Results for “open data format” — Page 11

NASA NTRSDate not supplied

Celestial Mapping System and Digital Lunar Library Initiative

We are preparing to create an interactive, global 3D lunar environment with integrated dataset and AI/ML tools to provide unique value to mission planners, scientists and the entire lunar community. This lunar environment will be based on NASA Ames Celestial Mapping System (CMS) [1] and Digital Lunar Library (DLL) Initiative. CMS provides a 3D virtual Lunar Globe with extensive user friendly tool sets, that include high resolution terrain visualization, elevation profiles, measurement kits, slope analysis, path optimization, line of sight analysis, equipment planning and placement tools and many other functionalities [1]. It has a thick client with less overhead to access hardware resources. This allows features such as terrain profiling and distance calculations to be performed on the client and on the fly. The application is developed to provide situational and domain awareness on the Lunar surface, planning capabilities for equipment placements and traverse path optimization. As data becomes available, CMS has the capabilities to integrate data sets that change dynamically in real-time, which will be useful for monitoring satellites and remotely-sensed data on the Lunar surface. CMS supports importing synthetic features in a variety of 3D, 2D, vector and raster formats. In the future, these capabilities will be enhanced by incorporating AI/ML tools and a plug-in architecture to enable customization by the user groups. With the help of DLL we will be able to : 1) Amplify the value of lunar information with AI-powered data enhancements 2) Acquire and integrate lunar data with AI-assisted georectification and homogenization 3) Analyze lunar data with advanced 3D visualization, intelligent search-by-example 4) Apply lunar data insights to specific use cases with an open plug-in architecture. The CMS-DLL initiative will have several potential use cases for NASA and the lunar community in general, including subsurface lava tube visualization and analysis, soil analysis, in-situ lunar resource visualization and representation on 3D globe, and data analytics for utilization. REFERENCES: [1] https://celestial.arc.nasa.gov/

3D Globe↗

NASA NTRS2023

Kamodo: Simplifying Model Data Access and Utilization

To address the lack of user-friendly software needed to simplify the utilization of model data across Heliophysics, the Community Coordinated Modeling Center (CCMC) at NASA’s Goddard Space Flight Center has developed a model-agnostic method via Kamodo for users to easily access and utilize model data in their workflows. By abstracting away the broad range of file formats and the intricacies of interpolation on specialized grids, this approach significantly lowers the barrier to model data access and utilization for the community while adding exciting new capabilities to their tool boxes. This paper describes the direct interfaces to the model data, called model readers, and a basic introduction on how to use them. Additionally, we detail the planned approach for including custom interpolation codes, and include current progress on specialized visualization developments. The CCMC is maintaining Kamodo as an official NASA open-sourced software to enable and encourage community collaboration.

Heliophysics↗

NASA NTRS1991

Parametric entry corridors for lunar/Mars aerocapture missions

Parametric atmospheric entry corridor data are presented for Earth and Mars aerocapture. Parameter ranges were dictated by the range of mission designs currently envisioned as possibilities for the Human Exploration Initiative (HEI). This data, while not providing a means for exhaustive evaluation of aerocapture performance, should prove to be a useful aid for preliminary mission design and evaluation. Entry corridors are expressed as ranges of allowable vacuum periapse altitude of the planetary approach hyperbolic orbit, with chart provided for conversion to an approximate flight path angle corridor at entry interface (125 km altitude). The corridor boundaries are defined by open-loop aerocapture trajectories which satisfy boundary constraints while utilizing the full aerodynamic control capability of the vehicle (i.e., full lift-up or full lift-down). Parameters examined were limited to those of greatest importance from an aerocapture performance standpoint, including the approach orbit hyperbolic excess velocity, the vehicle lift to drag ratio, maximum aerodynamic load factor limit, and the apoapse of the target orbit. The impact of the atmospheric density bias uncertainties are also included. The corridor data is presented in graphical format, and examples of the utilization of these graphs for mission design and evaluation are included.

Ling, Lisa M.↗

NASA NTRS1998

Oxygen Isotopic Constraints on the Genesis of Carbonates from Martian Meteorite ALH84001

Ion microprobe oxygen isotopic measurements of a chemically diverse suite of carbonates from Martian meteorite ALH84001 are reported. The delta(sup 18)O values are highly variable, ranging from +5.4 to + 25.3%, and are correlated with major element compositions of the carbonate. The earliest forming (Ca-rich) carbonates have the lowest delta(sup 18)O values and the late-forming (Mg-rich) carbonates have the highest delta(sup 18)O values. Two models are presented which can explain the isotopic variations. The carbonates could have formed in a water rich environment at relatively low, but highly variable temperatures. In this open-system case the lower limit to the temperature variation is approx. 125 C, with fluctuations of over 250 C possible within the constraints of the model. Alternatively, the data can be explained by a closed-system model in which the carbonates precipitated from a limited amount of CO2-rich fluid. This scenario can reproduce the isotopic variations observed at a range of temperatures, including relatively high temperatures (less than 500 C). Thus the oxygen isotopic compositions do not provide unequivocal evidence for formation of the carbonates at low temperature. Although more information is needed in order to distinguish between the models, neither of the implied environments is consistent with biological activity. Thus, we suggest that features associated with the carbonates which have been interpreted to be the result of biological activity were most probably formed by inorganic processes.

Leshin, Laurie A.↗

NASA NTRSDate not supplied

ImageLabler: Labeling and Managing Image Data for Machine Learning in the Earth Sciences

While machine learning techniques for image classification have been around for a long time, storing and managing the vast number of images required as training data is still a problem for scientists. This is especially true for the field of Earth science, where only recently have experts begun using machine learning techniques for image-based phenomena classification. Image Labeler, a fast and scalable cloud-based tagging platform for Earth science images, seeks to improve upon existing methods of managing images and associated metadata, such as maintaining categorized folders of images on a local machine, a process that can be cumbersome and difficult to scale. The platform facilitates rapid development of image-based Earth science phenomena training datasets by allowing scientists to upload their existing imagery as well as extract new samples from open satellite imagery services made available through NASA’s Global Imagery Browse Service (GIBS). Image Labeler also supports GeoTIFF data, with capabilities such as displaying GeoTIFFs on an interactive map, drawing shapefiles over them, and tagging them with additional metadata. This allows scientists to perform spatiotemporal subsetting with geographic information and develop training data more quickly. Built using modern web technologies, Image Labeler includes additional capabilities such as team collaboration for large-scale image tagging projects. Users can download their data in a machine-learning-ready format, allowing scientists to spend time on experimentation rather than on the collection of training data. In this presentation, we demonstrate how Image Labeler seeks to become a one-stop image data management solution for machine learning applications in Earth science.

Ashish Acharya↗

NASA NTRS1999

Isotopic Constraints on the Genesis of Carbonates in Martian Meteorite ALH 84001

Oxygen isotopic analyses in approximately 20 micrometer spots in a chemically diverse suite of carbonates from ALH 84001 show highly variable delta(exp 18)O values from +5.4 to +25.3%. The isotopic data are correlated with the major element composition of the carbonate. The earliest forming (Ca-rich) carbonates have the lowest delta(exp 18)O values and the late-forming Mg-rich carbonates have the highest delta(exp 18)O values. Two models that can explain the isotopic variation were investigated. The carbonates could have formed in a water-rich environment at relatively low, but highly variable temperatures. In this open-system case the lower limit to the temperature variation is approximately 125 C, with fluctuations of over 250 C possible within the constraints of the model, depending on fluid composition. Alternatively the data can be explained by a closed-system model in which carbonates precipitated from a limited amount of a CO2-rich fluid. This scenario can reproduce the range of isotopic values observed, even at relatively high temperatures (greater than 500 C). Thus, the oxygen isotopic compositions do not provide unequivocal evidence for formation of the carbonates at low temperature. Neither of these scenarios is consistent with a biological origin of the carbonates and their associated features. Olivine from ALH 84001 occurs as clusters within orthopyroxene adjacent to fractures containing disrupted carbonate globules and feldspathic shock glass. The inclusions are irregular in shape and range in size from approximately 40 micrometers to submicrometer. The olivine exhibits a limited range of chemical composition from Fo(sub 65) to Fo(sub 66). We measured delta(exp 18)O values of the olivine to be +5.1 +/- 1.4%, indistinguishable within uncertainty from the host orthopyroxene. The data suggest that the olivine formed at high temperature (greater than 800 C), and is probably unrelated to carbonate formation. Instead the olivine probably formed by metamorphic reactions involving either dehydration of hydrous silicates or reduction of opx + spinel. If the reactions took place after carbonate formation, they could have caused devolatilization of siderite, producing the magnetite in the ALH carbonate globules. This scenario is also inconsistent with a biological origin for the features in ALH 84001.

Leshin, Laurie A.↗

NASA NTRS1994

Record of fluid-rock interactions on Mars from the meteorite ALH84001

Allan Hills (ALH) 84001 is the most recently recognized member of a suite of meteorites--the SNCs--that almost certainly originated on Mars. Several factors distinguish ALH84001 from the other SNC meteorites. Preliminary studies suggest that it may be older than other martian meteorites. Moreover, it contains abundant, zoned domains of calcium-iron-magnesium carbonate that are indigenous to the sample and thus may hold important clues regarding near-surface processes on Mars and the evolution of the martian atmosphere. We report here analyses of the carbon and oxygen stable-isotope compositions of the carbonates that place constraints on their formation conditions. Our results imply the presence of at least two chemically distinct carbonates--one Ca,Fe-rich, the other Mg-rich--that are enriched in 13C relative to terrestrial carbonates (delta 13C approximately +41/1000), consistent with martian atmospheric CO2 as the carbon source. The oxygen isotope compositions of the carbonates indicate that they precipitated from a low-temperature fluid in the martian crust. Combined with textural and bulk geochemical considerations, the isotope data suggest that carbonate deposition took place in an open-system environment in which the ambient temperature fluctuated.

Carbonates/analysis↗

NASA NTRS2018

Serving NASA GES DISC Multi-Spatiotemporal Earth Science Data to the GIS community

NASA Earth Science (ES) data is essential to a wide range of GIS research and applications. However, for many GIS users, searching, accessing, using and analyzing NASA ES data can be of a great challenge- ranging from the sheer data volumes, types of science parameters, and to the complexity of data encoding formats. As one of the twelve NASA Science Mission Directorate (SMD) Data Centers, Goddard Earth Sciences (GES) Data and Information Services Center (DISC) archives and distributes petabytes of ES parameters covering atmosphere, land, and ocean fields. Most data are multidimensional and multi-spatiotemporal in nature and are encoded in different science data formats (e.g, HDF, HDF-EOS, netCDF, GRIB, binary), which usually contain multiple variables and different metadata information. By far, GES DISC has been developing a number of services and online tools to help GIS users to easily explore our data products. In this presentation, we will describe our ArcGIS-based data accessing and visualization services and portals, which allow users directly exploring the multi-spatiotemporal ES data in ArcGIS clients without having to pre-download/import the data. The ArcGIS services are also compliant with the Open Geospatial Consortium (OGC) Web Coverage Service (WCS) and Web Map Service (WMS) protocols and can be accessed by any other WCS/WMS clients to get customized GES DISC EO data on-the-fly from such services.

Wei, Jennifer↗

NASA NTRSDate not supplied

Simplifying Analysis of Hierarchical HDF5 and NetCDF4 Files with Xarray-Datatree

NASA’s Earth Observing System Data and Information System (EOSDIS) contains thousands of Earth science datasets from satellites, models, and field campaigns. EOSDIS data are stored in formats that are well supported by the Earth Science community. These formats include the Hierarchical Data Format (HDF), with derivative flavors such as HDF-5 and the Network Common Data Format (NetCDF-4). The HDF specification allows for a directory-like hierarchy within a single file, known as "groups". Observational data and associated metadata within a single file can be distributed amongst multiple internal groups, which can also be nested to multiple levels. Working with datasets that have a group hierarchical structure can be difficult because of the nested structure of groups. Widely used packages, such as xarray, have data models that do not accommodate the hierarchical structure within HDF files, requiring users to traverse the file and open different HDF groups as separate, unrelated objects. Xarray-datatree is a Python package developed to solve the difficulty of traversing HDFs with a hierarchical group structure by creating a tree-like hierarchical data structure in xarray. The tree-like structure allows each group to be accessed once a DataTree object is instantiated. The migration of xarray-datatree into the xarray core library will reduce barriers to accessing Earth science data by eliminating the need to understand and traverse the specific hierarchy of a grouped HDF file.

Eni Awowale↗

NASA NTRSDate not supplied

NASA Open Science Data Repository: Biomedical FAIR Data, Analysis Tools, User Communities, and Discoveries for Deep Space Missions

Increased biomedical risks and challenges associated with deep space missions require new knowledge discovery, new health countermeasures, and development of novel ecosystems, life support, crop production, and biomedical support capabilities. To meet NASA’s Moon to Mars strategic program goals for Human and Biological Sciences, findable, accessible, interoperable, reusable (FAIR), and maximally open-access data is going to be required to enable humanity to thrive in deep space. Indeed, this cornerstone perspective on FAIR and maximally open access data was also recommended in the recent 2023-2032 Decadal Survey from the National Academies of Sciences, Engineering, and Medicine. The NASA Open Science Data Repository (OSDR) is a maximally open access and FAIR database, and meets various scientific, technical, and operational spaceflight needs. It offers public users and submitters the ability to upload, download, search, share, analyze, and visualize data across ‘omics, physiological, phenotypic, behavioral, bioimaging, video, and environmental monitoring telemetry datasets. OSDR includes NASA GeneLab, NASA Ames Life Sciences Data Archive, and the NASA Biological Institutional Scientific Collection. OSDR has >455 studies with datasets from model organisms and non-NASA human astronauts. There are ~12 datasets from the Inspiration 4 (I4) mission, spanning metagenomics, comprehensive metabolic panels, clonal hematopoiesis, spatial transcriptomics, proteomics, and cytokine panels. In the interest of data privacy, two I4 datasets have raw FASTQ and FASTA files relating to the epitranscriptome, and a new request feature is live in OSDR (with a backend review process established) which was developed based on industry norms. OSDR also recently began a collaboration with the European Space Agency (ESA) to scientifically curate and make available >200 terabytes of human and model organism space-relevant data. The OSDR submission portal is designed to ingest and curate ~25 ‘omics assay data types, and ~50 physiological-phenotypic-imaging assay data types, spanning ultrasonography, micro-computed tomography, histology, morphometric photography, rebound tonometry, gait analysis, optical coherence tomography, novel object recognition, flow cytometry, and immunohistochemistry. A suite of analysis tools are available for OSDR users including: 1) an Environmental Data Application to compare radiation, CO2, relative humidity, temperature, and other telemetry across missions and subjects, 2) the RadLab database, a collaboration between NASA, ESA, the German and Italian Space Agencies, and the Bulgarian Academy of Sciences, which compiles radiation measurements relevant to human spaceflight and provides tools for accessing and manipulating the data, and 3) a Multi-study visualization tool which enables users to look across and combine GeneLab’s omics datasets across different experiments and missions. There are ~600 volunteer OSDR Analysis Working Group (AWG) members who: 1) provide feedback on scientific standards for reuse (subject and assay metadata; processing pipelines; dataset formats and uniformed structures for machine-readability), and 2) collaborate to mine-reuse OSDR data conducting scientific analysis. OSDR has enabled 60 publications as of September 2023, many directly from AWG collaborations most notably the Cell Press package in 2020. Lastly, there are at least 15 articles which mine OSDR data part of a package of ~50 articles across Nature Portfolio with research stemming from I4, the Japan Aerospace Exploration Agency, NASA Space Biology, and the NASA Human Research Program.

open access↗

NASA NTRS2004

Improving the Simulation of Sea Ice Lead Conditions and Turbulent Fluxes Using RGPS Products and Merged RADARSAT, AVHRR and MODIS Data

The importance of sea ice leads in the ice-ocean-atmosphere system lies in the fact that each of the boxes in the 'surface processes' interface in this diagram is closely linked to lead conditions. For example, heat, moisture and salt exchange between the Ocean and atmosphere within the ice pack occur nearly entirely through leads. The shear, divergence and convergence associated with lead formation and closure alter surface and basal roughness and topography, which in turn affects momentum transfer in the atmosphere and ocean boundary layers, and modifies the accumulation of snow on the ice surface, which then affects heat conduction and summertime albedo. In addition to providing openings for loss of heat and moisture fluxes to the atmosphere, leads absorb solar energy, which is used to melt ice and is transmitting to the underlying ocean. Given that leads dominate the ice-ocean interface in this manner, then it stands to reason that focusing on lead treatments within models can identify performance limitations of models and yield routes for significant improvements.

Maslanik, James A.↗

NASA NTRSDate not supplied

The Satellite Flythrough and Reconstruction Softwares at CCMC

The next-generation of model data visualization to be offered at the Community Coordinated Modeling Center (CCMC) will be based on Kamodo, an open source python package. To increase the usefulness of our services, we are also developing new capabilities based on this software, called the satellite flythrough and the reconstruction tools, to be offered both as packages for offline analysis and through an online interface (coming soon). The satellite flythrough software ‘flies’ a satellite trajectory, whether real or imaginary, through either model data hosted at CCMC or on a personal machine. This service greatly simplifies the complexity of users’ access to model data, abstracting away the time-consuming details of model data formats and interpolation. We demonstrate execution times of a few seconds to a few minutes for several example flythroughs of a trajectory stretching over a few days, depending on the parameters chosen. We also demonstrate a reconstruction tool built on top of the satellite flythrough software, for use with mission planning and model-data comparisons. This tool, based on reconstructions provided for the GDC Science and Technology Definition Team, converts multiple, simultaneous satellite flythroughs into two-dimensional reconstructions. The reconstruction tool provides a software capability for satellite constellations to determine how many satellites are needed and in what configuration to resolve the desired features in the model data. Both tools are currently available through GitHub for a selection of CCMC-hosted ITM models. Finally, we present initial results from work in progress and plans for future work, including an expansion of the reconstruction tool to provide 3D reconstruction capabilities and a line-of-sight calculation tool.

software, python↗

NASA NTRSDate not supplied

Detecting And Characterizing Archetypes of Unintended Consequences in Engineered Systems

When designing engineered systems, the potential for unintended consequences of design policies or design decisions exists despite best intentions. Conditions that might cause the formation of unintended consequences are often known only in hindsight. However, since these conditions are associated with a single event, it is difficult to uncover the general patterns of conditions leading to unintended consequences. In this research, patterns of conditions associated with unintended consequences are learned from historical data and represented in the form of archetypes. While previous work using systems theoretic modeling has identified high-level archetypes, this work leverages a self-organizing map to learn archetypes of unintended consequences from human-tagged risk factors in a large data set of lessons learned from adverse events at NASA. The sixty-six identified archetypes contain patterns of conditions such as complexity and human-machine interaction associated with the formation of unintended consequences. To validate the archetypes, a sample of the archetypes is represented using system dynamics in order to illustrate that the identified archetypes are specialized versions of known high-level archetypes of unintended consequences. While the research is based upon a specific dataset, the archetypes apply to any engineered system and the pattern of leading indicators open a new path to manage unintended consequences and mitigate the magnitude of potentially adverse outcomes.

Hannah S Walsh↗

NASA NTRS1994

Pyrolaser Operating System

Software provides for control and acquisition of data from optical pyrometer. There are six individual programs in PYROLASER package. Provides quick and easy way to set up, control, and program standard Pyrolaser. Temperature and emisivity measurements either collected as if Pyrolaser in manual operating mode or displayed on real-time strip charts and stored in standard spreadsheet format for posttest analysis. Shell supplied to allow macros, which are test-specific, added to system easily. Written using Labview software for use on Macintosh-series computers running System 6.0.3 or later, Sun Sparc-series computers running Open-Windows 3.0 or MIT's X Window System (X11R4 or X11R5), and IBM PC or compatible computers running Microsoft Windows 3.1 or later.

Roberts, Floyd E., III↗

NASA NTRSDate not supplied

Ramdb: The NASA Raman Spectral Database (version 1.00).

Given that, in most instances, minimal sample preparation is required and due to its contactless instrument design, Raman spectroscopy is one of the most versatile vibrational spectroscopic techniques for the chemical analysis of environmental and biological specimens. The diversity of applications of Raman spectroscopy ranges anywhere from art [1] to planetary science missions [2]. The advancement in the use of Raman spectroscopy in Solar System missions, notably in post-mission sample return analysis, requires a spectral library holding the broad range of specimens that could be found in Solar System sources. For this purpose, we have initiated the development of a Raman spectral database (Ramdb) at NASA Ames Research Center. Currently, the database includes experimental and theoretical Raman spectra of PAHs [3, 4], as well as laboratory Raman spectra of amino acids, carbon allotropes, minerals, and analogs relevance to Earth Sciences [5], Exobiology [6], Planetary [7], and Astrochemistry [8] to name just a few examples. Ramdb can be found on the web at www.astrochemistry.org/ramdb, where raw and processed Raman spectra can be downloaded in CSV format. The laboratory Raman spectra are measured using a laser Raman spectrometer (JASCO NRS-5500-532QRI). The Raman instrument is equipped with three excitation lasers, with wavelengths of 405, 532, and 785 nm. A clean silicon substrate is used as the internal standard for wavenumber calibration. Powdered samples were prepared (microscopic >10 um, grounded microscopic < 10 um) on glass slides. Some raw data exhibited a background signal arising as a combination of laser-induced fluorescence from the sample. To correct this background, we developed a Python pipeline that uses open-source Python libraries. Ramdb provides both raw and processed (using Python pipeline) data, which includes tabulated Raman shift transitions and other measurement details. The theoretical Raman band positions of PAHs (pyrene monomers and tetramer clusters) were computed using density functional theory (DFT) with the help of the Gaussian 16 suite of programs [9]. In the near future, Ramdb will serve as a repository of Raman spectral data from Laboratory Astrophysics and Planetary Science experiments involving the irradiation of organic compounds under simulated space and planetary conditions. In addition, online and offline tools will be developed for utilising the database for comparison to the user’s sample.

N Punnakayathil↗

NASA NTRSDate not supplied

The NASA Open Science Data Repository: Biomedical Fair Data, Analysis Tools, User Communities, Publications, and Discoveries for Deep Space Missions

Increased biomedical risks and challenges associated with deep space missions require new knowledge discovery, new health countermeasures, and development of novel ecosystems, life support, crop production, and biomedical support capabilities. To meet NASA’s Moon to Mars strategic program goals for Human and Biological Sciences, findable, accessible, interoperable, reusable (FAIR), and maximally open-access data is going to be required to enable humanity to thrive in deep space. Indeed, this cornerstone perspective on FAIR and maximally open access data was also recommended in the recent 2023-2032 Decadal Survey from the National Academies of Sciences, Engineering, and Medicine. The NASA Open Science Data Repository (OSDR) is a maximally open access and FAIR database, and meets various scientific, technical, and operational spaceflight needs. It offers public users and submitters the ability to upload, download, search, share, analyze, and visualize data across ‘omics, physiological, phenotypic, behavioral, bioimaging, video, and environmental monitoring telemetry datasets. OSDR includes NASA GeneLab, NASA Ames Life Sciences Data Archive, and the NASA Biological Institutional Scientific Collection. OSDR has >455 studies with datasets from model organisms and non-NASA human astronauts. There are ~12 datasets from the Inspiration 4 (I4) mission, spanning metagenomics, comprehensive metabolic panels, clonal hematopoiesis, spatial transcriptomics, proteomics, and cytokine panels. In the interest of data privacy, two I4 datasets have raw FASTQ and FASTA files relating to the epitranscriptome, and a new request feature is live in OSDR (with a backend review process established) which was developed based on industry norms. OSDR also recently began a collaboration with the European Space Agency (ESA) to scientifically curate and make available >200 terabytes of human and model organism space-relevant data. The OSDR submission portal is designed to ingest and curate ~25 ‘omics assay data types, and ~50 physiological-phenotypic-imaging assay data types, spanning ultrasonography, micro-computed tomography, histology, morphometric photography, rebound tonometry, gait analysis, optical coherence tomography, novel object recognition, flow cytometry, and immunohistochemistry. A suite of analysis tools are available for OSDR users including: 1) an Environmental Data Application to compare radiation, CO2, relative humidity, temperature, and other telemetry across missions and subjects, 2) the RadLab database, a collaboration between NASA, ESA, the German and Italian Space Agencies, and the Bulgarian Academy of Sciences, which compiles radiation measurements relevant to human spaceflight and provides tools for accessing and manipulating the data, and 3) a Multi-study visualization tool which enables users to look across and combine GeneLab’s omics datasets across different experiments and missions. There are ~600 volunteer OSDR Analysis Working Group (AWG) members who: 1) provide feedback on scientific standards for reuse (subject and assay metadata; processing pipelines; dataset formats and uniformed structures for machine-readability), and 2) collaborate to mine-reuse OSDR data conducting scientific analysis. OSDR has enabled 60 publications as of September 2023, many directly from AWG collaborations most notably the Cell Press package in 2020. Lastly, there are at least 15 articles which mine OSDR data part of a package of ~50 articles across Nature Portfolio with research stemming from I4, the Japan Aerospace Exploration Agency, NASA Space Biology, and the NASA Human Research Program.

space biology↗

NASA NTRS2005

Lunar and Planetary Science XXXVI, Part 4

Contents include the following: High-Resolution Electron Energy-Loss Spectroscopy (HREELS) Using a Monochromated TEM/STEM. Dynamical Evolution of Planets in Open Clusters. Experimental Petrology of the Basaltic Shergottite Yamato 980459: Implications for the Thermal Structure of the Martian Mantle. Cryogenic Reflectance Spectroscopy of Highly Hydrated Sulfur-bearing Salts. Implications for Core Formation of the Earth from High Pressure-Temperature Au Partitioning Experiments. Uranium-Thorium Cosmochronology. Protracted Core Differentiation in Asteroids from 182Hf-182W Systematics in the Eagle Station Pallasite. Maximizing Mission Science Return Through Use of Spacecraft Autonomy: Active Volcanism and the Autonomous Sciencecraft Experiment. Classification of Volcanic Eruptions on Io and Earth Using Low-Resolution Remote Sensing Data. Isotopic Mass Fractionation Laws and the Initial Solar System (sup26)Al/(sup27)Al Ratio. Catastrophic Disruption of Porous and Solid Ice Bodies (sup187)Re-(sup187)Os Isotope Disturbance in LaPaz Mare Basalt Meteorites. Comparative Petrology and Geochemistry of the LaPaz Mare Basalt Meteorites. A Comparison of the Structure and Bonding of Carbon in Apex Chert Kerogenous Material and Fischer-Tropsch-Type Carbons. Broad Spectrum Characterization of Returned Samples: Orientation Constraints of Small Samples on X-Ray and Other Spectroscopies. Apollo 14 High-Ti Picritic Glass: Oxidation/Reduction by Condensation of Alkali Metals. New Lunar Meteorites from Oman: Dhofar 925, 960 and 961. The First Six Months of Iapetus Observations by the Cassini ISS Camera. First Imaging Results from the Iapetus B/C Flyby of the Cassini Spacecraft. Radiative Transfer Calculations for the Atmosphere of Mars in the 200-900 nm Range. Geomorphologic Map of the Atlantis Basin, Terra Sirenum, Mars. The Meaning of Iron 60: A Nearby Supernova Injected Short-lived Radionuclides into Our Protoplanetary Disk.

Source record↗

NASA NTRS2007

The Development of Microshutters for the Near Infrared Spectrograph on the James Webb Space Telescope

One of the James Webb Space Telescope's (JWST) primary science goals is to characterize the epoch of galaxy formation in the universe and observe the first galaxies and clusters of galaxies. This goal requires multi-band imaging and spectroscopic data in the near infrared portion of the spectrum for large numbers of very faint galaxies. Because such objects are sparse on the sky at the JWST resolution, a multi-object spectrograph is necessary to efficiently carry out the required observations. We have developed a fully programmable microshutter array that will be used as the field selector for the Near Infrared Spectrograph (NIRSpec) on JWST. This device allows slits to be opened at the locations of selected galaxies in the field of view while blocking other unwanted light from the sky background and bright sources. In practice, greater than 100 objects within the field of view will be observed simultaneously. In this paper, we describe the microshutter arrays, their development, fabrication, testing, and progress toward delivery of flight qualified devices to the NIRSpec instrument team in 2008.

Silverberg, Robert F.↗