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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Visualizing Geospatial Data through ESRI Story Maps for Earth Science Education: Lessons Learned from My NASA Data

For 20 years My NASA Data (MND) has curated NASA Earth science data and provided the data to educators in engaging learner-centered resources. MND has recently featured story maps as an innovative way to engage students in NASA Earth data. A story map is a cloud-based lesson that engages the learner in interactive geospatial maps using NASA data, and other multimedia content, text, and tasks that can be seamlessly incorporated in classroom instruction. This immersive technology eliminates the need for the user to move among tricky interfaces to access and visualize Earth science data, and no special software is required to be downloaded. Each story map integrates data from different NASA satellite missions, retrieved from Distributed Active Archive Centers (DAACs). Story maps also employ data analysis tools, such as time series options and swipe tools that allow learners to view and analyze relationships between scientific variables. MND has produced 25 story map lesson plans on the topics of air quality, the urban heat island effect, Earth’s energy budget, phytoplankton distribution, hurricane formation, solar eclipses, ocean circulation patterns, sea ice extent, and volcanic eruptions. Nine of them are extended story maps and written in the 5E format, which is internationally recognized as best practice based on how children learn science. Each story map resource is developed by the MND team featuring a GIS programming specialist, a lead scientist, and educational specialist/s to ensure the context, content, and methods are scientifically and educationally sound. The MND story maps are written for middle and high school science teachers and students as they connect with the Earth Systems Science phenomena featured in the Next Generation Science Standards. Each story map includes supporting resources for smooth integration in the classroom. During Fiscal Year 2023, The My NASA Data website received over 100,000 story map engagements during. These metrics highlight the interest in story maps as an Earth Science educational resource.

Desiray Wilson↗
NASA NTRSDate not supplied

Increasing Discovery and Usability of Earth Science Satellite Data with My NASA Data

For 20 years, the My NASA Data project at NASA Langley Research Center has developed innovative approaches to increase the use of NASA’s satellite data by learners. My NASA Data offers a variety of authentic Earth Science datasets and a data visualization tool, eliminating the need for educators and/or learners to obtain specialized knowledge of GIS data formats and software to access and use authentic Earth Science data. While there is no shortage of available data, as federal government agencies such as NASA house petabytes of freely accessible Earth Science datasets, much of the data are only available for download and visualization in specialized formats and software, limiting their accessibility to educators and learners, especially those in primary and secondary school. Using the Google Earth Engine platform, the My NASA Data team has recently reinvented their data visualization tool, called the Earth System Data Explorer (ESDE). The ESDE gives users the capability to explore over 60 Earth Science satellite datasets in a multitude of formats such as maps, graphs, and data table Its new and improved user interface design was developed based on the preferences of educators, whom the My NASA Data project has over 20 years’ experience working with. Earth Science and GIS Subject Matter Experts (SMEs) structured the data in a professional and scientific manner. During Fiscal Year 2023, the My NASA Data website received over 1 million digital engagements, with over one-third being visitors to the data visualization tool. These metrics highlight the interest in a visualization tool that is simple and free to use with reliable and trusted datasets. The ESDE empowers users to readily relate and analyze NASA Earth Science data within their area of interest. The team used a user-centered design (UCD) framework to receive and incorporate feedback into the application’s design. Core requested features include the ability to create time series graphs, comparative analysis of maps, and download the data as CSV file. Responses indicate that advances in data visualization tools such as the ESDE make authentic Earth Science data more accessible. This presentation will cover how the My NASA Data project develops tools to enhance data discovery and accessibility, as well as how SME and user suggestions are incorporated.

Desiray Wilson↗
DOE OSTI2020

The role of peer review and science for advancing public understanding

We live in a time of rapid change. The Covid-19 pandemic has united the world to understand and develop solutions to protect the health and wellbeing of society. At the same time, access to information on the internet and social media has exploded. People are exposed to information with many claims. Some of the information is relevant and accurate. A significant fraction may be inaccurate, biased, and potentially dangerous. With Covid-19, the information might point to cures that are toxic or risks that are not relevant. The scientific community has developed a process to develop and convey knowledge. The validation of results and their interpretation is critical to advancing knowledge. The core of the scientific process is based on developing a hypothesis-driven concept, designing and executing an experimental approach to prove or disprove the hypothesis, conducting a statistical analysis of the results to confirm their validity, and interpreting their meaning and impact. When their work is completed the scientist prepares to publish the work. Publication requires peer review. Hypotheses, experimental approaches, results, and interpretation of results are independently and anonymously reviewed by a scientific peer. The reviewers are selected based on their expertise in the field. The peer review process is essential for the integrity of the scientific process. Without a robust scientific process, society cannot discriminate between validated results and interpretations and biased, inaccurate, and potentially dangerous conjecture. With inaccurate science society and policy makers may make poor decisions that could hurt people and the world around them. While scientists should not censor information available to the public, scientists have a responsibility to inform the public. We must articulate what the scientific process is and why it is essential when considering the validity of information. Scientist are responsible for pointing out when public information has not been vetted through a scientific process and therefore cannot be considered conclusive. Scientists are responsible for highlighting information that has been generated and vetted with the scientific process. Over time, our goal is for the public to value the scientific process based on peer review. The public could become enlightened to the necessity for peer review to support decisions and action. Scientists need to contribute to advancing public knowledge. When invited to serve as a peer reviewer, scientists have a responsibility to contribute to the process. We all are extremely busy making peer review a distraction. While peer review does not directly benefit our own work and career, it benefits our chosen field of science. This is very important for the research area that our journal, Water-Energy Nexus, is focusing on. We cover the convergence of science and technology integrating across large spatial ranges (micro to global) in environmental pollution and the balance of remediation issues with energy use. Water-Energy Nexus wants to provide scientists with a platform for scientific debate and discussion on this rich and complicated topic. With the manuscripts submitted to WEN cover integrated research topics across a broad range of subjects from environment sciences through energy engineering, the role of peer review is essential. Peer review on a new submission to WEN should not be biased towards a specific science field. It should be done considering the complex nature of issues in the water-energy nexus. Scientists need to contribute to the public dialog. To accomplish these goals, we need to be honest, accurate, articulate, and use understandable language. The impact of WEN is very diverse affecting society in many ways. The scientific audience for WEN is diverse and readers may not fully understand the content of the papers outside their research expertise. Therefore, scientists, especially those who want to contribute to WEN, should work with communications specialists to convey message to benefit society. The audience includes the general public and researchers outside the author’s core specialty. While the peer-reviewed journal article is the cornerstone of our careers and critical for advancing scientific knowledge, a general interest story could benefit society even more. The author cannot lose sight that our work has two audiences, the science community, and more importantly, our family, friends, neighbors, and policy makers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Named Entity Recognition and Normalization Applied to Large-Scale Information Extraction from the Materials Science Literature

The number of published materials science articles has increased manyfold over the past few decades. Now, a major bottleneck in the materials discovery pipeline arises in connecting new results with the previously established literature. A potential solution to this problem is to map the unstructured raw text of published articles onto structured database entries that allow for programmatic querying. To this end, we apply text mining with named entity recognition (NER) for large-scale information extraction from the published materials science literature. The NER model is trained to extract summary-level information from materials science documents, including inorganic material mentions, sample descriptors, phase labels, material properties and applications, as well as any synthesis and characterization methods used. Our classifier achieves an accuracy (f 1 ) of 87%, and is applied to information extraction from 3.27 million materials science abstracts. We extract more than 80 million materials-science-related named entities, and the content of each abstract is represented as a database entry in a structured format. We demonstrate that simple database queries can be used to answer complex "meta-questions" of the published literature that would have previously required laborious, manual literature searches to answer. Finally, all of our data and functionality has been made freely available on our Github ( https://github.com/materialsintelligence/matscholar ) and website ( http://matscholar.com ), and we expect these results to accelerate the pace of future materials science discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Data Science and Computation for Rapid and Dynamic Compression Experiment Workflows at Experimental Facilities, September 8-11, 2020. Workshop Report

The application of high pressure to materials has enabled discoveries in scientific fields such as planetary science, materials science, and materials synthesis. Recent advances in X-ray user light sources and other facilities, co-location and integration of user facilities with high-pressure drivers, availability of high-performance computing (HPC) platforms, and the development of new data science techniques have created opportunities for, and challenges in, advancing data analytics for rapid and dynamic compression experiments. To address these challenges, harness the emerging technology now available, and expedite scientific discovery, Los Alamos National Laboratory (LANL) hosted a virtual workshop entitled “Data Science and Computation for Rapid and Dynamic Compression Workflows at Experimental Facilities” from September 8 to 11, 2020. The workshop included 95 registered scientists and analytics experts from 15 universities, 9 United States (US) national laboratories, 5 US and European X-ray light sources, neutron sources such as the Los Alamos Neutron Science Center (LANSCE), other big science facilities such as the National Ignition Facility (NIF), and an industry representative. The workshop included 31 invited talks and 4 lightning talks by students and postdocs.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The 2024 “Hacking Limnology” Workshop Series and Virtual Summit: Increasing Inclusion, Participation, and Representation in the Aquatic Sciences

The 4th Aquatic Ecosystem MOdeling Network—Junior (AEMON-J) Hacking Limnology Workshop and 5th Virtual Summit: Incorporating Data Science and Open Science in the Aquatic Sciences (DSOS) convened 15–19 July 2024. During the week, these joint communities engaged in activities at the intersection of big data, open science, modeling, remote sensing, and the aquatic sciences. The weeklong event, with over 100 aquatic science practitioners and enthusiasts, followed a similar structure to previous years, comprising three days of workshops followed by two days of the virtual summit.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Adaptive Sample Preparation and Target Fabrication for High-Throughput Materials Science

High-repetition-rate brilliant and coherent light sources are significantly increasing the rate at which scientific experiments can be performed. An investment in transformative technologies to make samples of condensed matter could enable a paradigm shift for that field or open new exciting frontiers in high-energy density science (HEDS). This will especially be true for dynamic materials in extremes research or HEDS, where the repetition rate for placing samples into extreme environments is increasing and the samples or targets are irreversibly destroyed in each experiment. Research teams that are able to implement solutions to all aspects of the experimental process and enable a paradigm of high-throughput science will have the greatest success and impact. There are two different directions for adaptive samples. One is research when the number of experiments can be greatly increased with increased volume, such as in high energy density science. The other is when flexibility and agility can aid Bayesian optimization computational methods and speed up the discovery process, as with materials science. Conducting a similar equation-of-state (EOS) experiment took three years on the OMEGA laser facility, compared to five days of shifts at the LCLS XFEL. New materials with improved properties have been found by guided optimization of experimental science. Adaptive sample preparation and target fabrication can create a tremendous return on scientific investment. High-throughput enabling precision science is also a desirable goal. To address these issues, we sought a diverse set of innovative participants who had ideas of how to achieve this paradigm shift. We invited 42 researchers from a variety of disciplines and fields to attend a workshop in College Station, Texas, May 14–16, 2019. Many of the participants had never been in the same room before, and most found it very exciting to hear about new and different research. The goal was twofold: to define the challenges, i.e., “what would we like to be able to do and why it is difficult to do so,” and to describe the progress, approaches and capabilities, as well as the vision, “what we could do if we had more support.”

36 MATERIALS SCIENCE↗
DOE OSTI2025

2020 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is essential for addressing the increasingly complex national workforce demands stemming from the growth of computational science and engineering challenges. Computational science and engineering (CSE) takes a multidisciplinary approach that utilizes scientific computing to tackle practical problems and provide technical tools across the spectrum of scientific discovery. The DOE CSGF specifically highlights high-performance computing (HPC) as a critical enabling technology in CSE, driving advancements in science and engineering that are vital to both the DOE and the broader economy. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines have been transformed through the augmentation of scientific observation via HPC. At government laboratories, academic institutions, and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, quantum information systems, fusion-reactor design, machine learning, additive manufacturing, nano materials for next-generation batteries and transistors, and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing. Computational biology, machine learning, and quantum computing are among the subjects that began to swell in the ranks of CSGF applicants before the labs were hiring as high a percentage of employees in these categories.” The explosion of scientific and technological data has heightened the demand for advanced high-performance computing (HPC) to transform these data into meaningful scientific insights. As access to vast amounts of data increases, the fields of Machine Learning and Artificial Intelligence are experiencing a resurgence, enhancing the established practices of computational modeling and simulation. In its September 2020 subcommittee report on "AI/ML, Data Intensive Science, and High-Performance Computing," the DOE Advanced Scientific Computing Advisory Committee (ASCAC) specifically called for a fellowship program to train computational and data scientists to address exascale and data-intensive computing challenges. This integration of empirical and theoretical modeling will increasingly guide federal policymakers in making decisions that impact American society and future generations. It demands a workforce of highly skilled and intellectually agile computational scientists capable of navigating the rapid advancements in scientific computing within the DOE National Laboratory research environment. The DOE CSGF program has consistently addressed this critical need.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Multi-system analysis of offshore geologic carbon storage: a review of open-source data science solutions

Geologic carbon storage projects are maturing worldwide and the footprint of deployment in the offshore is expanding. At present, there are ten projects in operation or that have been completed, more than 50 in construction and development, and dozens of characterization studies completed or underway. Offshore geologic carbon storage offers potential benefits over onshore geologic carbon storage. These offshore projects are generally remote in location, distant from population centers, and avoid complicated pore space rights while having abundant prospective storage potential. Some offshore fields targeted for carbon storage have comparatively fewer prior borehole penetrations except for areas that have been explored for petroleum production, minimizing potential issues such as pressure interference and infrastructure impacts. Yet offshore geologic carbon storage projects face distinctive technical and economic challenges, such as seafloor geohazards (e.g., seabed instability), expensive maritime transport, and meteorological-oceanographic conditions that can damage infrastructure and impact operations. Analytical capabilities and improved computational speeds have advanced engineering, earth and energy sciences in the wake of the arrival of modern data science over the last decade. These advancements have created an opportunity for integrated, multi-systems modeling approaches utilizing artificial intelligence and machine learning that are no longer limited by computational issues. Analytical tools developed alongside this advancement in data science can be leveraged to calibrate the potential advantages and challenges of carbon storage operations in the offshore. New methods and approaches that incorporate data science to analyze multiple aspects of engineered and natural systems can provide insights that complement the characterization and onsite engineering that traditional commercial and operational software addresses. These new methods and approaches can potentially improve the outcome of energy operations and carbon storage. Providing multi-system, science-driven data analytics enhances the knowledge base that offshore developers, operators, and regulatory bodies may draw from to improve offshore site selection and operational efficiency. Here, we provide a brief synopsis of geologic carbon storage efforts to date, an overview of the engineered and natural systems involved in offshore geologic carbon storage, and a review of publicly available, open-source, offshore and/or carbon storage related data- and science-driven tools developed by 2010 or later that are suitable for screening and assessing regions for offshore geologic carbon storage.

artificial intelligence↗
NASA NTRS1994

(abstract) Space Science with Commercial Funding

The world-wide recession, and other factors, have led to reduced or flat budgets in real terms for space agencies around the world. Consequently space science projects and proposals have been under pressure and seemingly will continue to be pressured for some years into the future. A new concept for space science funding is underway at JPL. A partnership has been arranged with a commercial, for-profit, company that proposes to implement a (bandwidth-on-demand) information and telephone system through a network of low earth orbiting satellites (LEO). This network will consist of almost 1000 satellites operating in polar orbit at Ka-band. JPL has negotiated an agreement with this company that each satellite will also carry one or more science instruments for astrophysics, astronomy, and for earth observations. This paper discussed the details of the arrangement and the financial arrangements. It describes the technical parameters, such as the 60 GHz wideband inter-satellite links and the frequency, time, and position control, on which the science is based, and it also discusses the complementarity of this commercially funded space science with conventional space science.

observations↗
NASA NTRS2014

UAS Applications for Hurricane Science, Hurrican and Severe Storm Sentinel (HS3)

Earth Science Industry Update: UAS Applications for Hurricane Science Unmanned systems can significantly transform hurricane observations and monitoring, improving our knowledge about and ability to forecast storm formation, track, and intensity change. NASA's use of the Global Hawk has demonstrated the scientific value of this platform and provided a proof-of-concept for operational applications. However, science flight operations face several challenges and constraints. In this session, learn about how NASA adapted the Global Hawk to do science; How NASA conducts its hurricane missions, and some of the challenges and constraints they face; Science results from NASA's recent hurricane field campaigns using the Global Hawk. How assimilation of dropsonde and radar data into weather prediction models may improve forecast accuracy; Other Earth science problems that could be addressed with Global Hawks.

Hurricane Science↗
NASA NTRS2010

Coordinating Multiple Spacecraft Assets for Joint Science Campaigns

This paper describes technology to support a new paradigm of space science campaigns. These campaigns enable opportunistic science observations to be autonomously coordinated between multiple spacecraft. Coordinated spacecraft can consist of multiple orbiters, landers, rovers, or other in-situ vehicles (such as an aerobot). In this paradigm, opportunistic science detections can be cued by any of these assets where additional spacecraft are requested to take further observations characterizing the identified event or surface feature. Such coordination will enable a number of science campaigns not possible with present spacecraft technology. Examples from Mars include enabling rapid data collection from multiple craft on dynamic events such as new Mars dark slope streaks, dust-devils or trace gases. Technology to support the identification of opportunistic science events and/or the re-tasking of a spacecraft to take new measurements of the event is already in place on several individual missions such as the Mars Exploration Rover (MER) Mission and the Earth Observing One (EO1) Mission. This technology includes onboard data analysis techniques as well as capabilities for planning and scheduling. This paper describes how these techniques can be cue and coordinate multiple spacecraft in observing the same science event from their different vantage points.

automated commanding↗
NASA NTRS2015

Deriving Earth Science Data Analytics Requirements

Data Analytics applications have made successful strides in the business world where co-analyzing extremely large sets of independent variables have proven profitable. Today, most data analytics tools and techniques, sometimes applicable to Earth science, have targeted the business industry. In fact, the literature is nearly absent of discussion about Earth science data analytics. Earth science data analytics (ESDA) is the process of examining large amounts of data from a variety of sources to uncover hidden patterns, unknown correlations, and other useful information. ESDA is most often applied to data preparation, data reduction, and data analysis. Co-analysis of increasing number and volume of Earth science data has become more prevalent ushered by the plethora of Earth science data sources generated by US programs, international programs, field experiments, ground stations, and citizen scientists.Through work associated with the Earth Science Information Partners (ESIP) Federation, ESDA types have been defined in terms of data analytics end goals. Goals of which are very different than those in business, requiring different tools and techniques. A sampling of use cases have been collected and analyzed in terms of data analytics end goal types, volume, specialized processing, and other attributes. The goal of collecting these use cases is to be able to better understand and specify requirements for data analytics tools and techniques yet to be implemented. This presentation will describe the attributes and preliminary findings of ESDA use cases, as well as provide early analysis of data analytics toolstechniques requirements that would support specific ESDA type goals. Representative existing data analytics toolstechniques relevant to ESDA will also be addressed.

data analytics↗
NASA NTRS2019

Earth Science Technology Office (ESTO) New Observing Strategies (NOS) and NOS-Testbed (NOS-T)

With the advancement of space hardware technologies such as smaller spacecraft, component and instrument miniaturization and high performance space processors, and with the advancement of software technologies in artificial intelligence, big data analysis and autonomous decision making, Earth Science is looking at novel ways to observe phenomena that previously could not have been studied or would have been too expensive to study with traditional missions. In particular, the New Observing Strategies (NOS) component of the NASA Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) Program aims at leveraging these novel technologies as well as low cost and easy access to space to acquire multi-temporal or simultaneous multi-angular, multi-locations, multi-resolution and multi-spectral observations that will provide better multi-source measurements and will build a more dynamic and comprehensive picture of Earth Science phenomena that need to be studied and analyzed. For applications such as water resources management, air quality monitoring, biodiversity studies or disaster management, NOS will integrate the use of small instruments, small spacecraft, constellations of spacecraft and networks of sensors to design new missions that will provide the necessary measurements to improve future forecast and science modeling systems.Measurement acquisition will therefore be approached as a system of systems rather than on a mission basis, and a system of this complexity should not be expected to work without full integration and experimental characterization. Although most of the individual technologies enabling to link and coordinate multi-source observations are more or less mature, a few technologies need to be developed and all of them need to be integrated and tested as a system. In order for this validation to occur, the AIST Program is developing the NOS Testbed that includes 3 main goals:1.Validate novel NOS technologies, independently and as a system2.Demonstrate novel distributed operations concepts3.Socialize new Distributed Spacecraft Mission (DSM) and SensorWeb (SW) technologies and concepts to the science community by significantly retiring the risk of integrating these new technologies.The NOS Testbed will consist of multiple sensing nodes, simulated or actual, representing space, air and/or ground measurements, that are interconnected by a communications fabric (infrastructure that permits nodes to transmit and receive data between one another and interact with each other). Each node will be supported by hardware capabilities required to perform nodes monitoring and command & control, as well as intelligent "onboard" computing. The nodes will work together in a collaborative manner to demonstrate optimal science capabilities. The testbed will enable to validate technologies such as inter-node communication models, techniques and protocols; inter-node coordination; real-time data fusion and understanding; planning; sensor re-targeting; etc. Additionally, the testbed will have the capability to interact with various mission design tools, OSSEs and one or several forecast models. More details about the NOS Testbed will be presented at the confererence.

Earth Science missions; Advanced information Syste↗
NASA NTRSDate not supplied

The Integration of Life Sciences in Space: Astrobiology and Space Biology Virtual Workshops Report

A series of virtual workshops was held during June 2020 to seek ways to integrate the efforts of the astrobiology and space biology research communities under a broad umbrella of space life sciences. The overall goal was to help inspire creativity that will guide us towards new synergistic ideas complementing these existing disciplines that are of such importance to NASA. Workshop participants aspired to: (1) Exploit synergies across the biological sciences at NASA, (2) Foster research, enabling technology, and mission concepts that support commonalities in space biology, astrobiology, synthetic biology, planetary protection, and relevant human health, performance, and habitation concerns, (3) Envision the development of an “Arc of Biology in Space” to encompass this multi-faceted joint research community. The focused objective of the workshop series was to explore and demonstrate how the integration of astrobiology and space biology could be achieved, identify strengths and weaknesses in the current state of the art, and recognize where our greatest challenges lay. Specifically, we seek to: (1) Establish a scientific framework for an integrated life sciences effort, (2) Pioneer discovery by creating unique opportunities in the fundamental biological sciences, (3) Explore novel combinations of existing technologies across the relevant disciplines, (4) Invent new technologies and applications in space life sciences, and (5) Creatively increase access to spaceflight, emerging and novel technologies, Earth analogs, and simulated natural and spaceflight environments. The community aims for a broad arc of biological competence in the context of space and planetary science, spaceflight, and habitation. We will present dominant themes and innovative ideas that resulted from this interchange of relevant communities.

astrobiology↗
NASA NTRSDate not supplied

Feasibility Study of a Robotic Science Arm on Future Martian Rotorcraft

Science arms are indispensable tools for planetary exploration, allowing vehicles to interact with and manipulate their surroundings in a manner similar to a human field geologist. A majority of the rovers and landers sent to Mars, beginning with Viking I and II in 1976, have made extensive use of these articulated, arm-like devices that allow for sample collection, surface preparation, instrument positioning, and the deployment of ground-contact sensors. Although proven useful, traditional rovers and landers are limited by the rough and difficult terrain of Mars. However, given the successful demonstration of flight on Mars by the Ingenuity helicopter, efforts are underway to outfit larger rotorcraft with science payloads to allow them to explore Mars’ surface and lower atmosphere with significantly more efficiency than land vehicles. Such vehicles could also be designed to work in tandem with landers or rovers. The Mars Science Helicopter (MSH) is a conceptual hexacopter design that is currently under early development by both NASA Ames and JPL. Equipping a vehicle like MSH with a science arm has the potential to further expand its scientific capabilities. This paper approaches the mission and design requirements to equip a science arm on MSH while highlighting the unique technical challenges for robotic arm and science instrument capability. Current plans for MSH development do not include the addition of a robotic arm to the vehicle. However, it is anticipated that future variants of the MSH design might well incorporate such adaptable surface interactive capabilities.

Robotic Science Arm↗
NASA NTRSDate not supplied

NASA Life Sciences Portal (NLSP): Supporting Scientific Transparency and Reproducibility

NASA’s Life Sciences Ports (NLSP) serves the scientific community by providing curated data from space life science experiment. The Human Research Program (HRP) with the help of NLSP is currently transforming their life sciences data archive systems and processes to improve compliance with the FAIR principles [1]. Some of these improvements will at the same time support the twin pillars of Open Science [2]: transparency of methods and reproducibility of results. Scientific transparency is marked by the easily intelligible communication of what has been investigated: what were the procedures for collecting sample and the characteristics of samples collected? what kinds of measurements were made, what were the environmental conditions of the measurements? What were the analysis techniques of the collected data? Reproducibility of the results and findings from the investigation requires a high level of transparency for all but the simplest investigations; the slightest deviation in communicating and replicating complex experimental procedures or data analyses can often yield quite different data and even findings, thwarting their validation. One of the ways the NLSP is aiming to improve the communication of scientific information is through the use of ontology-driven metadata. Ontologies are powerful, graph-based knowledge representation structures, which can be leveraged to increase data interoperability, the area of the FAIR principles in which many data systems most lack compliance. Over the past decade, there has been a concerted effort in the biomedical community to develop modular and narrowly focused domain and application-specific ontologies in a common, open-source framework, the Open Biological and Biomedical Ontology (OBO) Foundry [3]. The open sharing and modular nature of this effort promises huge increases in harmonized data sharing for systems that leverage these models. Which is in line with the FAIR Data Principles of Findability, Accessibility, Interoperability, and Reuse for scientific data management and stewardship. 1. Wilkinson, M.D., et al., The FAIR Guiding Principles for scientific data management and stewardship. Sci Data, 2016. 3: p. 160018. 2. National Academies of Sciences, E. and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. 2018, Washington, DC: The National Academies Press. 232. 3. Smith, B., et al., The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol, 2007. 25(11): p. 1251-5.

Life Sciences data↗
NASA NTRSDate not supplied

NASA’s Student Airborne Science Activation for Minority Serving Institutions: Inaugural Program, Educational Outcomes, and Lessons Learned

The NASA Student Airborne Science Activation (SaSa) for Minority Serving Institutions (MSIs) held its inaugural summer research program for early career undergraduates interested in the Geosciences. SaSa is a NASA Science Activation funded 8-week summer internship program. Twenty-four first- and second-year undergraduates from MSIs across the U.S. participated in the summer program - June 6 to July 29, 2022. Students had the opportunity to gain hands-on research experience in all components of an airborne science campaign including flying on-board a NASA research aircraft to collect atmospheric measurements. Students conducted independent research projects related to the atmosphere, ocean, and geosciences that feed into NASA’s broader Earth Science Division’s and Decadal Survey goals using air quality, meteorological, and oceanic measurements from surface, airborne, and satellite-based observations. The program split its time between partner institution, University of Maryland Baltimore County and NASA’s Wallops Flight Facility in Wallops Island, Virginia. Students also made site visits at partner institutions, including: Hampton University, University of Maryland Eastern Shore, Morgan State University, Howard University, and Coppin State University and attended lectures from visiting faculty and NASA Subject Matter Experts. Students were guided on their research projects by near-peer graduate mentors, SaSa program leadership, co-Is at partner institutions, and NASA scientists to address two major research themes: 1) how human-caused air pollution has human and environmental implications, and 2) how large-scale meteorological factors influence local weather conditions. Students sorted into research groups, based on sub-discipline areas in the Geosciences, including: “Clouds, Aerosols and Radiation”, “Meteorology and Planetary Boundary Layer”, “Air Quality: Particle Pollution and Trace Gases”, and “Air-Water-Land Interface”. Their research was presented as 3-minute lightning talks and in-person poster presentations at a close-out event at NASA Goddard Space Flight Center in Greenbelt, Maryland. The students’ inter- and trans-disciplinary research experiences centered in the use of multiple ground, airborne, and satellite remote sensing NASA Earth Science Division assets. Providing a unique experience aligned to recognize the societal benefits that NASA contributes in the areas of resource management, air quality monitoring and policy decisions, energy and weather predictions, and research on the Earth’s climate. The SaSa program aims to increase the number of students from MSIs that identify as underrepresented or underserved individuals in the Geosciences discipline, Earth System Science graduate programs, and the NASA workforce. A summary of the summer research program, educational, scientific, and programmatic outcomes, as well as lessons learned will be presented.

NASA↗