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NASA NTRS2019

Cloud Giovanni: Reining in Costs and Improving Performance with Analytical Data Stores Using Scalable Serverless Architecture

Giovanni is the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure developed at NASA GES DISC which provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science data. It receives large number of user requests each day for a variety of analysis and visualization services, which leads to the big data challenge of serving gradually increasing large data volumes with diverse statistical algorithms. We hereby propose a multi-dimensional accumulation method which provides fast and cost-efficient cloud analysis for diverse services including both area averaging and time averaging. This method involves the weighted volume integration over multiple variable dimensions (time and space), and is implemented in AWS using Athena providing serverless and highly scalable data analysis. Compared to the standard method, this approach dramatically reduced the computational time by order of magnitude with a minimal AWS cost incurred. For example, for a benchmark of 10-year area averaging over the 1x1 degree daily variable, the computational time was reduced from minutes to seconds, and the Athena cost is only $5 for 100,000 requests.

Zhang, Hailiang↗
NASA NTRS1973

Sleep-monitoring, experiment M133

The Skylab sleep-monitoring experiment simulated the timelines and environment expected during a 56-day Skylab mission. Two crewmembers utilized the data acquisition and analysis hardware, and their sleep characteristics were studied in an online fashion during a number of all night recording sessions. Comparison of the results of online automatic analysis with those of postmission visual data analysis was favorable, confirming the feasibility of obtaining reliable objective information concerning sleep characteristics during the Skylab missions. One crewmember exhibited definite changes in certain sleep characteristics (e.g., increased sleep latency, increased time Awake during first third of night, and decreased total sleep time) during the mission.

Frost, J. D., Jr.↗
NASA NTRS1999

NASA/NOAA: Earth Science Electronic Theater 1999

The Electronic Theater (E-theater) presents visualizations which span the period from the original Suomi/Hasler animations of the first ATS-1 GEO weather satellite images in 1966 to the latest 1999 NASA Earth Science Vision for the next 25 years. Hot off the SGI-Onyx Graphics-Supercomputer are NASA's visualizations of Hurricanes Mitch, Georges, Fran and Linda. These storms have been recently featured on the covers of National Geographic, Time, Newsweek and Popular Science. Highlights will be shown from the NASA hurricane visualization resource video tape that has been used repeatedly this season on National and International network TV. Results will be presented from a new paper on automatic wind measurements in Hurricane Luis from 1-min GOES images that appeared in the November BAMS. The visualizations are produced by the NASA Goddard Visualization and Analysis Laboratory (VAL/912), and Scientific Visualization Studio (SVS/930), as well as other Goddard and NASA groups using NASA, NOAA, ESA, and NASDA Earth science datasets. Visualizations will be shown from the Earth Science E-Theater 1999 recently presented in Tokyo, Paris, Munich, Sydney, Melbourne, Honolulu, Washington, New York, and Dallas. The presentation Jan 11-14 at the AMS meeting in Dallas used a 4-CPU SGI/CRAY Onyx Infinite Reality Super Graphics Workstation with 8 GB RAM and a Terabyte Disk at 3840 X 1024 resolution with triple synchronized BarcoReality 9200 projectors on a 60ft wide screen. Visualizations will also be featured from the new Earth Today Exhibit which was opened by Vice President Gore on July 2, 1998 at the Smithsonian Air & Space museum in Washington, as well as those presented for possible use at the American Museum of Natural History (NYC), Disney EPCOT, and other venues. New methods are demonstrated for visualizing, interpreting, comparing, organizing and analyzing immense HyperImage remote sensing datasets and three dimensional numerical model results. We call the data from many new Earth sensing satellites, HyperImage datasets, because they have such high resolution in the spectral, temporal, spatial, and dynamic range domains. The traditional numerical spreadsheet paradigm has been extended to develop a scientific visualization approach for processing HyperImage datasets and 3D model results interactively. The advantages of extending the powerful spreadsheet style of computation to multiple sets of images and organizing image processing were demonstrated using the Distributed image SpreadSheet (DISS). The DISS is being used as a high performance testbed Next Generation Internet (NGI) VisAnalysis of: 1) El Nino SSTs and NDVI response 2) Latest GOES 10 5-min rapid Scans of 26 day 5000 frame movie of March & April '98 weather and tornadic storms 3) TRMM rainfall and lightning 4)GOES 9 satellite images/winds and NOAA aircraft radar of hurricane Luis, 5) lightning detector data merged with GOES image sequences, 6) Japanese GMS, TRMM, & ADEOS data 7) Chinese FY2 data 8) Meteosat & ERS/ATSR data 9) synchronized manipulation of multiple 3D numerical model views; and others will be illustrated. The Image SpreadSheet has been highly successful in producing Earth science visualizations for public outreach. Many of these visualizations have been widely disseminated through the world wide web pages of the HPCC/LTP/RSD program which can be found at http://rsd.gsfc.nasa.gov/rsd The one min interval animations of Hurricane Luis on ABC Nightline and the color perspective rendering of Hurricane Fran published by TIME, LIFE, Newsweek, Popular Science, National Geographic, Scientific American, and the "Weekly Reader" are some of the examples which will be shown.

Hasler, A. Fritz↗
NASA NTRS2011

Scientific Visualization to Study Flux Transfer Events at the Community Coordinated Modeling Center

In this paper we present results of modeling of reconnection at the dayside magnetopause with subsequent development of flux transfer event signatures. The tools used include new methods that have been added to the suite of visualization methods that are used at the Community Coordinated Modeling Center (CCMC). Flux transfer events result from localized reconnection that connect magnetosheath magnetic field and plasma with magnetospheric fields and plasma and results in flux rope structures that span the dayside magnetopause. The onset of flux rope formation and the three-dimensional structure of flux ropes are studied as they have been modeled by high-resolution magnetohydrodynamic simulations of the dayside magnetosphere of the Earth. We show that flux transfer events are complex three-dimensional structures that require modern visualization and analysis techniques. Two suites of visualization methods are presented and we demonstrate the usefulness of those methods through the CCMC web site to the general science user.

Rastatter, Lutz↗
NASA NTRS2019

NASA Global Satellite and Model Data Products and Services for Tropical Cyclone Research

The lack of observations over vast tropical oceans is a major challenge for tropical cyclone research. Satellite observations and model reanalysis data play an important role in filling these- gaps. Established in the mid-1980's, the Goddard Earth Sciences Data and Information Services Center (GES DISC), as one of the 12 NASA data centers, archives and distributes data from several Earth science disciplines such as precipitation, atmospheric dynamics, atmospheric composition, hydrology, including well-known NASA satellite missions (e.g. TRMM, GPM) and model assimilation projects (MERRA-2). Acquiring datasets suitable for tropical cyclone research in a large data archive is a challenge for many, especially for those who are not familiar with satellite or model data. Over the years, the GES DISC has developed user-friendly data services. For example, Giovanni is an online visualization and analysis tool, allowing users to visualize and analyze over 2000 satellite- and model-based variables with a Web browser, without downloading data and software. In this chapter, we will describe data and services at the GES DISC with emphasis on tropical cyclone research. We will also present two case studies and discuss future plans.

Liu, Zhong↗
NASA NTRS1993

A distributed system for visualizing and analyzing multivariate and multidisciplinary data

THe Linked Windows Interactive Data System (LinkWinds) is being developed with NASA support. The objective of this proposal is to adapt and apply that system in a complex network environment containing elements to be found by scientists working multidisciplinary teams on very large scale and distributed data sets. The proposed three year program will develop specific visualization and analysis tools, to be exercised locally and remotely in the LinkWinds environment, to demonstrate visual data analysis, interdisciplinary data analysis and cooperative and interactive televisualization and analysis of data by geographically separated science teams. These demonstrators will involve at least two science disciplines with the aim of producing publishable results.

Jacobson, Allan S.↗
NASA NTRS2006

A-Train Data Depot: Integrating, Visualizing, and Extracting Cloudsat, CALIPSO, MODIS, and AIRS Atmospheric Measurements Along the A-Train Tracks

The succession of US and international Earth observing satellites that follow each other, seconds to minutes apart, across the local afternoon equator crossing is called the ATrain. The A-Train consists of the following satellites, in order of equator crossing: OCO, EOS Aqua, CloudSat, CALIPSO, PARASOL, and EOS Aura. Flying in such formation increases the number of observations, validates observations, and enables coordination between science observations, resulting in a more complete virtual science platform (Kelly, 2000). The goal of this project is to create the first ever A-Train virtual data portal/center, the A-Train Data Depot (ATDD), to process, archive, access, visualize, analyze and correlate distributed atmosphere measurements from various A-Train instruments along A-Train tracks. The ATDD will enable the free movement of remotely located A-Train data so that they are combined to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. Once the infrastructure of the ATDD is in place, it will be easily evolved to serve data from all A-Train data measurements: one stop shopping. The innovative approach of analyzing and visualizing atmospheric profiles along the platforms track (i.e., time) will be accommodated by reusing the GSFC Atmospheric Composition Data and Information Services Center (ACDISC) visualization and analysis tool, GIOVANNI, existing data reduction tools, on-line archiving for fast data access, access to remote data without unnecessary data transfers, and data retrieval by users finding data desirable for further study. Initial measurements utilized include CALIPSO lidar backscatter, CloudSat radar reflectivity, clear air relative humidity, water vapor and temperature from AIRS, and cloud properties and aerosols from both MODIS. This will be foilowed by associated measurements from TVILS, =MI, HIRDLS, sad TES. Given the independent nature of instrumentlplatform development, the ATDD project has been met with many interesting challenges that, once resolved, will provide a much greater understanding of the relative flight dynamics and data co-registration of the suite of A-Train instruments, thus greatly increasing the accuracy of A-Train data analysis. Some of these challenges will be illustrated and discussed. The project's early visualizations and analysis efforts illustrate the importance of managing data so that measurements from various missions can be combined to enhance the understanding of the atmosphere. A-Train data management coordination, as performed here, is extremely significant in facilitating the A-Train science of clouds, precipitation, aerosol and chemistry.

Kempler, Steven↗
NASA NTRS1992

A distributed system for visualizing and analyzing multivariate and multidisciplinary data

The Linked Windows Interactive Data System (Link Winds) is being developed with NASA support. The objective of this proposal is to adapt and apply that system in a complex network environment containing elements to be found by scientists working multidisciplinary teams on very large scale and distributed data sets. The proposed three year program will develop specific visualization and analysis tools, to be exercised locally and remotely in the Link Winds environment, to demonstrate visual data analysis, interdisciplinary data analysis and cooperative and interactive televisualization and analysis of data by geographically separated science teams. These demonstrations will involve at least two science disciplines with the aim of producing publishable results.

Jacobson, Allan S.↗
NASA NTRS1973

Finite element analysis and computer graphics visualization of flow around pitching and plunging airfoils

A general computational method for analyzing unsteady flow around pitching and plunging airfoils was developed. The finite element method was applied in developing an efficient numerical procedure for the solution of equations describing the flow around airfoils. The numerical results were employed in conjunction with computer graphics techniques to produce visualization of the flow. The investigation involved mathematical model studies of flow in two phases: (1) analysis of a potential flow formulation and (2) analysis of an incompressible, unsteady, viscous flow from Navier-Stokes equations.

Bratanow, T.↗
NASA NTRS2008

Small-Body Extensions for the Satellite Orbit Analysis Program (SOAP)

An extension to the SOAP software allows users to work with tri-axial ellipsoid-based representations of planetary bodies, primarily for working with small, natural satellites, asteroids, and comets. SOAP is a widely used tool for the visualization and analysis of space missions. The small body extension provides the same visualization and analysis constructs for use with small bodies. These constructs allow the user to characterize satellite path and instrument cover information for small bodies in both 3D display and numerical output formats. Tri-axial ellipsoids are geometric shapes the diameters of which are different in each of three principal x, y, and z dimensions. This construct provides a better approximation than using spheres or oblate spheroids (ellipsoids comprising two common equatorial diameters as a distinct polar diameter). However, the tri-axial ellipsoid is considerably more difficult to work with from a modeling perspective. In addition, the SOAP small-body extensions allow the user to actually employ a plate model for highly irregular surfaces. Both tri-axial ellipsoids and plate models can be assigned to coordinate frames, thus allowing for the modeling of arbitrary changes to body orientation. A variety of features have been extended to support tri-axial ellipsoids, including the computation and display of the spacecraft sub-orbital point, ground trace, instrument footprints, and swathes. Displays of 3D instrument volumes can be shown interacting with the ellipsoids. Longitude/latitude grids, contour plots, and texture maps can be displayed on the ellipsoids using a variety of projections. The distance along an arbitrary line of sight can be computed between the spacecraft and the ellipsoid, and the coordinates of that intersection can be plotted as a function of time. The small-body extension supports the same visual and analytical constructs that are supported for spheres and oblate spheroids in SOAP making the implementation of the more complex algorithms largely transparent to the user.

Carnright, Robert↗
NASA NTRSDate not supplied

Data Democratization: Challenges and Opportunities

Democratizing Earth data is one of the challenges many organizations around the world face in order to maximize the use of their Earth data for research, applications, education, and societal benefits. For example, at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC), over 1600 global and regional datasets in several NASA Earth science focus areas, including atmospheric composition, water and energy cycles, and climate variability, are archived and distributed to the public. Giovanni, the Geospatial Interactive Online Visualization and Analysis Infrastructure, was developed by GES DISC to facilitate data access and exploration, especially for novice users of Earth science. With Giovanni, users can analyze and visualize over 2000 Earth science variables (e.g., precipitation, aerosol, surface wind) without downloading data, software, the expert understanding of data formats and structures, and coding skills, lowering the barrier to data analysis/comparison by preprocessing and accessing to the data. Results of data analysis and visualization can be accessed in several popular formats (e.g., NetCDF, CSV). As a result of Giovanni's efforts, more than 3000 referral papers have been published in various fields. In spite of this, Giovanni is still difficult to use for some users. For instance, if one searches for "precipitation," it will return over 150 related variables. The question is, which one to use? Furthermore, variables from different data providers (e.g., satellites and models) are named differently with different units, further confusing users, especially those outside the communities. Data democratization is complex and multifaceted. Challenges include service and data discovery, user experiences, visualization, data quality, trustworthiness, and more. In this presentation, we will examine Giovanni as an example of challenges and opportunities in developing data democratization services.

data democratization↗
NASA NTRS1993

DataHub - Science data management in support of interactive exploratory analysis

DataHub addresses four areas of significant need: scientific visualization and analysis; science data management; interactions in a distributed, heterogeneous environment; and knowledge-based assistance for these functions. The fundamental innovation embedded within the DataHub is the integration of three technologies, viz. knowledge-based expert systems, science visualization, and science data management. This integration is based on a concept called the DataHub. With the DataHub concept, science investigators are able to apply a more complete solution to all nodes of a distributed system. Both computational nodes and interactive nodes are able to effectively and efficiently use the data services (access, retrieval, update, etc.) in a distributed, interdisciplinary information system in a uniform and standard way. This allows the science investigators to concentrate on their scientific endeavors, rather than to involve themselves in the intricate technical details of the systems and tools required to accomplish their work. Thus, science investigators need not be programmers. The emphasis is on the definition and prototyping of system elements with sufficient detail to enable data analysis and interpretation leading to information. The DataHub includes all the required end-to-end components and interfaces to demonstrate the complete concept.

Handley, Thomas H., Jr.↗
NASA NTRSDate not supplied

Creating Satellite Data Products in the Cloud: SatCORPS Global Cloud Composites

Real time satellite observations and real time derived cloud products are becoming an important tool for both science as well as business ventures. The SatCORPS group leverages public and private cloud-based sources of satellite observations to create its Global Cloud Composite product in near real-time. This dataset allows others access to cloud information that can be accessed directly from the cloud. In this work, we describe the software algorithms and software infrastructure that we have created to create and distribute this product through our hybrid cloud and on-premises system that leverages the strengths and weaknesses of each platform. We will also describe the GCC product itself in terms of the scientific parameters available, resolution and temporal availability. Finally, we will also describe our web-based tools including our Geographic Information System that can be used for visualization and analysis. The products from the processing can be geospatially-service enabled as ArcGIS Image Services and Open Geospatial Consortium (OGC) Web Mapping/Coverage Services for visualization and analysis via a web mapping application and common geospatial software. The SatCORPS Global Composite Cloud product provides sophisticated global cloud products with very low latency which we see that as filling a rapidly growing need in the research, modelling and business community. We present a detailed description of the SatCORPS GCC product in terms of the capabilities and research benefits as well as the delivery architecture in AWS. We take the discussion further and describe the web tools that the SatCORPS group has developed that allow users to access and use the GIS data that it creates.

Global Cloud Composite SatCORPS SMCE AWS↗
NASA NTRS1993

Visualization techniques to aid in the analysis of multispectral astrophysical data sets

The goal of this project was to support the scientific analysis of multi-spectral astrophysical data by means of scientific visualization. Scientific visualization offers its greatest value if it is not used as a method separate or alternative to other data analysis methods but rather in addition to these methods. Together with quantitative analysis of data, such as offered by statistical analysis, image or signal processing, visualization attempts to explore all information inherent in astrophysical data in the most effective way. Data visualization is one aspect of data analysis. Our taxonomy as developed in Section 2 includes identification and access to existing information, preprocessing and quantitative analysis of data, visual representation and the user interface as major components to the software environment of astrophysical data analysis. In pursuing our goal to provide methods and tools for scientific visualization of multi-spectral astrophysical data, we therefore looked at scientific data analysis as one whole process, adding visualization tools to an already existing environment and integrating the various components that define a scientific data analysis environment. As long as the software development process of each component is separate from all other components, users of data analysis software are constantly interrupted in their scientific work in order to convert from one data format to another, or to move from one storage medium to another, or to switch from one user interface to another. We also took an in-depth look at scientific visualization and its underlying concepts, current visualization systems, their contributions and their shortcomings. The role of data visualization is to stimulate mental processes different from quantitative data analysis, such as the perception of spatial relationships or the discovery of patterns or anomalies while browsing through large data sets. Visualization often leads to an intuitive understanding of the meaning of data values and their relationships by sacrificing accuracy in interpreting the data values. In order to be accurate in the interpretation, data values need to be measured, computed on, and compared to theoretical or empirical models (quantitative analysis). If visualization software hampers quantitative analysis (which happens with some commercial visualization products), its use is greatly diminished for astrophysical data analysis. The software system STAR (Scientific Toolkit for Astrophysical Research) was developed as a prototype during the course of the project to better understand the pragmatic concerns raised in the project. STAR led to a better understanding on the importance of collaboration between astrophysicists and computer scientists. Twenty-one examples of the use of visualization for astrophysical data are included with this report. Sixteen publications related to efforts performed during or initiated through work on this project are listed at the end of this report.

Brugel, E. W.↗
NASA NTRS1993

Visualization techniques to aid in the analysis of multi-spectral astrophysical data sets

The goal of this project was to support the scientific analysis of multi-spectral astrophysical data by means of scientific visualization. Scientific visualization offers its greatest value if it is not used as a method separate or alternative to other data analysis methods but rather in addition to these methods. Together with quantitative analysis of data, such as offered by statistical analysis, image or signal processing, visualization attempts to explore all information inherent in astrophysical data in the most effective way. Data visualization is one aspect of data analysis. Our taxonomy as developed in Section 2 includes identification and access to existing information, preprocessing and quantitative analysis of data, visual representation and the user interface as major components to the software environment of astrophysical data analysis. In pursuing our goal to provide methods and tools for scientific visualization of multi-spectral astrophysical data, we therefore looked at scientific data analysis as one whole process, adding visualization tools to an already existing environment and integrating the various components that define a scientific data analysis environment. As long as the software development process of each component is separate from all other components, users of data analysis software are constantly interrupted in their scientific work in order to convert from one data format to another, or to move from one storage medium to another, or to switch from one user interface to another. We also took an in-depth look at scientific visualization and its underlying concepts, current visualization systems, their contributions, and their shortcomings. The role of data visualization is to stimulate mental processes different from quantitative data analysis, such as the perception of spatial relationships or the discovery of patterns or anomalies while browsing through large data sets. Visualization often leads to an intuitive understanding of the meaning of data values and their relationships by sacrificing accuracy in interpreting the data values. In order to be accurate in the interpretation, data values need to be measured, computed on, and compared to theoretical or empirical models (quantitative analysis). If visualization software hampers quantitative analysis (which happens with some commercial visualization products), its use is greatly diminished for astrophysical data analysis. The software system STAR (Scientific Toolkit for Astrophysical Research) was developed as a prototype during the course of the project to better understand the pragmatic concerns raised in the project. STAR led to a better understanding on the importance of collaboration between astrophysicists and computer scientists.

Brugel, Edward W.↗
NASA NTRS1994

A Space and Atmospheric Visualization Science System

SAVS (a Space and Atmospheric Visualization Science system) is an integrated system with user-friendly functionality that employs a 'push-button' software environment that mimics the logical scientific processes in data acquisition, reduction, analysis, and visualization. All of this is accomplished without requiring a detailed understanding of the methods, networks, and modules that link the tools and effectively execute the functions. This report describes SAVS and its components, followed by several applications based on generic research interests in interplanetary and magnetospheric physics (IMP/ISTP), active experiments in space (CRRES), and mission planning focused on the earth's thermospheric, ionospheric, and mesospheric domains (TIMED). The final chapters provide a user-oriented description of interface functionalities, hands-on operations, and customized modules, with details of the primary modules presented in the appendices. The overall intent of the report is to reflect the accomplishments of the three-year development effort and to introduce potential users to the power and utility of the integrated data acquisition, analysis, and visualization system.

Szuszczewicz, E. P.↗