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The Data Management System-1100 is designed to operate in conjunction with the UNIVAC 1100 Series Operating System on any 1100 Series computer. DMS-1100 is divided into the following four major software components: (1) Data Definition Languages (DDL); (2) Data Management Routine (DMR); (3) Data Manipulation Languages (DML); and (4) Data Base Utilities (DBU). These software components are described in detail.
The paper describes the system configuration and data manipulation capabilities of a solar image display system which allows interactive analysis of visual images and on-line manipulation of digital data. Image processing features include smoothing or filtering of images stored in the display, contrast enhancement, and blinking or flickering images. A computer with a core memory of 28,672 words provides the capacity to perform complex calculations based on stored images, including computing histograms, selecting subsets of images for further analysis, combining portions of images to produce images with physical meaning, and constructing mathematical models of features in an image. Some of the processing modes are illustrated by some image sequences from solar observations.
A FORTRAN-4 computer program for handling fuel pin data is described. Its main features include standardized output, easy access for data manipulation, and tabulation of important material property data. An additional feature allows simplified preparation of input decks for a fuel swelling computer code (CYGRO-2). Data from over 300 high temperature nitride and carbide based fuel pin irradiations are listed.
The Pilot Climate Data System (PCDS) was found to be useful in examining a subset of data from the Nimbus-7 Total Ozone Mapping Spectrometer (TOMS). The TOMS instrument scans with six channels between .3 and .4 micrometers. It was suggested that by analyzing albedo values from the longer wavelength channels of the TOMS, the effects of increasing optical depth could be determined. It is spectral relationship of albedo-to-optical depth that is investigated here. The question can be stated: Is there spectral differentiation in albedo with changes in the optical depth of clouds? Nimbus-7 TOMS data were obtained through the PCDS for an area and time period for which correlative NOAA AVHRR data were available. The AVHRR data were important in determining the existing cloud patterns. As expected, no spectral differentiation was observed at very high albedos (associated with high optical depths). However, at lower optical depths, evidence of spectral dependence on albedo was observed. Mapping the results geographically was deemed highly desirable but was not possible through the PCDS at the time. The PCDS can be viewed as an effective research tool to access selected portions of data. Without being intimately familiar with a data set, a PCDS user can successfully manipulate data in a scientific study.
The post processor program was developed to view Large Angle Transient Dynamics (LATDYN) output data in predefined, predetermined formats. The post processor is used for plotting data, creating and maintaining a data base of plotting requests, comparing and manipulating data sets in the data base, and the preparing plots for documentation.
A scenario of relational, hierarchial, and network data bases is presented and a distributed access view integrated data base system (DAVID) is described for uniformly accessing data bases which are heterogeneous and physically distributed. The DAVID system is based on data base logic so that the relational approach is generalized to the heterogeneous approach. The global data manager is explained as are global data manipulation languages which can operate on all the data bases and can query the data dictionary and the data directory.
Techniques for the review, display, and manipulation of multidimensional data are developed and described. Multidimensional data is meant in this context to describe scalar data associated with a three dimensional geometry or otherwise too complex to be well represented by traditional graphs. Raster graphics techniques are used to display a shaded image of a three dimensional geometry. The use of color to represent scalar data associated with the geometries in shaded images is explored. Distinct hues are associated with discrete data ranges, thus emulating the traditional representation of data with isarithms, or lines of constant numerical value. Data ranges are alternatively associated with a continuous spectrum of hues to show subtler data trends. The application of raster graphics techniques to the display of bivariate functions is explored.
The development of an accurate close range (from 0.0 meters to 30.0 meters) radar system for Teleoperator Maneuvering Systems (TMS) is discussed. The system under investigation is a digital processor that converts incoming signals from the radar system into their related frequency spectra. Identification will be attempted by correlating spectral characteristics with accurate range determinataions. The system will utilize an analog to digital converter for sampling and converting the signal from the radar system into 16-bit digital words (two bytes) for RAM storage, data manipulations, and computations. To remove unwanted frequency components the data will be retrieved from RAM and digitally filtered using large scale integration (LSI) circuits. Filtering will be performed by a biquadratic routine within the chip which carries out the required filter algorithm. For conversion to a frequency spectrum the filtered data will be processed by a Fast Fourier Transform chip. Analysis and identification of spectral characteristics for accurate range determinations will be made by microcomputer computations.
In their paper Petrinec and Russell (PR) (1993) claim to have developed a 'more homogeneous and accurate set of solar wind data' by 'correcting' the reported ion densities from three plasma instruments: the Los Alamos National Laboratory (LANL) ion electrostatic analyzer on ISEE 3 and the LANL electrostatic analyzer and the Massachusetts Institute of Technology (MIT) Faraday cup plasma instrument on Interplanetary Monitoring Platform 8 (IMP 8). Their data manipulation techniques are examined. The foundations on which their data set are built, are discussed. Reanalysis by MIT on the MIT instrument (IMP 8) was done. Initial results have been issued. The Petrinec & Russell (1993) (PR) paper does not provide accurate density estimates and is an exercise that will only bring confusion to users of the data. The results of PR should be treated with skepticism.
A combination of a local network, a mass storage system, and an autonomous set processor serving as a data/storage management machine is described. Its characteristics include: content-accessible data bases usable from all connected devices; efficient storage/access of large data bases; simple and direct programming with data manipulation and storage management handled by the set processor; simple data base design and entry from source representation to set processor representation with no predefinition necessary; capability available for user sort/order specification; significant reduction in tape/disk pack storage and mounts; flexible environment that allows upgrading hardware/software configuration without causing major interruptions in service; minimal traffic on data communications network; and improved central memory usage on large processors.
In order to develop a solid earth science framework for understanding and studying of active tectonic and earthquake processes, this task develops simulation and analysis tools to study the physics of earthquakes using state-of-the art modeling, data manipulation, and pattern recognition technologies. We develop clearly defined accessible data formats and code protocols as inputs to the simulations. these are adapted to high-performance computers because the solid earth system is extremely complex and nonlinear resulting in computationally intensive problems with millions of unknowns. With these tools it will be possible to construct the more complex models and simulations necessary to develop hazard assessment systems critical for reducing future losses from major earthquakes.
Current approaches to satellite observation data storage and distribution implement separate visualization and data access methodologies which often leads to the need in time consuming data ordering and coding for applications requiring both visual representation as well as data handling and modeling capabilities. We describe an approach we implemented for a data-encoded web map service based on storing numerical data within server map tiles and subsequent client side data manipulation and map color rendering. The approach relies on storing data using the lossless compression Portable Network Graphics (PNG) image data format which is natively supported by web-browsers allowing on-the-fly browser rendering and modification of the map tiles. The method is easy to implement using existing software libraries and has the advantage of easy client side map color modifications, as well as spatial subsetting with physical parameter range filtering. This method is demonstrated for the ASTER-GDEM elevation model and selected MODIS data products and represents an alternative to the currently used storage and data access methods. One additional benefit includes providing multiple levels of averaging due to the need in generating map tiles at varying resolutions for various map magnification levels. We suggest that such merged data and mapping approach may be a viable alternative to existing static storage and data access methods for a wide array of combined simulation, data access and visualization purposes.
Data base uniformization refers to the building of a common user interface facility to support uniform access to any or all of a collection of distributed heterogeneous data bases. Such a system should enable a user, situated anywhere along a set of distributed data bases, to access all of the information in the data bases without having to learn the various data manipulation languages. Furthermore, such a system should leave intact the component data bases, and in particular, their already existing software. A survey of various aspects of the data bases uniformization problem and a proposed solution are presented.
We are developing simulation and analysis tools in order to develop a solid Earth science framework for understanding and studying active tectonic and earthquake processes. The goal of QuakeSim and its extension, the Solid Earth Research Virtual Observatory (SERVO), is to study the physics of earthquakes using state-of-the-art modeling, data manipulation, and pattern recognition technologies. We are developing clearly defined accessible data formats and code protocols as inputs to simulations, which are adapted to high-performance computers. The solid Earth system is extremely complex and nonlinear resulting in computationally intensive problems with millions of unknowns. With these tools it will be possible to construct the more complex models and simulations necessary to develop hazard assessment systems critical for reducing future losses from major earthquakes. We are using Web (Grid) service technology to demonstrate the assimilation of multiple distributed data sources (a typical data grid problem) into a major parallel high-performance computing earthquake forecasting code. Such a linkage of Geoinformatics with Geocomplexity demonstrates the value of the Solid Earth Research Virtual Observatory (SERVO) Grid concept, and advances Grid technology by building the first real-time large-scale data assimilation grid.
The Pilot Climate Data System (PCDS) was developed by the Information Management Branch of NASA's Goddard Space Flight Center to manage a large collection of climate-related data of interest to the research community. The PCDS now provides uniform data catalogs, inventories, access methods, graphical displays and statistical calculations for selected NASA and non-NASA data sets. Data manipulation capabilities were developed to permit researchers to easily combine or compare data. The current capabilities of the PCDS include many tools for the statistical survey of climate data. A climate researcher can examine any data set of interest via flexible utilities to create a variety of two- and three-dimensional displays, including vector plots, scatter diagrams, histograms, contour plots, surface diagrams and pseudo-color images. The graphics and statistics subsystems employ an intermediate data storage format which is data-set independent. Outside of the graphics system there exist other utilities to select, filter, list, compress, and calculate time-averages and variances for any data of interest. The PCDS now fully supports approximately twenty different data sets and is being used on a trial basis by several different in-house research grounds.
The data management problem comprises data processing and data tracking. Data processing is the creation of new data based on existing data sources. Data tracking consists of storing metadata descriptions of available data. This paper addresses the data management problem by casting it as an AI planning problem. Actions are data-processing commands, plans are dataflow programs and goals are metadata descriptions of desired data products. Data manipulation is simply plan generation and execution, and a key component of data tracking is inferring the effects of an observed plan. We introduce a new action language for data management domains, called ADILM. We discuss the connection between data processing and information integration and show how a language for the latter must be modified to support the former. The paper also discusses information gathering within a data-processing framework, and show how ADILM metadata expressions are a generalization of Local Completeness.
During the first six month period, the RECON (Regenerative Concepts Group) team collected reference material, made visits to consult with other researchers, and invited distinguished visitors to speak on the status of closed life support activities. A decision was made to develop the data base and modeling such that artificial intelligence (AI) methods could be used to manipulate data and examine concept alternatives. Six discrete tasks and a project schedule were outlined for the first year. The first two tasks have been essentially completed and have resulted in a sample set of assumptions for general use in defining candidate systems and for the specification of closed system characteristics. To model a closed environment, decisions were necessary to establish the amounts of food, air, water and waste products. Although recognized that data would eventually be normalized on the basis of a single human, the amount of data in existence for four person crews led to the decision to use this as a baseline. Information on existing concepts was collected from NASA sources, from industry, and libraries. Concept modeling was begun, hardware and software obtained, technical tasks identified and experimental work initiated.
Several commercial applications of remote sensing data, such as water resources management, environmental monitoring, climate prediction, agriculture, forestry, preparation for and migration of extreme weather events, require access to vast amounts of archived high quality data, software tools and services for data manipulation and information extraction. These on the other hand require gaining detailed understanding of the data's internal structure and physical implementation of data reduction, combination and data product production. The time-consuming task must be undertaken before the core investigation can begin and is an especially difficult challenge when science objectives require users to deal with large multi-sensor data sets of different formats, structures, and resolutions.