can be saved to a format that is readable on a personal computer as well. Further, the data can be exported to more powerful relational databases, capabilities, and use of the LDEF databases and describe how to get copies of the database for your own research.

Bohnhoff-Hlavacek, Gail↗

Searching Across the International Space Station Databases

Data access in the enterprise generally requires us to combine data from different sources and different formats. It is advantageous thus to focus on the intersection of the knowledge across sources and domains; keeping irrelevant knowledge around only serves to make the integration more unwieldy and more complicated than necessary. A context search over multiple domain is proposed in this paper to use context sensitive queries to support disciplined manipulation of domain knowledge resources. The objective of a context search is to provide the capability for interrogating many domain knowledge resources, which are largely semantically disjoint. The search supports formally the tasks of selecting, combining, extending, specializing, and modifying components from a diverse set of domains. This paper demonstrates a new paradigm in composition of information for enterprise applications. In particular, it discusses an approach to achieving data integration across multiple sources, in a manner that does not require heavy investment in database and middleware maintenance. This lean approach to integration leads to cost-effectiveness and scalability of data integration with an underlying schemaless object-relational database management system. This highly scalable, information on demand system framework, called NX-Search, which is an implementation of an information system built on NETMARK. NETMARK is a flexible, high-throughput open database integration framework for managing, storing, and searching unstructured or semi-structured arbitrary XML and HTML used widely at the National Aeronautics Space Administration (NASA) and industry.

Maluf, David A.↗

Implementation of a Computerized Maintenance Management System

A primer Computerized Maintenance Management System (CMMS) has been established for NASA Ames pressure component certification program. The CMMS takes full advantage of the latest computer technology and SQL relational database to perform periodic services for vital pressure components. The Ames certification program is briefly described and the aspects of the CMMS implementation are discussed as they are related to the certification objectives.

Shen, Yong-Hong↗

Space Station Freedom environmental database system (FEDS) for MSFC testing

The Water Recovery Test (WRT) at Marshall Space Flight Center (MSFC) is the first demonstration of integrated water recovery systems for potable and hygiene water reuse as envisioned for Space Station Freedom (SSF). In order to satisfy the safety and health requirements placed on the SSF program and facilitate test data assessment, an extensive laboratory analysis database was established to provide a central archive and data retrieval function. The database is required to store analysis results for physical, chemical, and microbial parameters measured from water, air and surface samples collected at various locations throughout the test facility. The Oracle Relational Database Management System (RDBMS) was utilized to implement a secured on-line information system with the ECLSS WRT program as the foundation for this system. The database is supported on a VAX/VMS 8810 series mainframe and is accessible from the Marshall Information Network System (MINS). This paper summarizes the database requirements, system design, interfaces, and future enhancements.

Story, Gail S.↗

Using semantic data modeling techniques to organize an object-oriented database for extending the mass storage model

A methodology for optimizing organization of data obtained by NASA earth and space missions is discussed. The methodology uses a concept based on semantic data modeling techniques implemented in a hierarchical storage model. The modeling is used to organize objects in mass storage devices, relational database systems, and object-oriented databases. The semantic data modeling at the metadata record level is examined, including the simulation of a knowledge base and semantic metadata storage issues. The semantic data model hierarchy and its application for efficient data storage is addressed, as is the mapping of the application structure to the mass storage.

Campbell, William J.↗

Elevating the Quality of Space Omics Sequencing Data: Innovations and Methodologies from NASA GeneLab Sample Processing Laboratory

NASA’s GeneLab, part of the NASA Open Science Data Repository, is a space-related database that hosts a diverse range of transcriptomics, proteomics, epigenomics and genomics data. The NASA GeneLab Sample Processing Laboratory (SPL) generates omics data from biological experiments conducted aboard the International Space Station, Space Shuttle and space related ground experiments, this omics data then hosted on the GeneLab repository. Samples generated such experiments pose numerous technical challenges such as small experimental sample size, variance in dissection times, limited tissue preservation methods, prolonged storage time, and more. GeneLab SPL team had developed specialized expertise in nucleic acid extraction, library preparation and sequencing of such biological samples via extensive training and years of experience. In order to ensure data accuracy and consistency across experiments, SPL has developed standardized protocols for each species and tissue type. These protocols in conjunction with quality control metrics and data standards are crucial in generating of high-quality data. SPL protocols and standards have been developed in collaboration with the scientific community and had been made publicly available on the GeneLab portal, guaranteeing comparability of datasets across spaceflight experiments. To ensure reliability of data generation, SPL leverages cutting-edge innovations in laboratory automation for sample processing. By leveraging these state-of-the-art platforms, SPL achieves high levels of data reproducibility while significantly minimizing sources of bias and variability, especially across experiments with large numbers of samples. Over the past few years, the space biology investigator community has accessed SPL-generated data from the Open Science Data Repository for a myriad of data re-analysis and re-use studies. We observe a trend that in-house SPL-generated data consistently outperforms outsourced sequencing data in terms of technical standards, quality control metrics, timeliness of data delivery, and sequencing and reagent efficiency. Superior data generation has and will continue to enable discoveries in disease, diagnostic tools, and the biological effects of long duration spaceflight.

GeneLab↗

Elevating the Quality of Space Omics Sequencing Data: Innovations and Methodologies from NASA GeneLab Sample Processing Laboratory

NASA’s GeneLab, part of the NASA Open Science Data Repository, is a space-related database that hosts a diverse range of transcriptomics, proteomics, epigenomics and genomics data. The NASA GeneLab Sample Processing Laboratory (SPL) generates omics data from biological experiments conducted aboard the International Space Station, Space Shuttle and space related ground experiments, this omics data then hosted on the GeneLab repository. Samples generated such experiments pose numerous technical challenges such as small experimental sample size, variance in dissection times, limited tissue preservation methods, prolonged storage time, and more. GeneLab SPL team had developed specialized expertise in nucleic acid extraction, library preparation and sequencing of such biological samples via extensive training and years of experience. In order to ensure data accuracy and consistency across experiments, SPL has developed standardized protocols for each species and tissue type. These protocols in conjunction with quality control metrics and data standards are crucial in generating of high-quality data. SPL protocols and standards have been developed in collaboration with the scientific community and had been made publicly available on the GeneLab portal, guaranteeing comparability of datasets across spaceflight experiments. To ensure reliability of data generation, SPL leverages cutting-edge innovations in laboratory automation for sample processing. By leveraging these state-of-the-art platforms, SPL achieves high levels of data reproducibility while significantly minimizing sources of bias and variability, especially across experiments with large numbers of samples. Over the past few years, the space biology investigator community has accessed SPL-generated data from the Open Science Data Repository for a myriad of data re-analysis and re-use studies. We observe a trend that in-house SPL-generated data consistently outperforms outsourced sequencing data in terms of technical standards, quality control metrics, timeliness of data delivery, and sequencing and reagent efficiency. Superior data generation has and will continue to enable discoveries in disease, diagnostic tools, and the biological effects of long duration spaceflight.

GeneLab↗

Towards the Interoperability of Web, Database, and Mass Storage Technologies for Petabyte Archives

At the San Diego Supercomputer Center, a massive data analysis system (MDAS) is being developed to support data-intensive applications that manipulate terabyte sized data sets. The objective is to support scientific application access to data whether it is located at a Web site, stored as an object in a database, and/or storage in an archival storage system. We are developing a suite of demonstration programs which illustrate how Web, database (DBMS), and archival storage (mass storage) technologies can be integrated. An application presentation interface is being designed that integrates data access to all of these sources. We have developed a data movement interface between the Illustra object-relational database and the NSL UniTree archival storage system running in a production mode at the San Diego Supercomputer Center. With this interface, an Illustra client can transparently access data on UniTree under the control of the Illustr DBMS server. The current implementation is based on the creation of a new DBMS storage manager class, and a set of library functions that allow the manipulation and migration of data stored as Illustra 'large objects'. We have extended this interface to allow a Web client application to control data movement between its local disk, the Web server, the DBMS Illustra server, and the UniTree mass storage environment. This paper describes some of the current approaches successfully integrating these technologies. This framework is measured against a representative sample of environmental data extracted from the San Diego Ba Environmental Data Repository. Practical lessons are drawn and critical research areas are highlighted.

Moore, Reagan↗

IUEAGN: A database of ultraviolet spectra of active galactic nuclei

In 13 years of operation, IUE has gathered approximately 5000 spectra of almost 600 Active Galactic Nuclei (AGN). In order to undertake AGN studies which require large amounts of data, we are consistently reducing this entire archive and creating a homogeneous, easy-to-use database. First, the spectra are extracted using the Optimal extraction algorithm. Continuum fluxes are then measured across predefined bands, and line fluxes are measured with a multi-component fit. These results, along with source information such as redshifts and positions, are placed in the IUEAGN relational database. Analysis algorithms, statistical tests, and plotting packages run within the structure, and this flexible database can accommodate future data when they are released. This archival approach has already been used to survey line and continuum variability in six bright Seyfert 1s and rapid continuum variability in 14 blazars. Among the results that could only be obtained using a large archival study is evidence that blazars show a positive correlation between degree of variability and apparent luminosity, while Seyfert 1s show an anti-correlation. This suggests that beaming dominates the ultraviolet properties for blazars, while thermal emission from an accretion disk dominates for Seyfert 1s. Our future plans include a survey of line ratios in Seyfert 1s, to be fitted with photoionization models to test the models and determine the range of temperatures, densities and ionization parameters. We will also include data from IRAS, Einstein, EXOSAT, and ground-based telescopes to measure multi-wavelength correlations and broadband spectral energy distributions.

Pike, G.↗

Managing Data in a GIS Environment

A Geographic Information System (GIS) is a computer-based system that enables capture, modeling, manipulation, retrieval, analysis and presentation of geographically referenced data. A GIS operates in a dynamic environment of spatial and temporal information. This information is held in a database like any other information system, but performance is more of an issue for a geographic database than a traditional database due to the nature of the data. What distinguishes a GIS from other information systems is the spatial and temporal dimensions of the data and the volume of data (several gigabytes). Most traditional information systems are usually based around tables and textual reports, whereas GIS requires the use of cartographic forms and other visualization techniques. Much of the data can be represented using computer graphics, but a GIS is not a graphics database. A graphical system is concerned with the manipulation and presentation of graphical objects whereas a GIS handles geographic objects that have not only spatial dimensions but non-visual, i e., attribute and components. Furthermore, the nature of the data on which a GIS operates makes the traditional relational database approach inadequate for retrieving data and answering queries that reference spatial data. The purpose of this paper is to describe the efficiency issues behind storage and retrieval of data within a GIS database. Section 2 gives a general background on GIS, and describes the issues involved in custom vs. commercial and hybrid vs. integrated geographic information systems. Section 3 describes the efficiency issues concerning the management of data within a GIS environment. The paper ends with a summary of the main concerns of this paper.

Beltran, Maria↗

Generative engineering databases - Toward expert systems

Engineering data management, incorporating concepts of optimization with data representation, is receiving increasing attention as the amount and complexity of information necessary for performing engineering operations increases and the need to coordinate its representation and use increases. Research in this area promises advantages for a wide variety of engineering applications, particularly those which seek to use data in innovative ways in the engineering process. This paper presents a framework for a comprehensive, relational database management system that combines a knowledge base of design constraints with a database of engineering data items in order to achieve a 'generative database' - one which automatically generates new engineering design data according to the design constraints stored in the knowledge base. The representation requires a database that is able to store all of the data normally associated with engineering design and to accurately represent the interactions between constraints and the stored data while guaranteeing its integrity. The representation also requires a knowledge base that is able to store all the constraints imposed upon the engineering design process.

Rasdorf, W. J.↗

Autonomous mission planning and scheduling: Innovative, integrated, responsive

Autonomous mission scheduling, a new concept for NASA ground data systems, is a decentralized and distributed approach to scientific spacecraft planning, scheduling, and command management. Systems and services are provided that enable investigators to operate their own instruments. In autonomous mission scheduling, separate nodes exist for each instrument and one or more operations nodes exist for the spacecraft. Each node is responsible for its own operations which include planning, scheduling, and commanding; and for resolving conflicts with other nodes. One or more database servers accessible to all nodes enable each to share mission and science planning, scheduling, and commanding information. The architecture for autonomous mission scheduling is based upon a realistic mix of state-of-the-art and emerging technology and services, e.g., high performance individual workstations, high speed communications, client-server computing, and relational databases. The concept is particularly suited to the smaller, less complex missions of the future.

Sary, Charisse↗

HOPE: An On-Line Piloted Handling Qualities Experiment Data Book

A novel on-line database for capturing most of the information obtained during piloted handling qualities experiments (either flight or simulated) is described. The Hyperlinked Overview of Piloted Evaluations (HOPE) web application is based on an open-source object-oriented Web-based front end (Ruby-on-Rails) that can be used with a variety of back-end relational database engines. The hyperlinked, on-line data book approach allows an easily-traversed way of looking at a variety of collected data, including pilot ratings, pilot information, vehicle and configuration characteristics, test maneuvers, and individual flight test cards and repeat runs. It allows for on-line retrieval of pilot comments, both audio and transcribed, as well as time history data retrieval and video playback. Pilot questionnaires are recorded as are pilot biographies. Simple statistics are calculated for each selected group of pilot ratings, allowing multiple ways to aggregate the data set (by pilot, by task, or by vehicle configuration, for example). Any number of per-run or per-task metrics can be captured in the database. The entire run metrics dataset can be downloaded in comma-separated text for further analysis off-line. It is expected that this tool will be made available upon request

Jackson, E. B.↗

TEQUEL: The query language of SADDLE

A relational database management system is presented that is tailored for engineering applications. A wide variety of engineering data types are supported and the data definition language (DDL) and data manipulation language (DML) are extended to handle matrices. The system can be used either in the standalone mode or through a FORTRAN or PASCAL application program. The query language is of the relational calculus type and allows the user to store, retrieve, update and delete tuples from relations. The relational operations including union, intersect and differ facilitate creation of temporary relations that can be used for manipulating information in a powerful manner. Sample applications are shown to illustrate the creation of data through a FORTRAN program and data manipulation using the TEQUEL DML.

Rajan, S. D.↗