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At least 1,315 records · Page 73

Artemis Internal Science Team Update: Deployed Payloads

Artemis will reestablish human presence on the Moon and lead to a new era of scientific discovery and exploration. Led by the National Aeronautics and Space Administration (NASA), the Artemis effort includes a collaboration of space agencies and companies from around the world. In support of Artemis, a cross-disciplinary effort of science, engineering, operations, and human factors personnel is currently developing the best methods, facilities, and field locations to test hardware, train astronauts, and evaluate concepts of operations. This poster, as part of the Artemis Internal Science Team (AIST), provides an update to NASA’s plans for the solicitation, development, and operations of deployed surface payloads. In calendar year 2023, NASA’s Science Mission Directorate will solicit proposals for instruments to be deployed by crew on the surface of the Moon (Fig. 1), beginning with Artemis III. The Artemis III mission will land in the south polar region of the Moon, within 6º of latitude from the south pole, in the vicinity of both persistently illuminated and permanently shadowed areas of the Moon, with potential access to surface-accessible volatile deposits. Several of the proposed landing regions are located among some of the oldest parts of the Moon, and together with the permanently shadowed regions, provide the opportunity to learn about the history of the Moon through previously unexplored lunar regions. Deployed payloads will be a critical part of a notional program that captures the highest-priority science for Artemis III and provides the greatest feed-forward to follow-on missions and the build-up to the Artemis Base Camp.

R. C. Weber↗

Science Status of the NASA-ISRO SAR Mission

The NASA-ISRO SAR (NISAR) Mission is entering its second phase of integration and test, preparing for a launch in January 2023. The mission will exploit synthetic aperture radar to map Earth’s surface every 12 days, persistently on ascending and descending portions of the orbit, over all land and ice-covered surfaces. The mission’s primary objectives will be to study Earth land and ice deformation, and ecosystems, in areas of common interest to the US and Indian science communities. This single observatory solution with an L-band (24 cm wavelength) and S-band (10 cm wavelength) radar has a swath of over 240 km at fine resolution, and will operate primarily in a dual-polarimetric mode in an exact repeat orbit. The science teams at NASA and ISRO are working jointly to finalize the joint science plan, calibration and validation plan, and science products, and operational procedures.

Kumar, Raj↗

The Open Data Repository - an Open Science Platform for Long-Tail Research Data

Introduction: ‘Long-tail’ research is performed by individual PIs and small research teams, producing what are often highly diverse, but relatively small da-tasets that span a variety of traditional scientific disci-plines. ‘Long-tail’ research is a fundamental part of realizing NASA’s goals in planetary sciences and a key input feeding into mission life cycles. The ‘long-tail’ has traditionally lacked the resources (available to larg-er groups and missions) to overcome barriers inhibit-ing the adoption of open science practices, including lack of acknowledgment, time, money, guidance, ex-pertise, and trust in available platforms1. Here we show how the Open Data Repository’s (ODR) data publish-ing platform could help lower some of these barriers and accelerate the adoption of open-science practices in planetary science.

‘Long-tail’ research↗

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields in the last two decades, in part thanks to an increasing culture of open data sharing and reuse. Due to its capability for identifying complex relationships and patterns, AI/ML methodology is particularly well suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are many key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Even with the positive culture of Open Science and data sharing, inexperienced researchers working quickly without proper checks can produce models that perform poorly outside of the immediate training dataset. Lessons learned from biological AI/ML research indicate that Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Andrew Casaletto↗

Enabling Model Organism and Commercial Astronaut Data Access Through the NASA Open Science Data Repository

NASA’s Open Science Data Repository (OSDR) brings together omics data from NASA’s GeneLab project and non-omics data, including physiological, phenotypic, imaging, and behavioral data from NASA’s Ames Life Sciences Data Archive (ALSDA) collected from decades of space biology research, providing open and FAIR (findable, accessible, interoperable, and reusable) access of these precious data to scientists world-wide. This rich source of meticulously curated metadata and data from spaceflight and analog studies has been mined by the scientific community resulting in dozens of high impact scientific publications that reveals a complex network of molecular and physiological effects of spaceflight across living systems, from microbes to plants, to mammals. Understanding how these effects translate to the human condition is critical as we move deeper into the era of commercial space travel. However, the integration of data, specifically omics data, from astronauts is particularly challenging due to their sensitive nature. OSDR has risen to this challenge by developing a mechanism to control access to identifiable levels of omics data, such as raw sequence data, while enabling public access to processed, unidentifiable, data and associated metadata that will allow the scientific community to interrogate human astronaut data alongside data from model organisms to begin answering these critical questions. The 2021 SpaceX Inspiration4 (I4) mission collected a comprehensive atlas of biological measurements from four civilian astronauts, providing a wealth of data to characterize the effects of spaceflight on the human body. These data include both non-omics and omics assays such as direct RNA sequencing (RNA-seq), single nuclei ATAC-seq and RNA-seq, metagenomics, proteomics, and comprehensive metabolic and cytokine panels, all of which have been integrated into the OSDR system across no less than 9 studies. Each study has been carefully curated using community-backed OSDR standards for sample and assay level metadata ensuring these data are findable and accessible. In addition to hosting both raw and processed data from the principal investigator team for each assay type, the GeneLab team plans to re-process the I4 omics data using GeneLab’s standard processing pipelines. The GeneLab processed data outputs will allow for comparisons across studies on OSDR and enable visualization of these data through the OSDR data visualization platform thereby enabling data reusability and interoperability. Here we describe the robust privacy and security protocols implemented by OSDR to safeguard sensitive health data from astronauts while facilitating metadata and processed data sharing for research purposes. We further provide a road map for navigating the vast amount of data provided for each I4 study on the OSDR, including experimental design, associated experiments, payloads, and missions, data generation and analysis protocols, and associated scientific articles. Additionally, we illustrate how to interrogate the standardized metadata provided in the sample and assay tables as well as various means to download and access the data including programmatically through the GeneLab Open API (GLOpenAPI). The open access of datasets in NASA’s OSDR provides a unique opportunity for the scientific community, as well as citizen scientists and students, to continue using OSDR resources to further unlock profound insights into the consequences of space travel on the human body. Through implementation of security measures to protect sensitive human data, the OSDR seeks to strengthen the science exchange between the Biological and Physical Sciences Program and the Human Research Program, per recommendation 4-1 of the 2023-2032 Decadal Survey, and encourage further sharing and dissemination of astronaut data to provide the scientific community with the resources needed to lay the groundwork for developing targeted mitigation strategies to help withstand the rigors of long-duration spaceflight.

Amanda Marie Saravia-butler↗

NASA’s Satellite Needs Working Group Management Office: Developing Solutions in an Agile, Open Science Environment

Every two years, the National Aeronautics and Space Administration (NASA) leads an assessment of U.S. Federal civilian agency Earth observation needs submitted through the Satellite Needs Working Group (SNWG) survey. In four survey cycles beginning in 2016, nearly 400 high-priority satellite needs have been identified, spanning Earth Science and representing a wide variety of potential applications for Earth observation data. During each assessment cycle, new data products and services (i.e., solutions) that meet the needs of multiple agencies are identified and proposed for funding. The majority of solutions being developed or currently operational are global in scope, including harmonized land surface reflectance data from Landsat and Sentinel-2; composites of cloud properties derived from MODIS, VIIRS, and five geostationary satellites; dynamic surface water extent and land surface disturbance products derived from multiple optical and radar missions; a suite of low-latency products from the ICESat-2 mission; and a soil moisture product derived from the upcoming NISAR mission. The SNWG Management Office, within the Earth Action element of NASA’s Earth Science Division, manages both the biennial SNWG survey assessment and the development of solutions starting at full capacity with the 2020 cycle. Each solution project is required to align with NASA’s open science policy, including developing source code in an open code repository, having an open-source software license, and making all data freely available via NASA’s Earthdata website. The presentation will include an overview of the SNWG process, its emphasis on open science, and highlight several operational solutions freely available to the global research and applications communities.

Katrina Virts↗

Scientific Content Curation in an Open Science Era

Today’s open science environment, in combination with the Big Data era, means more scientific data, software, tools, documentation, publications and other resources are available than ever. The promise of the open science era is that scientists will spend less time reinventing the wheel and more time doing actionable research. Yet navigating this vast and complex information landscape can feel overwhelming to scientists trying to get their bearings. In this presentation, we define and discuss the importance of scientific content curation for enhancing discovery and use of scientific data and information. We also share two examples of scientific content curation in action: the Catalog of Archived Suborbital Earth Science Investigations (CASEI) and the Science Discovery Engine (SDE).

Kaylin Bugbee↗

Open Science Practices at the Community Coordinated Modeling Center

Open Science is defined as “the principle and practice of making research products and processes available to all, while respecting diverse cultures, maintaining security and privacy, and fostering collaborations, reproducibility, and equity” by Federal Agencies. The CCMC has been practicing open science based on FAIR (Findable, Accessible, Interoperable and Reusable) principle by providing access to the state-of -the art space science and space weather models to users around the world through various simulation services such as Runs-on-Request, Instant Runs, Real time runs on iSWA system. The CCMC also provides a wide range of tools and framework to help users easily utilize modeled data. One of the tools is the official NASA open-sourced software called Kamodo. Kamodo allows users to work with complex space weather models and data with little or no coding experience. Additionally, to support transparent model validation efforts, the CCMC is providing an integrated and flexible framework called CAMEL. CAMEL allows users to seamlessly compare model outputs with observational data sets. Currently, we are working on a user-friendly database of the papers and research that used CCMC services, so that the future users will have open access to previously performed research by other users and its details. In this presentation, we will show the open tools and resources provided by the CCMC. Furthermore, we will share our new efforts to support open data and open science results.

Ja Soon Shim↗

Connecting Community Scientific Hypotheses to Mars Sample Science

The proposed Mars Sample Return (MSR) program seeks to bring back to Earth a set of specially curated samples from the surface of Mars. The first segment of the MSR program is presently under-way; the Mars 2020 rover Perseverance has, to date, collected 24 samples of martian rock, regolith, and at-mosphere within Jezero crater. Its geologically diverse rock sample set can provide insight into the time evolu-tion of the Jezero environment, including the possible preservation of ancient biosignatures. Presently, a cache of 10 samples has been deposited in the Three Forks region on the floor of Jezero crater. These sam-ples, deemed scientifically return worthy by the Mars science community [1], are intended as a contingency sample set, as Perseverance has subsequently obtained more samples, and is therefore storing a more compre-hensive and scientifically valuable set of samples that will grow as the rover ascends to the rim of Jezero crater. The return of samples from Mars has been identi-fied as the highest priority planetary mission in the past three National Academies Decadal Surveys [2-4]. Sub-stantial work has gone into establishing science objec-tives for an MSR program, an overall framework for sample retrieval and analysis, and the expected impact on future Mars science and exploration (e.g., [5]). These objectives have been established at a relatively high level, e.g., “Interpret the primary geologic pro-cesses and history that formed the martian geologic rec-ord, with an emphasis on the role of water.” (Objective 1 in [5]) and are designed to encapsulate the broad sci-entific priorities of, and lay the groundwork for, inves-tigation strategies and measurements to be conducted by a future MSR program. It is from this overarching framework that the Connecting Community Scientific Hypotheses to Mars Sample Science workshop (‘The Workshop’) was conceived, with the purpose of distil-ling these high-level scientific objectives into discrete, testable hypotheses across a range of scientific disci-plines. The output of the workshop is meant to be a ‘hy-pothesis document’ serving as a starting point for cata-loging and condensing specific hypotheses for consid-eration by the scientific community. The template for this approach is based on the “driving hypotheses” de-veloped by the OSIRIS-REx team as part of their Sam-ple Analysis Plan [6].

Michael A Mischna↗

Science Objectives and Investigations for the Lunar GNSS Receiver Experiment (LuGRE)

In July 2020, NASA selected the Lunar GNSS Receiver Experiment (LuGRE) as the 10th payload of CLPS Task Order 19D. Firefly's Blue Ghost lander will deliver LuGRE and the other CLPS 19D payloads to the Moon's Mare Crisium. Developed jointly by NASA and the Italian Space Agency (ASI), LuGRE is intended to be the first demonstration of GNSS-based navigation beyond an altitude of 30 RE and the first to use GNSS on the lunar surface, expanding the proven reach of usable GNSS signals. Subsequent missions will be able to leverage LuGRE data and lessons learned to operationalize GNSS in the lunar regime, adding an existing, proven, real-time navigation source for spacecraft exploring the Moon. The primary goal of the LuGRE project is to extend GNSS-based navigation and timing to the Moon. LuGRE will fulfill this goal by gathering and processing GNSS data across several mission phases. The LuGRE Science Definition Team (SDT) was formed for the purpose of proposing science and technology investigations to be executed by the LuGRE project. A primary outcome of the work of the LuGRE SDT is a set of specific, high-value, achievable investigations to be performed as part of the science program. This paper provides a detailed description of the LuGRE science investigations and will present preliminary analyses that show how these investigations will be used to support the realization of lunar GNSS use in the future.

Lauren Konitzer↗

Implementation Plan for a NASA Integrated Lunar Science Strategy in the Artemis Era

This Implementation Plan provides a snapshot of NASA’s plans to implement the strategy recommended in OWL and to address the M2M objectives relevant to lunar science. The word “integrated” in the title refers to integrating the capabilities and new opportunities afforded by Artemis and CLPS alongside more traditional mechanisms such as The Discovery and New Frontiers Programs and various Research and Analysis (R&A) elements to achieve our lunar science objectives. It is an opportunity to present the full scope of tools currently available to NASA and how they map to high-priority lunar science that can be accomplished on and at the Moon. It is also an opportunity to build a plan for future NASA-led, lunar focused science and exploration activities that is flexible and can be adapted to a changing landscape (i.e., capability growth, priority evolution, and budgetary fluctuation).

Moon↗

ARM Aerosol Measurement Science Group Charter

The Atmospheric Radiation Measurement (ARM) Aerosol Measurement Science Group (AMSG) is tasked with providing enhanced coordination of ARM Climate Research Facility observations of aerosols and atmospheric trace gases with the needs of its users. Its objective is to ensure advanced, well-characterized observational measurements and data products at the spatial and temporal scales necessary for improving climate science and climate model forecasts. The primary function of the AMSG will be to provide strategies to the ARM Technical Director and ARM Chief Operations Officer that can be used to implement a coherent measurement and data processing approach that addresses the priority aerosol science needs of ARM and Atmospheric System Research. The group fulfills the need for an integrated oversight to the planning, coordination, and leadership of aerosol instrumentation selection and deployment, measurement strategy and quality, and data product development from both science and operations perspectives.

Source record↗

ARM Radar Science Recommendations from 2017 6th ARM Radar Workshop

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s radar organization was formed to provide an integrated approach to meet the scientific objectives of ARM. The radar organization consists of two groups: Radar Science and Radar Engineering and Operations. The two groups work closely for planning, coordination, and communications to produce high-quality observations and products from the ARM radar network, which consists of complex radars deployed in very challenging environments. In addition, scanning cloud radars are relatively new in the community, with very limited products that are mature enough to be applied for modeling studies. The Radar Science Group and Radar Engineering and Operations Group meet regularly along with researchers and users from the community in a workshop. The overarching objective of the workshop is to maximize the usage of ARM radar data for improving our understanding of processes and, ultimately improving representation of clouds and precipitation in models. The 6th DOE ARM Radar Engineering and Radar Science Workshop was held October 24-26, 2017, at Stony Brook University. Approximately 40 participants were present; a detailed list of participants is listed in Section 5. This report documents recommendations made by members of the science community who attended the workshop. Their recommendations appear italicized in the report. ARM management will consider these recommendations in their future planning and prioritization activities. The topics addressed during the workshop are contained in the agenda (Section 4). Significant action items, recommendations, and comments that came out of the meeting are contained in Section 3. The content in Section 3 presents a path through important discussions that were pursued during the Workshop.

Southern Great Plains, North Slope of Alaska, East↗

A Workshop on the History of Plutonium Processing at Hanford Washington as the Foundation for Modern-day Plutonium Process Science

Numerous national laboratories in the United States have roots related to the Manhattan Project that contributed to the end of World War II. The pioneering science and engineering that took place over the decades that followed continues to influence modern-day actinide-related research at those institutions, leading to unique strengths and cutting-edge ideas and perspectives. These same national laboratories also face a challenge: figuring out how to capture the expertise of a retiring workforce who had first-hand experience in these pioneering nuclear efforts. Recently, at PNNL a “Train-the-Trainer” approach has been piloted where mentors and mentees are paired together to develop and deliver interactive workshops on historical topics that relate to modern-day research, such as Plutonium Processing or Environmental Management of Legacy Nuclear Waste. This approach was used to develop a workshop that beings with the Historic Hanford process plutonium chemistry and engineering, describes its influence on current plutonium separation and process science, and then details the chemistry of plutonium as it progresses from a minor constituent in irradiated fuel to purified solid product. This workshop is targeted to the practitioner of applied science and technology wishing to gain a better understanding of the history and process-related chemistry of element 94 so that they may better direct the tools of their specific craft toward the present and future needs of plutonium science.

Smith, Frances N.↗

Science Federation Emulation Testbed: Demonstration of VFSIE Functionalities

The Virtual Federated Science Instrument Environment (VFSIE) is a digital twin of a federated infrastructure of multiple sites with science instruments and computing systems that are geographically dispersed. It emulates the federation using containers and virtual hosts (vhosts) connected over local and wide-area networks for the main purpose of supporting the development and testing of science workflows and software stacks, which will subsequently transition to the physical infrastructure. In this demo, we present VFSIE of a four sites scenario and illustrate the following use cases: (i) execution of federation stack components that expose resources to enable a science user to execute workflows, (ii) execution of remote control commands of beam-line instruments to collect measurements and position the sensor, and (iii) remote execution and access of Jupyter Notebook for tomographic image computations

Al Najjar, Anees↗

Enhancing the actinide sciences in Europe through hot laboratories networking and pooling: from ACTINET to TALISMAN

Since 2004, Europe supports the strengthening of the European actinides sciences scientific community through the funding of dedicated networks: (i) from 2004 to 2008, the ACTINET6 network of excellence (6. Framework Programme) gathered major laboratories involved in nuclear research and a wide range of academic research organisations and universities with the specific aims of funding and implementing joint research projects to be performed within the network of pooled facilities; (ii) from 2009 to 2013, the ACTINET-I3 integrated infrastructure initiative (I3) supports the cost of access of any academics in the pooled EU hot laboratories. In this continuation, TALISMAN (Trans-national Access to Large Infrastructures for a Safe Management of Actinides) gathers now the main European hot laboratories in actinides sciences in order to promote their opening to academics and universities and strengthen the EU-skills in actinides sciences. Furthermore, a specific focus is set on the development of advanced cutting-edge experimental and spectroscopic capabilities, the combination of state-of-the art experimental with theoretical first-principle methods on a quantum mechanical level and to benefit from the synergy between the different scientific and technical communities. ACTINET-I3 and TALISMAN attach a great importance and promote the Education and Training of the young generation of actinides scientists in the Trans-national access but also by organizing Schools (general Summer Schools or Theoretical User Lab Schools) or by granting students to attend International Conference on actinide sciences. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

New Science, New Media: An Assessment of the Online Education and Public Outreach Initiatives of The Dark Energy Survey

As large-scale international collaborations become the standard for astronomy research, a wealth of opportunities have emerged to create innovative education and public outreach (EPO) programming. In the past two decades, large collaborations have focused EPO strategies around published data products. Newer collaborations have begun to explore other avenues of public engagement before and after data are made available. We present a case study of the online EPO program of The Dark Energy Survey, currently one of the largest international astronomy collaborations actively taking data. DES EPO is unique at this scale in astronomy, as far as we are aware, as it evolved organically from scientists' passion for EPO and is entirely organized and implemented by the volunteer efforts of collaboration scientists. We summarize the strategy and implementation of eight EPO initiatives. For content distributed via social media, we present reach and user statistics over the 2016 calendar year. DES EPO online products reached ~2,500 users per post, and 94% of these users indicate a predisposition to science-related interests. We find no obvious correlation between post type and post reach, with the most popular posts featuring the intersections of science and art and/or popular culture. We conclude that one key issue of the online DES EPO program was designing material which would inspire new interest in science. The greatest difficulty of the online DES EPO program was sustaining scientist participation and collaboration support; the most successful programs are those which capitalized on the hobbies of participating scientists. We present statistics and recommendations, along with observations from individual experience, as a potentially instructive resource for scientists or EPO professionals interested in organizing EPO programs and partnerships for large science collaborations or organizations.

Wolf, R. C.↗

Ensuring that ecological science contributes to natural resource management using a Delphi-derived approach

This chapter approaches participatory modeling in environmental decision making from an atypical perspective. It broadly addresses the question of how to assure that science conducted to assist practitioners improves resource management. More specifically, it describes a case involving environmental science and natural resource management at Fort Benning, a U.S. Army installation in the southeastern United States where disparate environmental research projects were funded by a single federal agency to enhance the ability of Fort Benning resource managers to achieve their resource management goals. The role of our effort was to integrate the scientific studies in a manner that would be meaningful and useful for resource managers. Hence we assembled a team consisting of an anthropologist, ecologist, microbiologist, statistician, and geographic information systems specialist who developed a common framework that served as the basis for this integration. The team first used a Delphi expert elicitation, which evolved into an approach more akin to facilitated negotiation. This second approach arose organically, particularly when our team took advantage of an opportunity for face-to-face interaction. Although the shift in our approach was unplanned, it proved to be highly productive. We discuss the potential utility of our approach for other situations and suggest that it would be useful to initiate at the beginning of research where the aim is to produce scientific results that meet practitioners needs, specifically in the realm of environmental science and resource management.

Delphi approach↗