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All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Restoration of APOLLO Data by the NSSDC and PDS Lunar Data Node

The Apollo Lunar Surface Experiment Packages (ALSEPs), suites of instruments deployed by the Apollo 12. 14, 15, 16 and 17 astronauts on the lunar surface, still represent the only in-situ measurements of the Moon's environment taken over long time periods, Much of these data are housed at the National Space Science Data Center (NSSDC) at Goddard Space Flight Center but are in forms that are not readily usable, such as microfilm, hardcopy, and magnetic tapes with older, obsolete formats. The Lunar Data Node (LDN) has been formed under the auspices of the Planetary Data System (PDS) Geosciences Node to put relevant, scientifically important Apollo data into accessible digital form for use by researchers and mission planners. The LDN has prioritized the restoration of these data based on their scientific and engineering value and the level of effort required. We will report on progress made and plans for future data restorations.

Williams, David R.↗
NASA NTRS2017

The Joint Polar Satellite System (JPSS) Program's Algorithm Change Process (ACP): Past, Present and Future

The Joint Polar Satellite System (JPSS) Program Office is the supporting organization for the Suomi National Polar Orbiting Partnership (S-NPP) and JPSS-1 satellites. S-NPP carries the following sensors: VIIRS, CrIS, ATMS, OMPS, and CERES with instruments that ultimately produce over 25 data products that cover the Earths weather, oceans, and atmosphere. A team of scientists and engineers from all over the United States document, monitor and fix errors in operational software code or documentation with the algorithm change process (ACP) to ensure the success of the S-NPP and JPSS 1 missions by maintaining quality and accuracy of the data products the scientific community relies on. This poster will outline the programs algorithm change process (ACP), identify the various users and scientific applications of our operational data products and highlight changes that have been made to the ACP to accommodate operating system upgrades to the JPSS programs Interface Data Processing Segment (IDPS), so that the program is ready for the transition to the 2017 JPSS-1 satellite mission and beyond.

Joint Polar Satellite System↗
NASA NTRS1967

The Effect of Planetary Albedo on Solar Orientation of Spacecraft

The analytical expression for the solar orientation error caused by planetary albedo is derived. A typical solar sensor output characteristic is assumed and a computer solution to the analytical is obtained. The computer results are presented for a spacecraft in the vicinity of Earth, Venus, Mars, and the Moon. Each planetary body is assumed to be a spherical diffuse reflector with cylindrical shadows and a constant albedo. The data generated herein permit the selection of an appropriate coarse-sensor to fine-sensor switching angle for solar orientation control systems and facilitate the the interpretation of solar-referenced scientific experiment data.

SPACE ORIENTATION↗
NASA NTRS2014

Exploration of the Saturn System by the Cassini Mission: Observations with the Cassini Infrared Spectrometer

The Cassini mission is a joint NASA-ESA international mission, launched on October 17, 1997 with 12 instruments on board, for exploration of the Saturn system. A composite Infrared Spectrometers is one of the major instruments. Successful insertion of the spacecraft in Saturn's orbit for an extended orbital tour occurred on July 1, 2004. The French Huygens-Probe on board, with six instruments was programmed for a soft landing on Titan's surface occurred in January 2005. The broad range scientific objectives of the mission are: Exploration of the Saturn system for investigations of the origin, formation, & evolution of the solar system, with an extensive range of measurements and the analysis of the data for scientific interpretations. The focus of research dealing with the Cassini mission at NASA/MSFC in collaboration with the NASA/Goddard Space Flight Center, JPL, as well as the research teams at Oxford/UK and Meudon Observatory/France, involves the Infrared observations of Saturn and its satellites, for measurements of the thermal structure and global distributions of the atmospheric constituents. A brief description of the Cassini spacecraft, the instruments, the objectives, in particular with the infrared observations of the Saturn system will be given. The analytical techniques for infrared radiative transfer and spectral inversion programs, with some selected results for gas constituent distributions will be presented.

Abbas, Mian M.↗
NASA NTRS1977

Assess 2: Spacelab simulation. Executive summary

An Airborne Science/Spacelab Experiments System Simulation (ASSESS II) mission, was conducted with the CV-990 airborne laboratory in May 1977. The project studied the full range of Spacelab-type activities including management interactions, experiment selection and funding, hardware development, payload integration and checkout, mission specialist and payload specialist selection and training, mission control center payload operations control center arrangements and interactions, real time interaction during flight between principal investigators and the flight crew, and retrieval of scientific flight data. ESA established an integration and coordination center for the ESA portion of the payload as planned for Spacelab. A strongly realistic Spacelab mission was conducted on the CV-990 aircraft. U.S. and ESA scientific experiments were integrated into a payload and flown over a 10 day period, with the payload flight crew fully-confined to represent a Spacelab mission. Specific conclusions for Spacelab planning are presented along with a brief explanation of each.

Source record↗
NASA NTRSDate not supplied

Beyond Fair: Engagement, Data Usability, and Open Community Productivity through the NASA Open Science Data Repository

The FAIR principle (findable, accessible, interoperable, and reusable) governs the storage and sharing of NASA space biology and health data[1]. These guiding principles maximize reuse of data and the reproducibility of scientific findings. The NASA Open Science Data Repository (OSDR; an expansion of NASA GeneLab) was built on the FAIR principles and houses over 500 studies and close to 1000 datasets from decades of space life sciences experiments. OSDR embodies the FAIR principles through data governance that includes mediated, embargoed, and fully open access data. The FAIR data governance principles were recently proposed to be expanded to encompass a FAIREST framework for assessing research data repositories (FAIR + Engagement, Social connections, and Trust)[2]. FAIREST emphasizes the importance of data repositories engaging with the scientific community and gaining the trust of researchers regarding data quality. Trust also refers to the TRUST principles developed for assessment of digital repositories: Transparency, Responsibility, User Focus, Sustainability, Technology[3]. We present the “Open Science for Life in Space” Analysis Working Groups (AWGs) as evidence regarding the power of engagement, social connections, and trust which has enhanced OSDR’s capabilities and productivity. AWG members engage in two main activities. One, members provide feedback on OSDR scientific standards for data ingestion, curation, and reuse (study, subject and assay metadata; processing pipelines; dataset formats and uniformed structures for machine-readability). Two, AWG members collaborate to mine-reuse OSDR data to conduct scientific analysis. With nearly 800 active members, the AWGs have resulted in 32 publications re-using OSDR data and contributed many papers in two major special issues in Cell (2020) and Nature (2024). AWGs also serve as networking groups, facilitate social connections between researchers at all levels of experience, and also have a social online ‘Forum’ used to keep members informed on projects and opportunities. This community-centric, productive, and trustworthy data culture has resulted in a broader effect with international space agencies, academics, and the commercial space sector wanting to submit their data to OSDR. Ten studies of Inspiration 4 data were recently publicly released by OSDR, as were some JAXA human data. Coming up soon in OSDR are data submissions from the European Space Agency, Virgin Galactic PIs, and SpaceX Polaris Dawn. A major benefit of OSDR is the array of standardized and uniformly formatted data (which was developed through AWG member consensus), from which visualization tools, analysis tools, and machine learning models can be built or trained. This talk will cover the Multi-Study Visualization Tool, the Environmental Data Application, RadLab, and a UCSF-NSF funded knowledge graph biomedical health discovery tool ‘SPOKE’ currently being integrated with OSDR. OSDR also provides training programs in bioinformatics and machine learning to improve the scientific community’s awareness of data availability and to boost their ability to perform data analysis. The increasing engagement of the scientific community and the public with technologies powered by artificial intelligence (AI) heightens the need for data analysis to be transparent. The AI for Life in Space initiative leverages the data products provided in OSDR to train AI models, with an emphasis on explainable and trustworthy AI, which would not be possible without FAIR data and metadata. Overall, here we will demonstrate the importance for NASA life sciences data repositories to adhere to the FAIREST framework, by providing examples and success stories from different aspects of OSDR.

data↗
NASA NTRS1983

Comparison of scientific and administrative database management systems

Some characteristics found to be different for scientific and administrative data bases are identified and some of the corresponding generic requirements for data base management systems (DBMS) are discussed. The requirements discussed are especially stringent for either the scientific or administrative data bases. For some, no commercial DBMS is fully satisfactory, and the data base designer must invent a suitable approach. For others, commercial systems are available with elegant solutions, and a wrong choice would mean an expensive work-around to provide the missing features. It is concluded that selection of a DBMS must be based on the requirements for the information system. There is no unique distinction between scientific and administrative data bases or DBMS. The distinction comes from the logical structure of the data, and understanding the data and their relationships is the key to defining the requirements and selecting an appropriate DBMS for a given set of applications.

Stoltzfus, J. C.↗
NASA NTRS2017

A View from Above: Earth Observations

Since the 1960s, satellites have been looking down at the Earth to monitor weather patterns and track severe storms, observe how our land surface is changing and responding to hydrometerological extremes, and even to sense how the Earth's crust is deforming from earthquakes and volcanoes. Space and airborne platforms can provide unique views of the disaster lifecycle, informing pre-event mitigation and preparedness, emergency response following an event, and monitoring longer-term recovery. These remotely-sensed data, products and models can provide a global perspective to see beyond administrative boundaries, reach remote places where in situ observations are di cult or non-existent, and provide the necessary context and situational awareness to aid in disaster response. So how do these platforms work? Instruments aboard satellites use different portions of the electromagnetic spectrum to passively or actively observe energy across a range of wavelengths, which can be turned into meaningful data on geophysical, atmospheric, and hydrological variables. e US has had a broad range of Earth observation (EO) platforms delivering open data for scientific research and societal benefits for decades. e Landsat programme, a joint initiative between the US Geological Survey (USGS) and NASA, has the world's longest continuous collection of space-based satellite imagery of the Earth, extending from 1972 to present. e Landsat satellites provide visible, near infrared, and thermal data that are used to support emergency response and disaster relief by mapping changes in water during floods, and dramatic land surface changes, including those resulting from landslides, wild res, severe weather, volcanic plumes, and dust storms.

FEMA↗
NASA NTRS2011

Techniques and Tools for Estimating Ionospheric Effects in Interferometric and Polarimetric SAR Data

The InSAR Scientific Computing Environment (ISCE) is a flexible, extensible software tool designed for the end-to-end processing and analysis of synthetic aperture radar data. ISCE inherits the core of the ROI_PAC interferometric tool, but contains improvements at all levels of the radar processing chain, including a modular and extensible architecture, new focusing approach, better geocoding of the data, handling of multi-polarization data, radiometric calibration, and estimation and correction of ionospheric effects. In this paper we describe the characteristics of ISCE with emphasis on the ionospheric modules. To detect ionospheric anomalies, ISCE implements the Faraday rotation method using quadpolarimetric images, and the split-spectrum technique using interferometric single-, dual- and quad-polarimetric images. The ability to generate co-registered time series of quad-polarimetric images makes ISCE also an ideal tool to be used for polarimetric-interferometric radar applications.

Ionosphere↗
NASA NTRS2007

Extraterrestrial Moessbauer Spectroscopy: More than Three Years of Mars Exploration and Developments for Future Missions

The NASA Mars Exploration Rovers (MER), Spirit and Opportunity, landed on the Red Planet in January 2004. Both rovers are equipped with a miniaturized Moessbauer spectrometer MIMOS II. Designed for a three months mission, both rovers and both Moessbauer instruments are still working after more than three years of exploring the Martian surface. At the beginning of the mission, with a landed intensity of the Moessbauer source of 150 mCi, a 30 minute touch and go measurement produced scientifically valuable data while a good quality Moessbauer spectrum was obtained after approximately eight hours. Now, after about five halflives of the sources have passed, Moessbauer integrations are routinely planned to last approx.48 hours. Because of this and other age-related hardware degradations of the two rover systems, measurements now occur less frequently, but are still of outstanding quality and scientific importance. Summarizing important Moessbauer results, Spirit has traversed the plains from her landing site in Gusev crater and is now, for the greater part of the mission, investigating the stratigraphically older Columbia Hills. Olivine in rocks and soils in the plains suggests that physical rather than chemical processes are currently active.

Schroeder, Christian↗
NASA NTRS2000

High Performance Fortran for Aerospace Applications

This paper focuses on the use of High Performance Fortran (HPF) for important classes of algorithms employed in aerospace applications. HPF is a set of Fortran extensions designed to provide users with a high-level interface for programming data parallel scientific applications, while delegating to the compiler/runtime system the task of generating explicitly parallel message-passing programs. We begin by providing a short overview of the HPF language. This is followed by a detailed discussion of the efficient use of HPF for applications involving multiple structured grids such as multiblock and adaptive mesh refinement (AMR) codes as well as unstructured grid codes. We focus on the data structures and computational structures used in these codes and on the high-level strategies that can be expressed in HPF to optimally exploit the parallelism in these algorithms.

Mehrotra, Piyush↗
NASA NTRS2004

Automatic Generation of Algorithms for the Statistical Analysis of Planetary Nebulae Images

Analyzing data sets collected in experiments or by observations is a Core scientific activity. Typically, experimentd and observational data are &aught with uncertainty, and the analysis is based on a statistical model of the conjectured underlying processes, The large data volumes collected by modern instruments make computer support indispensible for this. Consequently, scientists spend significant amounts of their time with the development and refinement of the data analysis programs. AutoBayes [GF+02, FS03] is a fully automatic synthesis system for generating statistical data analysis programs. Externally, it looks like a compiler: it takes an abstract problem specification and translates it into executable code. Its input is a concise description of a data analysis problem in the form of a statistical model as shown in Figure 1; its output is optimized and fully documented C/C++ code which can be linked dynamically into the Matlab and Octave environments. Internally, however, it is quite different: AutoBayes derives a customized algorithm implementing the given model using a schema-based process, and then further refines and optimizes the algorithm into code. A schema is a parameterized code template with associated semantic constraints which define and restrict the template s applicability. The schema parameters are instantiated in a problem-specific way during synthesis as AutoBayes checks the constraints against the original model or, recursively, against emerging sub-problems. AutoBayes schema library contains problem decomposition operators (which are justified by theorems in a formal logic in the domain of Bayesian networks) as well as machine learning algorithms (e.g., EM, k-Means) and nu- meric optimization methods (e.g., Nelder-Mead simplex, conjugate gradient). AutoBayes augments this schema-based approach by symbolic computation to derive closed-form solutions whenever possible. This is a major advantage over other statistical data analysis systems which use numerical approximations even in cases where closed-form solutions exist. AutoBayes is implemented in Prolog and comprises approximately 75.000 lines of code. In this paper, we take one typical scientific data analysis problem-analyzing planetary nebulae images taken by the Hubble Space Telescope-and show how AutoBayes can be used to automate the implementation of the necessary anal- ysis programs. We initially follow the analysis described by Knuth and Hajian [KHO2] and use AutoBayes to derive code for the published models. We show the details of the code derivation process, including the symbolic computations and automatic integration of library procedures, and compare the results of the automatically generated and manually implemented code. We then go beyond the original analysis and use AutoBayes to derive code for a simple image segmentation procedure based on a mixture model which can be used to automate a manual preproceesing step. Finally, we combine the original approach with the simple segmentation which yields a more detailed analysis. This also demonstrates that AutoBayes makes it easy to combine different aspects of data analysis.

Fischer, Bernd↗
NASA NTRS1992

Functional requirements document for the Earth Observing System Data and Information System (EOSDIS) Scientific Computing Facilities (SCF) of the NASA/MSFC Earth Science and Applications Division, 1992

Five scientists at MSFC/ESAD have EOS SCF investigator status. Each SCF has unique tasks which require the establishment of a computing facility dedicated to accomplishing those tasks. A SCF Working Group was established at ESAD with the charter of defining the computing requirements of the individual SCFs and recommending options for meeting these requirements. The primary goal of the working group was to determine which computing needs can be satisfied using either shared resources or separate but compatible resources, and which needs require unique individual resources. The requirements investigated included CPU-intensive vector and scalar processing, visualization, data storage, connectivity, and I/O peripherals. A review of computer industry directions and a market survey of computing hardware provided information regarding important industry standards and candidate computing platforms. It was determined that the total SCF computing requirements might be most effectively met using a hierarchy consisting of shared and individual resources. This hierarchy is composed of five major system types: (1) a supercomputer class vector processor; (2) a high-end scalar multiprocessor workstation; (3) a file server; (4) a few medium- to high-end visualization workstations; and (5) several low- to medium-range personal graphics workstations. Specific recommendations for meeting the needs of each of these types are presented.

Botts, Michael E.↗
NASA NTRS1972

Circulation of Prince William Sound

The author has identified the following significant results. Visual examination of the available ERTS-1 and NASA NP-3 aircraft imagery has suggested that sediment-laden plumes from rivers may be useful in tracking surface circulation over the regions where these plumes retain their visible identities. Plumes of ice derived from tidewater glaciers are highly visible on the ERTS-1 imagery, but are generally of too small an areal extent to be useful in tracing surface circulation. Shore-fast ice is also highly visible on the ERTS-1 data. Practical scientific results include a corroboration of the westward flow just offshore in the Gulf of Alaska with inflow through Hinchinbrook Entrance into Prince William Sound. The tracer in this case was the Copper River Plume, which originates at the mouth of the Copper River east of Prince William Sound. A single partial image of Port Valdez, in northeastern Prince William Sound, suggests by the visible suspended sediment distribution that surface circulation there was cyclonic, as deduced previously from oceanographic baseline data. Surf along the shoreline of the Gulf of Alaska is highly visible on ERTS-1 imagery.

Muench, R. D.↗
NASA NTRS1973

Orbiting astronomical observatory-Copernicus

Of the three observatories planned in NASA's OAO program, one, OAO-3, is still in orbit and producing scientifically useful data. The prime experiment is the Princeton telescope spectrometer. Following a brief history of the OAO program, a description is given of the Princeton telescope with its 80-cm primary mirror, and of the spectrometer, which yields a resolution of up to 0.05 A. The spacecraft guidance system is also described. This system initially points the observatory to within a few arc minutes of the target, places the 0.3-arc sec slit on the star in less than 3 minutes, and holds on the star for up to 50 minutes with errors less than 0.05 arc sec. The main scientific results are described under the following categories: (1) the widespread presence of molecular hydrogen; (2) the search for other molecules, including detection of CO; (3) the nature of the interstellar medium as inferred from the detection of various atomic lines; (4) the study of chromospheres in late type stars; and (5) the study of mass loss in binaries and single stars.

York, D. G.↗
NASA NTRS2012

Finding Near-Earth Asteroid (NEA) Destinations for Human Exploration: Implications for Astrobiology

The current number of known potential NEA targets for HSF is limited to those objects whose orbital characteristics are similar to that of the Earth. This is due to the projected capabilities of the exploration systems currently under consideration and development at NASA. However, NEAs with such orbital characteristics often have viewing geometries that place them at low solar elongations and thus are difficult to detect from the vicinity of Earth. While ongoing ground-based surveys and data archives maintained by the NEO Program Observation Program Office and the Minor Planet Center (MPC) have provided a solid basis upon which to build, a more complete catalog of the NEO population is required to inform a robust and sustainable HSF exploration program. Since all the present NEO observing assets are currently confined to the vicinity of the Earth, additional effort must be made to provide capabilities for detection of additional HSF targets via assets beyond Earth orbit. A space-based NEO survey telescope located beyond the vicinity of the Earth, has considerable implications for planetary science and astrobiology. Such a telescope will provide foundational knowledge of our Solar System small body population and detect targets of interest for both the HSF and scientific communities. Data from this asset will yield basic characterization data on the NEOs observed (i.e., albedo, size determination, potential for volatiles and organics, etc.) and help down select targets for future HSF missions. Ideally, the most attractive targets from both HSF and astrobiology perspectives are those NEAs that may contain organic and volatile materials, and which could be effectively sampled at a variety of locations and depths. Presented here is an overview of four space-based survey concepts; any one of which after just a few years of operation will discover many highly accessible NEO targets suitable for robotic and human exploration. Such a space-based survey mission will reveal incredible returns for several disciplines including: exploration, in situ resource utilization, planetary defense, and science. Of particular, interest to the scientific

Landis, Rob↗
NASA NTRS2006

Implementing Access to Data Distributed on Many Processors

A reference architecture is defined for an object-oriented implementation of domains, arrays, and distributions written in the programming language Chapel. This technology primarily addresses domains that contain arrays that have regular index sets with the low-level implementation details being beyond the scope of this discussion. What is defined is a complete set of object-oriented operators that allows one to perform data distributions for domain arrays involving regular arithmetic index sets. What is unique is that these operators allow for the arbitrary regions of the arrays to be fragmented and distributed across multiple processors with a single point of access giving the programmer the illusion that all the elements are collocated on a single processor. Today's massively parallel High Productivity Computing Systems (HPCS) are characterized by a modular structure, with a large number of processing and memory units connected by a high-speed network. Locality of access as well as load balancing are primary concerns in these systems that are typically used for high-performance scientific computation. Data distributions address these issues by providing a range of methods for spreading large data sets across the components of a system. Over the past two decades, many languages, systems, tools, and libraries have been developed for the support of distributions. Since the performance of data parallel applications is directly influenced by the distribution strategy, users often resort to low-level programming models that allow fine-tuning of the distribution aspects affecting performance, but, at the same time, are tedious and error-prone. This technology presents a reusable design of a data-distribution framework for data parallel high-performance applications. Distributions are a means to express locality in systems composed of large numbers of processor and memory components connected by a network. Since distributions have a great effect on the performance of applications, it is important that the distribution strategy is flexible, so its behavior can change depending on the needs of the application. At the same time, high productivity concerns require that the user be shielded from error-prone, tedious details such as communication and synchronization.

James, Mark↗