Results for “INTEROPERABILITY” — Page 26

NASA NTRSDate not supplied

Surface Systems and Interface Standardization

Space exploration on planetary surfaces will require the use of various surface systems which will likely need to interface with one another. These systems must communicate and share data, as well as distribute power and transfer fluids for sustainable surface operations. Such systems can range from landers, surface habitats, mobility systems, cargo, and In-Situ Resource Utilizations (ISRUs). Previous and current programs have developed space interoperability standards that help aid in reducing potential risks of interface integration. One example of this is the International Deep Space Interoperability Standards (IDSIS) which focuses on deep space exploration. A goal of the Artemis program is to develop a sustained human presence on the lunar surface that would be a training ground for future Mars exploration. Therefore, it will be beneficial to identify interface standards between the surface assets which will help mitigate risk and reduce complexity in the harsh environments of space exploration. A key contribution to sustainability is commonality between hardware and software interfaces. Generic interfaces for data, power, and fluids will reduce risk, promote interoperability, and define standard interfaces across surface exploration projects and programs. Standardized interfaces would be advantageous for improving efficiency and reducing overall complexity, which are critical considerations for future space exploration. Furthermore, it will provide cost reductions to the Artemis programs over their life cycle (in Operations & Maintenance (O&M) and Logistics). Unique proprietary interfaces if considered or allowed would not only increase complexity but also add cost to the programs. Of course, understanding what will work and not work effectively in these unique environments such as the lunar surface is important. These unique environments require much needed intelligent design, prototyping, comprehensive testing, and field experience, utilizing consensus on common interface solutions.

Jaime Gomez↗

NASA NTRSDate not supplied

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

The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, whole organism, behavior; tabular, imagery). Open Science is the concept that the more people have access to scientifically curated data, the more knowledge will be gained. This led NASA to start the development of GeneLab in 2015. GeneLab houses spaceflight and space-analog multi-omics datasets from plant, rodent, small animal, and microbial experiments. The success and knowledge gained from GeneLab led to a new alliance of NASA “Open Science Data Repositories” (OSDR), which include the Ames Life Sciences Data Archive (ALSDA) and the NASA Biological Institutional Scientific Collection (NBISC). Both are adopting the GeneLab data system, so data are more findable, accessible, interoperable, and reusable (FAIR). OSDR systems provide users the ability to upload, download, search, share, analyze, and visualize. Open Science also needs strong confidence in the data, which is gained through building science communities. With ~400 current members, GeneLab and ALSDA formed Analysis Working Groups (AWGs) to provide feedback on processing pipelines, metadata curation standards (for ‘omics and phenotypic-physiological-behavioral assays), and to collaborate in effectively reusing data. The AWG also led to the development of the Radiation Biology Ontology (RBO), ensuring radiation metadata are efficiently captured, connected, and interoperable. Feedback from the AWG provided design input toward the new single point-of-entry data submission portal for all investigators to submit, curate, and share their research data. Space biological data is now maximally open access, collected-curated with rich metadata, and formatted for interoperability to enable systems biology, meta-analysis, knowledge graphs, machine learning, modeling, and other reuse approaches. With potential for further federation of OSDR for data mining with traditional biological and medical databases (NIH, NCI, EBI, etc.), a new era for space biology has begun to support the knowledge discovery necessary for Lunar and Martian missions.

Ryan T Scott↗

NASA NTRSDate not supplied

Investigating Neighbor Discovery for High-Rate Delay Tolerant Networking

A neighbor discovery protocol that enables the dynamic discovery of nodes for NASA Glenn Research Center’s High Rate Delay Tolerant Networking (HDTN) project is needed to satisfy mission scalability and interoperability objectives. The purpose of this study is to primarily examine a DTN IP neighbor discovery (IPND) implementation to understand the inner workings of the protocol before approaching a neighbor discovery implementation for the HDTN project. Using a rust-based DTN IPND implementation, this study analyzed the neighbor discovery process. DTN IPND was found to help meet both mission scalability and interoperability objectives by enabling dynamic routing capabilities. This study definitively answers the question regarding mission scalability and interoperability concerns. Further studies are needed to establish the most optimal neighbor discovery implementation for HDTN.

Prash Choksi↗

NASA NTRS2023

Flexible User Radio for Lunar Missions

NASA’s Artemis program and other lunar exploration and development programs are planning over 40 lunar missions before 2030. Lunar missions, both crewed and uncrewed, include orbiters, landers, rovers, and surface stations. All these missions require communications with Earth, either via Direct to Earth (DTE) links or through relays in lunar orbit. Multiple DTE options are available among existing and planned ground stations: Deep Space Network (DSN), European Space Agency, and others. Relay options include the planned Lunar Gateway, LunaNet compliant relays, and some lunar landers propose to launch dedicated orbiters. The dilemma for lunar system designers is to identify a communication link which meets mission requirements but does not have issues of limited access (e.g. DSN is in high demand supporting deep space missions with high priority and some with inflexible schedules), system impacts (high power Radio Frequency (RF) for DTE links), cost (dedicated relay), or operational date. To avoid this difficult decision, a Flexible Radio for Lunar Missions is proposed, which will enable system designs to proceed prior to any final decision on the communication network to be used, by enabling compatibility with any of multiple DTE or orbital relay communication systems. The Flexible Radio will support the necessary frequency, bandwidth, modulation, and power requirements to interoperate with the majority of known or planned DTE or relay systems, and can be designed into a lunar mission without prior knowledge of which link will ultimately be used. Furthermore, the link being used can be changed as needed during the mission, in near real time. The Flexible Radio design will leverage work already completed at NASA in the areas of Wideband RF, Software Defined Radio, Adaptive Coding and Modulation, and Phased Array antennas. The Flexible Radio requires sufficient bandwidth to cover the allocated frequencies for both the operation of links in cislunar space and for space-to-Earth links; the flexibility to support multiple modulations, data rates, and coding schemes; the ability to identify available relays, detect and recognize the signals of those relays, and adapt its own frequency, modulation, symbol rate, and code rate to operate with the detected relay (or DTE station); and finally, it requires appropriate software to support network configuration and interoperability with the detected network. The Flexible Radio can be designed in a sufficiently small, lightweight, and low-power package to be used in a wide variety of lunar systems. The initial implementation, as proposed, will focus on the Ka-band, supporting up to 2 GHz bandwidth around the 27 GHz frequency for return links, and 23 GHz for forward links. Other frequency bands are under consideration for future configurations. The software defined modem will support OQPSK, BPSK, and NASA-defined modulations which also support two-way ranging with data. For near-real time adaptation, the Flexible Radio will scan the sky for available relays, using a phased array antenna with Adaptive/Cognitive Communications. It will then configure for network interoperability supporting DTN and other protocol options. The Flexible Radio will support scheduled connections and on-demand use when available.

Lunar Space Communications↗

NASA NTRSDate not supplied

NASA’s Safety, Reliability, and Mission Assurance Digital Future

The evolution from “document-centric” to “data-centric” and “model-centric” information leveraging structured data and model-based approaches is at the heart of digital engineering transformational efforts underway across industry and government. It is these approaches that pave the way for data lakes, Authoritative Sources of Truth (ASOTs), and systems- of-systems interoperability and the corresponding transformational benefits thereof. Such benefits include increased data availability, data access equity, data traceability, real-time analytics, batch analytics, and (most importantly) acceleration of the time-to-value and time-to-insights associated with engineering products and analyses. The longer-term benefits of reusability, customization and traceability are even more promising. For Safety and Mission Assurance (SMA), and Mission Success (SMS) activities; realization of such benefits is essential to provide engineers and analysts alike vital information when needed to support critical decision making throughout the entire life cycle. The SMA community often operate in parallel with engineering activities, for which information exchange with relevant context is paramount. Far too often, such information lags key decision points and/or is absent of the robust, integrated, knowledge needed, given inherent barriers associated with traditional document-centric means to data sharing, analysis, and reporting. This paper provides an overview of how NASA’s Office of Safety and Mission Assurance (OSMA) is evolving its policies, standards, guidance, and training to transform to eliminate such barriers, thus realizing the benefits emerging in this new digital era. A roadmap for achieving this digital future is presented along with key building blocks involving use and implementation of concepts such as: Objectives-Hierarchies, Objective-Driven Requirements, Accepted Standards, Safety and Assurance Cases, data digitization (i.e., ontologies, structured data, and model-centric data), FAIR (Findable, Accessible, Interoperable, & Reusable) and/or FAIRUST (Findable, Accessible, Interoperable, Reusable, Understandable, Secure, and Trusted) principles [1]. This paper also describes how OSMA, leveraging the Agency’s overall commitment to Digital Transformation (DT), is using the power of Policy, “Digital” Domain representation, Product Evolution, and Community Outreach and Engagement as part of a strategic vision and roadmap to evolve and transform its SMA organizations to become better able to serve its stakeholders and customers. Future publications will elaborate on these building blocks and deeper concepts.

Authoritative Source of Truth (ASOT),↗

NASA NTRSDate not supplied

Flexible User Radio for Lunar Missions

NASA’s Artemis program and other lunar exploration and development programs are planning over 40 lunar missions before 2030. Lunar missions, both crewed and uncrewed, include orbiters, landers, rovers, and surface stations. All these missions require communications with Earth, either via Direct to Earth (DTE) links or through relays in lunar orbit. Multiple DTE options are available among existing and planned ground stations: Deep Space Network (DSN), European Space Agency, and others. Relay options include the planned Lunar Gateway, LunaNet compliant relays, and some lunar landers propose to launch dedicated orbiters. The dilemma for lunar system designers is to identify a communication link which meets mission requirements but does not have issues of limited access (e.g. DSN is in high demand supporting deep space missions with high priority and some with inflexible schedules), system impacts (high power Radio Frequency (RF) for DTE links), cost (dedicated relay), or operational date. To avoid this difficult decision, a Flexible Radio for Lunar Missions is proposed, which will enable system designs to proceed prior to any final decision on the communication network to be used, by enabling compatibility with any of multiple DTE or orbital relay communication systems. The Flexible Radio will support the necessary frequency, bandwidth, modulation, and power requirements to interoperate with the majority of known or planned DTE or relay systems, and can be designed into a lunar mission without prior knowledge of which link will ultimately be used. Furthermore, the link being used can be changed as needed during the mission, in near real time. The Flexible Radio design will leverage work already completed at NASA in the areas of Wideband RF, Software Defined Radio, Adaptive Coding and Modulation, and Phased Array antennas. The Flexible Radio requires sufficient bandwidth to cover the allocated frequencies for both the operation of links in cislunar space and for space-to-Earth links; the flexibility to support multiple modulations, data rates, and coding schemes; the ability to identify available relays, detect and recognize the signals of those relays, and adapt its own frequency, modulation, symbol rate, and code rate to operate with the detected relay (or DTE station); and finally, it requires appropriate software to support network configuration and interoperability with the detected network. The Flexible Radio can be designed in a sufficiently small, lightweight, and low-power package to be used in a wide variety of lunar systems. The initial implementation, as proposed, will focus on the Ka-band, supporting up to 2 GHz bandwidth around the 27 GHz frequency for return links, and 23 GHz for forward links. Other frequency bands are under consideration for future configurations. The software defined modem will support OQPSK, BPSK, and NASA-defined modulations which also support two-way ranging with data. For near-real time adaptation, the Flexible Radio will scan the sky for available relays, using a phased array antenna with Adaptive/Cognitive Communications. It will then configure for network interoperability supporting DTN and other protocol options. The Flexible Radio will support scheduled connections and on-demand use when available.

Lunar Space Communications↗

NASA NTRSDate not supplied

Objective Structured Clinical Evaluation (OSCE) of an Artificial Intelligence (AI) Clinical Decision Support System (CDSS) Tool

BACKGROUND Objective Structured Clinical Evaluations (OSCEs) have long been established as a robust methodology for summative assessment of clinical skills and decision-making during medical education. The recent integration of Artificial Intelligence (AI) into clinical decision-making processes has prompted the need for novel evaluation frameworks to assess the efficacy and reliability of AI clinical decision support system (CDSS) tools. This abstract outlines the process of quantitatively evaluating a novel CDSS (“Doc in a Box” Google 2024) trained on curated medical spaceflight data in the psychomotor domain as it interfaces with a human volunteer acting as the crew medical officer (CMO). PURPOSE The AI CDSS under review was developed as part of the Lunar Command and Control Interoperability (LuCCI) project, which is intended to address a gap in how Lunar Surface Systems (LSS) would interoperate across multiple programs, commercial partners, and international partners. The project objective is to define, prototype, integrate, and evaluate an interoperable lunar command, control, data, and software reference architecture to enable autonomy and informatics capability through common standards across LSS. A multi-modal AI-based CDSS compatible with Federated LSS will assist clinicians in diagnosing and managing complex medical conditions by providing evidence-based recommendations through predictive analytics. Given the critical role of decision-support as NASA continues to evolve its Earth-independent medical operations (EIMO), it is imperative to ensure that such AI tools perform reliably and align with clinical standards during progressive lunar and Martian exploration class missions. METHODS The OSCE framework, traditionally used for evaluating human clinicians, was adapted to assess the AI tool's decision-making capabilities in simulated clinical scenarios. In this adapted OSCE, the AI CDSS was tested across a series of structured clinical scenarios designed to mimic real-life spaceflight patient cases. These scenarios included a range of conditions and complexities, allowing for comprehensive assessment of the tool's performance. Key evaluation metrics included accuracy of diagnosis, timeliness of decision-making, and appropriate recommendations for therapies. The OSCE was scored by human physician evaluators who assessed the AI's recommendations in comparison with expert clinicians' medical decision making to ensure alignment with best practices and the standard of care. RESULTS Preliminary results indicate that the AI CDSS demonstrated high accuracy in diagnostic recommendations and decision support across various scenarios. However, certain limitations were noted, such as occasional discrepancies in handling complex or nuanced cases that required a more contextual understanding. Additionally, the tool scored higher on the diagnostic portion of the rubric, with lower scores in the therapeutic recommendations. These findings highlight the importance of continuous refinement and validation of AI tools through rigorous evaluation frameworks like the OSCE. The adaptation of OSCEs for AI tools presents several advantages, including a structured and reproducible approach to evaluation, the ability to test AI systems in diverse clinical scenarios, and the opportunity to benchmark AI performance against established clinical standards to permit charting of future progress as aerospace medicine evolves as a discipline. Remaining challenges include ensuring that these evaluations capture the full spectrum of clinical decision-making scenarios that will be confronted by CMOs during missions and adequately reflecting real-world variability of the austere spaceflight environment. CONCLUSION Employing OSCEs to evaluate AI clinical decision support tools offers a promising approach to validating their clinical utility and efficacy. This methodology not only provides insights into the tool's performance but also fosters ongoing improvement and alignment with standard of care practices. Future research should focus on refining these evaluation processes and addressing limitations to enhance the integration of AI tools in clinical spaceflight settings. REFERENCES Scott S, Hearns V, Barker MA. Testing Clinical Skills: A Look at the OSCE and USMLE Clinical Skills Exams. S D Med. 2019 Oct;72(10):451-453. Majumder MAA, Kumar A, Krishnamurthy K, Ojeh N, Adams OP, Sa B. An evaluative study of objective structured clinical examination (OSCE): students and examiners perspectives. Adv Med Educ Pract. 2019 Jun 5;10:387-397. Karam VY, Park YS, Tekian A, Youssef N. Evaluating the validity evidence of an OSCE: results from a new medical school. BMC Med Educ. 2018 Dec 20;18(1):313.

Ariana M Nelson↗

DOE OSTI2022

A Blockchain Based Co-Simulation Framework for Integrating DERs to Wholesale Electricity Markets

As the number of distributed energy resources (DERs) continue to increase across energy-delivery systems, there remains a need for integrating their capabilities into traditional grid operations. In this paper, a blockchain-based solution is proposed to facilitate FERC's Order No. 2222 implementations. The presented use-case enables small-scale DERs to participate in wholesale market operations through DER aggregators, while also enabling local distribution system operators to enforce distribution system constraints in a secure and traceable manner. The presented use case is built around the Unified Testing Platform (UTP) being developed as a part of the Blockchain for Optimized Security and Energy Management (BLOSEM) project. This is a multi-lab effort intended to simplify the deployment of blockchain-powered grid solutions by enabling the integration of simulation tools, and blockchain technologies through the use of system-agnostic interfaces that provide a modular, interoperable, and reusable connectivity layer.

blockchain interoperability↗

DOE OSTI2015

IEEE 1547 Standards Advancing Grid Modernization

Technology advances including development of advanced distributed energy resources (DER) and grid-integrated operations and controls functionalities have surpassed the requirements in current standards and codes for DER interconnection with the distribution grid. The full revision of IEEE Standards 1547 (requirements for DER-grid interconnection and interoperability) and 1547.1 (test procedures for conformance to 1547) are establishing requirements and best practices for state-of-the-art DER including variable renewable energy sources. The revised standards will also address challenges associated with interoperability and transmission-level effects, in addition to strictly addressing the distribution grid needs. This paper provides the status and future direction of the ongoing development focus for the 1547 standards.

1547↗

DOE OSTI2016

FY16 ASC ATDM L2 Milestone: PARTISN Research and FleCSI Updates

These are slides for a presentation on PARTISN Research and FleCSI Updates. The following topics are covered: SNAP vs PARTISN, Background Research, Production Code (structural design and changes, kernel design and implementation, lessons learned), NuT IMC Proxy, FleCSI Update (design and lessons learned). It can all be summarized in the following manner: Kokkos was shown to be effective in FY15 in implementing a C++ version of SNAP's kernel. This same methodology was applied to a production IC code, PARTISN. This was a much more complex endeavour than in FY15 for many reasons; a C++ kernel embedded in Fortran, overloading Fortran memory allocations, general language interoperability, and a fully fleshed out production code versus a simplified proxy code. Lessons learned are Legion. In no particular order: Interoperability between Fortran and C++ was really not that hard, and a useful engineering effort. Tracking down all necessary memory allocations for a kernel in a production code is pretty hard. Modifying a production code to work for more than a handful of use cases is also pretty hard. Figuring out the toolchain that will allow a successful implementation of design decisions is quite hard, if making use of "bleeding edge" design choices. In terms of performance, production code concurrency architecture can be a virtual showstopper; being too complex to easily rewrite and test in a short period of time, or depending on tool features which do not exist yet. Ultimately, while the tools used in this work were not successful in speeding up the production code, they helped to identify how work would be done, and provide requirements to tools.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Tsdat: An Open-Source Data Standardization Framework for Marine Energy and Beyond

Many organizations are tasked with the collection and processing of large quantities of data from various measurement devices. Data reported from these sources are often not interoperable with datasets and software used by analysts and other organizations in the same domain, introducing barriers for collaboration on large-scale projects. This poses a particular problem for cross-device comparisons and machine learning applications, which rely on large quantities of data from multiple sources. To address these challenges, the open-source Time-Series Data Pipelines (Tsdat) Python framework was developed by Pacific Northwest National Laboratory, with strategic guidance and direction provided by the National Renewable Energy Laboratory and Sandia National Laboratories to facilitate collaboration and accelerate advancements in the marine energy domain through the development of an open-source ecosystem of tools. This paper will describe the Tsdat framework and the data standards within which it operates. A beta version of Tsdat has been released and is being used by several projects in marine energy, wind energy, and building energy systems.

big data↗

DOE OSTI2023

Overview on Transactive Energy—Advantages and Challenges for Weak Power Grids

This document lists some challenges that researchers face when implementing transactive energy in weak power grids. These challenges often include high voltage fluctuations, limited generation, high line loadability, and unbalanced grids. The operation of transactive energy, as well as optimization techniques, are also considered, highlighting the performance and functionalities depending on power grid characteristics and market topology. Some of the most used optimization techniques for market clearing, considering the characteristics and topology, are presented as part of the research work. In addition, this paper compares different market topologies and highlights their advantages and challenges. Furthermore, this paper contains a brief description of the interoperability frameworks applied to a smart grid. As a result, it was determined that interoperability is necessary for the proper functioning of the grid. Moreover, all methods were found to be effective for their purpose from the user’s point of view as each technique has different characteristics relevant to the user and the grid. It was concluded that it is convenient to combine the optimization techniques to consider different constraints in the market clearing.

14 SOLAR ENERGY↗

DOE OSTI2021

A restructured and updated global soil respiration database (SRDB-V5)

Field-measured soil respiration (R S , the soil-to-atmosphere CO 2 flux) observations were compiled into a global soil respiration database (SRDB) a decade ago, a resource that has been widely used by the biogeochemistry community to advance our understanding of R S dynamics. Novel carbon cycle science questions require updated and augmented global information with better interoperability among datasets. Here, we restructured and updated the global R S database to version SRDB-V5. The updated version has all previous fields revised for consistency and simplicity, and it has several new fields to include ancillary information (e.g., R S measurement time, collar insertion depth, collar area). The new SRDB-V5 includes published papers through 2017 (800 independent studies), where total observations increased from 6633 in SRDB-V4 to 10 366 in SRDB-V5. The SRDB-V5 features more R S data published in the Russian and Chinese scientific literature and has an improved global spatio-temporal coverage and improved global climate space representation. We also restructured the database so that it has stronger interoperability with other datasets related to carbon cycle science. For instance, linking SRDB-V5 with an hourly timescale global soil respiration database (HGRsD) and a community database for continuous soil respiration (COSORE) enables researchers to explore new questions. The updated SRDB-V5 aims to be a data framework for the scientific community to share seasonal to annual field R S measurements, and it provides opportunities for the biogeochemistry community to better understand the spatial and temporal variability in R S , its components, and the overall carbon cycle.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Bridging Control and Deployment: A Cross-Layer Analysis of Scalable Building Cluster Control

Building cluster control has emerged as a promising approach for enabling flexible and coordinated operation of distributed building systems, yet its transition from pilot demonstrations to routine grid-interactive operation remains limited. This paper argues that this gap cannot be explained by control algorithms alone. Instead, it arises from interacting barriers in communication infrastructure, data and semantic interoperability, uncertainty management, stakeholder participation, market design, and policy support. Accordingly, the paper reviews both technical and non-technical barriers to building cluster control. Technical challenges include heterogeneous devices and protocols, communication latency and reliability, distributed decision-making, and uncertainty propagation across aggregated loads. Non-technical barriers include user participation, stakeholder coordination, incentive allocation, and data governance. Existing solution approaches are synthesized, including semantic interoperability frameworks, edge and hierarchical communication architectures, distributed and transactive control strategies, uncertainty-aware optimization, policy mechanisms, and market reforms. Based on this analysis, two research directions are identified: testing infrastructures that can evaluate control performance under realistic multi-building conditions, and abstraction methods that allow building clusters to interact with other energy sectors through standardized flexibility representations. Overall, the paper provides a structured review of how building cluster control can move from isolated demonstrations toward reproducible, market-compatible, and grid-relevant implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRSDate not supplied

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

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

Life Sciences data↗

NASA NTRSDate not supplied

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

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

Life Sciences data↗

NASA NTRSDate not supplied

A Discussion of Time Management Concepts and Time Constraint Equations for Multi-Rate Federation Executions

The High Level Architecture (HLA) is a simulation interoperability standard developed by the Simulation Interoperability Standards Organization (SISO) and published as the international standard IEEE 1516-2010 by the Institute for Electrical and Electronics Engineers (IEEE). HLA is a widely used standard for the development and execution of collaborative distributed simulations. HLA provides a number of Management Services to simulation developers: Federation, Declaration, Object, Ownership, Data Distribution, and Time. Of those services, Time Management Services is probably one of the least understood and least used. However, Time Management Services are critical to technical simulations like those created for space systems using the Space Reference Federation Object Model (SpaceFOM). Time Management can be used to insure data coherence and execution repeatability in distributed simulations. When combined with real time execution policies, Time Management is being used to support real time execution of mixed software and hardware in the loop integration, verification, and validation simulations for active space systems development. This paper starts by providing an overview of the HLA Time Management Services. This provides the background to discuss the challenges associated with Time Management and its use, starting with simple common rate frame scheduled simulations, then simple multi-rate simulations, and ending with complex mixed rate simulations. The authors then formulate the significant time constraint relationships between identified frame scheduling parameters. The intent of the paper is to provide a concise discussion of how to use Time Management in both simple cases and in more complex mixed frame rate federation executions.

Simulation Interoperability↗

NASA NTRSDate not supplied

A Discussion of Time Management Concepts and Time Constraint Equations for Multi-Rate Federation Executions

The High Level Architecture (HLA) is a simulation interoperability standard developed by the Simulation Interoperability Standards Organization (SISO) and published as the international standard IEEE 1516-2010 by the Institute for Electrical and Electronics Engineers (IEEE). HLA is a widely used standard for the development and execution of collaborative distributed simulations. HLA provides a number of Management Services to simulation developers: Federation, Declaration, Object, Ownership, Data Distribution, and Time. Of those services, Time Management Services is probably one of the least understood and least used. However, Time Management Services are critical to technical simulations like those created for space systems using the Space Reference Federation Object Model (SpaceFOM). Time Management can be used to insure data coherence and execution repeatability in distributed simulations. When combined with real time execution policies, Time Management is being used to support real time execution of mixed software and hardware in the loop integration, verification, and validation simulations for active space systems development. This paper starts by providing an overview of the HLA Time Management Services. This provides the background to discuss the challenges associated with Time Management and its use, starting with simple common rate frame scheduled simulations, then simple multi-rate simulations, and ending with complex mixed rate simulations. The authors then formulate the significant time constraint relationships between identified frame scheduling parameters. The intent of the paper is to provide a concise discussion of how to use Time Management in both simple cases and in more complex mixed frame rate federation executions.

Simulation Interoperability↗