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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

TOLNet’s FAIR Journey: Yesterday, Today, and Tomorrow

The Tropospheric Ozone Lidar Network (TOLNet) has generated over a decade of ozone vertical profile data products over North America and contributed to several air quality focused field studies. The science value of the TOLNet data has been demonstrated in numerous peer-reviewed publications on air quality and ozone relevant research. As the broad scientific community has moved towards adopting FAIR Principles to make data more findable, accessible, interoperable, and (re)usable, the TOLNet team has been consistently making data more FAIR. This effort has many challenges, partially reflecting on the FAIR principles being domain agnostic while the implementation needs to be domain specific. The FAIR principles declare the dependence on the community standards, domain-relevant metadata, and rich metadata. This presentation uses the TOLNet data and data system as an example to explore the best practices to implement FAIR principle. Particularly, we will examine the metadata and the “richness” to support findability and usability as well as machine-to-machine actionability via API. Last year, as part of our FAIR journey, we launched the TOLNet website (https://tolnet.larc.nasa.gov/) and the API (https://tolnet.larc.nasa.gov/api/). Part of this process included extracting and cataloging metadata across the entire TOLNet mission timeframe. This enabled users to search through the mission by various metadata criteria, improving the findability and accessibility. And computers could connect directly to the TOLNet API to extract both metadata and data, providing a level of interoperability never present before for TOLNet data. On top of that, all new TOLNet data is now automatically validated using the API to ensure it complies with GEOMS standards, aiding in reusability. It takes both technology and scientists working together to make progress. The next step is to evaluate the current TOLNet offerings against NASA’s Practical Guide for Open, Free & FAIR NASA Earth Science Data Products (https://doi.org/10.5067/DOC/ESCO/ESDSWG-0002V1).

TOLNet↗

DOE OSTI2026

Universal Workflow Language and Software Enable Geometric Learning and FAIR Scientific Protocol Reporting

Written language and conventional data structures for representing scientific procedures suffer from low process detail, often fail to accurately represent protocols, and lack universality. New strategies for the handling of experimental data are needed to provide viable process information for both humans and machines. In this work, we present the universal workflow language (UWL) and interface (UWLi). UWL is a findable, accessible, interoperable, and reusable (FAIR)-compatible, graph-based data architecture that can capture arbitrary scientific procedures through workflow representation, and UWLi is an accompanying software package for building, manipulating, and interpreting UWL entries. The UWL format was found to be highly effective in identifying deficiencies in the reported process details of high-impact, peer-reviewed scientific journals, and in simulated scenarios, the graph format was shown to be more effective than conventional methods in predictively modeling the outcome of diverse scientific protocols. Implementation of UWL could enable more accurate scientific communication and more impactful process datasets.

14 SOLAR ENERGY↗

DOE OSTI2024

BindingDB in 2024: a FAIR knowledgebase of protein-small molecule binding data

Abstract BindingDB (bindingdb.org) is a public, web-accessible database of experimentally measured binding affinities between small molecules and proteins, which supports diverse applications including medicinal chemistry, biochemical pathway annotation, training of artificial intelligence models and computational chemistry methods development. This update reports significant growth and enhancements since our last review in 2016. Of note, the database now contains 2.9 million binding measurements spanning 1.3 million compounds and thousands of protein targets. This growth is largely attributable to our unique focus on curating data from US patents, which has yielded a substantial influx of novel binding data. Recent improvements include a remake of the website following responsive web design principles, enhanced search and filtering capabilities, new data download options and webservices and establishment of a long-term data archive replicated across dispersed sites. We also discuss BindingDB’s positioning relative to related resources, its open data sharing policies, insights gleaned from the dataset and plans for future growth and development.

Liu, Tiqing↗

NASA NTRSDate not supplied

An Overview of NASA’s Catalog of Archived Suborbital Earth Science Investigations (CASEI): Supporting FAIR and Open Access to Airborne and Field Data

Since 2019, NASA’s Airborne Data Management Group (ADMG) within the Interagency Implementation and Advanced Concepts Team (IMPACT) has worked to promote and ensure the discoverability and accessibility of the agency’s non-satellite Earth science observations. A primary component of this effort is the development of NASA’s Catalog of Archived Suborbital Earth Science Investigations (CASEI) and the vetting of key contextual details required to sustain this unique inventory of airborne and field metadata. CASEI provides information on the science objectives motivating data collection, key events/time periods in the observational record aligned with the science objectives, complementary simultaneous observations, programmatic details, and much more. The diverse set of data formats and disciplines served by CASEI have required the implementation of a common data model to organize suborbital observation metadata and efficiently connect appropriate campaigns, platforms, and instruments. The CASEI inventory provides a single entry point for users to search and browse NASA’s airborne and field data archives, regardless of which repository is responsible for their stewardship. This presentation will provide a summary of the motivations for and the development of the CASEI system. Particular attention will be granted to how CASEI facilitates discovery and reuse of these lesser-known NASA data, supporting the Open Science vision and enhancing the return on investments made to collect these unique and varied observations. An up-to-date summary of CASEI inventory content and initial metrics will be provided. Current and future avenues ADMG is pursuing to enhance both CASEI and specific components of suborbital data stewardship at various stages of the data life cycle will also be discussed.

Stephanie M. Wingo↗

NASA NTRS1975

Quantitative suspended sediment mapping using aircraft remotely sensed multispectral data

Suspended sediment is an important environmental parameter for monitoring water quality, water movement, and land use. Quantitative suspended sediment determinations were made from analysis of aircraft remotely sensed multispectral digital data. A statistical analysis and derived regression equation were used to determine and plot quantitative suspended sediment concentration contours in the tidal James River, Virginia, on May 28, 1974. From the analysis, a single band, Band 8 (0.70-0.74 microns), was adequate for determining suspended sediment concentrations. A correlation coefficient of 0.89 was obtained with a mean inaccuracy of 23.5 percent for suspended sediment concentrations up to about 50 mg/l. Other water quality parameters - secchi disc depth and chlorophyll - also had high correlations with the remotely sensed data. Particle size distribution had only a fair correlation with the remotely sensed data.

Johnson, R. W.↗

NASA NTRS1989

Large scale advanced propeller blade pressure distributions - Prediction and data

Two Euler analysis techniques, finite difference and finite volume, are employed to predict the blade surface pressure distributions of a large scale advanced propeller. The predicted pressure distributions are compared with wind tunnel data. Both techniques produced blade pressure distributions which are in fairly good agreement with the data over the range of test Mach numbers of 0.2 to 0.78. However, the numerical simulations fail to predict correctly the measured pressure distributions for the low Mach number, high power case which seem to have a leading edge vortex. A discussion of the compressibility effects is also presented.

Nallasamy, M.↗

NASA NTRS1989

Large-scale advanced propeller blade pressure distributions: Prediction and data

Two Euler analyses techniques, finite difference and finite volume, were employed to predict the blade surface pressure distributions of a large scale advanced propeller. The predicted pressure distributions were compared with wind tunnel data. Both techniques produced blade pressure distributions that are in fairly good agreement with the data over the range of test Mach numbers of 0.2 to 0.78. However, the numerical simulations fail to predict correctly the measured pressure distributions for the low Mach number, high power case. The data indicate the presence of a leading edge vortex for this case. A discussion of the compressibility effects is also presented.

Nallasamy, M.↗

NASA NTRSDate not supplied

Blast from the Past: ASDC Curation for NASA Suborbital Legacy Missions to Promote Data Discovery and Accessibility

NASA has an extensive history of conducting suborbital field campaigns to further advances in atmospheric sciences. Beginning with the Chemical Instrument Test and Evaluation (CITE) conducted in 1983-1984, NASA has completed many suborbital campaigns over the past three decades. Since the early 2010s, suborbital missions are typically assigned to a NASA Distributed Active Archive Center (DAAC) prior to the mission for long-term archival and distribution. Efforts are being made by NASA’s Earth Science Data and Information System (ESDIS) Project and the Airborne Data Management Group (ADMG) to assign legacy missions to DAACs for permanent archival and distribution, so that these valuable datasets remain to be available to the scientific community. NASA’s Atmospheric Science Data Center (ASDC) has been named the assigned DAAC for nearly 20 atmospheric composition legacy missions, including missions conducted as part of the Global Tropospheric Experiment (GTE) and expects to be named the assigned DAAC for more of these missions over the next few years. The primary goal of the ASDC is to provide access to the datasets as they are currently formatted to the broad user community and enhance their findability and accessibility. However, data reporting standards have evolved significantly since 1983 and the datasets span a wide variety of file formats, including text, Ames, GTE, and ICARTT (International Consortium for Atmospheric Research on Transport and Transformation), and the amount of metadata and relevant information included in the files also varies greatly and can not be readily extracted without subject matter knowledge. This has caused challenges for the ASDC’s suborbital metadata extraction pipeline in ensuring that accurate and necessary metadata is being provided for the missions by all the ASDC’s existing search mechanisms. To make the data more findable and accessible, the ASDC has begun researching ways to further enhance the datasets, including distributing value-added products (i.e. consistent file format such as ICARTT or netCDF), adding standard names from the ESDIS Standards Coordination Office (ESCO)-approved Atmospheric Composition Variable Standard Names Convention (ACVSNC), and creating outreach materials such as ArcGIS StoryMaps, User Guides, and Micro Articles, providing overviews of the missions and what type of data was collected during the missions. These efforts also help support NASA’s Open-Source Science by enhancing the FAIRness of the legacy data products. This presentation will review the ASDC’s ongoing efforts, progress made, and future plans for legacy missions.

Megan Buzanowicz↗

NASA NTRS2000

Experimental and Numerical Investigation of Losses in Low-Pressure Turbine Blade Rows

Experimental data and numerical simulations of low-pressure turbines have shown that unsteady blade row interactions and separation can have a significant impact on the turbine efficiency. Measured turbine efficiencies at takeoff can be as much as two points higher than those at cruise conditions. Several recent studies have revealed that the performance of low-pressure turbine blades is a strong function of the Reynolds number. In the current investigation, experiments and simulations have been performed to study the behavior of a low-pressure turbine blade at several Reynolds numbers. Both the predicted and experimental results indicate increased cascade losses as the Reynolds number is reduced to the values associated with aircraft cruise conditions. In addition, both sets of data show that tripping the boundary layer helps reduce the losses at lower Reynolds numbers. Overall, the predicted aerodynamic and performance results exhibit fair agreement with experimental data.

Dorney, Daniel J.↗

DOE OSTI2025

FedEFsz: Fair Cross-Silo Federated Learning System With Error-Bounded Lossy Compression

Cross-Silo federated learning systems have been identified as an efficient approach to scaling DNN training across geographically-distributed data silos to preserve the privacy of the training data. Communication efficiency and fairness are two major issues that need to be both satisfied when federated learning systems are deployed in practice. Simultaneously guaranteeing both of them, however, is exceptionally difficult because simply combining communication reduction and fairness optimization approaches often causes non-converged training or drastic accuracy degradation. Here, to bridge this gap, we propose FedEFsz. On the one hand, it integrates the state-of-the-art error-bounded lossy compressor SZ3 into cross-silo federated learning systems to significantly reduce communication traffic during the training. On the other hand, it achieves a high fairness (i.e., rather consistent model accuracy and performance across different clients) through a carefully designed heuristic algorithm that can tune the error-bound of SZ3 for different clients during the training. Extensive experimental results based on a GPU cluster with 65 GPU cards show that FedEFsz improves the fairness across different benchmarks by up to 60.88% and meanwhile reduces the communication traffic by up to 315×.

Cross-Silo Federated Learning Systems↗

NASA NTRS1972

Fuel droplet burning rates at high pressures

Combustion of methanol, ethanol, propanol -1, n - pentane, n - heptane and n - decane was observed in air under natural convection conditions at pressures up to 100 atm. The droplets were simulated by porous spheres with diameters in the range 0.63 - 1.90 cm. The pressure levels of the tests were high enough so that near critical combustion was observed for methanol and ethanol. Measurements were made of the burning rate and liquid surface temperatures of the fuels. The data were compared with variable property analysis of the combustion process, including a correction for natural convection. The burning rate predictions of the various theories were similar and in fair agreement with the data. The high pressure theory gave the best prediction for the liquid surface temperatures of ethanol and propanol -1 at high pressure. The experiments indicated the approach of critical burning conditions for methanol and ethanol at pressures on the order of 80 - 100 atm, which was in good agreement with the predictions of both the low and high pressure analysis.

Canada, G. S.↗

NASA NTRSDate not supplied

Expanding Repository Data Available For Sharing and Knowledge Discovery

Some of the hardest space biology and space health challenges require data-intensive, bioinformatic, meta-analytical, and computer-assisted research approaches. These challenges include examining interdisciplinary space life science research across experiments and across interacting spaceflight hazards (radiation, altered gravity, confinement, hostile-closed environments, distance-duration from Earth). The approaches to confront these challenges involve mining multiple datasets simultaneously from various hierarchical organizations of biological complexity, all while concurrently evaluating how experimental design factors affect endpoints of standard assays. To enable this field, it is essential that principal investigators (PIs) submit data in a structure so it can be maximally re-used. The purpose of the NASA Ames Life Sciences Data Archive (ALSDA) is to collect, curate, and make publicly available all non-human space-relevant biological data. ALSDA must also ensure data are open-access, and maximally findable, accessible, interoperable, and reusable (FAIR). The scope of ALSDA data collected and submitted by PIs include subject and study design metadata, assay metadata parameters, raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). ALSDA recently integrated into a collaborative group of Open Science projects to facilitate a suite of new tools and workflows that will improve data submission, accessibility, and reusability by implementing digital data submission agreements, and adopting the data management system originally developed by NASA GeneLab. ALSDA intends to bring current biological repository data and all future collected data into this new scientific data reuse reality. This new suite of tools will enable ALSDA to deploy a science curation system using scientific assay configurations for the data submission portal. It will capture essential assay parameters according to established standards in each sub-field within biology. The submission portal expedites data collection by enhancing ease of PI data submission, providing a user interface and specificity for which data is to be submitted. Data submissions can be brought into cutting-edge informatic analysis portals to enable mining of physiological, behavioral, biochemical, and imaging datasets in conjunction with ‘omics-level datasets. As ALSDA datasets are submitted, curated, and published (e.g., micro-computed tomography, histology, pulse oximetry, serum metabolites, magnetic resonance imaging, intraocular pressure, novel object recognition, etc.), the merging together of spaceflight data along this multi-hierarchical complexity of biology will enable informatics and data-intensive approaches resulting in knowledge discoveries across missions, space hazards, and biological disciplines.

Biology↗

NASA NTRSDate not supplied

Expanding Repository Data Available For Sharing And Knowledge Discovery

life science↗

NASA NTRS1986

Simultaneous rocket and MST radar observation of an internal gravity wave breaking in the mesosphere

In June, 1983, the Structure and Atmospheric Turbulence Environment (STATE) rocket and Poker Flat Mesophere-Stratosphere-Troposphere radar campaign was conducted to measure the interaction between turbulence, electron density and electron density gradient that has produced unusually strong MST radar echoes from the summer mesosphere over Poker Flat, Alaska. Analysis or radar wind measurements and a concurrent wind and temperature profile obtained from a rocket probe carrying a three-axis accelerometer are given. The two data sets provide a fairly complete (and in some cases, redundant) picture of the breaking (or more correctly, the saturation) of a large-amplitude, low-frequency, long-wavelength internal gravity wave. The data show that small-scale turbulence and small-scale wave intensity is greatest at those altitudes where the large-scale wave-induced temperature lapse rate is most negative or most nearly unstable, but the wind shear due to the large-scale wave is a minimum. A brief review of linear gravity-wave theory is presented as an aid to the identification of the gravity-wave signature in the radar and rocket data. Analysis of the time and height cross sections of wind speed and turbulence intensity observed by the Poker Flat MST radar follows. Then, the vertical profile of temperature and winds measured by a rocket probe examined. Finally, the use of the independent data sets provided by the rocket and the radar are discussed and implications for theories of wave saturation are presented.

Smith, S. A.↗

NASA NTRS1951

Dynamics of a turbojet engine considered as a quasi-static system

A determination of the dynamic characteristics of a typical turbojet engine with a centrifugal compressor, a sonic-flow turbine-nozzle diaphragm, and fixed area exhaust nozzle is presented. A generalized equation for transient behavior of the engine was developed; this equation was then verified by calculations using compressor and turbine performance charts extrapolated from equilibrium operating data and by experimental data obtained from an engine operated under transients in fuel flow. The results indicate that a linear differential equation for engine acceleration as a function of fuel flow and engine speed for operation near a steady-state operating condition can be written. The coefficients of this equation can be obtained either from actual transient data or, with a fair degree of accuracy, from the steady-state performance maps of the compressor and turbine, and can be corrected for altitude in the same manner that steady-state performance data are corrected.

Otto, Edward W↗

NASA NTRS1991

Flight experiments measuring boundary-layer disturbances in laminar flow and correlation with stability analysis

Flight test results are reported from an experiment designed to study the detailed growth of disturbances in the laminar boundary layer. A gloved wing section incorporating closely-spaced flush-mounted streamwise-located instrumentation for measuring instability frequencies and amplitude growths as well as pressure distributions was used. The growth of Tollmien-Schlichting (T-S) and crossflow instabilities is predicted by the linear e exp n method and compared to the measured boundary-layer disturbance frequencies. The predictions showed good agreement with the measured data. The results exhibited fair agreement with previous n(T-S) and n(CF) flight correlations for several of the conditions analyzed. It is inferred from the high n(T-S) values for these data that moderately swept wings at compressible speeds can withstand higher combinations of n(T-S) and n(CF) values and still remain laminar than previously thought.

Lee, Cynthia C.↗

NASA NTRS2001

Analysis and Quality Assurance of the SKYMAP 4.0 Guidance and Tracking Star Catalog: The NASA SKY2000 Spacecraft Attitude Determination Star Catalog

An updated and improved NASA spacecraft attitude determination catalog, now called SKY2000, Version 3, has been prepared and quality assured. The highest priority goals were to replace the astrometric (positions and motions) and photometric (brightnesses and colors) data with the most recent and accurate data available. Quality assurance has been performed in a fairly straightforward manner, i.e., without extensive data checking and analysis, and many errors and Inconsistencies were corrected. Additional work should eventually be done on the variability and multiple-star data In the catalog, while certain other data can be significantly Improved. The current version of the catalog can be found at the GSFC Flight Dynamics website: http://cheli.gsfc.nasa.gov/dist/attitude/skymap.html. Supporting information and reference materials (published papers, format and data descriptions, etc.) can also be found at the website.

Warren, Wayne H., Jr.↗