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NASA NTRS2000

Level 1 Processing of MODIS Direct Broadcast Data From Terra

In February 2000, an effort was begun to adapt the Moderate Resolution Imaging Spectroradiometer (MODIS) Level 1 production software to process direct broadcast data. Three Level 1 algorithms have been adapted and packaged for release: Level 1A converts raw (level 0) data into Hierarchical Data Format (HDF), unpacking packets into scans; Geolocation computes geographic information for the data points in the Level 1A; and the Level 1B computes geolocated, calibrated radiances from the Level 1A and Geolocation products. One useful aspect of adapting the production software is the ability to incorporate enhancements contributed by the MODIS Science Team. We have therefore tried to limit changes to the software. However, in order to process the data immediately on receipt, we have taken advantage of a branch in the geolocation software that reads orbit and altitude information from the packets themselves, rather than external ancillary files used in standard production. We have also verified that the algorithms can be run with smaller time increments (2.5 minutes) than the five-minute increments used in production. To make the code easier to build and run, we have simplified directories and build scripts. Also, dependencies on a commercial numerics library have been replaced by public domain software. A version of the adapted code has been released for Silicon Graphics machines running lrix. Perhaps owing to its origin in production, the software is rather CPU-intensive. Consequently, a port to Linux is underway, followed by a version to run on PC clusters, with an eventual goal of running in near-real-time (i.e., process a ten-minute pass in ten minutes).

Lynnes, Christopher↗

NASA NTRS2012

LEGION: Lightweight Expandable Group of Independently Operating Nodes

LEGION is a lightweight C-language software library that enables distributed asynchronous data processing with a loosely coupled set of compute nodes. Loosely coupled means that a node can offer itself in service to a larger task at any time and can withdraw itself from service at any time, provided it is not actively engaged in an assignment. The main program, i.e., the one attempting to solve the larger task, does not need to know up front which nodes will be available, how many nodes will be available, or at what times the nodes will be available, which is normally the case in a "volunteer computing" framework. The LEGION software accomplishes its goals by providing message-based, inter-process communication similar to MPI (message passing interface), but without the tight coupling requirements. The software is lightweight and easy to install as it is written in standard C with no exotic library dependencies. LEGION has been demonstrated in a challenging planetary science application in which a machine learning system is used in closed-loop fashion to efficiently explore the input parameter space of a complex numerical simulation. The machine learning system decides which jobs to run through the simulator; then, through LEGION calls, the system farms those jobs out to a collection of compute nodes, retrieves the job results as they become available, and updates a predictive model of how the simulator maps inputs to outputs. The machine learning system decides which new set of jobs would be most informative to run given the results so far; this basic loop is repeated until sufficient insight into the physical system modeled by the simulator is obtained.

Burl, Michael C.↗

NASA NTRS2021

Trajectory Design and Maneuver Performance of the OSIRIS-REx Low-Altitude Reconnaissance of Bennu

With more than a year of asteroid proximity operations, the OSIRIS-REx team was able to identify one primary and one backup site for sample collection. The next step was to finalize on-board, localized image libraries and site-specific terrain information prior to attempting sample acquisition. Collecting this information required additional, low-altitude asteroid flyby reconnaissance activities. These activities, referred to as ‘sorties’, involved special maneuver and trajectory designs, unique from any other OSIRIS-REx maneuver activity. In order to minimize time between flybys and decrease the total number of maneuvers required, this trajectory design departed from and returned to a frozen Sun-terminator plane orbit within the span of a few hours. This work discusses the trajectory design and performance of the four flybys that were used to collect key topographic science observations of the primary and backup sample sites, which helped lead to a successful sample collection.

Andrew Levine↗

NASA NTRS2003

NASA Education Forum at SAO on the Structure and Evolution of the Universe

NASA's Structure and Evolution of the Universe (SEU) science theme offers an unparalleled opportunity to capture the public's imagination and inspire the next generation of scientific explorers-the generation that will determine America's lead in science and technology in the 21st century. The missions and research programs of SEU science are transporting the public to some of the universe's most exotic destinations: the beginning of time, the edge of space at the entrance to a black hole, and the great cycles of matter and energy that have slowly brought life to the universe. NASA's Office of Space Science (OSS) has put in place an Education and Public Outreach (EPO) initiative designed to do just that. Spanning all of NASA's OSS science themes, the initiative is a far-reaching partnership with the education community. As a result, NASA space science now reaches every avenue of education-from the nation's schools, science museums and planetariums, to libraries, community groups and after-school programs. As a partner in this enterprise, the,SEU Forum has successfully brought SEU science to a large and diverse audience. But this is an ongoing process, and much still needs to be done. Working with our colleagues in the OSS Support Network, and with our partners in the space science and education communities, we look forward to ensuring that the public supports and participates in the great explorations of the SEU theme. Working with the SEU missions and members of the OSS Support Network, the Forum will harness the assets of the SEU science community to: Inform, inspire, and involve the public in the explorations of the SEU science theme. Use the unique resources of the SEU science theme to enhance K-14 science, technology, and mathematics education. Identify and develop high-leverage opportunities for the SEU science community to contribute to education and outreach.

Rosendhal, Jeffrey↗

NASA NTRS1995

SAVS: A Space and Atmospheric Visualization Science system

The research environment faced by space and atmospheric scientists in the 1990s is characterized by unprecedented volumes of new data, by ever-increasing repositories of unexploited mission files, and by the widespread use of empirical and large-scale computational models needed for the synthesis of understanding across data sets and discipline boundaries. The effective analysis and interpretation of such massive amounts of information have become the subjects of legitimate concern. With SAVS (a Space and Atmospheric Visualization Science System), we address these issues by creating a 'push-button' software environment that mimics the logical scientific processes in data acquisition, reduction, and analysis without requiring a detailed understanding of the methods, networks, and modules that link the tools and effectively execute the functions. SAVS provides (1) a customizable framework for accessing a powerful set of visualization tools based on the popular AVS visualization software with hooks to PV-Wave and access to Khoros modules, (2) a set of mathematical and statistical tools, (3) an extensible library of discipline-specific functions and models (e.g., MSIS, IRI, Feldstein Oval, IGRF, satellite tracking with CADRE-3, etc.), and (4) capabilities for local and remote data base access. The system treats scalar, vector, and image data, and runs on most common Unix workstations. We present a description of 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).

Szuszczewicz, E. P.↗

NASA NTRS2015

Earth Science Data Fusion with Event Building Approach

Objectives of the NASA Information And Data System (NAIADS) project are to develop a prototype of a conceptually new middleware framework to modernize and significantly improve efficiency of the Earth Science data fusion, big data processing and analytics. The key components of the NAIADS include: Service Oriented Architecture (SOA) multi-lingual framework, multi-sensor coincident data Predictor, fast into-memory data Staging, multi-sensor data-Event Builder, complete data-Event streaming (a work flow with minimized IO), on-line data processing control and analytics services. The NAIADS project is leveraging CLARA framework, developed in Jefferson Lab, and integrated with the ZeroMQ messaging library. The science services are prototyped and incorporated into the system. Merging the SCIAMACHY Level-1 observations and MODIS/Terra Level-2 (Clouds and Aerosols) data products, and ECMWF re- analysis will be used for NAIADS demonstration and performance tests in compute Cloud and Cluster environments.

Lukashin, C.↗

NASA NTRSDate not supplied

Improving GES Disc Data Search and Discovery Through AI Metadata Augmentation

NASA’s Goddard Earth Science (GES) Data and Information Services Center (DISC) is one of twelve data centers in NASA's Science Mission Directorate (SMD), providing vital earth science data to a diverse user base. To enhance the discoverability of this data, GES DISC employs a keyword search system, which leverages scientific keywords embedded in dataset metadata. However, the evolving nature of scientific applications of our data necessitates regular review and augmentation of these keywords. To address this, we developed a service to automatically predict missing science keywords in the metadata. This service constructs a knowledge graph from the latest GES DISC metadata within NASA’s Common Metadata Repository (CMR). Using an open-source library, we trained a machine learning model to predict absent science keywords in the metadata. Our preliminary results indicate that the model has high levels of accuracy at predicting science keywords in the dataset metadata when exposed to data not included in its training. These predicted keywords were then evaluated by GES DISC data curation scientists and compared against other AI tools for metadata augmentation. We aim to enhance the overall usability and accessibility of NASA’s earth science data by implementing this tool in our data curation processes.

Kendall Gilbert↗

NASA NTRS2018

NASA GeneLab Project: Bridging Space Radiation Omics with Ground Studies

Accurate assessment of risk factors for long-term space missions is critical for human space exploration: therefore it is essential to have a detailed understanding of the biological effects on humans living and working in deep space. Ionizing radiation from Galactic Cosmic Rays (GCR) is one of the major risk factors factor that will impact health of astronauts on extended missions outside the protective effects of the Earth's magnetic field. Currently there are gaps in our knowledge of the health risks associated with chronic low dose, low dose rate ionizing radiation, specifically ions associated with high (H) atomic number (Z) and energy (E). The GeneLab project (genelab.nasa.gov) aims to provide a detailed library of Omics datasets associated with biological samples exposed to HZE. The GeneLab Data System (GLDS) currently includes datasets from both spaceflight and ground-based studies, a majority of which involve exposure to ionizing radiation. In addition to detailed information for ground-based studies, we are in the process of adding detailed, curated dosimetry information for spaceflight missions. GeneLab is the first comprehensive Omics database for space related research from which an investigator can generate hypotheses to direct future experiments utilizing both ground and space biological radiation data. In addition to previously acquired data, the GLDS is continually expanding as Omics related data are generated by the space life sciences community. Here we provide a brief summary of space radiation related data available at GeneLab.

Genelab↗

NASA NTRSDate not supplied

Introduction of the NASA Microgravity Research Library

As opportunities for conducting experiments in space are rare, more studies have been published using ground-based analogs that simulate microgravity conditions. For example, when conducting a literature search in PubMed for peer-reviewed articles and studies that used simulated microgravity conditions, results will yield over 5,000 publications dating back to 1961. The issue with this search technique and medium is that these articles are vast in quantity and spread out across multiple web-based databases, repositories, and libraries; some of which, are wholly inaccessible. For example, in PubMed for a single year, we found 1,000+ microgravity research articles among more than 12,000 general, space research articles; these, were within an overarching 350,000+ total, general medical research articles for just 2020. The KSC Microgravity Simulation Support Facility (MSSF), with support from the KSC Information Technology (IT) Applications Development Team and the NASA Space Biology Program, took the initiative to develop a database that would serve as the central repository for existing microgravity research. This repository site is open to the public and houses not only peer-reviewed publications relating to microgravity research, but also dissertations, technical publications such as white papers, NASA technical publications, and patent publications. In this presentation, we will discuss some of our literature research findings as well as present a working prototype version of the Library. It is our goal that the future infrastructure of this database advance to become a fully-functional, NASA Space Life-Sciences Research Library.

Anna Maria Ruby↗

NASA NTRSDate not supplied

Introduction of the NASA Microgravity Research Library

Anna Maria Ruby↗

NASA NTRS1993

Modernization and unification: Strategic goals for NASA STI program

Information is increasingly becoming a strategic resource in all societies and economies. The NASA Scientific and Technical Information (STI) Program has initiated a modernization program to address the strategic importance and changing characteristics of information. This modernization effort applies new technology to current processes to provide near-term benefits to the user. At the same time, we are developing a long-term modernization strategy designed to transition the program to a multimedia, global 'library without walls.' Notwithstanding this modernization program, it is recognized that no one information center can hope to collect all the relevant data. We see information and information systems changing and becoming more international in scope. We are finding that many nations are expending resources on national systems which duplicate each other. At the same time that this duplication exists, many useful sources of aerospace information are not being collected because of resource limitations. If nations cooperate to develop an international aerospace information system, resources can be used efficiently to cover expanded sources of information. We must consider forming a coalition to collect and provide access to disparate, multidisciplinary sources of information, and to develop standardized tools for documenting and manipulating this data and information. In view of recent technological developments in information science and technology, as well as the reality of scarce resources in all nations, it is time to explore the mutually beneficial possibilities offered by cooperation and international resource sharing. International resources need to be mobilized in a coordinated manner to move us towards this goal. This paper reviews the NASA modernization program and raises for consideration new possibilities for unification of the various aerospace database efforts toward a cooperative international aerospace database initiative that can optimize the cost/benefit equation for all participants.

Blados, W.↗

NASA NTRS2010

Planetary Image Geometry Library

The Planetary Image Geometry (PIG) library is a multi-mission library used for projecting images (EDRs, or Experiment Data Records) and managing their geometry for in-situ missions. A collection of models describes cameras and their articulation, allowing application programs such as mosaickers, terrain generators, and pointing correction tools to be written in a multi-mission manner, without any knowledge of parameters specific to the supported missions. Camera model objects allow transformation of image coordinates to and from view vectors in XYZ space. Pointing models, specific to each mission, describe how to orient the camera models based on telemetry or other information. Surface models describe the surface in general terms. Coordinate system objects manage the various coordinate systems involved in most missions. File objects manage access to metadata (labels, including telemetry information) in the input EDRs and RDRs (Reduced Data Records). Label models manage metadata information in output files. Site objects keep track of different locations where the spacecraft might be at a given time. Radiometry models allow correction of radiometry for an image. Mission objects contain basic mission parameters. Pointing adjustment ("nav") files allow pointing to be corrected. The object-oriented structure (C++) makes it easy to subclass just the pieces of the library that are truly mission-specific. Typically, this involves just the pointing model and coordinate systems, and parts of the file model. Once the library was developed (initially for Mars Polar Lander, MPL), adding new missions ranged from two days to a few months, resulting in significant cost savings as compared to rewriting all the application programs for each mission. Currently supported missions include Mars Pathfinder (MPF), MPL, Mars Exploration Rover (MER), Phoenix, and Mars Science Lab (MSL). Applications based on this library create the majority of operational image RDRs for those missions. A Java wrapper around the library allows parts of it to be used from Java code (via a native JNI interface). Future conversions of all or part of the library to Java are contemplated.

Deen, Robert C.↗

NASA NTRS2022

Europa Clipper Payload Verification and Validation: Avionics-Instrument Interface Test Campaign

NASA's Europa Clipper mission will investigate Jupiter's icy moon Europa using a payload suite consisting of nine instruments to address a range of scientific objectives concerning Europa's habitability. As the project proceeds past its Critical Design Review, confidence is being built in the system's ability to achieve mission objectives through the implementation of a rigorous payload verification and validation (V&V) program. As part of this payload V&V program, instrument box-level testing was performed by the payload team to verify select instrument-avionics interface requirements. This testing was performed at JPL using the avionics testbed's Bulk Data Storage Emulator (BDSEM) with visiting instrument Test Models. This paper summarizes the Data Link test campaign involving roughly four days of functional testing per instrument, including planning, testing methods, types of issues found, and the requirement closure process. Detail is also provided on the development, deployment, and validation of a standardized analysis tool used in data reviews. This testing verified requirements related to commanding rates, loss of link, packet format, clock counters, loopback test capability, and SpaceWire jitter and skew margins. Additional risk reduction testing of basic commanding, counter behavior, science data collection and transfer, and interface swapping was also performed. Because the BDSEM venue was not originally designed to be a run for record venue, the process of characterizing venue fidelity and establishing suitability for requirement closure using data collected in this venue will also be addressed.In order to close requirements, an extensible tool was developed to post-process instrument command and telemetry data from their original binary to a human-readable format and give visibility to errors detected within the data, such as packets with Cyclic Redundancy Check errors. This tool, called payload-packet-parser, is a Python 3.9 command line tool built using a variety of open-source Python libraries. Payload-packet-parser was designed to support parsing command and telemetry packets for all Europa Clipper instruments and additional analysis tools were developed for verification of specific information interface requirements. This test campaign, including post-processing using a single parsing and verification toolset, allowed for early interface testing, alleviating testing burdens on instrument teams and buying down risk on the instrument-avionics interface by finding hardware and software issues and idiosyncrasies prior to integration with system test venues. Over twenty issues were discovered across the payload, resulting in software updates and instrument rework well in advance of any system impacts. This paper concludes with an assessment of benefits and costs of this type of testing and lessons learned.

Montanez, Leticia↗

NASA NTRSDate not supplied

Automated Collection of Scientific Publications Linked to NASA Earth Science Datasets

NASA's Earth Observing System Data and Information System (EOSDIS) began dataset Digital Object Identifier (DOI) registration in 2012. The number of dataset DOIs registered as of January of 2023 exceeds 11,000. As the research community becomes aware of the importance of sharing data through Open Science and optimizing data reuse through Findability, Accessibility, Interoperability, and Reuse (FAIR) data management principles, datasets are increasingly being cited in scientific publications. When datasets are cited explicitly by DOI within published works, automated methods can be developed for collecting these published works from a variety of bibliometric sources. The coverage of the sources varies, so each source can collect citations that are only available within it. Using major citation databases such as Scopus and Web of Science, the Google Scholar search engine, the CrossRef Open Citation Index, and the dataset DOI registry DataCite, we present an automated workflow for dataset citation collection. By harvesting citations automatically, a citation library is created explicitly linking EOSDIS datasets to publications that cite them. Using Zotero, a free and open-source citation manager, we demonstrate how to access and browse this library by the tags indicating bibliometric sources, dataset DOI, and the dataset archive center. We also demonstrate temporary trends in the number of publications harvested from bibliometric sources.

Infometrics↗

NASA NTRS1994

CESDIS

CESDIS, the Center of Excellence in Space Data and Information Sciences was developed jointly by NASA, Universities Space Research Association (USRA), and the University of Maryland in 1988 to focus on the design of advanced computing techniques and data systems to support NASA Earth and space science research programs. CESDIS is operated by USRA under contract to NASA. The Director, Associate Director, Staff Scientists, and administrative staff are located on-site at NASA's Goddard Space Flight Center in Greenbelt, Maryland. The primary CESDIS mission is to increase the connection between computer science and engineering research programs at colleges and universities and NASA groups working with computer applications in Earth and space science. Research areas of primary interest at CESDIS include: 1) High performance computing, especially software design and performance evaluation for massively parallel machines; 2) Parallel input/output and data storage systems for high performance parallel computers; 3) Data base and intelligent data management systems for parallel computers; 4) Image processing; 5) Digital libraries; and 6) Data compression. CESDIS funds multiyear projects at U. S. universities and colleges. Proposals are accepted in response to calls for proposals and are selected on the basis of peer reviews. Funds are provided to support faculty and graduate students working at their home institutions. Project personnel visit Goddard during academic recess periods to attend workshops, present seminars, and collaborate with NASA scientists on research projects. Additionally, CESDIS takes on specific research tasks of shorter duration for computer science research requested by NASA Goddard scientists.

Source record↗

NASA NTRS2022

The Psyche Planning Software Subsystem: Creating a Robust Toolset for a Discovery-class Mission

Psyche is a Discovery-class mission to the small metal-rich asteroid (16) Psyche, and is slated to launch in 2022. Psyche, like many missions, requires low-cost activity planning and sequence generation that serves as the backbone to overall uplink design. Such tools must be maintainable over long periods of operations, and powerful enough to solve complex issues that deep-space one-off missions encounter. In this paper we introduce cost-effective solutions that leverage inner- and open-source principles to meet a variety of common and novel use cases.The uplink process that was designed to meet these challenges is presented, as well as the data-flow through the high-level architecture of the planning software subsystem. The user-facing planning tools are described, particularly the Science Opportunity Analyzer, the Plan Editor, Psyche’s planning automation in the Blackbird framework, and Psyche Simulation Reports. All these applications are either new or have been substantially revamped to meet Psyche’s concept of operations. In particular, ensuring the entire toolchain can correctly process epoch-relative activities is discussed. Underlying the main applications are a common set of dependencies developed and maintained by a new cross-mission association of planning developers. In this way, Psyche can inherit well-tested functionality which saves effort and ensures its developers can focus on solving domain challenges. Quality control of the applications and libraries is ensured with a code-review and unit-test based novel ‘CM lite’ process. Collaboration with international industry and academia using the open-source modules is already occurring.The planning and scheduling software is designed to maximize operator awareness of the integrated plan at every step of the process and use common interfaces and file formats to easily transfer information. Design choices plus the team’s test-driven development process enables more expansive capabilities compared to the decentralized planning and sequence generation functions typical of Discovery-class orbiters without significant development cost increases. Benefits and drawbacks of Psyche’s approach are discussed, including comparison to other missions and tools where appropriate.

Ramanathan, Keshav↗

NASA NTRS2006

Earth Observing System Data Gateway

The Earth Observing System Data Gateway (EDG) software provides a "one-stop-shopping" standard interface for exploring and ordering Earth-science data stored at geographically distributed sites. EDG enables a user to do the following: 1) Search for data according to high-level criteria (e.g., geographic location, time, or satellite that acquired the data); 2) Browse the results of a search, viewing thumbnail sketches of data that satisfy the user s criteria; and 3) Order selected data for delivery to a specified address on a chosen medium (e.g., compact disk or magnetic tape). EDG consists of (1) a component that implements a high-level client/server protocol, and (2) a collection of C-language libraries that implement the passing of protocol messages between an EDG client and one or more EDG servers. EDG servers are located at sites usually called "Distributed Active Archive Centers" (DAACs). Each DAAC may allow access to many individual data items, called "granules" (e.g., single Landsat images). Related granules are grouped into collections called "data sets." EDG enables a user to send a search query to multiple DAACs simultaneously, inspect the resulting information, select browseable granules, and then order selected data from the different sites in a seamless fashion.

Pfister, Robin↗

NASA NTRS2021

Synthesis and Characterization of Fe(III)-Fe(II)- Mg- Al Smectite Solid Solutions and Implications for Planetary Science

This study demonstrates the synergies and limits of multiple measurement types for the detection of smectite chemistry and oxidation state on planetary surfaces to infer past geochemical conditions. Smectite clay minerals are common products of water-rock interactions throughout the solar system, and their detection and characterization provides important clues about geochemical conditions and past environments if sufficient information about their composition can be discerned. Here, we synthesize and report on the spectroscopic properties of a suite of smectite samples that span the intermediate compositional range between Fe(II), Fe(III), Mg, and Al end-member species using bulk chemical analyses, X-ray diffraction, Vis/IR reflectance spectroscopy, UV and green-laser Raman spectroscopy, and Mössbauer spectroscopy. Our data show that smectite composition and the oxidation state of octahedral Fe can be reliably identified in the near infrared on the basis of combination and fundamental metal-OH stretching modes between 2.1–2.9 μm, which vary systematically with chemistry. Smectites dominated by Mg or Fe(III) have spectrally distinct fundamental and combination stretches, whereas Al-rich and Fe(II)-rich smectites have similar fundamental minima near 2.76 μm, but have distinct combination M-OH features between 2.24 and 2.36 μm. We show that with expanded spectral libraries that include intermediate composition smectites and both Fe(III) and Fe(II) oxidation states, more refined characterization of smectites from MIR data is now possible, as the position of the 450 cm–1 absorption shifts systematically with octahedral Fe content, although detailed analysis is best accomplished in concert with other characterization methods. Our data also provide the first Raman spectral libraries of smectite clays as a function of chemistry, and we demonstrate that Raman spectroscopy at multiple excitation wavelengths can qualitatively distinguish smectite clays of different structures and can enhance interpretation by other types of analyses. Our sample set demonstrates how X-ray diffraction can distinguish between dioctahedral and trioctahedral smectites using either the (02,11) or (06,33) peaks, but auxiliary information about chemistry and oxidation state aids in specific identifications. Finally, the temperature-dependent isomer shift and quadrupole splitting in Mössbauer data are insensitive to changes in Fe content but reliability differentiates Fe within the smectite mineral structure.

Valerie K Fox↗