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NASA NTRS1991

A model for diurnal patterns of carbon fixation in a Precambrian microbial mat based on a modern analog

Microbial mat communities are one of the first and most prevalent biological communities known from the Precambrian fossil record. These fossil mat communities are found as laminated sedimentary rock structures called stromatolites. Using a modern microbial mat as an analog for Precambrian stromatolites, a study of carbon fixation during a diurnal cycle under ambient conditions was undertaken. The rate of carbon fixation depends primarily on the availability of light (consistent with photosynthetic carbon fixation) and inorganic carbon, and not nitrogen or phosphorus. Atmospheric PCO2 is thought to have decreased from 10 bars at 4 Ga (10(9) years before present) to approximately 10(-4) bars today, implying a change in the availability of inorganic carbon for carbon fixation. Experimental manipulation of levels of inorganic carbon to levels that may have been available to Precambrian mat communities resulted in increased levels of carbon fixation during daylight hours. Combining these data with models of daylength during the Precambrian, models are derived for diurnal patterns of photosynthetic carbon fixation in a Precambrian microbial mat community. The models suggest that, even in the face of shorter daylengths during the Precambrian, total daily carbon fixation has been declining over geological time, with most of the decrease having occurred during the Precambrian.

Review↗

NASA NTRS2006

Orbiter Return-To-Flight Entry Aeroheating

The Columbia accident on February 1, 2003 began an unprecedented level of effort within the hypersonic aerothermodynamic community to support the Space Shuttle Program. During the approximately six month time frame of the primary Columbia Accident Investigation Board activity, many technical disciplines were involved in a concerted effort to reconstruct the last moments of the Columbia and her crew, and understand the critical events that led to that loss. Significant contributions to the CAIB activity were made by the hypersonic aerothermodynamic community(REF CAIB) in understanding the re-entry environments that led to the propagation of an ascent foam induced wing leading edge damage to a subsequent breech of the wing spar of Columbia, and the subsequent breakup of the vehicle. A core of the NASA hypersonic aerothermodynamics team that was involved in the CAIB investigation has been combined with the United Space Alliance and Boeing Orbiter engineering team in order to position the Space Shuttle Program with a process to perform in-flight Thermal Protection System damage assessments. This damage assessment process is now part of the baselined plan for Shuttle support, and is a direct out-growth of the Columbia accident and NASAs response. Multiple re-entry aeroheating tools are involved in this damage assessment process, many of which have been developed during the Return To Flight activity. In addition, because these aeroheating tools are part of an overall damage assessment process that also involves the thermal and stress analyses community, in addition to a much broader mission support team, an integrated process for performing the damage assessment activities has been developed by the Space Shuttle Program and the Orbiter engineering community. Several subsets of activity in the Orbiter aeroheating communities support to the Return To Flight effort have been described in previous publications (CFD?, Cavity Heating? Any BLT? Grid Generation?). This work will provide a description of the integrated process utilized to perform Orbiter tile damage assessment, and in particular will seek to provide a description of the integrated aeroheating tools utilized to perform these assessments. Individual aeroheating tools will be described which provide the nominal re-entry heating environment characterization for the Orbiter, the heating environments for tile damage, heating effects due to exposed Thermal Protection System substrates, the application of Computational Fluid Dynamics for the description of tile cavity heating, and boundary layer transition prediction. This paper is meant to provide an overall view of the integrated aeroheating assessment process for tile damage assessment as one of a sequence of papers on the development of the boundary layer transition prediction capability in support of Space Shuttle Return To Flight efforts.

Campbell, Charles H.↗

NASA NTRS2002

Science opportunity analyzer - a multi-mission tool for planning

For many years the diverse scientific community that supports JPL's wide variety ofinterplanetary space missions has needed a tool in order to plan and develop their experiments. The tool needs to be easily adapted to various mission types and portable to the user community. The Science Opportunity Analyzer, SOA, now in its third year of development, is intended to meet this need. SOA is a java-based application that is designed to enable scientists to identify and analyze opportunities for science observations from spacecraft. It differs from other planning tools in that it does not require an in-depth knowledge of the spacecraft command system or operation modes to begin high level planning. Users can, however, develop increasingly detailed levels of design. SOA consists of six major functions: Opportunity Search, Visualization, Observation Design, Constraint Checking, Data Output and Communications. Opportunity Search is a GUI driven interface to existing search engines that can be used to identify times when a spacecraft is in a specific geometrical relationship with other bodies in the solar system. This function can be used for advanced mission planning as well as for making last minute adjustments to mission sequences in response to trajectory modifications. Visualization is a key aspect of SOA. The user can view observation opportunities in either a 3D representation or as a 2D map projection. The user is given extensive flexibility to customize what is displayed in the view. Observation Design allows the user to orient the spacecraft and visualize the projection of the instrument field of view for that orientation using the same views as Opportunity Search. Constraint Checking is provided to validate various geometrical and physical aspects of an observation design. The user has the ability to easily create custom rules or to use official project-generated flight rules. This capability may also allow scientists to easily impact the cost to science if flight rule changes occur. Data Output generates information based on the spacecraft's trajectory, opportunity search results or based on a created observation. The data can be viewed either in tabular format or as a graph. Finally, SOA is unique in that it is designed to be able to communicate with a variety of existing planning and sequencing tools. From the very beginning SOA was designed with the user in mind. Extensive surveys of the potential user community were conducted in order to develop the software requirements. Throughout the development period, close ties have been maintained with the science community to insure that the tool maintains its user focus. Although development is still in its early stages, SOA is already developing a user community on the Cassini project, which is depending on this tool for their science planning. There are other tools at JPL that do various pieces of what SOA can do; however, there is no other tool which combines all these functions and presents them to the user in such a convenient, cohesive, and easy to use fashion.

SOA science planning mission operations sequence s↗

NASA NTRS2006

Promoting Lifelong Ocean Education: Shaping Tomorrow's Earth Stewards and the Science and Technology Workforce

The coming ocean observing systems provide an unprecedented opportunity to change both the public perception of our oceans, and to inspire, captivate and motivate our children, our young adults and even our fellow adults to pursue careers allied with the oceans and to become stewards of our Planet's last unexplored environment. Education plans for the operational component, the Integrated Ocean Observing System (IOOS), and for the research component, Ocean Research Interactive Observatory Networks (ORION), are designed to take advantage of this opportunity. In both cases, community recommendations were developed within the context of the following assumptions: 1. Utilize research on how people learn, especially the four-pronged model of simultaneous learner-centered, knowledge-center, assessment-centered and community-centered learning 2. Strive for maximum impact on national needs in science and technology learning 3. Build on the best of what is already in place 4. Pay special attention to quality, sustainability, and scalability of efforts 5. Use partnerships across federal, state and local government, academia, and industry. Community recommendations for 100s and ORION education have much in common and offer the opportunity to create a coherent education effort allied with ocean observing systems. Both efforts focus on developing the science and technology workforce of the future, and the science and technology literacy of the public within the context of the Earth system and the role of the oceans and Great Lakes in that system. Both also recognize that an organized education infrastructure that supports sustainability and scalability of education efforts is required if ocean observing education efforts are to achieve a small but measurable improvement in either of these areas. Efforts have begun to develop the education infrastructure by beginning to form a community of educators from existing ocean and aquatic education networks and by exploring needs and issues associated with using ocean observing information assets in education. Likewise efforts are underway to address workforce issues by a systematic analysis of current and future workforce and educational needs. These activities will be described as will upcoming opportunities for the community to participate in these efforts.

Meeson, Blanche↗

NASA NTRS2007

Unofficial Road Building in the Brazilian Amazon: Dilemmas and Models for Road Governance

Unofficial roads form dense networks in landscapes, generating a litany of negative ecological outcomes, but unofficial roads in frontier areas are also instrumental in local livelihoods and community development. This trade-off poses dilemmas for the governance of unofficial roads. Unofficial road building in frontier areas of the Brazilian Amazon illustrates the challenges of 'road governance.' Both state-based and community based governance models exhibit important liabilities for governing unofficial roads. Whereas state-based governance has experienced difficulties in adapting to specific local contexts and interacting effectively with local interest groups, community-based governance has a mixed record owing to social inequalities and conflicts among local interest groups. A state-community hybrid model may offer more effective governance of unofficial road building by combining the oversight capacity of the state with locally grounded community management via participatory decision-making.

Perz, Stephen G.↗

NASA NTRS2009

Common Infrastructure for Neo Scientific and Planetary Defense Missions

While defending the Earth against collisions with asteroids and comets has garnered increasing attention over the past few decades, our knowledge of the threats and methods of mitigation remain inadequate. There exists a considerable gap in knowledge regarding the size, composition, location, internal structure and formation of near earth asteroids and comets. Although estimates have been made, critical experiments have not yet been conducted on the effectiveness of various proposed mitigation techniques. Closing this knowledge gap is of interest to both the planetary defense and planetary science communities. Increased scientific knowledge of asteroid and comet composition and structure can confirm or advance current theories about the formation of the solar system. This proposal suggests a joint effort between these two communities to provide an economical architecture that supports multiple launches of characterization and mitigation payloads with minimal response time. The science community can use this architecture for characterization missions of opportunity when multiple scientific targets or targets of uncommon scientific value present themselves, while the planetary defense community would be able to fire characterization or mitigation payloads at targets that present a threat to the Earth. Both communities would benefit from testing potential mitigation techniques, which would reveal information on the internal structure of asteroids and comets. In return, the Earth would have the beginnings of a viable response system should an impact threat prove real in the near future.

Adams, Robert↗

NASA NTRS2009

NASA's Earth Observing Data and Information System

NASA's Earth Observing System Data and Information System (EOSDIS) has been a central component of NASA Earth observation program for over 10 years. It is one of the largest civilian science information system in the US, performing ingest, archive and distribution of over 3 terabytes of data per day much of which is from NASA s flagship missions Terra, Aqua and Aura. The system supports a variety of science disciplines including polar processes, land cover change, radiation budget, and most especially global climate change. The EOSDIS data centers, collocated with centers of science discipline expertise, archive and distribute standard data products produced by science investigator-led processing systems. Key to the success of EOSDIS is the concept of core versus community requirements. EOSDIS supports a core set of services to meet specific NASA needs and relies on community-developed services to meet specific user needs. EOSDIS offers a metadata registry, ECHO (Earth Observing System Clearinghouse), through which the scientific community can easily discover and exchange NASA s Earth science data and services. Users can search, manage, and access the contents of ECHO s registries (data and services) through user-developed and community-tailored interfaces or clients. The ECHO framework has become the primary access point for cross-Data Center search-and-order of EOSDIS and other Earth Science data holdings archived at the EOSDIS data centers. ECHO s Warehouse Inventory Search Tool (WIST) is the primary web-based client for discovering and ordering cross-discipline data from the EOSDIS data centers. The architecture of the EOSDIS provides a platform for the publication, discovery, understanding and access to NASA s Earth Observation resources and allows for easy integration of new datasets. The EOSDIS also has developed several methods for incorporating socioeconomic data into its data collection. Over the years, we have developed several methods for determining needs of the user community including use of the American Customer Satisfaction Index and a broad metrics program.

Mitchell, Andrew E.↗

NASA NTRS2013

Space Station Integrated Kinetic Launcher for Orbital Payload Systems (SSIKLOPS) - Cyclops

Access to space for satellites in the 50-100 kg class is a challenge for the small satellite community. Rideshare opportunities are limited and costly, and the small sat must adhere to the primary payloads schedule and launch needs. Launching as an auxiliary payload on an Expendable Launch Vehicle presents many technical, environmental, and logistical challenges to the small satellite community. To assist the community in mitigating these challenges and in order to provide the community with greater access to space for 50-100 kg satellites, the NASA International Space Station (ISS) and Engineering communities in collaboration with the Department of Defense (DOD) Space Test Program (STP) is developing a dedicated 50-100 kg class ISS small satellite deployment system. The system, known as Cyclops, will utilize NASA's ISS resupply vehicles to launch small sats to the ISS in a controlled pressurized environment in soft stow bags. The satellites will then be processed through the ISS pressurized environment by the astronaut crew allowing satellite system diagnostics prior to orbit insertion. Orbit insertion is achieved through use of the Japan Aerospace Exploration Agency's Experiment Module Robotic Airlock (JEM Airlock) and one of the ISS Robotic Arms. Cyclops' initial satellite deployment demonstration of DOD STP's SpinSat and UT/TAMU's Lonestar satellites will be toward the end of 2013 or beginning of 2014. Cyclops will be housed on-board the ISS and used throughout its lifetime. The anatomy of Cyclops, its concept of operations for satellite deployment, and its satellite interfaces and requirements will be addressed further in this paper.

Smith, James P.↗

NASA NTRS2017

Cultivating a Grassroots Aerospace Innovation Culture at NASA Ames Research Center

This paper details the adaptation of specific 'knowledge production' methods to implement a first of its kind, grassroots event that provokes a cultural change in how the NASA Ames civil servant community engages in the creation and selection of innovative ideas. Historically, selection of innovative proposals at NASA Ames Research Center is done at the highest levels of management, isolating the views and perspectives of the larger civil servant community. Additionally, NASA innovation programs are typically open to technical organizations and do not engage non-technical organizations to bring forward innovative processes/business practices. Finally, collaboration on innovative ideas and associated solutions tend to be isolated to organizational silos. In this environment, not all Ames employees feel empowered to innovate and opportunities for employee collaboration are limited. In order to address these issues, the 'innovation contest' method was adapted to create the NASA Ames Innovation Fair, a unique, grassroots innovation opportunity for the civil servant community. The Innovation Fair consisted of a physical event with a virtual component. The physical event provided innovators the opportunity to collaborate and pitch their innovations to the NASA Ames community. The civil servant community then voted for the projects that they viewed as innovative and would contribute to NASA's core mission, making this event a truly grassroots effort. The Innovation Fair website provided a location for additional knowledge sharing, discussion, and voting. On March 3rd, 2016, the 'First Annual NASA Ames Innovation Fair' was held with 49 innovators and more than 300 participants collaborating and/or voting for the best innovations. Based on the voting results, seven projects were awarded seed funding for projects ranging from innovative cost models to innovations in aerospace technology. Surveys of both innovators and Fair participants show the Innovation Fair was successful in fostering cross-organizational collaborations, soliciting participation of non-technical innovations, and increasing employee engagement in influencing the future of NASA Ames Research Center. The grassroots component of the Innovation Fair has been bench marked by the agency as a solid foundation for increasing employee engagement in the development of game changing aerospace technology and processes in support of NASA's mission.

Innovation↗

NASA NTRS2017

A New Architecture for Visualization: Open Mission Control Technologies

Open Mission Control Technologies (MCT) is a new architecture for visualisation of mission data. Driven by requirements for new mission capabilities, including distributed mission operations, access to data anywhere, customization by users, synthesis of multiple data sources, and flexibility for multi-mission adaptation, Open MCT provides users with an integrated customizable environment. Developed at NASAs Ames Research Center (ARC), in collaboration with NASAs Advanced Multimission Operations System (AMMOS) and NASAs Jet Propulsion Laboratory (JPL), Open MCT is getting its first mission use on the Jason 3 Mission, and is also available in the testbed for the Mars 2020 Rover and for development use for NASAs Resource Prospector Lunar Rover. The open source nature of the project provides for use outside of space missions, including open source contributions from a community of users. The defining features of Open MCT for mission users are data integration, end user composition and multiple views. Data integration provides access to mission data across domains in one place, making data such as activities, timelines, telemetry, imagery, event timers and procedures available in one place, without application switching. End user composition provides users with layouts, which act as a canvas to assemble visualisations. Multiple views provide the capability to view the same data in different ways, with live switching of data views in place. Open MCT is browser based, and works on the desktop as well as tablets and phones, providing access to data anywhere. An early use case for mobile data access took place on the Resource Prospector (RP) Mission Distributed Operations Test, in which rover engineers in the field were able to view telemetry on their phones. We envision this capability providing decision support to on console operators from off duty personnel. The plug-in architecture also allows for adaptation for different mission capabilities. Different data types and capabilities may be added or removed using plugins. An API provides a means to write new capabilities and to create data adaptors. Data plugins exist for mission data sources for NASA missions. Adaptors have been written by international and commercial users. Open MCT is open source. Open source enables collaborative development across organizations and also makes the product available outside of the space community, providing a potential source of usage and ideas to drive product design and development. The combination of open source with an Apache 2 license, and distribution on GitHub, has enabled an active community of users and contributors. The spectrum of users for Open MCT is, to our knowledge, unprecedented for mission software. In addition to our NASA users, we have, through open source, had users and inquires on projects ranging from Internet of Things, to radio hobbyists, to farming projects. We have an active community of contributors, enabling a flow of ideas inside and outside of the space community.

Trimble, Jay↗

NASA NTRS2017

Exposing the Strategies that Can Reduce the Obstacles: Improving the Science User Experience

It is now well established that pursuing generic solutions to what seem are common problems in Earth science data access and use can often lead to disappointing results for both system developers and the intended users. This presentation focuses on real-world experience of managing a large and complex data system, NASAs Earth Science Data and Information Science System (EOSDIS), whose mission is to serve both broad user communities and those in smaller niche applications of Earth science data and services. In the talk, we focus on our experiences with known data user obstacles characterizing EOSDIS approaches, including various technological techniques, for engaging and bolstering, where possible, user experiences with EOSDIS. For improving how existing and prospective users discover and access NASA data from EOSDIS we introduce our cross-archive tool: Earthdata Search. This new search and order tool further empowers users to quickly access data sets using clever and intuitive features. The Worldview data visualization tool is also discussed highlighting how many users are now performing extensive data exploration without necessarily downloading data. Also, we explore our EOSDIS data discovery and access webinars, data recipes and short tutorials, targeted technical and data publications, user profiles and social media as additional tools and methods used for improving our outreach and communications to a diverse user community. These efforts have paid substantial dividends for our user communities by allowing us to target discipline specific community needs. The desired take-away from this presentation will be an improved understanding of how EOSDIS has approached, and in several instances achieved, removing or lowering the barriers to data access and use. As we look ahead to more complex Earth science missions, EOSDIS will continue to focus on our user communities, both broad and specialized, so that our overall data system can continue to serve the needs of science and applications users.

communications↗

NASA NTRS2014

Cultivating an Emergent Earth Observation Analytics Ecosystem in the Cloud

A diverse set of data analytics systems for Earth Observations are sprouting up in the Earth Science community, with a wealth of processing algorithms and analysis methods. There is a similar wealth of data resources available via myriad data providers and clearinghouses, including large institutional systems like the Earth Observing System Data and Information System, Comprehensive Large Scale Array-data Stewardship System, and Federated Earth Observation Missions gateway. With Earth system science driving a need to work with more datasets together, and the community developing more analysis tools (some of them dataset-specific), how can we develop analysis workflows that incorporate far-flung datasets and leverage analysis resources from multiple organizations? Cloud computing points the way toward a solution in two different respects. Firstly, the access to and abstraction of virtually unlimited storage and computing power provides an environment that enables more straightforward means of pulling datasets and analysis resources together. Just as importantly, however, cloud computing serves as an example of an "ecosystem" of interoperating services, since the essence of cloud computing is the presentation of all resources as a service, from hardware to infrastructure to platform to software. This enables the combination of off-the-shelf, diverse services to construct entire systems that emerge out of an equally diverse community of architects and developers. This approach can be similarly applied to the data and analysis resources in the Earth Observation community. By exposing these resources via well understood services, and consuming resources in the same way, different organizations can construct bespoke analysis workflows and systems for their own purposes. The key leap the community needs to make is to develop analysis systems in components that interact with other components via services. The result would be a rich ecosystem of analytics components that can be combined to analyze datasets at scale and in conjunction with other datasets from other sources.

chaos↗

NASA NTRSDate not supplied

Urban Air Mobility Noise: Current Practice, Gaps, and Recommendations

AN Air Mobility (UAM) is an opportunity for aviation to improve transportation systems across the world. Representative UAM vehicle attributes include electrical vertical takeoff and landing (eVTOL) vehicles that can accommodate up to 6 passengers (or equivalent cargo), are possibly autonomous, perform missions of up to 100 nautical miles at altitudes up to 3000 ft. above ground level, have flight speeds up to 200 knots, and weigh between 800 and 8000 pounds. Along with the many anticipated benefits, there will be noise issues that need to be addressed. In 2018, NASA formed an Urban Air Mobility Noise Working Group (UNWG) to assemble noise experts from industry, universities and government agencies to identify, discuss, and address UAM noise issues. This oral presentation summarizes technology gaps and goals associated with four areas of interest: Tools & Technologies, Ground & Flight Testing, Human Response & Metrics, and Regulation & Policy, and is drawn from a draft white paper [1] by the same title. Tools & Technologies include noise prediction tools and noise reduction technologies that have been developed for conventional rotorcraft and fixed-wing vehicles that may be applicable or need to be modified for UAM. Prediction tools need to be able to account for variable speed rotors and other temporal variation effects that impact community noise. A reprioritization of noise sources needs to be done since UAM vehicles include multiple rotors/propellers, often in proximity to one another and/or the airframe, with dynamic transition, and new noise sources such as electric motors or hybrid-electric propulsion. Scattering and propagation methods need to be developed that include the vehicle components and surfaces near a receiver such as buildings and vertiports. Validation databases are needed to quantify prediction uncertainties. Prediction tools used to evaluate community noise will need source models appropriate for a wide range of UAM vehicles. Existing noise reduction technologies need to be evaluated and new noise reduction technologies should be developed in anticipation of future noise requirements. Although the prediction and treatment of interior cabin noise is a secondary goal, it is recognized that new tools and methods may be needed due to the uniqueness of the vehicle design and the presence of both acoustic and structure-borne loads. Ground & Flight Testing has been a critical part of validating noise reduction technologies and verifying that an air vehicle is ready for certification. UAM vehicles introduce new challenges for test procedures such as different source noise directivity, unsteady sources due to maneuvers, and a variety of takeoff and approach trajectories. The operating environment will be more complex than current aircraft with the introduction of vertiports in populated areas with “urban canyons” making reflections an important part of noise prediction and annoyance. It is expected that new test procedures and measurement methods will be necessary. Consideration will need to be given for both piloted and autonomous operations. Human Response & Metrics may be very different for UAM noise compared to current experience with airport noise. Current metrics used to certify rotorcraft and fixed-wing aircraft may not be as useful for evaluating UAM noise. Operations at lower altitudes may influence annoyance. Psychoacoustic and community testing will be needed to quantify annoyance and assess appropriate metrics. In addition to conventional noise level metrics, considerations such as audibility and temporal variation of the sound may be required. Differences between indoor or outdoor exposure will have an impact with dependence on urban and residential flight paths. Aircraft noise is currently regulated at a national level and typically involves partnerships with the industry to establish regulations. Regulators realize that current policies and procedures may not be appropriate for some of the emerging air vehicles and new procedures may be needed to address UAM noise. Development of new policies and procedures are needed so that local communities do not hastily attempt to establish their own restrictions that will both limit growth of the market and create an inconsistent and confusing regulatory environment. To expedite this development, it is crucial early measurement data are shared through partnership arrangements to support both noise certification and noise modeling/noise assessment. At the same time, an effective engagement strategy should be developed to address local community noise issues associated with UAM vehicles and flight operations as they arise.

urban air mobility↗

NASA NTRSDate not supplied

Phenomena Portal: Large- Scale Visual Exploration of Atmospheric Phenomena

The Earth science community is experiencing a high influx of remote sensing data due to recent advancements in sensor technology. This enables the community to extend their research on a larger scale than ever before. Unfortunately, traditional data processing techniques do not scale well to these new, high volume data sources. State-of-the-art machine learning (ML) pipelines have been proven to overcome these burdens in various other fields but are underexploited within the physical sciences community. Moreover, ML is reliant on labeled data, which is currently sparsely available, owing to the fact that ML adoption is still in the early stages within the Earth and atmospheric science communities. To address these issues, we developed the Phenomena Portal, a visual exploration tool that uses ML to detect various atmospheric phenomena on a global scale. This allows the Earth and atmospheric science communities to view trends of occurrences of phenomena, identify potential relationships between them, and analyze spatiotemporal patterns over time. These detections can also serve as initial labeled data for ML research pertaining to the respective phenomena. The tool also incorporates feedback from subject matter experts to further improve the model detection accuracy, thereby facilitating human-in-the-loop. This presentation will provide an overview of the ML model development and cloud deployment. We also discuss the capabilities of the user interface for displaying the detections.

Muthukumaran Ramasubramanian↗

NASA NTRSDate not supplied

Developing a Vision for Heliophysics Infrastructure: The LIKED Resource and the DIARieS Ecosystem

Heliophysics data and computational infrastracture are not equipped for 21st science, suffering from holes in the know-how to build better systems. Without a clear vision, efforts to improve the infrastructure have been incremental and incoherent. This poster presents both the vision and the technology required: an online LIbrary KnowledgE and Discovery (LIKED) resource for discovering and implementing knowledge, data, and infrastructure resources; and an online analysis ecosystem to simplify Discovery, Implementation, Analysis, Reproducibility, and Sharing (DIARieS) of scientific results and environments. The LIKED and DIARieS solutions adopt FAIR data principles and the best practices from the budding field of open science. The proposed new infrastructure components will close many of the current gaps in heliophysics’ infrastructure, such as the ability to search for data and knowledge by phenomenon across domains, and to find software and examples relevant to the desired data set (including model data). Further, these components will enable community members to more efficiently use the resources already present and improve upon the content via a community-curated and trusted library. Combining these solutions lowers the barriers to heliophysics resources for all, increasing the return on our investments. Finally, the structure behind these ideas are topic-agnostic, so they are fully extensible to other fields, leading to invaluable connections to other disciplines. Just as with the development and construction of a long-term satellite mission, we must work together as a community to build a vision of the infrastructure that will most benefit the community, and then collaborate to construct, assemble, and test all the necessary pieces individually and as a unit. Our purpose in presenting this work is to not only describe the proposed vision, but also to gather feedback from the community on this topic.

infrastructure↗

NASA NTRSDate not supplied

Models, In situ, and Remote Sensing of Aerosols (MIRA)

There is a natural partitioning of scientific interest amongst three specialties of aerosol re-search: modeling, in situ measurements, and remote sensing. The broader aerosol community benefits when these groups interact, and this strengthens overall scientific impact on climate and air quality research and predictions. The new MIRA working group establishes a forum for identifying collaborations and improving discussions amongst specialties and across regional boundaries. One area of keen interest is uniting satellite and ground-based lidar groups with other aerosol disciplines. Elastic backscatter lidars depend upon a priori knowledge of aerosol properties to convert measured lidar profiles into aerosol extinction profiles. Acquiring additional insight on aerosol properties and transport is highly valuable to these lidar groups to improve the data quality and aid in their scientific interpretation. Another area of interest is to facilitate the incorporation of measurements into global aerosol models. Modelers need aerosol optical look-up tables that enable quick conversions of hydrated (and dry) polydisperse size distributions into aerosol optical properties (extinction, scattering, etc.), but many of the existing tables are based upon outdated measurements. Thus, MIRA is building the Tables of Aerosol Optics (TAO), which is a community collection of aerosol optical calculations. This expands on the historical efforts of Shettle and Fenn, d’Almeida, GADS, OPAC, etc., except that TAO seeks continual input from the community. Thus, as aerosol measurement and computational techniques advance, so does the TAO collective. Since TAO is a community collective, it is expected that users will optionally upload computations for aerosol type as well as computations for all of the traditional aerosol species(like amm sulfate, amm nitrate, organics, etc.). The near-term purpose of the MIRA working group is to: *Characterize regional aerosol lidar ratios to support improvements of aerosol extinction profiles and understanding of aerosol typing. *Create TAO --a community cooperative of aerosol optical tables. *Facilitate international communications between aerosol measurement and modeling groups. *Encourage the use of regional knowledge to develop and improve remote sensing techniques for current and future backscatter lidars located in space. *Enable and foster communication between the scientists who run global aerosol models and scientists who analyze space-based lidar data. We will discuss how a collaborative aerosol working group will be organized on this topic. Those who are interested in MIRA can sign up for the MIRA email listserver at https://forms.gle/qdbCnngzNJc5YJi57.

Greg Schuster↗

NASA NTRSDate not supplied

Analytical Needs in a Sample Receiving Facility: Input from the MSR Operation Definition Team

The return of scientifically selected samples from Mars would provide a rare opportunity forinvestigation with the full range of the latest technology available, but to take full advantageof this opportunity, it is important to plan ahead to ensure the pristine nature of the samplesupon arrival within the Earth environment until scientific investigations can begin.The NASA/ESA science community-driven MSR Science Planning Group – Phase 2 (MSPG2)delivered recommendations and guidance regarding curation (1) and science (2, 3) activities tobe performed on the samples under containment. High-level requirements for the infrastruc-ture were also developed by MSPG2 (4). In order to prepare infrastructure-targeted input forthe ESA and NASA facility studies planned in the 2022-2023 timeframe, the agency-led MSROperational Scenarios Definition Team (MOSDT) was assembled to conceptualize the sampleoperations that will inform future architecture teams. Emphasis was placed on the respon-sibility of MOSDT to use community-defined requirements and to represent the view of the international scientific community.All necessary and sufficient instruments and analytical needs described in MSPG2 were inte-grated in MOSDT main deliverable, the operational workflow (see Hays et al, this conference).In MSPG2, notional instruments were split between curation analytical needs, and objective-driven (time-sensitive and sterilization-sensitive) science analytical needs. In MOSDT, whilethe first phases of curation, “pre-Basic Characterization” and “Basic Characterization” wererather streamlined and separate from other analytical needs, “Preliminary Examination” and“Science” instruments were not always physically segregated. In addition to the necessary andsufficient instruments described by MSPG2, the MOSDT recommended additional supportequipment for sterilization, cleanliness and contamination monitoring.It was sometimes necessary for the MOSDT to rely on assumptions to integrate instruments inthe activity workflow. In general, the assumptions were very conservative to limit contaminationand cross-contamination risks. It is expected that future work to refine limits of contaminationwill enable optimization of instrumentation.The community was consulted during the course of the MOSDT work. This abstract’s aimis two-fold: on one hand, inform the scientific community and overall MSR stakeholders, tobring their attention on the analytical needs currently considered as necessary and sufficient;on the other hand, to solicit feedback from a larger community audience to optimize and refineanalytical needs during the next phases of MSR ground-segment preparation.Disclaimer: The decision to implement Mars Sample Return will not be finalized until NASA’scompletion of the program’s National Environmental Policy Act (NEPA) process. This docu-ment is being made available for informational purposes only.[1] Tait et al. (2021) Preliminary planning for Mars Sample Return (MSR) curation activities ina Sample Receiving Facility (SRF). Astrobiology in press, doi:10.1089/ast.2021.0105. [2] Toscaet al. (2021) Time-sensitive aspects of Mars Sample Return (MSR) science. Astrobiologyin press, doi:10.1089/ast.2021.0115. [3] Velbel et al. (2021) Planning implications relatedto sterilization-sensitive science investigations associated with Mars Sample Return (MSR).Astrobiology in press, doi:10.1089/ast.2021.0113. [4] Carrier et al. (2021) Science and curationconsiderations for the design of a Mars Sample Return (MSR) Sample Receiving Facility (SRF).Astrobiology in press, doi:10.1089/ast.2021.0110.

Mars Sample Return↗

NASA NTRSDate not supplied

Constructing a Knowledge Graph & Applying Graph Algorithms to Draw Insights about GES-DISC Jira Tickets

In order to assess the complexities of Jira tickets created by NASA Goddard Earth Sciences Data and Information Services Center (GES-DISC), it was beneficial to create a knowledge graph. The knowledge graph receives ticket data through the Jira API. The creation of a knowledge graph will help to answer high-level questions about internal structure, knowledge gaps, and team organization within GES-DISC. To work towards this goal, the knowledge graph was constructed in adockerizedNeo4j graph database. Once the graph had been created, graph algorithms were applied to answer high-level questions, such as exploring the role of staff in relation to projects, which qualities of a ticket contribute to the formation of communities within the graph, etc. To answer these questions, centrality and community detection algorithms were applied using Cypher querying language. The analysis of the results of the algorithms indicated that, as expected, certain individuals were more connected to some projects, while others were serving as hub nodes between two or more projects. Similarly, specific keywords are more likely to increase a Jira ticket’s centrality in the graph. In terms of community detection, when tickets in a community have certain qualities, it is more probable for them to be grouped together. To best visualize which nodes had higher centrality scores or were grouped into certain communities, interactive graphs were created in Python using Plotly and Matplotlib. Ultimately, the project was successful in creating and deploying a knowledge graph to better understand the relationships between data in GES-DISC Jira tickets

Rebecca Lipton↗