Computer Scientists, Your Planet Needs You: An Introduction to Access-Optimized Data
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In the aftermath of the Space Shuttle Columbia accident February 1, 2003, the Columbia Accident Investigation Board recognized the need for better video data from launch, on-orbit, and landing to assess the status and safety of the shuttle orbiter fleet. The board called on NASA to improve its imagery assets and update the Agency s methods for analyzing video. This paper will feature details of several projects implemented prior to the return to flight of the Space Shuttle, including an airborne HDTV imaging system called the WB-57 Ascent Video Experiment, use of true 60 Hz progressive scan HDTV for ground and airborne HDTV camera systems, and the decision to utilize a wavelet compression system for recording. This paper will include results of compression testing, imagery from the launch of STS-114, and details of how commercial components were utilized to image the shuttle launch from an aircraft flying at 400 knots at 60,000 feet altitude. The paper will conclude with a review of future plans to expand on the upgrades made prior to return to flight.
The S-056 observations consist of 27,000 photographs (filterheliograms) obtained by the X-ray telescope and 1,100 h of proportional counter data obtained by the X-ray event analyzer in the soft X-ray region of the solar spectrum. A description of the S-056 data together with additional relevant information that may be needed by users of the data is given.
The dose from heavy ion beams has been calculated using a one-dimensional transport theory and evaluated for 670 MeV/amu 20 Ne beams in water. The result is presented so as to be applicable to arbitrary ions for which the necessary interaction data are known. The present evaluation is based on thar Silberg-Tsao fragmentation parameters augmented with light fragment production from intranuclear cascades, recently calculated nuclear absorption cross sections, and evaluated stopping power data. Comparison with recent experimental data obtained at the Lawrence Berkeley Laboratory reveals the need for more accurate fragmentation data.
UNIX Based Data Management System is collection of computer programs for use in Pilot Field Experiment (PiFEx), which attempts to mimic mobile/satellite-communications (MSAT) scenario. Major purposes to define mobile-communications channels and test workability of new concepts used to design various components of receiver system. Results, large amounts of raw data that must be retrieved according to researcher's needs. Intended to manage PiFEx data in interactive way. Written in either FORTRAN-77 or UNIX shell-scripts.
The NASA Lewis Research Center's Principal Investigator Microgravity Services project analyzes Orbital Acceleration Research Experiment and Space Acceleration Measurement System data for principal investigators of microgravity experiments. Principal investigators need a thorough understanding of data analysis techniques so that they can request appropriate analyses to best interpret accelerometer data. Accelerometer data sampling and filtering is introduced along with the related topics of resolution and aliasing. Specific information about the Orbital Acceleration Research Experiment and Space Acceleration Measurement System data sampling and filtering is given. Time domain data analysis techniques are discussed and example environment interpretations are made using plots of acceleration versus time, interval average acceleration versus time, interval root-mean-square acceleration versus time, trimmean acceleration versus time, quasi-steady three dimensional histograms, and prediction of quasi-steady levels at different locations. An introduction to Fourier transform theory and windowing is provided along with specific analysis techniques and data interpretations. The frequency domain analyses discussed are power spectral density versus frequency, cumulative root-mean-square acceleration versus frequency, root-mean-square acceleration versus frequency, one-third octave band root-mean-square acceleration versus frequency, and power spectral density versus frequency versus time (spectrogram). Instructions for accessing NASA Lewis Research Center accelerometer data and related information using the internet are provided.
This slide presentation reviews a Space-time query system that has been developed to assist the user in finding Earth science data that fulfills the researchers needs. It reviews the reasons why finding Earth science data can be so difficult, and explains the workings of the Space-Time Query with OpenSearch and how this system can assist researchers in finding the required data, It also reviews the developments with client server systems.
The 2017 Decadal Survey (DS) highlighted Earth System Science themes, science and application questions, and several high priority objectives that have led to the inclusion of Aerosols (A) and Clouds-Convection-Precipitation (CCP) as Designated Observables (DOs). On June 1, 2018, several NASA centers (GSFC, LaRC, JPL, MSFC, GRC and ARC) submitted a joint Study Plan to the NASA Earth Science Division for the Aerosol (A) and Cloud, Convection, and Precipitation (CCP) Pre-formulation Study (ACCP), with the ACCP Study concluding in early 2021. The new mission now in pre-phase A is being referred to as the Atmosphere Observing System (AOS), an integral part of NASA’s Earth System Observatory (ESO) strategy. The DS and the ACCP team recognized the science merit in combining the A and CCP DOs for both enhancing the ability to address a number of science objectives and also to provide an expanded capability to address additional objectives beyond those of the individual DOs. A critical element of the ACCP observing strategy is to make extensive use of new passive and active sensors as well as of the so-called Program-of-Record (PoR), complemented by a fully integrated sub-orbital component. In order to achieve maximum benefit, all these observations need to be integrated into comprehensive observing and modeling/data assimilation systems. Such an approach requires comprehensive model-data synthesis capabilities that needs to be conceived in conjunction with the space-based and suborbital components of AOS. In this presentation we will summarize the major science goals of AOS including cloud feedbacks, atmospheric convection, emphasizing aerosol processes and aerosol radiative effects, and the synergistic aspects of clouds-precipitation-aerosol interactions. We will describe examples of how AOS data will be used across space and time to better initialize forecasts and train modeling systems, and to infuse models and data assimilation systems with AOS data for advancing operational predictions and to generate expanded hindcasts and reconstruction of the climate record.
Writing efficient parallel programs is complicated by the need to select the right data structure alignments and distributions, which determine the nature and volume of inter-processor communications. A large number of performance tools for parallel programs have been developed recently to expose these inter-processor communications. However, none of them support performance views or provide statistics in terms of inter-processor data structure interactions. A performance tool that tracks the interaction between individual data structures and the context of these interactions is essential for understanding the performance of both explicit message passing programs and data-parallel languages such as HPF. In this paper we discuss the use of compiler front end tools for automatically tracking data structure movements in message passing programs, and low-overhead monitoring and postprocessing of such codes. We demonstrate that robust instrumentation and low overhead monitoring of inter-processor data structure movements is possible, with the use of a number of NAS benchmark codes, run on the i860 hypercube. We also show that the data so collected can be used effectively by post processing tools that expose performance bottlenecks using graphical displays and performance statistics.
In order to conduct research into global warming, the Earth Observing System Data and Information System (EOSDIS) generates a large and growing volume of data. This viewgraph presentation describes the architecture needed to manage the remote sensing data, and the numerical analysis used to process it.
One of the remaining challenges to structural biology is the solution of modulated structures. While small molecule crystallographers have championed this type of structure, to date, no modulated macromolecular structures have been determined. Modulation of the molecular structures within the crystal can produce satellite reflections or a superlattice of reflections in reciprocal space. We have developed the data collection methods and strategies that are needed to collect and analyze these data. If the macromolecule's crystal lattice is composed of physiologically relevant packing contacts, structural changes induced under physiological conditions can cause distortion relevant to the function and biophysical processes of the molecule making up the crystal. By careful measurement of the distortion, and the corresponding three-dimensional structure of the distorted molecule, we will visualize the motion and mechanism of the biological macromolecule(s). We have measured the modulated diffraction pattern produced by the semicrystalline state of profilin:actin crystals using highly parallel and highly monochromatic synchrotron radiation coupled with fine phi slicing (0.001-0.010 degrees) for structure determination. These crystals present these crystals present a unique opportunity to address an important question in structural biology. The modulation is believed to be due to the formation of actin helical filaments from the actin beta ribbon upon the pH-induced dissociation of profilin. To date, the filamentous state of actin has resisted crystallization and no detailed structures are available. The semicrystalline state profilin:actin crystals provides a unique opportunity to understand the many conformational states of actin. This knowledge is essential for understanding the dynamics underlying shape changes and motility of eukaryotic cells. Many essential processes, such as cytokinesis, phagocytosis, and cellular migration depend upon the capacity of the actin microfilament system to be restructured in a controlled manner via polymerization, depolymerization, severing, cross-linking, and anchorage. The structure the semicrystalline state of profilin:actin will challenge and validate current models of muscle contraction and cell motility. The methodology and theory under development will be easily extendable to other systems.
Coral reefs are the center of marine biodiversity, yet are under threat with an estimated 60% of coral reef habitats considered at risk by the World Resources Institute. The location and extent of coral reefs in the world are the basic information required for resource management and as a baseline for monitoring change. A NASA sponsored partnership between remote sensing scientists, international agencies and NGOs, has developed a new generation of global reef maps based on data collected by satellites. The effort, dubbed the Millennium Coral Reef Map aims to develop new methods for wide distribution of voluminous satellite data of use to the conservation and management communities. We discuss the tradeoffs between remote sensing data sources, mapping objectives, and the needs for conservation and resource management. SeaWiFS data were used to produce a composite global shallow bathymetry map at 1 km resolution. Landsat 7/ETM+ data acquisition plans were modified to collect global reefs and new operational methods were designed to generate the firstever global coral reef geomorphology map. We discuss the challenges encountered to build these databases and in implementing the geospatial data distribution strategies. Conservation applications include a new assessment of the distribution of the world s marine protected areas (UNEPWCMC), improved spatial resolution in the Reefs at Risk analysis for the Caribbean (WRI), and a global basemap for the Census of Marine Life's OBIS database. The Millennium Coral Reef map and digital image archive will pay significant dividends for local and regional conservation projects around the globe. Complete details of the project are available at http://eol.jsc.nasa.gov/reefs.
The Research Data Alliance (RDA) enables data to be shared across barriers through focused working groups and interest groups, formed of experts from around the world - from academia, industry and government. Its Big Data Analytics (BDA) interest groups seeks to develop community based recommendations on feasible data analytics approaches to address scientific community needs of utilizing large quantities of data. BDA seeks to analyze different scientific domain applications (e.g. earth science use cases) and their potential use of various big data analytics techniques. These techniques reach from hardware deployment models up to various different algorithms (e.g. machine learning algorithms such as support vector machines for classification). A systematic classification of feasible combinations of analysis algorithms, analytical tools, data and resource characteristics and scientific queries will be covered in these recommendations. This contribution will outline initial parts of such a classification and recommendations in the specific context of the field of Earth Sciences. Given lessons learned and experiences are based on a survey of use cases and also providing insights in a few use cases in detail.
The use of computer aided classification of LANDSAT data in developing water quality plans for New Jersey watersheds is used to exemplify how a state natural resource management program benefits from satellite imagery. The transition of a research and development system into an operational remote sensing system to help decision makers is demonstrated. Nontechnial issues that can assist (or hinder) an agency in adopting a new technology are examined. The progress of LANDSAT use by state government from the earliest stage of curiosity through to incorporation in actual state planning methods is charted. Potential applications of LANDSAT data to real information needs and solutions to management problems are examined. The problems and mistakes that occurred in using LANDSAT data in the past are discussed as well as the ways by which these problems were overcome.
In data mining, one often needs to analyze datasets with a very large number of attributes. Performing machine learning directly on such data sets is often impractical because of extensive run times, excessive complexity of the fitted model (often leading to overfitting), and the well-known "curse of dimensionality." In practice, to avoid such problems, feature selection and/or extraction are often used to reduce data dimensionality prior to the learning step. However, existing feature selection/extraction algorithms either evaluate features by their effectiveness across the entire data set or simply disregard class information altogether (e.g., principal component analysis). Furthermore, feature extraction algorithms such as principal components analysis create new features that are often meaningless to human users. In this article, we present input decimation, a method that provides "feature subsets" that are selected for their ability to discriminate among the classes. These features are subsequently used in ensembles of classifiers, yielding results superior to single classifiers, ensembles that use the full set of features, and ensembles based on principal component analysis on both real and synthetic datasets.
NASA has made science and technology investments to better utilize its large space-borne remote sensing data holdings of the Earth. With the launch of Terra, NASA created a data-rich environment where the challenge is to fully utilize the data collected from EOS however, despite unprecedented amounts of observed data, there is a need for increasing the frequency, resolution, and diversity of observations. Current terrestrial models that use remote sensing data were constructed in a relatively data and compute limited era and do not take full advantage of on-line learning methods and assimilation techniques that can exploit these data. NASA has invested in visualization, data mining and knowledge discovery methods which have facilitated data exploitation, but these methods are insufficient for improving Earth science models that have extensive background knowledge nor do these methods refine understanding of complex processes. Investing in interdisciplinary teams that include computational scientists can lead to new models and systems for online operation and analysis of data that can autonomously improve in prediction skill over time.
Two altimeter concepts based on spaceborne synthetic-aperture-radar (SAR) proposed to gather global, uniformly sampled, high-resolution, topographical data on land and ice. Wide swath and high pulse rate of SAR makes possible to acquire spatially contiguous data over large areas in reasonable amount of time, and time needed for altimetric processing of SAR data considerably less than that needed to generate topographical maps from stereoscopic photographs. Radar less vulnerable to cloud cover and other weather conditions than optical techniques.
As communication and networking technologies advance, networks will become highly complex and heterogeneous, interconnecting different network domains. There is a need to provide user authentication and data protection in order to further facilitate critical mission operations, especially in the tactical and mission-critical net-centric networking environment. The Autonomous Information Unit (AIU) technology was designed to provide the fine-grain data access and user control in a net-centric system-testing environment to meet these objectives. The AIU is a fundamental capability designed to enable fine-grain data access and user control in the cross-domain networking environments, where an AIU is composed of the mission data, metadata, and policy. An AIU provides a mechanism to establish trust among deployed AIUs based on recombining shared secrets, authentication and verify users with a username, X.509 certificate, enclave information, and classification level. AIU achieves data protection through (1) splitting data into multiple information pieces using the Shamir's secret sharing algorithm, (2) encrypting each individual information piece using military-grade AES-256 encryption, and (3) randomizing the position of the encrypted data based on the unbiased and memory efficient in-place Fisher-Yates shuffle method. Therefore, it becomes virtually impossible for attackers to compromise data since attackers need to obtain all distributed information as well as the encryption key and the random seeds to properly arrange the data. In addition, since policy can be associated with data in the AIU, different user access and data control strategies can be included. The AIU technology can greatly enhance information assurance and security management in the bandwidth-limited and ad hoc net-centric environments. In addition, AIU technology can be applicable to general complex network domains and applications where distributed user authentication and data protection are necessary. AIU achieves fine-grain data access and user control, reducing the security risk significantly, simplifying the complexity of various security operations, and providing the high information assurance across different network domains.