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NASA NTRSDate not supplied

Expanding Biological Repository Data Available for Sharing and Knowledge Discovery

Biology has developed next-generation data science and alternative analytical approaches with methodologies which require principal investigator (PI) experimental assay data be re-used. This new approach involves mining multiple datasets at once from various hierarchical organizations of biological complexity, while concurrently evaluating how experimental factors affect endpoints of standard assays. The purpose of the NASA Ames Life Sciences Data Archive (ALSDA) is to collect, curate, and make findable, accessible, interoperable, and reusable (FAIR) all non-human space-relevant biological data. These data include mission metadata, subject metadata, assay metadata (parameters), raw and processed assay data, assay imagery, and subject-experienced telemetry (radiation, temperature, humidity, acoustics, vibrations). ALSDA has transformed to bring current biological repository data and all future collected data into this new scientific data mining reality. It has integrated into the ‘NASA Open Science’ group of projects to facilitate a suite of new tools and workflows to improve data accessibility and reusability by implementing data management plans, automating data submission agreements, and adopting the single-point-of-entry data submission portal, originally developed by NASA GeneLab. These systems required ALSDA to develop science assay configurations for the submission portal, capturing essential assay parameters according to established norms in each sub-field within biology. The submission portal expedites data collection by enhancing ease of PI data submission, providing a user interface and specificity for which data is to be submitted. ALSDA datasets are curated to maintain rich metadata, accuracy of datasets, data transparency, provenance, and additionally ensure data are machine-readable (e.g., R and Python languages). ALSDA integration with GeneLab and its analysis portals enable higher-order physiological-level datasets be mined in conjunction with -omics datasets. As ALSDA physiological-level datasets are published (micro-computed tomography, histology, intraocular pressure, hormonal assays, immunostaining, ultrasonography), the merging of hierarchical organizations of biological complexity from spaceflight will enable new knowledge discovery approaches.

Ryan T Scott↗

NASA NTRSDate not supplied

Applications of Advanced Nondestructive Evaluation (NDE) and Structural Health Monitoring (SHM) Techniques to Address Safety of Flight Issues on NASA Spacecraft

Advanced NDE and SHM techniques are critical for ensuring the reliability and safety of NASA launch vehicles and spacecraft. NDE techniques such as infrared thermography, THz imaging, x-ray computed tomography and backscatter x-ray are used to detect indications of damage in spacecraft components and structures. Additionally, sensor and measurement systems are integrated into spacecraft to provide SHM to detect damaging events that occur during flight such as debris impacts during launch and assent or from micrometeoroid and orbital debris, or excessive loading due to anomalous flight conditions. A number of examples will be provided of how these NDE and SHM techniques have been applied to resolve safety critical inspection concerns for the Space Shuttle, International Space Station (ISS), and a variety of launch vehicles and unmanned spacecraft.

Advanced Nondestructive Evaluation (NDE)↗

NASA NTRSDate not supplied

A Markov Random Field Model for Texture-based Segmentation of Small Cracks in Thin InconelTubes

Markov random fields have been used for image segmentation since their introduction in the1980s. This work applies a method from Principal Component Thermography to enhance thecontrast in damage regions in 3D images derived from X-ray computed tomography (CT)inspections. The developed method is applied to sizing of small cracks in thin Inconel tubes designed as probability of detection (POD) samples for radiographic inspection.Misclassification errors arising from artifacts due to beam-hardening are reduced by fitting the boundary of the segmented damage region with the arc of an ellipse. Results are comparedagainst those obtained through manual inspection.

Image segmentation↗

NASA NTRSDate not supplied

Expanding Repository Data Available For Sharing and Knowledge Discovery

Some of the hardest space biology and space health challenges require data-intensive, bioinformatic, meta-analytical, and computer-assisted research approaches. These challenges include examining interdisciplinary space life science research across experiments and across interacting spaceflight hazards (radiation, altered gravity, confinement, hostile-closed environments, distance-duration from Earth). The approaches to confront these challenges involve mining multiple datasets simultaneously from various hierarchical organizations of biological complexity, all while concurrently evaluating how experimental design factors affect endpoints of standard assays. To enable this field, it is essential that principal investigators (PIs) submit data in a structure so it can be maximally re-used. The purpose of the NASA Ames Life Sciences Data Archive (ALSDA) is to collect, curate, and make publicly available all non-human space-relevant biological data. ALSDA must also ensure data are open-access, and maximally findable, accessible, interoperable, and reusable (FAIR). The scope of ALSDA data collected and submitted by PIs include subject and study design metadata, assay metadata parameters, raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). ALSDA recently integrated into a collaborative group of Open Science projects to facilitate a suite of new tools and workflows that will improve data submission, accessibility, and reusability by implementing digital data submission agreements, and adopting the data management system originally developed by NASA GeneLab. ALSDA intends to bring current biological repository data and all future collected data into this new scientific data reuse reality. This new suite of tools will enable ALSDA to deploy a science curation system using scientific assay configurations for the data submission portal. It will capture essential assay parameters according to established standards in each sub-field within biology. The submission portal expedites data collection by enhancing ease of PI data submission, providing a user interface and specificity for which data is to be submitted. Data submissions can be brought into cutting-edge informatic analysis portals to enable mining of physiological, behavioral, biochemical, and imaging datasets in conjunction with ‘omics-level datasets. As ALSDA datasets are submitted, curated, and published (e.g., micro-computed tomography, histology, pulse oximetry, serum metabolites, magnetic resonance imaging, intraocular pressure, novel object recognition, etc.), the merging together of spaceflight data along this multi-hierarchical complexity of biology will enable informatics and data-intensive approaches resulting in knowledge discoveries across missions, space hazards, and biological disciplines.

Biology↗

NASA NTRSDate not supplied

Challenges in Scaling Analysis from Coupons to Elements in 3D Woven Composites for a Launch Vehicle End-Ring Structure

The limitations of structural design with 3D woven composites based on homogenized material models characterized using coupon test data, representative unit cell analysis, or a combination of the two are discussed in the context of a space launch system (SLS)-scale end ring. Selected building block test configurations at the coupon, element, and subcomponent scales are described in detail. Highly instrumented tests and X-ray computed tomography inspections are used to characterize the structural behavior and associated damage progression with increasing load. It is shown that a single homogenized material constitutive relationship, applied at coupon and element scale, is not sufficient to model the structural response observed in both tests. In fact, substantially different stress-strain laws are required to predict the response of the coupon and element scale specimens, despite similar loading conditions. A model with discrete representation of the binder tows and cohesive interfaces to model matrix cracking shows much better agreement with the test data at the two length scales. Thus, evidence is provided showing that predictive structural analysis of 3D woven composites requires discrete representation of the tows, matrix cracking morphology, and their interactions in the structural configuration. With accurate knowledge of the element scale behavior, engineering approximations readily enable analysis scale-up to the subcomponent level.

Andrew C Bergan↗

NASA NTRSDate not supplied

Experimental Observations of Damage States in Unnotched and Notched 3D Orthogonal Woven Coupons Loaded in Tension

This paper describes a series of unnotched and notched tensile tests on two 3D orthogonal woven architectures loaded in the warp direction. Dogbone specimens were used for the unnotched tests, and open-hole specimens were used for the notched tests. For each architecture and test type, two specimens were loaded under monotonic displacement control to failure, and two specimens were incrementally loaded to failure in five steps. X-ray computed tomography (CT) was used to characterize the woven architecture and defects on each specimen prior to testing. Digital image correlation (DIC) images were obtained from both sides of the specimen throughout the loading and unloading. For the incremental tests, X-ray CT was used to document the damage progression after each load increment. The results for both architectures and test specimens followed a similar pattern where matrix cracks formed perpendicular to the load direction and were primarily located between the stacks of warp tows. Two-piece failure path always occurred perpendicular to the loading direction, along the through-thickness segments of the Z-tows. The combination of stress concentrations due to the specimen geometry, weave geometry, and cut tows created stress concentrations that appear to initiate failure.

Woven materials↗

NASA NTRSDate not supplied

Direct Measurement of the Composition of Aqueous Fluids from the Parent Body of Asteroid 162173 Ryugu

Imaging using X-ray absorption contrast by synchrotron nano-computed tomography (47.4 nm/voxel, 7keV) of a Ryugu pyrrhotite crystal (C0002-FC012-from the second touch-down site) revealed probable fluid inclusions (Fig. 1A,B) [1]. The inclusions were completely encapsuled in pyrrhotite, suggesting the fluids were trapped in the early stages of crystal growth, and filled with low-Z material. We performed Time-of Flight-Secondary Ion Mass Spectrometry (TOF-SIMS) depth profiling and high-resolution map-ping at -120°C to exposure and measure the composition of the trapped fluids in a frozen state.

M Zolensky↗

NASA NTRSDate not supplied

Expanding Repository Data Available For Sharing And Knowledge Discovery

life science↗

NASA NTRSDate not supplied

Overview of Nondestructive Evaluation Capabilities at NASA MSFC

Nondestructive evaluation (NDE) methods examine material integrity without impairing its usefulness. The NDE team at NASA Marshall Space Flight Center (MSFC) in Huntsville, Alabama is responsible for applying existing methods to new hardware designs and material systems, probability of detection studies to quantify detection capabilities, overseeing NDE requirements for flight hardware, inspecting development articles and flight hardware, engineering support for failure investigations, and investigating emerging NDE methods. NASA MSFC has been on the cutting edge of developing new NDE techniques, first for the space shuttle, then for composite structures, and most recently for additive manufacturing (AM). Standard in-house inspection capabilities include eddy current, magnetic particle, liquid penetrant, ultrasonic, and radiographic testing (including computed tomography). Other advanced inspection capabilities include infrared flash thermography, shearography, acoustic emission, and microwave/millimeter wave testing. Some recent research studies include AM probability of detection testing, investigating in-situ process monitoring methods for AM, and correlating the NDE response of true fatigue cracks with artificial notches.

nondestructive evaluation↗

NASA NTRSDate not supplied

Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery

The next era in human space exploration is rapidly approaching and will require the use of countermeasures to deep space health hazards. The development of countermeasures (or, the re-purposing of existing agents) will be highly dependent on our understanding of basic biological responses to space stressors (e.g. ionizing radiation, altered gravitational fields, altered day-night cycles, confinement, isolation, hostile-closed environments, distance-duration from Earth, exposure to celestial regolith, etc.). The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, imaging, whole organism and behavior). We will discuss here several strategies that NASA’s Biological and Physical Science Division has put in place to maximize the return on investment for spaceflight bioscience data. Open Science, as a scientific philosophy, is the concept that the more people who have access to the data, the more knowledge will be gained from it. This guiding principle led NASA to develop GeneLab in 2015. GeneLab houses spaceflight and relevant ground-based multi-omics data, and has grown to ~400 transcriptomic, proteomic, metabolomic and epigenomic datasets from plant, rodent, small animal, and microbial space experiments. GeneLab provides users with various tools for data analysis and a visualization portal that allows users to interact with gene expression data from space-related ‘omics experiments. Open Science is also about building scientific communities, and with this spirit in mind, GeneLab has spawned several Analysis Working Groups (AWGs), comprised of more than 200 volunteer scientists. The AWGs initially provided feedback on the processing pipeline and metadata ‘omics standards for GeneLab. Over the last few years, they have become a community-driven science enterprise, engaging in large meta-analysis of GeneLab datasets, resulting in 10 publications (beyond the originally submitted research). Overall, the Open Science nature of GeneLab has resulted in a high degree of data re-use, resulting in 38 additional publications derived from the original 67 publication over the past four years. The enormous success and knowledge gained from GeneLab has led to a collection of sister NASA “Open Science Data Repositories (OSDR)” and research support groups. These include the NASA Ames Life Sciences Data Archive (ALSDA), the NASA Biological Institutional Scientific Collection (NBISC), and the Biospecimen Sharing Program (BSP). All are adopting the GeneLab data architecture system to maximize open-access, find-ability, accessibility, interoperability, and reusability (FAIR). ALSDA collects and curates phenotypic-physiological bioimaging-behavioral data from space and space-relevant non-human experiments, oftentimes coming from the same omics-associated experimental datasets found in GeneLab. Since 2021, a community of ~100 researchers have rallied around ALSDA, to provide feedback in a new ALSDA AWG focused on phenotypic-physiological investigation-sample-assay metadata standards (e.g., Micro-Computed Tomography, Light/Fluorescence Microscopy, Western Blot, Flow Cytometry, Novel Object Recognition, Elevated Plus Maze, etc. of ~50 assays collected). These standards are part of a new single point-of-entry data submission portal for all non-human Space Biology and Human Research Program principal investigators, to submit, curate, and share their research data. With open-access space biological data now collected and curated together with rich metadata, and with the potential for linkage to “big data” from the international biological and medical communities (NIH, EBI, etc.), the artificial intelligence and machine learning (AI/ML) era has started for Space Biology. Several other talks will cover these topics in this conference.

life sciences↗

NASA NTRSDate not supplied

Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery

The next era in human space exploration is rapidly approaching and will require the use of countermeasures to deep space health hazards. The development of countermeasures (or, there-purposing of existing agents) will be highly dependent on our understanding of basic biological responses to space stressors (e.g. ionizing radiation, altered gravitational fields, altered day-night cycles, confinement, isolation, hostile-closed environments, distance-duration from Earth, exposure to celestial regolith, etc.). The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, imaging, whole organism and behavior). We will discuss here several strategies that NASA's Biological and Physical Science Division has put in place to maximize the return on investment for spaceflight bioscience data. Open Science, as a scientific philosophy, is the concept that the more people who have access to the data, the more knowledge will be gained from it. This guiding principle led NASA to develop GeneLab in 2015. GeneLab houses spaceflight and relevant ground-based multi-omics data, and has grown to ~400 transcriptomatic, proteomic, metabolomic and epigenomic datasets from plant, rodent, small animal, and microbial space experiments. GeneLab provides users with various tools for data analysis and a visualization portal that allows users to interact with gene expression data from space-related 'omics experiments. Open Science is also about building scientific communities, and with this spirit in mind, GeneLab has spawned several Analysis Working Groups (AWGs), comprised of more than 200 volunteer scientists. The AWGs initially provided feedback on the processing pipeline and metadata 'omics standards for GeneLab. Over the last few years, they have become a community-driven science enterprise, engaging in large meta-analysis of GeneLab datasets, resulting in 10 publications (beyond the originally submitted research). Overall, the Open Science nature of GeneLab has resulted in a high degree of data-use, resulting in 40 enabled publications by open data. The enormous success and knowledge gained from GeneLab has led to a collection of sister NASA "Open Science Data Repositories (OSDR)" and research support groups. These include the NASA Ames Life Sciences Data Archive (ALSDA), the NASA Biological Institutional Scientific Collection (NBISC), and the Biospecimen Sharing Program (BSP). All are adopting the GeneLab data architecture system to maximize open-access, find-ability, accessibility, interoperability, and reusability (FAIR). ALSDA collects and curates phenotypic-physiological bioimaging-behavioral data from space and space-relevant non-human experiments, oftentimes coming from the same omics-associated experimental datasets found in GeneLab. Since 2021, a community of ~100 researchers have rallied around ALSDA, to provide feedback in a new ALSDA AWG focused on phenotypic-physiological investigation-sample-assay metadata standards (e.g., Micro-Computed Tomography, Light/Flourescence Microscopy, Western Blot, Flow Cytometry, Novel Object Recognition, Elevated Plus Maze, etc. of ~50 assays collected). These standards are part of a new single point-of-entry data submission portal for all non-human Space Biology and Human Research Program principal investigators, to submit, curate, and share their research data. With open-access space biological data now collected and curated together with rich metadata, and with the potential for linkage to "big data" from the international biological and medical communities (NIH, EBI, etc.), the artificial intelligence and machine learning (AI/ML) era has started for Space Biology.

omics↗

NASA NTRSDate not supplied

Update on Measurement of the Composition of Ryugu Fluid Inclusions

Imaging using X-ray absorption contrast by synchrotron nano-computed tomography of a Ryugu pyrrhotite crystal (C0002-FC012 - from the second Hayabusa2 spacecraft touch-down site) revealed probable fluid inclusions in the center of a crystal of pyrrhotite, suggesting the parent fluids were trapped in the early stages of crystal growth on Ryugu’s parent asteroid. We previously described the performance of Time-of Flight-Secondary Ion Mass Spectrometry (TOF-SIMS) depth profiling and high-resolution mapping at -120°C to expose and measure the composition of the trapped fluids in a frozen state in two Ryugu inclusions [1,2]. Here we report results from follow-on measurements of additional inclusions in the same pyrrhotite crystal, and the initial results of measurement of standards. The ultimate goal is to reveal the quantitative composition of the fluids that caused aqueous alteration, in particular the H2O:CO2 ratio, which will also facilitate cosmochemical modeling of the alteration process.

M Zolensky↗

NASA NTRSDate not supplied

The Aguas Zarcas Breccia - Similarities to Surface Features of C-Complex Asteroids Ryugu and Bennu

Knowledge of the materials originally present in the proto-solar nebula is one of the most significant constraints for models concerning the formation of our solar system. The physicochemical properties of these original materials can be determined through two distinct and complementary approaches: astronomical observations of nascent stellar systems and the dense clouds from which they originated; and laboratory studies of available astromaterials such as meteorites, interplanetary dust particles, comets, as well as returned mission samples (e.g., from Hayabusa -1 -2;OSIRIS -Rex). Laboratory study of these extraterrestrial materials provides valuable information about the first solids portion of the early solar system and their evolution. Here, we present petrographic and mineralogical characteristics of the polymic beccias Aguas Zarcas based on the research results of [1].On April 23, 2019, at 21:07 local time, a meteorite fall occurred in Aguas Zarcas, San Carlos County, Alajuela province, Costa Rica. The rapid recovery of this brecciated carbonaceous chondrite after its fall provides an opportunity to study a freshly fallen, relatively uncontaminated, and highly brecciated meteorite to compare with samples returned by theHayabusa2 and OSIRIS-REx spacecraft from C-group asteroids. The study includes several pre-rain fragments [1].The X-ray Computed Tomography (XCT) results show many different lithologies. We describe the petrography and mineralogy of five different lithologies of the Aguas Zarcas meteorite. We also present data on bulk oxygen isotopes. We describe all fragments in detail and attempt to classify each lithology in order to understand the origin and formation history of the Aguas Zarcas parent body. Our results show that some lithologies of Aguas Zarcas are similar to those in CM chondrites, but others are unique. The different lithologies [1] also represent different degrees of hydration and heating, which are good analogues for the types of materials returned by the Bennu and Ryugu asteroids. Spectroscopic observations of the Ryugu and Bennu asteroids compared to laboratory measurements of meteorites suggest that the asteroids have some similarities to heated CM, heated CI, or CI chondrites[2-5]. Both asteroids are thought to be composed of materials altered by aqueous alteration (e.g., [5]) and formed by reaccretion after destruction by impacts and brecciation (e.g., [6-7]). Considering the different lithologies in Aguas Zarcas [2] and other CM chondrites [8-9], these types of carbonaceous chondrites can be considered good analogues for samples from the Ryugu and Bennu asteroids. The presence of unique and rare lithologies in the Aguas Zarcas, different from the typical CM chondrite lithologies, suggests complex mixing of different materials in a highly dynamic environment.

Imene Kerraouch↗

NASA NTRS2022

A Discussion of the Failure of a Quad Diode Module and Efforts to Assure the Flight Spares

In 2019 the International Space Station (ISS) experienced an on on-orbit failure that affected 1 of 28 Battery Charge Discharge Units (BCDUs). Telemetry pointed to a short circuit failure of a Power Rectifier Quad Diode Module. Astronauts removed the failed unit from service which was then returned to Earth for failure analysis. The failure analysis confirmed that the quad diode module had failed short circuit. The investigation identified silver dendrites had grown on the insulated, sloped edge of the mesa semiconductor die of the failed diode and also a 2nd diode in the same quad diode module. Voids between the diode’s protective encapsulating ring and the die provided space within which dendrites were able to form and cause catastrophic failure. The NASA Engineering & Safety Center (NESC) convened a EEE Parts Sub-Team to investigate root cause and to assist with risk assessment for all of the flight diode modules (4 distinct production lots) and the flight spares (from a 5th lot). Analysis of the original diode manufacturer’s read and record screening test data identified some lots which contained diodes with parametric instabilities that could signal conditions suited for silver dendrite formation. Computed Tomography (CT) X-ray screening inspection was performed on flight spare modules to identify diodes that do not exhibit voids between the edge of die and encapsulating ring as a mitigation against dendrite formation.

Jay Brusse↗

NASA NTRSDate not supplied

Finite Element Modeling for Compression Strength Prediction of Honeycomb Cores with Geometric Imperfections Measured using X-ray CT Imaging

Aluminum honeycomb cores have been used extensively in composite sandwich panels due to having high bending rigidity while maintaining low density. During manufacturing of the aluminum honeycomb, the thin metal walls are susceptible to imperfections that deviate from an ideal honeycomb shape. Computational tools to quantify imperfections and investigate their effects on quasi-static compression and impact response can inform design criteria to construct safer and lighter launch vehicle structures. This paper presents the results of a study on finite element modeling of metallic honeycomb cores (HCC) with geometric imperfections measured using X-ray Computer Tomography (CT), to predict the compression response. Finite element (FE) models are constructed with measured imperfections with appropriate boundary conditions. It is shown that the average behavior of larger 10x11 cell models can be predicted by sampling single cell models from the larger domain. Amplification of imperfections for cells at the center of sampled specimens are mode switched from the larger out-of-plane imperfection to the mode shape of the adjacent cells resulting in strengthening of the center specimens.

aluminum honeycomb↗

NASA NTRSDate not supplied

From Apollo to Artemis: How Processing ANGSA Core Samples 73001/2 Can Help to Prepare for Future Sample Return Missions to the Moon and Beyond.

Introduction: Apollo Sample 73001/2 is a ~71cm long double drive tube consisting of an upper part (73002) and a lower part (73001) that contains regolith collected near Lara Crater at the Apollo 17 site, Station 3. The double drive tube is believed to have penetrated a lunar landslide deposit that was transported from the slope of the South Massif into the Taurus-Littrow Valley [1]. As part of the ANGSA (Apollo Next Generation Sample Analyses) initiative, preparing a preliminary examination (PE) catalog of 73001/2 is a crucial first step for the early identification of material types such as rock fragments and potential stratigraphy within the core. Many new curation and scientific tools such as X-ray computed tomography (XCT) [3], multi-spectral imaging [4], and gas extraction manifold with piercing tool [5-7], have been applied to the ANGSA core to benefit curation strategy, PE efforts, sample allocation to the planetary science community, and ultimately help to prepare for future sample return missions like Artemis. 73001/2 Preliminary Examination and Processing: Sample 73002 was successfully opened and extruded in Nov. 2019 and fully dissected at the end of 2021. Sample 73001 (Fig. 1) was successfully extruded in March 2022 after careful planning before opening the Core Sample Vacuum Container (CSVC) that was holding the drive tube of 73001. XCT, as part of PE, was used to scan the bottom and top part of the 73001 core tube within the CSVC prior to opening it to 1) facilitate non-destructive, rapid detection of any contamination potentials due to piercing of the CSVC during gas extraction [7]; and 2) to aid in the Artemis sample tool development and provide data on the knife edge seal of the CSVC. This knowledge will help us connect the mechanics of the implemented design (i.e., XCT data) to the performance of the seal (i.e., data on the gas samples will tell us how well the seal preserved the volatile record of lunar samples). Both type of information will feed forward into Artemis tool and storage strategies for future samples. Results and Lessons learned: The XCT data of the CSVC and core tube within showed that the bottom Teflon cap was not pierced during gas extraction (Fig. 1c) and thus, the sample integrity remained guaranteed during piercing and subsequent gas extraction. However, the XCT scan of the top of the core (Fig. 1b) revealed that the drive tube was overfilled with lunar soil and the tool that keeps the soil constrained within the drive tube was not fully deployed. These preliminary data allowed us to implement the necessary steps to prevent loss of sample integrity, including any potential stratigraphy shifts during extrusion. Processing Apollo core 73001/2, creating an informative PE catalog, and applying new and refined tools and technologies for sample analyses are invaluable activities that will assist in circumventing any potential pitfalls, aid in the characterization of samples, and help in the assessment of how well any lunar material has been collected and preserved in the past. This will aid in designing future sample collections and curation procedures and help to prepare for future human exploration and sampling missions such as Artemis. References: [1] Schmitt H. (2017) Icarus 298, 2-33. [3] Zeigler et al. (2021) LPSC 52nd, #2632; [4] Sun et al. (2021), LPSC 52nd, #1789; [5] Parai et al. (2021), LPSC 52nd #2665; [6] Schild et al. (2021) LPSC 52nd #1888; [7] McDonald (2022) ESL 2022.

ANGSA↗

NASA NTRSDate not supplied

Enabling Space Biological Knowledge Discovery Through Image and Video Data Sharing

Increased biomedical risks and challenges associated with deep space missions and experiments (cis-Lunar, Mars transit/surface) require new knowledge discovery and development of novel ecosystems. Supporting distant and long-duration missions and experiments requires biological data (from yeast, microbes, fruit flies, C. elegans, plants, crops, rodents, humans) be findable, accessible, interoperable, reusable (FAIR), and maximally open-access. As data-intensive, bioinformatic, meta-analytical, and computer-assisted approaches continue to be a centerpiece of modern research, the NASA Biological and Physical Sciences division is expanding its Open Science capabilities beyond NASA GeneLab. The NASA Ames Life Sciences Data Archive (ALSDA) is a repository which is responsible for collecting and access to space biological imagery and video, alongside tabular and environmental data. In this presentation, we will discuss strategies dealing with archiving, curating, and accessibility of images from very distinct imaging modalities (e.g., micro-computed tomography, magnetic resonance imaging, photographic images of plants, fluorescence microscopy, behavioral videos, etc.). There are two main challenges: 1. Open-source data storage and 2. Metadata related to the imagery-video. Both have been solved by leveraging two existing open-source systems. For data storage, ALSDA is utilizing components through the Open Microscopy Environment (OME), which can read most imaging proprietary formats and display on a web interface complex multidimensional images (Z stack, multi-channel, temporal, spectral). Most technical metadata from imaging modalities are captured seamlessly. For metadata capturing experimental details, ALSDA (like GeneLab) uses the ISA-Tab specification which relies on the ISA data model to order and classify metadata. The ISA data model uses a tree structure with three files to capture the metadata: The top layer is the Investigations file, the second layer is the Study file(s), and the last layer is the Assay file(s). We believe such an approach may be useful for other types of image research data from other investigators in the AGU community.

imaging↗

NASA NTRSDate not supplied

Biological Data for Deep Space Mission Support

Increased biomedical risks and challenges associated with deep space missions (cis-Lunar, Mars transit, Mars surface) require new knowledge discovery and development of novel ecosystem and biomedical support capabilities. This paradigm shift supporting distant and long-duration missions requires biological data to be findable, accessible, interoperable, reusable (FAIR), and maximally open-access (i.e., there is a data governance continuum from closed to mediated to embargoed to open). The NASA “Open Science Data Repositories” (OSDR) aims to meet scientific, technical, and operational spaceflight needs, and offers the ability to upload, download, search, share, analyze, and visualize data across physiological, behavioral, ‘omics, and environmental monitoring telemetry datasets. OSDR includes NASA GeneLab, NASA Ames Life Sciences Data Archive (ALSDA), and NASA Biological Institutional Scientific Collection (NBISC). In the past year, ALSDA has undergone a transformation in its data collection, curation, and architecture methods. Standardizing non-genomic (phenotypic) datasets was, and will continue to be, a challenge because of their diverse nature (e.g., molecular, cellular, tissue, whole organism behavior; micro-computed tomography, intraocular pressure, fluorescence microscopy, western blot, ultrasonography; tabular, images, video). This year ALSDA, alongside GeneLab, introduced the Biological Data Management Environment (BDME) with the purpose to accept submission of data from space relevant experiments including spaceflight, radiation, simulated gravity, gravitropism, isolation and confinement, hostile closed environments and/or distance from Earth. In addition to bringing together omics, phenotypic, physiological, bioimaging, and behavioral data into one repository. By integrating with GeneLab a multi-project submission portal aims to reduce the burden on PIs submitting data and enabling the discovery of both omics and phenotypic data. The purpose of ALSDA is to collect, curate, and make all non-human space-relevant biological data maximally findable, accessible, interoperable, and reusable (FAIR). These scope of ALSDA data collected and submitted by PIs include study design metadata, subject metadata, assay metadata (parameters), raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). In 2021, a community of researchers rallied to form the ALSDA Analysis Working Group (AWG) and provided scientific consensus on dataset sample and assay metadata. The community and excitement around the ALSDA/OSDR system has already led to several data reuse studies, demonstrating value using machine learning (ML), knowledge graphs, and meta-analysis approaches.

space biology↗