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Spacecube: A Family of Reconfigurable Hybrid On-Board Science Data Processors

SpaceCube is a family of Field Programmable Gate Array (FPGA) based on-board science data processing systems developed at the NASA Goddard Space Flight Center (GSFC). The goal of the SpaceCube program is to provide 10x to 100x improvements in on-board computing power while lowering relative power consumption and cost. SpaceCube is based on the Xilinx Virtex family of FPGAs, which include processor, FPGA logic and digital signal processing (DSP) resources. These processing elements are leveraged to produce a hybrid science data processing platform that accelerates the execution of algorithms by distributing computational functions to the most suitable elements. This approach enables the implementation of complex on-board functions that were previously limited to ground based systems, such as on-board product generation, data reduction, calibration, classification, eventfeature detection, data mining and real-time autonomous operations. The system is fully reconfigurable in flight, including data parameters, software and FPGA logic, through either ground commanding or autonomously in response to detected eventsfeatures in the instrument data stream.

reconfigurable computing

EP/TOMS Science Data Processing Programmer's Guide. Version 1.9

This EP/TOMS Programmer's Guide provides detailed information concerning the data, software, operations, and maintenance of the EP/TOMS Science Data Processing System. This system was developed for the NASA Goddard Space Flight Center (GSFC), Laboratory for Atmospheres, Atmospheric Chemistry Branch (Code 916) by SSAI. The description of the EP/TOMS Science Data Processing System starts with an overall system perspective (Section 3). A description of all data files ingested, stored, and/or produced follows in Section 4. Detailed descriptions of each major software subsystem are in Section 5. Section 6 presents processing procedures. Section 7 presents maintenance procedures. Procedures for updating this document are included in Section 7.

Source record

DataHub: Science Data Management in Support of Interactive Exploratory Analysis

The 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, videlicet knowledge-based expert systems, science visualization, and science data management. With the DataHub concept, science investigators are able to apply a more complete solution to all nodes of a distributed system.

science

Collaborative Metadata Curation in Support of NASA Earth Science Data Stewardship

Growing collection of NASA Earth science data is archived and distributed by EOSDIS’s 12 Distributed Active Archive Centers (DAACs). Each collection and granule is described by a metadata record housed in the Common Metadata Repository (CMR). Multiple metadata standards are in use, and core elements of each are mapped to and from a common model – the Unified Metadata Model (UMM). Work done by the Analysis and Review of CMR (ARC) Team.

data stewardship

Calibration and Performance of Juno Radio Science Data

Juno Radio Science measures the frequency of X- and Ka-band radio links between the Juno spacecraft and the Earth-based observing stations of NASA’s Deep Space Network (DSN) in order to determine the gravitational field of Jupiter. The received frequency contains information on the gravitational field and is also perturbed by the propagation environment, including Earth troposphere and ionosphere, electrons in the solar plasma, electrons in the Io Plasma Torus around Jupiter, and instrumental effects on both the spacecraft and the ground electronics. Each of these effects must be calibrated out of the data to ensure an accurate estimation of the Jupiter gravitational field. This work discusses the data processing, calibration, and performance of the frequency measurements. The precision of the frequency measurements average 1.1 mHz (1σ standard deviation at 60 second integration time), or 5.3 microns/sec in units of velocity. The remaining noise sources are primarily from residual troposphere and charged particles. Further improvement could be made in future radio science experiments with the addition of a cross-link and stiffer ground antennas.

Buccino, Dustin R

Calibration and Performance of Juno Radio Science Data

Juno Radio Science measures the frequency of X- and Ka-band radio links between the Juno spacecraft and the Earth-based observing stations of NASA’s Deep Space Network (DSN) in order to determine the gravitational field of Jupiter. The received frequency contains information on the gravitational field and is also perturbed by the propagation environment, including Earth troposphere and ionosphere, electrons in the solar plasma, electrons in the Io Plasma Torus around Jupiter, and instrumental effects on both the spacecraft and the ground electronics. Each of these effects must be calibrated out of the data to ensure an accurate estimation of the Jupiter gravitational field. This work discusses the data processing, calibration, and performance of the frequency measurements. The precision of the frequency measurements average 1.1 mHz (1σ standard deviation at 60 second integration time), or 5.3 microns/sec in units of velocity. The remaining noise sources are primarily from residual troposphere and charged particles. Further improvement could be made in future radio science experiments with the addition of a cross-link and stiffer ground antennas.

Oudrhiri, Kamal

Giovanni in the Cloud: Earth Science Data Exploration in Amazon Web Services

Giovanni is an exploration tool at the NASA Goddard Earth Sciences Data Information Services Center (GES DISC), providing 22 analysis and visualization services for over 1600 Earth Science data variables. Owing to its popularity, Giovanni has experienced a consistent growth in overall demand, with periodic usage spikes attributed to trainings by education organizations, extensive data analysis in response to natural disasters, preparations for science meetings, etc. Furthermore, the new generation of spaceborne sensors and high resolution models have resulted in an exponential growth in data volume with data distributed across the traditional boundaries of data centers. Seamless exploration of data (without users having to worry about data center boundaries) has been a key recommendation of the GES DISC User Working Group. These factors have required new strategies for delivering acceptable performance. The cloud-based Giovanni, built on Amazon Web Services (AWS), evaluates (1) AWS native solutions to provide a scalable, serverless architecture; (2) open standards for data storage in the Cloud; (3) a cost model for operations; and (4) end-user performance. Our preliminary findings indicate that the use of serverless architecture has a potential to significantly reduce development and operational cost of Giovanni. The combination of using AWS managed services, storage of data in open standards, and schema-on-read data access strategy simplifies data access and analytics, in addition to making data more accessible to the end users of Giovanni through popular programming languages.

Giovanni

NASA space and Earth science data on CD-ROM

The National Space Science Data Center (NSSDC) is very interested in facilitating the widest possible use of the scientific data acquired through NASA spaceflight missions. Therefore, NSSDC has participated with projects and data management elements throughout the NASA science environment in the creation, archiving, and dissemination of data using Compact Disk-Read Only Memory (CD-ROM). This CD-ROM technology has the potential to enable the dissemination of very large data volumes at very low prices to a great many researchers, students and their teachers, and others. This catalog identifies and describes the scientific CD-ROM's now available from NSSDC including the following data sets: Einstein Observatory CD-ROM, Galileo Cruise Imaging on CD-ROM, International Halley Watch, IRAS Sky Survey Atlas, Infrared Thermal Mapper (IRTM), Magellan (MIDR), Magellan (ARCDR's), Magellan (GxDR's), Mars Digital Image Map (MDIM), Outer Planets Fields & Particles Data, Pre-Magellan, Selected Astronomical Catalogs, TOMS Gridded Ozone Data, TOMS Ozone Image Data, TOMS Update, Viking Orbiter Images of Mars, and Voyager Image.

Towheed, Syed S.

Multimission image processing and science data visualization

The Operational Science Analysis (OSA) Functional area supports science instrument data display, analysis, visualization and photo processing in support of flight operations of planetary spacecraft managed by the Jet Propulsion Laboratory (JPL). This paper describes the data products generated by the OSA functional area, and the current computer system used to generate these data products. The objectives on a system upgrade now in process are described. The design approach to development of the new system are reviewed, including use of the Unix operating system and X-Window display standards to provide platform independence, portability, and modularity within the new system, is reviewed. The new system should provide a modular and scaleable capability supporting a variety of future missions at JPL.

Green, William B.

Improving the Accessibility and Use of NASA Earth Science Data

Many of the NASA Langley Atmospheric Science Data Center (ASDC) Distributed Active Archive Center (DAAC) multidimensional tropospheric and atmospheric chemistry data products are stored in HDF4, HDF5 or NetCDF format, which traditionally have been difficult to analyze and visualize with geospatial tools. With the rising demand from the diverse end‐user communities for geospatial tools to handle multidimensional products, several applications, such as ArcGIS, have refined their software. Many geospatial applications now have new functionalities that enable the end user to: Store, serve, and perform analysis on each individual variable, its time dimension, and vertical dimension. Use NetCDF, GRIB, and HDF raster data formats across applications directly. Publish output within REST image services or WMS for time and space enabled web application development. During this webinar, participants will learn how to leverage geospatial applications such as ArcGIS, OPeNDAP and ncWMS in the production of Earth science information, and in increasing data accessibility and usability.

Tisdale, Matthew

Cassini/Huygens Program Archive Plan for Science Data

The purpose of this document is to describe the Cassini/Huygens science data archive system which includes policy, roles and responsibilities, description of science and supplementary data products or data sets, metadata, documentation, software, and archive schedule and methods for archive transfer to the NASA Planetary Data System (PDS).

NASA Planetary Science Data System

Enabling Communities in the Use and Application of NASA's Earth Science Data and Information Products: Interactive Webinars that Work

The vast active archives of NASA's Earth science data reflect the agency's ongoing commitment to producing the highest quality data, services and tools intended for a myriad of science and application uses worldwide. These data span the whole of Earth science domains, and most have direct uses in societal applications. As many internet-based tools mature they enable NASA to increase the availability to and, most importantly, the uses of these disparate data types. This poster/paper highlights one particularly effective tool the NASA Earth Science Data and Information System (ESDIS) Project is utilizing to increase our user communities' understanding of these data, services and tools and their varied uses. Webinars, or video-based, on-line, interactive discussions and presentations have become a staple for exchanging information via the internet. The NASA ESDIS Project is using this platform to create a rich, highly-available, source of cutting-edge insights into the uses of Earth science data and applications. As evidence, we present a representative sample of the webinar offerings created by ESDIS beginning in 2013.

Lindsay, Francis E.

MISR Level 1A CCD Science data, all cameras (MIL1A_V2)

The Level 1A data are raw MISR data that are decommutated, reformatted 12-bit Level 0 data shifted to byte boundaries, i.e., reversal of square-root encoding applied and converted to 16 bit, and annotated (e.g., with time information). These data are used by the Level 1B1 processing algorithm to generate calibrated radiances. The science data output preserves the spatial sampling rate of the Level 0 raw MISR CCD science data. CCD data are collected during routine science observations of the sunlit portion of the Earth. Each product represents one 'granule' of data. A 'granule' is defined to be the smallest unit of data required for MISR processing. Also, included in the Level 1A product are pointers to calibration coefficient files provided for Level 1B processing. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180].

AM-1

MISR Level 1A CCD Science data, all cameras (MIL1A_V1)

The Level 1A data are raw MISR data that are decommutated, reformatted 12-bit Level 0 data shifted to byte boundaries, i.e., reversal of square-root encoding applied and converted to 16 bit, and annotated (e.g., with time information). These data are used by the Level 1B1 processing algorithm to generate calibrated radiances. The science data output preserves the spatial sampling rate of the Level 0 raw MISR CCD science data. CCD data are collected during routine science observations of the sunlit portion of the Earth. Each product represents one 'granule' of data. A 'granule' is defined to be the smallest unit of data required for MISR processing. Also, included in the Level 1A product are pointers to calibration coefficient files provided for Level 1B processing. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180].

CCD

The Advantages of Synergy-Quantitative Earth Science Data Visualization and Analysis with Giovanni, Panoply, and Excel

The NASA Giovanni data analysis system provides a multitude of basic analysis capabilities for numerous Earth science data products which are available in the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) archive, as well as for additional selected data products provided by other NASA Distributed Active Archive Center (DAAC) archives. In Giovanni, users can easily generate time-averaged data maps, area-averaged time-series, Latitude-Time and Longitude-Time Hovmoeller diagrams, correlation maps, accumulation maps, and map animations (22 analysis options are available in total). While ASCII text output is available for time-series plots, it is not included as an option for data maps. In order to provide a quantitative, easy-to-use numerical output in ASCII text form, the NetCDF file output from a Giovanni visualization is downloaded and then opened with the free NASA visualization software package Panoply. Panoply provides the capability of translating the Giovanni file into comma-separated-variable (CSV) output. Panoply also provides additional visualization options, including the facile calculation of difference maps and quasi-anomaly maps using Giovanni output files. The CSV files from Panoply can then be imported into an Excel spreadsheet, where an Excel macro converts the CSV files. The output consists of latitude-longitude-data value triads in text form for maps, and either longitude-time-data value or latitude-time-data value triads in text form for Hovmoeller diagrams. This presentation will explicate the basic procedure for the conversion, and then provide several examples where the procedure is applied to Giovanni output from different analysis options.

Earth science

The NPOESS Preparatory Project (NPP) Science Data Segment (SDS) Data Depository and Distribution Element (SD3E) System Architecture

The National Polar-orbiting Operational Environmental Satellite System (NPOESS), the U.S. Government's future low-Earth orbiting satellite system, will monitor global weather and environmental conditions. Serving as a risk reduction for NPOESS, the NPOESS Preparatory Project (NPP) will provide remotely sensed atmospheric, land, ocean, ozone, and sounder data that will serve the meteorological and global climate change scientific communities. The National Aeronautics and Space Administration (NASA) NPP Science Data Segment's (SDS) primary role is to independently assess the quality of the NPP science and environmental data records for their ability to support climate research. The SDS is composed of nine elements; an input element that receives data from the operational agencies and acts as a buffer, a calibration analysis element, five elements devoted to measurement based quality assessment, an element used to test algorithmic improvements, and an element that provides overall science direction. Each element requires a set of sensor specific science data products for their evaluation. There are four NPP sensors that will be flown on the NPP observatory. They are the Visible Infrared Imagining Radiometer Suite (VIIRS), the Advanced Technology Microwave Sounder (ATMS), the Cross-Track Infrared Sounder (CrIS), and the Ozone Mapper/Profiler Suite (OMPS). It is estimated that these four sensors combined will make daily data requests for approximately six terabytes of NPP science products from the operational data providers. As a result, issues associated with duplicate data requests, data transfers of large volumes of diverse products, and data transfer failures raised concerns with respect to the network traffic and bandwidth consumption. Therefore, a central data broker system for receiving and buffering data requests and data products for the SDS was developed. The data element for this system is called the SDS Data Depository and Distribution Element (SD3E). It supports science mission data assessment by assuring the timely and validated acquisition and subsequent transfer of the NPP Science Mission data to the SDS Elements and NPP Science Team. The six science elements that interface with the SD3E span across the NASA Goddard Space Flight Center (GSFC), the NASA Jet Propulsion Laboratory (JPL), and the University of Wisconsin. As the primary communication vehicle for the science elements and science team, the SD3E has an interface to the operational data providers: National Environment Satellite, Data, and Information Service (NESDIS) Interface Data Processing System (IDPS) and the National Oceanic Atmospheric Administration's (NOAA) Comprehensive Large Array-data Stewardship system (CLASS) Archive Data System (ADS), that are responsible for product generation and archive and distribution respectively. The SD3E is designed to be a semi-customizable and semi-automated system. This system is designed to provide flexibility and ease of use for the science users in accessing the latest data products by creating a rolling data cache that temporarily stores the products locally before transferring the data to the SDS Measurement based elements for the land, ocean, atmosphere, sounder, and ozone. This paper describes the design and architecture of one of the nine SDS elements, the SD3E, and how this system has provided a mechanism for efficient data exchange, how it has helped in alleviating some of the network traffic and usage, and how it has contributed to reducing operational costs.

Ho, Evelyn L.