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This report presents a usability evaluation of NASA’s Open Science 101 (OS101) interface. It offers design recommendations for improving the user experience (UX) and user interface (UI) of the initial self-paced OS101 release. The author initially conducted an independent heuristic evaluation, followed by an analysis of written user feedback to corroborate findings. Overall, the usability evaluation found that the OS101 interface offers a linear and interactive UX, with areas for improvement across five major, three minor, and two cosmetic aspects of usability.

The Gateway to Astronaut Photography of Earth (GAPE, eol.jsc.nasa.gov) contains the complete collection of all Earth observing photography captured as part of the Crew Earth Observations (CEO) project on the International Space Station. Astronaut photography is a valuable remote sensing data set that can provide images ranging from high resolution (~4m/pixel) nadir views to oblique views through the atmosphere. Nighttime imagery collected as part of CEO constitutes the highest resolution publicly available nighttime visible light data. This data support dozens of research projects looking at urbanization, land use/change, disaster response, and many others. Our team has deployed a new interactive map tool that greatly expands the functionality of the GAPE data set, enabling researchers to easily search our collection of fully georeferenced daytime and nighttime imagery around the world. Users can download the georeferenced tiles directly through the portal or through an API interface. The data hosted on this new tool is growing every day as more images are processed through our auto-georeferencing process.

Datasets, unlike publications, can be updated over time, with each new version receiving a DOI but not always being linked to previous ones. This complicates tracking citations across a dataset’s lifecycle. We address this by integrating dataset versions and citations into a knowledge graph (KG), which helps trace dataset citations and analyze dataset usage in applied research. To categorize publications from various journals, we fine-tuned NASA IMPACT INDUS Large Language Model (LLM) on a labeled publication set, assigning publications to one of twenty applied research areas. By linking datasets to these research areas, we improved dataset searchability and discovery through these domains.

Sixty years of spacesuit knowledge capture and lessons learned by spacesuit subject matter experts are documented on videos and presentations and archived with the NASA Engineering and Safety Center (NESC) Academy. The NESC Academy is a web-based platform that hosts online courses by technical experts. A process is underway to transition these decades of lessons learned from the U.S. Spacesuit Knowledge Capture Program Library into more quicky searchable databases and to proactively provide this information to those working on spacesuit projects. Hundreds of lessons learned from Project Mercury, Gemini, Apollo, Apollo- Soyuz Test Project, Skylab, Space Shuttle, International Space Station, and Artemis have been captured in a format that can be quickly searched, enabling users to find information directly applicable to their needs. Transitioning this information to a NASA wiki page will further enhance search and retrieval of data immediately useful to users. This paper provides information about how the lessons learned were determined and how to access them.

As the National Aeronautics and Space Administration (NASA) works to develop a crewed Moon to Mars Architecture, it is dealing with a large decision space consisting of the overlay of human exploration architectures for both the Moon and for Mars. Efforts are underway to enable reasoning, analysis, and deliberation on this decision space. A critical first step is to develop a model of the decision space, which will then allow for various methods and techniques to be applied in support of the larger architecture decision-making process. The Trade Space Ontology consists of a set of terminologies and relations (an ontology) and a MagicDraw resource that enables documentation of decisions and alternatives. It also provides a means by which decisions and alternatives can be traced to other Systems Engineering artifacts. For documenting alternatives, the Trade Space Ontology adapts the Morphological Matrix methodology to The Systems Modeling Language (SysML) through a profile; custom diagrams are also implemented to simplify the profile's use. With the profile and custom diagrams, system architects can specify options for architecture attributes, as well as compatibility between them, in a compact visual format. While the approach shares similarities to a trade tree, the emphasis at this stage is less on enumerating specific combinations of options and instead on specifying the options and their compatibility. Enumeration of alternatives is performed by an external analysis that operates on an output file from a model constructed using the Trade Space Ontology. For decisions, the Trade Space Ontology provides a way to model generic precedence relationships as well as documenting inputs and outputs. These may include what alternatives, criteria, and rationale are understood to be relevant for each decision. Importantly, the decision-making side of the Trade Space Ontology is defined at a more general level, such that it can be adapted to the specific terms in use by projects and programs at NASA. However, this adaptability also means that less capability is provided ``out-of-the-box'' from installation. Currently the resource includes plugin functionality to enumerate paths through generic precedence relationships between decisions and to export these paths to a spreadsheet. Custom dependency stereotypes are included in the profile to indicate the cross-cutting relationships between the trade space and the architecture decisions, providing a means to map which parts of the trade space enumerate alternatives for a decision, and to identify how the output of a decision may modify the trade space through pruning or down-selection. While the motivating use case for this resource is in human exploration architectures, the broad applicability of the Morphological Matrix methodology indicates that the Trade Space Ontology should also be useful for other activities and tasks at the agency.

With the first crewed missions of the Artemis Program on the horizon, including the return of humans to another planetary surface, the space medicine and research communities have a renewed interest in buying down risk on these missions using historic Apollo datasets. Archivists with NASA’s Life Sciences Data Archive (LSDA) and epidemiologists with the Lifetime Surveillance of Astronaut Health (LSAH) are collaborating on a project aiming at improving access to historic datasets from the Apollo Program. The Apollo Records Synthesis Project (ARSP) seeks to expand the available historic biomedical knowledge base by examining physical records located across a wide range of collections, including examples such as pre-flight and post-flight physicals, lab reports, and handwritten flight surgeon and biomedical engineer logs from Apollo missions. The ARSP team has been able to identify several previously undocumented sources of biomedical information from Apollo missions. In the future, the team will modernize record storage and accessibility of these resources using digitization and natural language processing. This poster will discuss the progress of the project, give context to the dual research-clinical care nature of the records, and highlight the challenges and opportunities in using data from historical records. This poster will also provide information on how researchers can request access to datasets from these records.

Attribution of datasets that were used to generate research results described in peer-reviewed publications to the original source of these datasets (which are often archived at NASA Earth Science data centers) has been very challenging. Even though the data citation standard of citing datasets as research artifacts and citing them with Digital Object Identifiers (DOIs) was introduced over a decade ago, most authors do not properly reference the data used in their studies and merely mention them in the text. The lack of proper citations of datasets makes the peer-reviewed publication less transparent, imperils reproducibility, and impedes open science. We offer an open-source publication management methodology and a tool that can help to enhance usage-based data discovery, prominence, and provenance of the data; reproducibility of the research results; and potentially increase the return on investment on NASA-funded research.

JSC’s Electronic Document System (EDS) was published in 2013 by SMA to store and process Task Performance Sheets (TPS), Discrepancy Reports (DR), Hardware Movement Documents (EZT), etc. The 2013 transition turned a fully paper process into an electronic routing one with document level electronic approvals but maintained an in-line paper process. - Today, all work and buy-offs continue to be captured on paper, walked between buildings, and is susceptible to approval errors, a rapidly slowing processing time, and led to projects requesting waivers to use alternate WAD systems, damaging JSC’s QMS. - NT Data Systems team collaborated with multiple platform providers, test user groups, and stakeholders, to find a solution for this growing need in a way that exceeds JSC’s current process, is adaptable to future innovation, and within our limited resource constraints

State-of-the-art cloud computing platforms such as Google Earth Engine (GEE) enable regional-to-global land cover and land cover change mapping with machine learning algorithms. However, collection of high-quality training data, which is necessary for accurate land cover mapping, remains costly and labor-intensive. To address this need, we created a global database of nearly 2 million training units spanning the period from 1984 to 2020 for seven primary and nine secondary land cover classes. Our training data collection approach leveraged GEE and machine learning algorithms to ensure data quality and biogeographic representation. We sampled the spectral-temporal feature space from Landsat imagery to efficiently allocate training data across global ecoregions and incorporated publicly available and collaborator-provided datasets to our database. To reflect the underlying regional class distribution and post-disturbance landscapes, we strategically augmented the database. We used a machine learning-based cross-validation procedure to remove potentially mis-labeled training units. Our training database is relevant for a wide array of studies such as land cover change, agriculture, forestry, hydrology, urban development, among many others.

Integrated Computational Materials Engineering (ICME) has received a growing emphasis in attention due its potential impact on rapid material design, reduction in cost and time to market for new applications, and the promise of ‘fit-for-purpose’ materials coupled with recent advances in high performance computing and material characterization tools. However, for an organization to implement ICME practices for material discovery and design, a series of both technical and cultural challenges must be overcome to foster an environment that enables efficient, traceable, and predictive multiscale simulations of material behavior to enable virtual design of materials. In 2016, NASA sponsored a 2040 Vision study to define the potential 25-year future state required for integrated multiscale modeling of materials and systems to improve both the associated time and cost for aerospace and aeronautical innovation. The study envisions a cyber-physical-social ecosystem of experimentally validated computational models, tools, and techniques, along with the associated digital tapestry, that can enable rapid, optimized, ‘fit-for-purpose’ design of materials, components, and systems. A key requirement for such an ecosystem is the development of a robust information management system for materials across their full lifecycle, including material pedigree, experimental (real) and virtual (simulation) data, developed material models, and the implementation of models in engineering applications, such that process-structure-property-performance relationships can be established, thereby enabling the virtual design and optimization of materials. Such an information management system must be able to effectively capture: i) material information at each length scale; ii) test data and analysis; iii) associated material models; and iv) material and model deployment in engineering applications. These systems must also provide traceability between experimental and virtual representations of the material to ensure, when appropriate, the material digital twin is maintained. Additionally, this robust material information management system must be able to seamlessly connect with both commercial and an organization’s in-house software tools, be they analysis tools, other material databases, product lifecycle management (PLM) or simulation data management (SDM) tools, etc., such that automation of the design and analysis of a material across multiple length scales is possible. In this paper, an executive summary of the NASA GRC ICME Schema for materials information management is presented. The database best practices and schema design philosophy specifically for ICME materials data management and an overview description of each element in the schema is given, along with its associated role in an ICME workflow. Additionally, auxiliary tools that interact with the database and provide judicious automation with regards to importing, exporting, and analyzing materials data are presented. Such tools are critical to an ICME ecosystem, not only for their role in enabling optimization, but also in relieving users of tedious manual tasks, thus helping to promote adoption and combat the cultural challenges organizations face in enabling ICME.

The purpose of this handbook is intended to be a how-to guide to prepare for, conduct, and close-out an Integrated Baseline Review (IBR). It discusses the steps that should be considered, describes roles and responsibilities, tips for tailoring the IBR based on risk, cost, management insight benefits, and provides lessons learned from past IBRs. The appendices contain example documentation typically used in connection with an IBR. Note: Appendices are examples only, and should be tailored to meet the needs of individual projects and contracts. Following the guidance in this handbook will help customers and suppliers preparing for an IBR understand the expectations of the IBR, and ensure that the IBR meets the requirements for both in-house and contract efforts.

This project created a visualization and simulation software platform for the entire lunar surface. Given the polar Artemis landing targets, the challenging terrain, lighting, and associated integrated crew / vehicle risk assessment, a more integrated approach to mission safety certification, potentially impacting equipment design and crew activity is required. This integrated capability will enable Safety and Mission Assurance (SMA), Flight Operations (FOD), and EVA to effectively collaborate to reduce human lunar exploration operational risk utilizing the identical tools to perform mission planning, rehearsal simulations, and providing the Safety Review Panel with integrated risk analysis capability.

NASA AIST Program is now designing and developing Digital Twins of the Earth and/or Earth systems. Organized around interconnected, multi-domain, high-scale modeling capabilities, the three major components of an Earth System Digital Twin are a continuously updated Digital Replica of the Earth System of interest, dynamic Forecasting models, and Impact Assessment capabilities. This document identifies the key features and capabilities needed in an ESDT and describes the major notional components of the system and some key relationships, while providing room for a variety of architectures to respond to them. It provides a generic system diagram of an ESDT, including the interfaces to external observing systems and models.

On July 12, 2023, the Advanced Information Systems Technology (AIST) program conducted grouped annual reviews of all its Analytic Collaborative Frameworkds (ACF) projects. This report regroups all these technical presentations.

After more than 20 years in orbit, NASA’s Terra and Aqua satellites have both started drifting away from their historically maintained orbits. The MODIS instruments on Terra and Aqua continue to collect valuable Earth observation data, but the changing orbits present a challenge for maintaining accurate calibration. The MODIS reflective solar bands (RSB), spanning the wavelength range from 412 nm to 2130 nm, are calibrated on orbit using a combination of regular data collections from an on-board solar diffuser, the Moon, and pseudo-invariant Earth scenes. Starting in the Collection 6 Level 1B (L1B) data products, the RSB calibration began using data from desert targets for a few of the visible bands to better track changes in the response versus scan angle that could not be captured by the on-board calibration. The use of Earth scene data has been extended recently for Terra MODIS calibration in Collection 6.1 (C6.1) and the upcoming Collection 7 (C7) L1B to also include data from ocean scenes and deep convective clouds (DCC). Drifts in both the orbit inclination and ground track of Terra and Aqua lead to changes in the solar illumination angles and satellite view angles of the Earth scenes. We discuss how these orbital changes impact the desert and DCC targets used for MODIS RSB calibration and present the accompanying changes made to our C6.1 and C7 calibration algorithms. We also discuss remaining future challenges, such as better characterization of bi-directional reflectance distribution functions, and possible alternative calibration strategies.

The collection of astronaut photography hosted on the Gateway to Astronaut Photography of Earth (GAPE, eol.jsc.nasa.gov) forms one of the most extensive historical compilations of Earth remote sensing data sets available to researchers and the public. The GAPE database contains astronaut photography spanning all manned NASA spaceflight missions over the past 60 years and continuing to this day with operations on the International Space Station (ISS). The continuous crew presence in low Earth orbit (LEO) on the ISS for the last 22+ years and the advent of digital handheld cameras has resulted in an exponential increase in astronaut photography, growing the GAPE collection to over 4.5M photographs (Figs. 1 and 2). This increase in astronaut photography of Earth has corresponded to a significant increase in interest in the collection by the research community and the public. The Earth Science and Remote Sensing (ESRS) group at Johnson Space Center, which manages Crew Earth Observations (CEO) from the ISS, has been developing multiple new tools to improve the GAPE database so that users can more quickly find the imagery they need. The three major enhancements to GAPE are: a new API to interface with the database, a method for automatically georeferencing ISS photos (Fig. 3), and a new tool for automatically generating timelapse movies.

On June 23, 2023, the Advanced Information Systems Technology (AIST) program conducted grouped annual reviews of all its Earth System Digital Twins (ESDT) projects. This report regroups all these technical presentations.

A more accessible, open data-sharing infrastructure will engage a broader community of contributors, helping to develop satellite data products that benefit Earth science research and applications.

The value of scientific data depends on their findability, accessibility, integrability and reusability according to the FAIR principles. Together with the sustainability of data preservation and access, these principles underpin the long term benefits of scientific research. Within the domain of radiobiology we have a huge array of data types, themes and complexities which make standardisation of metadata, data structure and data integration very challenging. Moreover, it is clear that, for example, in the area of disaster preparedness, the ready discovery and availability of multiple types of data, for example on biological effects of exposure, climatology, ecology, human behavioural and attitudinal studies, is important for an integrated scientific approach. Because these data are spread over many databases, journal supplementary information resources and even the computers of the investigators, their discovery and reuse can be challenging. Despite exhortations from funding agencies and scientific institutions over the past two decades there is still a serious deficit in the willingness and in some cases the ability of investigators to share data, and although much may not be formally "Public domain“, information about the existence of the data, their metadata, and how to obtain them should always be available. We report the progress of work on three databases, the STORE and the NASA GeneLab and LSDA repositories to leverage the Radiation Biology Ontology (RBO), a structured terminology for metadata that can be used by all radiation biology-relevant databases to unite federated and automated data searches across multiple databases, for example using web services, and through semantic web technologies supporting data discovery. The initial primary use-cases for RBO were archiving data in the STORE database (https://www.storedb.org/), the repository used for the RadoNorm and Pianoforte Projects among others, and in the NASA Open Science Data Repository (https://osdr.nasa.gov/bio). The scope of radiobiology research ranges from basic physics to radiation oncology to sociolegal studies; no existing ontology had the necessary breadth or depth to fulfill this need. In addition, a formal ontology has the advantage of being usable for machine learning and, importantly, for tasks like data integration, knowledge extraction from the scientific literature and for query extension and data classification. Standardisation of metadata is one of the primary objectives of the FAIR principles for open data; RBO is an important landmark for FAIR-compliant radiation biology data sharing. The RBO is developed using the open-source tools of GitHub and the OBO Foundry-led Ontology Development Kit, and published through GitHub and the NIH/NCBI BioPortal website. This initial phase of concept modeling has yielded an ontology that has more than 300 declared concepts, with more than 3500 additional concepts imported from other OBO Foundry ontologies with relevance to radiation biology (for example, concepts from the ISO standard Basic Formal Ontology, the Environment Ontology and the Gene Ontology). We welcome input into the development of RBO and encourage its adoption.

In 2014, The GEOSS Water Strategy – From Observations to Decisions was published and steps were taken to implement the Strategy’s recommendations. The Strategy highlighted priority areas where the application of Earth observations to water research and water management decisions would have significant scientific and societal benefits. This article reviews the implementation of the Strategy’s recommendations over the past eight years. After a review of the Strategy’s assessment of the needs for water observations and their applications, it then reviews actions taken in response to the Strategy’s recommendations in its four major themes: improved data acquisition for Essential Water Variables, research and product development, interoperability, and capacity development. It highlights significant achievements in the implementation of the Strategy including some motivated by factors beyond this Strategy, reviews actions taken by participating agencies and programs for each of the main themes and summarizes the remaining challenges in achieving the Strategy’s full implementation. The article not only is an update for the Water Community regarding the GEOSS Water Strategy, but it is also an example of how other communities could develop and promulgate a set of strategic recommendations, monitor progress, and carry out assessments of their effectiveness.

Robust prediction of Solar Energetic Particle (SEP) events is among the key priorities of the space weather community. In the framework of NASA’s Early Stage Innovation Program, we develop the Solar Energetic Particle Prediction Portal (SEP3: https://sun.njit.edu/SEP3), which hosts web applications that allow the users to retrieve the database records. In particular, SEP3 lists the API examples to query each data source potentially important for the SEP prediction. The Portal has a search page for browsing the events from the most widely used catalogs (https://sun.njit.edu/SEP3/search.php) and a dedicated space to share the most recent achievements of the team. In addition, we have added a CDAW SEP catalog and a LASCO/SOHO CME catalog and introduced the possibility of displaying the properties of the connected events (parental solar flares and CMEs for SEPs) on the search page. The interactive widget has the capability to display GOES soft X-ray and proton flux time series from different satellites with the GOES flare records on top of them. The data portal has been used to evaluate the forecasts of the solar proton events based on the statistical properties of the GOES soft X-ray and proton fluxes and investigate machine-learning approaches to the SEP prediction.

Establishing the Sun-Earth connection requires overcoming the challenges of exploring the data from past and current missions and leveraging tools and models (data mining) to create an efficient system treatment of the Sun and heliosphere. However, solar and heliospheric environment data constitute a vast source of information whose potential is far from being optimally exploited. In the next decade, the solar and heliospheric community will have to manage the increasing amount of information coming from new missions, improve reanalysis of data from past and current missions, and create new data products from the application of new methodologies. This complex task is further complicated by practical challenges such as different datasets and catalogs in different formats that may require different pre-processing and analysis tools, and the need for numerous analysis approaches that are not all fully optimized for large volumes of data. While several ongoing efforts aim at addressing these problems, the available datasets and tools are not always used to their full potential often due to lack of awareness of available resources. In this paper, we summarize the issues raised and goals discussed by members of the community during recent conference sessions focused on data mining for science.

The purpose of this document is to establish a set of EVA compatibility design requirements for the HLS Program. This document contains the fundamental information required for building hardware compatible with suited EVA flight crewmembers to perform EVAs. Compatibility requirements are located in section 3.0 with a gravity field applicability table provided in APPENDIX G, Human Landing System Program Applicability Matrix. Each HLS Provider will use the EHP-provided matrix in Appendix G to assess applicability to the awarded mission provider on a per-mission basis. Providers will negotiate applicability with EHP, and this will be documented in the appropriate Annex (reference section 2.2)

This concept of operations describes: - High-level Government goals, objectives, and needs for the CLD program, vehicle(s), and missions, - Strategies, policies, and processes for developing, certifying, maintaining, using, and retiring CLDs in the context of Government use, and - Government and CLD partner roles, responsibilities, and interactions during various phases of Government CLD operations. The intent of this document is to describe the overall high-level concept of how the end-to-end CLD service will be used to convey the nature and scope of services the Government intends to procure from the CLD partner. It will provide insight into NASA’s concepts for CLD operations rather than to provide mature, explicit, or complete requirements. It addresses how the concept of operations will be used to meet NASA expectations from an operational perspective to facilitate an understanding of the end-to-end CLD service needs, goals, and objectives (NGOs). Formal CLD requirements and standards are detailed in the NASA Commercial LEO Development Program’s (CLDP) various requirements, interface, process, and standards documents, as well as the contractual Statements of Work (SOW) and Data Requirement Deliverables (DRD). As such, the Concept of Operations can use terms such as “should” or “may” or “expects to” since it is not a contractual requirements document. It exists solely to convey the initial nature and type of services the Government intends to procure and is not, per se, a requirements document.

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. Some of these improvements will at the same time support the twin pillars of Open Science: transparency of methods and reproducibility of results. This video is a high level overview of the NLSP for existing and new users.

This handbook provides guidance based on best practices for the planning, preparation, review, reporting, and closeout of Standing Review Board (SRB) activities. Revision C updates the Revision B version of the SRB Handbook published in 2016 to incorporate updates to NASA Procedural Requirements (NPR) 7120.5F, NASA Space Flight Program and Project Management Requirements. These updates include: - Changing the Dissenting Opinion process to the Formal Dissent process, which retains the current process augmented with an expedited escalation path. - Updates to requirements for establishing an Agency Baseline Commitment (ABC) and for performing Joint Cost and Schedule Confidence Level (JCL) analyses for tightly coupled programs. - Additional requirements for performing a JCL analysis for single-project programs and projects over $1B Life-Cycle Cost (LCC). - Use of initial capability cost estimates instead of LCC estimates in specific, identified instances for single-project programs and projects that plan continuing operations and production, including integration of capability upgrades, with an unspecified Phase E end point. These single-project programs and projects define an initial capability during Phase A and develop an initial capability cost that establishes the ABC at Key Decision Point (KDP) C. Initial capability is the first operational mission flight (or as defined in the KDP B Review Plan) and is documented in the KDP B Decision Memorandum. Initial capability cost includes operations cost for the initial capability. The Phase E cost estimate for continuing operations and production is established separately as part of the Operational Readiness Review (ORR) and KDP E for the 5 years after initial capability and subsequently updated and documented annually for the next 5-year period. Upgrades during Phase E that meet the Agency criteria for a major project for external reporting are treated as projects for the purposes of establishing their own development ABC outside the Phase E cost estimate. The Phase E cost estimate is updated to include production and operations costs associated with these upgrades. Development, production, and operations costs of other (i.e., non-major) upgrades are included in the Phase E cost estimate. (See NPR 7120.5, Sections 2.4.1.5 and 2.4.1.6 and the NASA Space Flight Program and Project Management Handbook (PM Handbook), Section 5.5.4 for additional information.) The scope of the SRB’s assessment with respect to initial capability, Phase E cost estimate, and major upgrades for these single-project programs and projects is defined in the Terms of Reference (ToR).

Freedom to explore the unknown is key to scientific discovery. Maximizing modern individualistic measures of scientific productivity like citations and number of publications may impede the progress of science as a whole.

This PFAS Site Assessment Progress Report (SAPR) presents the findings of the 2022 PFAS investigation conducted from November 2021 through August 2022 at Solid Waste Management Unit (SWMU) 114 located within Kennedy Space Center (KSC), Florida. SWMU 114 includes area around Fire Station #2, Former Sewage Treatment Plant #17, the southern portion of the Shuttle Landing Facility Runway, Remote Launch Vehicle Hangar, and the Towway area. Fire Station #2 was constructed in 2008 and is currently active, housing fire station personnel and equipment, including aqueous film forming foam (AFFF). Releases of AFFF has occurred at SWMU 114. Previous environmental assessments have been performed at SWMU 114, including soil, groundwater, and surface water sampling for volatile organic compounds, polycyclic aromatic hydrocarbons, total petroleum hydrocarbons, and metals. No active remediation has been performed at the SWMU 114. PFAS site assessment field activities were conducted at SWMU 114 from November 2021 through August 2022. During the 2021-2022 Site Assessment, 124 direct-push samples were collected from 27 locations, 17 surface water samples were collected from 15 locations, 41 groundwater samples were collected from 37 newly installed monitoring wells, five concrete samples were collected from four locations, and one asphalt sample was collected. Additionally, two soil borings were advanced to 60 feet for lithologic descriptions, ten staff gauges were installed, and one round of water level measurements were collected from monitoring wells and staff gauges for groundwater flow determination. All groundwater and surface water samples were analyzed for 25 PFAS analytes by USEPA Method 537M. Concrete, and asphalt samples were analyzed by synthetic precipitation leaching procedure (SPLP) PFAS analysis by USEPA Modified Method 537M. Groundwater results were compared to the most recent Regional Screening Levels (RSLs) published by USEPA for residential tap water (USEPA, 2022a) to determine the extent of PFAS contamination at SWMU 114 for six PFAS analytes (PFOA, PFNA, PFBS, PFHxS, PFOS, and GenX). Surface water results were compared to the FDEP surface water screening levels (SW SLs) (FDEP, 2020) for PFOA and PFOS. The PFAS investigation concluded that groundwater exceeding RSLs extends east and south to Banana Creek and west to approximately the center of the SLF runway. The extent of PFAS is approximated to the north, to an area between Sharkey Road and Astronaut Road, where samples below the RSLs do not fully bound SWMU 114. At least two distinct PFAS source areas are located near Fire Station #2 and along Towway, at S114-MW0007S, within SWMU 114. Groundwater head measurements indicate that flow at SWMU 114 is generally similar across the shallow and intermediate water tables. A northeast to southwest trending groundwater divide is located near the middle of Towway where groundwater southeast of the divide flows to the south and groundwater northwest of the divide flows to the west. The groundwater divide generally separates the two areas of higher PFAS concentrations. Surface water samples indicated concentrations of PFOS above the SW SLs in surface water bodies across the site. Further assessment and sampling are required to better understand the interaction between groundwater and surface water at SWMU 114. Concrete and asphalt samples collected confirm that a significant release of AFFF occurred near the stormwater pond northwest of Fire Station #2. Additional concrete samples surrounding Fire Station #2 and at the northwest and southeast edges of the SLF tarmac indicate elevated PFOS concentrations. These results indicate that discharges of AFFF in these locations have infiltrated into asphalt and concrete and may act as a continuing source of PFAS to groundwater and surface water after rain events. Additional direct-push samples are required to delineate PFAS at SWMU 114. Samples may need to extend beyond the Former SLF Rescue Building and Morpheous Test Site to delineate PFAS in groundwater. Monitoring wells should be sampled and gauged quarterly to determine if seasonal impacts are observable, especially in shallow wells near surface water features. Furthermore, surface water samples should be collected from additional ditches to further define the extent of surface water impacts at SWMU 114 and extending along the SLF runway. Staff gauges should be gauged quarterly with groundwater gauging to determine surface water flow and interaction with groundwater. The PFAS sampling results and path forward for SWMU 114 were presented to the KSC Remediation Team in October 2022. Once the PFAS SAPR is approved, it will be submitted to the Florida Department of Environmental Protection.

Over the last few decades, advances in high-performance computing, new material characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. In 2016 NASA sponsored a 2040 Vision study (which appeared in 2018) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. The study envisions a cyber-physical-social ecosystem comprised of experimentally verified and validated (V & V) computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of “fit-for-purpose” materials, components, and systems. Consequently, the development of a robust information management system that incorporates (across the full life cycle) both experimental (real data) and virtual data resulting from the application of various simulation tools (at single or multiple length scales), therefore enabling the virtual design and optimization of materials throughout their processing – internal structure – property – performance envelope, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality, and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. This is particularly true when attempting to merge ICME practices with recent additive manufacturing technology which will enable production of the resulting 2040 Vision material and structural designs. At NASA Glenn Research Center we are exploring the future of material science through the use of novel characterization methodologies, high performance computing, and recently an emphasis on integrated computational materials engineering (ICME). Herein, recent efforts to incorporate an Application Table within NASA Glenn Research Center’s ICME Granta MI database is presented. The goal is to provide a place where material and structural application information/requirements can be linked so as to marry the “design the-material” and the “design-with-material” paradigms and thereby enable application-driven design and optimization of materials and structures by providing a central location that links material processing at various length scales to the application’s performance requirements. This paper discusses the specifics of this Application Table as well as best practices and key principles for the development of a robust materials information management system to enable the 2040 Vision integrated materials and structures ecosystem. Furthermore, it presents the intended role of the Application Table in the future of ICME design of “fit-for-purpose” materials, showing the need for a well-established framework that can successfully bridge the gap between the design “the material” and design “with-the-material” paradigms.

Safety, failure, and incident reports are common artifacts across various domains, including aviation and wildfire response. These reports are often mandatory to submit, resulting in the culmination of large repositories of text-based documents. Simultaneously, these reports and corresponding repositories are often only manually analyzed and queried by users via out-of-date search engines. As a consequence, we have been developing the Manager for Intelligent Knowledge Access (MIKA) toolkit, which uses natural language processing to improve information access and reuse. In this presentation, we discuss natural language processing techniques for knowledge discovery and apply these methods to a repository of aerial wildfire mishap reports. Two methods are used for knowledge discovery: topic modeling and named-entity recognition. We use topic modeling to identify hazards and perform a trend analysis to produce a data-driven risk matrix. A custom named-entity recognition model, build from fine tuning a pre-trained language model, is used to identify failure modes, failure causes, failure effects, control processes, and recommendations to aid in failure modes and effects analysis (FMEA). Throughout the presentation, we discuss and apply natural language processing techniques to better leverage the vast amount of information contained in report repositories.

This tool utilizes Data fusion capabilities developed from the 2020-2022 Information Fusion (IFDA) IRAD to enhance functionality of a Human Spaceflight (HSF) Aggregate Risk Product developed by the JSC Flight Safety Office. The tool compiles and present risk data from multiple Program and Commercial Provider sources to provide a holistic assessment for Program Managers and Technical Authorities to evaluate residual risk prior to HSF Launches. The aggregation, or coupling of risks from multiple sources (Ex: PRA, variances, anomaly data bases, CRM data, technical review board minutes, Hazard Analysis, etc.) identifies areas of elevated risk in components, systems or mission phases that would otherwise be undetected by non-integrated program risk management tools and possesses. Data is then displayed in an interactive user interface/dashboard that enables users to see potential areas of concern requiring more in-depth analysis.

The Information Fusion & Data Analytics (IFDA) project commenced in FY20, continued through FY21, and its final platform development phase continues in FY22. The objective remains the fusion and rapid accessibility of large quantities of disparate sourced human spaceflight data. IFDA is a platform tailored for NA (S&MA) to develop highly advanced operational data integration and analysis techniques. IFDA leverages the JSC ER7 modeling, simulation,and data fusion capabilities to collect, warehouse, and augment data human exploration data integration and analysis techniques. The IFDA project’s integrated data visualizations have been demonstrated in two validation scenarios in FY21, and provided the architecture and platform basis for development of a full-scale data analysis suite and storage solution useful to all JSC organizations engaged in real time operations and safety tasks. Scenarioand prototypical development including the construction of a full scale data analysis suite and storage solution, useful to all JSC organizations engaged in real time operations and safety tasks, is central to IFDA Phase 3 and provides a demonstrable pathway for the Digital Transformation Program. IFDA Phase 3 is focused on data provider, data utilizer, and SME hands-on workshops that will conclude the Dem / Valphase and deliver a program-ready data integration tool as a product.

Extended mission budgets fund a significant part of our community, particularly young scientists who in a relatively short time are exposed to a broad range of experiences and opportunities available in space science and other STEM fields. In particular, mission-funded science offers a relatively stable funding stream that enables meaningful mentoring efforts and interactions, including apprenticeships ranging from project management, to mission operations, to data processing and analysis, to hardware and software development, to STEM-related education and outreach. It moreover provides professional contacts that fuel diversity in mission leadership and in the science and technical workforce at-large. Last but not least, it sustains the scientific productivity of NASA’s missions, which constitute major national investments meriting their full exploitation. Budgets cuts, however, are exercising pressure on the science and operations of the extended mission fleet despite being only a small portion of the overall Division budget. The history of Heliophysics has demonstrated that maintaining the operation of missions beyond their prime phase invariably leads to a much deeper knowledge of the original mission science goals, together with new applications often not foreseen during their original design. Their operation as part of the Heliophysics System Observatory (HSO)---a coordinated, 1eliophysics, multipoint observing system of the heliosphere, is a prime example. Some of the first activities undertaken by the Parker Solar Probe and Solar Orbiter missions required recreating the larger context of their new observations by using the diversity of HSO mission capabilities. The marginal cost of maintaining this valuable, working science resource, in the form of both continuing high quality data access and expertise, is small compared to the cost of the original missions or of new missions to achieve similar objectives, making the operation of extended missions, the best “science per dollar” investment in Heliophysics. We argue that reducing both extended mission operations and science budgets will have a ripple effect across the community, including reducing employment and training opportunities for young scientists, to lowering the quality/impact of the Heliophysics Systems Observatory. Instead, we suggest that the proposal process for mission extension should be re-examined. We offer several ideas for reducing costs of extended missions toward maintaining science output and streamlining the management process.

For over a decade, the National Aeronautics and Space Administration (NASA) has tracked and configuration-managed approximately 30 risks to astronaut health and performance that occur before, during and after spaceflight. The Human System Risk Board (HSRB), a Health and Medical Technical Authority (HMTA) Board at NASA Johnson Space Center, is the entity responsible for identifying, assessing, analyzing, and monitoring the official understanding of the risk or risk posture for each of the Human System Risks and determining – based on evaluation of the available evidence – when that risk posture changes. The ultimate purpose of tracking and researching these risks is to find ways to reduce the risk that astronaut crews face during spaceflight. Historically, research, development and operations relevant to one risk have been conducted in isolation from other risks; these individual risk ‘silos’ enabled initial characterization of each specific risk. In spaceflight however, the impact of exposure to risk for astronaut crews is cumulative, and not independent of exposures or other risks, as all the adverse effects of the spaceflight environment begin at launch, continue throughout the duration of the mission and in some cases across the lifetime of the crews. In January of 2020, the HSRB at NASA embarked on a pilot project designed to assess the potential value of causal diagramming as a tool to facilitate understanding of these cumulative and interdependent effects as applied within Human System Risk management. This process uses directed acyclic graphs as a means of formalizing a shared mental model of the causal flow of risk among Risk Board stakeholders. Initially this model was to improve communication among those stakeholders, but the potential value exceeds communication alone. The causal diagrams are formulated as directed acyclic graphs (DAGs) to function as a type of knowledge graph for reference for the board and its stakeholders. This document is a sister document to NASA/TM 20220006812 Directed Acyclic Graph Guidance Documentation (1). In that document, the basic guidance for creating and standardizing directed acyclic graphs as tools for cross-risk analysis is provided. This document contains the initial configuration managed DAGs that were created as a result of applying those principles. These initial versions were accepted by the HSRB in January of 2022. Each of the Human System Risks are represented by a DAG that has been reviewed by the larger Human Health and Performance community at NASA including life scientists, physical scientists, physicians, nurses, pharmacists, exercise specialists and more. These results show the starting point for Human System Risk DAGs as shared mental models and communication aids across the boundaries of the various expertise needed to understand and mitigate the human risks in spaceflight. Because they are a starting point, each of these DAGs can be expected to change over time as new or refined evidence becomes available. The process for updating these DAGs can be found in the JSC-66705 Human System Risk Management Plan (2) that is publicly available on the NASA Technical Reports Server.

The NASA Rapid Model Import Tool (RMIT) is designed to import 3D models built in commercially available Computer Aided Design (CAD) and Digital Content Creation (DCC) development software such as; Catia, Creo, 3DS Max, Maya, etc. Upon import, RMIT processes the models to reduce file size and exports the results in a format compatible with Augmented Reality (AR) and Virtual Reality (VR) development software applications. RMIT intends to make CAD models directly accessible to engineers from local AR/VR compatible laptops and desktops.

NASA has updated its planetary protection policy and implementation approach in response to advances in scientific understanding of solar system targets, upcoming mission opportunities for exploration and sample return, and the private sector’s emerging capability to plan missions to Earth’s Moon and Mars. In September 2021, the NASA Procedural Requirements NPR 8715.24, entitled “Planetary Protection Provisions for Robotic Extraterrestrial Missions” was released which repositions planetary protection in existing NASA mission and program management structures, introduces risk-informed decision making, expands on key roles and responsibilities for both programmatic and the Office of Safety and Mission Assurance, updates the categorization process and streamlines the planetary protection documentation approval and schedule. NASA is working on a more detailed technical standard to accompany NPR 8715.24 which will include the detailed technical requirements to address organic contamination, inadvertent impact avoidance, biological control and management, end of mission disposal and restricted Earth-Return sample safety and assurance. This report to the COSPAR community will describe the current NASA planetary protection policy and its alignment with the revised COSPAR planetary protection policy. NASA’s plans for updating the supporting “Handbook for Implementing Planetary Protection Technical Requirements” and future policies for addressing planetary protection of crewed missions will also be presented.

For over a decade, the National Aeronautics and Space Administration (NASA) has tracked and configuration-managed approximately 30 risks to astronaut health and performance that occur before, during and after spaceflight. The Human System Risk Board (HSRB), a Health and Medical Technical Authority (HMTA) Board at NASA Johnson Space Center, is the entity responsible for identifying, assessing, analyzing, and monitoring the official understanding of the risk or risk posture for each of the Human System Risks and determining – based on evaluation of the available evidence – when that risk posture changes. The ultimate purpose of tracking and researching these risks is to find ways to reduce the risk that astronaut crews face during spaceflight. Historically, research, development and operations relevant to one risk have been conducted in isolation from other risks; these individual risk ‘silos’ enabled initial characterization of each specific risk. In spaceflight however, the impact of exposure to risk for astronaut crews is cumulative, and not independent of exposures or other risks, as all the adverse effects of the spaceflight environment begin at launch, continue throughout the duration of the mission and in some cases across the lifetime of the crews. In January of 2020, the HSRB at NASA embarked on a pilot project designed to assess the potential value of causal diagramming as a tool to facilitate understanding these cumulative and interdependent effects as applied within Human System Risk management. This process uses directed acyclic graphs as a means of formalizing a shared mental model of the causal flow of risk among Risk Board stakeholders. Initially this model was to improve communication among those stakeholders, but the potential value exceeds communication alone. Formalization of the process for creating these causal diagrams will enable the creation of a composite risk network that is vetted by members of the NASA community and configuration managed. The causal diagrams are formulated as directed acyclic graphs (DAGs) to function as a type of knowledge graph for reference for the board and its stakeholders. This document outlines the pilot process, the standardized approaches, and guidance for risk custodian teams when creating and updating DAGs as a part of the NASA Human System Risk Management process.

This handbook is the companion document to NPR 7120.5F, NASA Space Flight Program and Project Management Requirements. It represents the accumulation of knowledge on managing program and projects derived from NASA’s human, robotic, and scientific missions. It incorporates the “corporate knowledge” for existing and future NASA space flight programs and projects, including NASA’s Artemis missions to establish a sustainable human presence on the Moon through collaboration with commercial and international partners, NASA’s James Webb Space Telescope (JWST) mission, and NASA’s robotic missions on Mars. The practices discussed have evolved as a function of NASA’s core values of safety, integrity, teamwork, excellence, and inclusion, and may also prove a resource for other agencies, the private sector, and academia. The knowledge gained from the Agency’s victories and defeats, including the checks and balances and initiatives to better control cost and risk, provides a foundation for continuing an exciting and healthy space program. This handbook provides implementation guidance for NPR 7120.5F and includes the changes and updates to key procedural requirements in NPR 7120.5F since NPR 7120.5E. The goal of the NPR requirements is to ensure programs and projects are developed and successfully executed in the most cost-effective and efficient manner possible. This handbook provides context, rationale, and explanation to facilitate the application of requirements and to pass on some of the hard-won best practices and lessons learned.

These Data Release Notes provide information on the processing and export of data from the Transiting Exoplanet Survey Satellite (TESS). The data products included in this data release are full frame images (FFIs), target pixel files, light curve files, collateral pixel files, cotrending basis vectors (CBVs), and Data Validation (DV) reports, time series, and associated xml files