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DOE OSTI2025

Datum: A Scientific Metadata Catalog

The data catalog market is currently flooded with a myriad of different products, but none serve the scientific community well. There are cloud-native tools like Databricks, Snowflake,to on-premise solutions like Collibra and Datahub. The common failing of all these tools however, is their inability to serve the scientific data community directly. Most catalogs are targeted towards financial, health, or user data - not sensor or scientific domain data. They also prioritize integrations that often don’t exist or are just starting to be used in the scientific realm - all while ignoring common scientific tools and file types. Datum is a catalog which targets the scientific data directly, including the tools and networks in which those tools are used. We work with the producers and consumers of the data where they are, targeting cloud and on-premise with a focus on classified networks. Datum is an Erlang/Elixir application. Technical Features Note: The features listed below are still under development and may change, slightly, upon final delivery of the product. File Formats - Datum has the ability to read additional metadata and provides processing pipelines for the following file formats: Plain Text, PDF, LaTeX, HTML, Open Document Format (.odt), XML, CSV/TSV (and other standard delimiters), OpenDocument Database and Spreadsheets, Geo-Referenced TIFF, Common Data Format, HDF/HDF5, LabView TDMS, Excel, DeltaTables, Parquet, Apache Iceberg, Apache Hudi and many others. Metadata Collection - Scanners for the local and networked file systems and cloud storage providers. Network integration with common databases such as MSSQL and MySQL. User Plugin System - Users are able to provide either file processing, metadata extraction, or sampling plugins in the programming language of their choice. Authentication/Authorization -: OIDC integration, SCIM provisioning and EntraID integration out of the box. Full user and group management system with a “least privilege” operating mode. Governance - Customizable data governance platform; dictate and enforce required metadata, enforce data embargos, and enforce user agreements and NDAs before data access. Ability to create health checks on data, rejecting abandoned or poorly curated data and automatically removing it from the search index. Ability for users to submit corrections. Search - Semantic search is a first class citizen. No licenses to expensive, external software required. Integrated use of vectors and vector-based search allows for AI agent integration at all levels of operation. Metadata Model - Display and control data’s lineage and connections to other data and data directories. Data is modeled after a filesystem - an organization instantly recognizable and navigable by most any user. CLI and SDK - Ships with a Command Line Interface (CLI) tool and with a fully-featured Python SDK. This allows for rapid and programmatic use of Datum by every level of user. Minimal Infrastructure - Datum ships as a single executable file and can be run on any operating system and most CPU architectures. Datum has no reliance on external databases, search indexing tools, or other outside services - and it runs equally well on edge computing devices, cloud services, or in a clustered HPC environment.

darrington, john↗

NASA NTRS2008

GIDEP Batching Tool

This software provides internal, automated search mechanics of GIDEP (Government- Industry Data Exchange Program) Alert data imported from the GIDEP government Web site. The batching tool allows the import of a single parts list in tab-delimited text format into the local JPL GIDEP database. Delimiters from every part number are removed. The original part numbers with delimiters are compared, as well as the newly generated list without the delimiters. The two lists run against the GIDEP imports, and output any matches. This feature only works with Netscape 2.0 or greater, or Internet Explorer 4.0 or greater. The user selects the browser button to choose a text file to import. When the submit button is pressed, this script will import alerts from the text file into the local JPL GIDEP database. This batch tool provides complete in-house control over exported material and data for automated batch match abilities. The batching tool has the ability to match capabilities of the parts list to tables, and yields results that aid further research and analysis. This provides more control over GIDEP information for metrics and reports information not provided by the government site. This software yields results quickly and gives more control over external data from the government site in order to generate other reports not available from the external source. There is enough space to store years of data. The program relates to risk identification and management with regard to projects and GIDEP alert information encompassing flight parts for space exploration.

Fong, Danny↗

NASA NTRS1970

A computer-controlled scintiscanning system and associated computer graphic techniques for study of regional distribution of blood flow.

Two methods whereby a digital computer may be used to regulate a scintiscanning process are discussed from the viewpoint of computer input-output software. The computer's function, in this case, is to govern the data acquisition and storage, and to display the results to the investigator in a meaningful manner, both during and subsequent to the scanning process. Several methods (such as three-dimensional maps, contour plots, and wall-reflection maps) have been developed by means of which the computer can graphically display the data on-line, for real-time monitoring purposes, during the scanning procedure and subsequently for detailed analysis of the data obtained. A computer-governed method for converting scintiscan data recorded over the dorsal or ventral surfaces of the thorax into fractions of pulmonary blood flow traversing the right and left lungs is presented.

Coulam, C. M.↗

NASA NTRS1972

Government liability for meteorological satellite data

Possible legal ramifications to the U.S. Government as a result of utilization and distribution of meteorological satellite data are explored.

Smith, D. D.↗

DOE OSTI2026

Data Cards for Standardized Metadata Across DOE-Aligned Data Initiatives: Toward Transparent, Interoperable, and Governed Dataset Documentation

As data-intensive research, advanced computing, and artificial intelligence become increasingly central to scientific and operational workflows, the need for consistent, transparent, and machine-actionable documentation has grown correspondingly. Multiple DOE-aligned communities—including Office of Science, Genesis Mission, American Science Cloud (AmSC), National Nuclear Security Administration (NNSA) stewardship and governance, and related cross-laboratory collaborations—have independently developed metadata practices to support discovery, access, reuse, repository deposit, and compliance.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2025

DeepLynx Ecosystem 2025

Poor data integration and governance continue to plague complex engineering projects, resulting in missed cost, schedule, and performance targets. Departments operate in isolated systems with manual data exchange, creating fragmented information that compounds errors and leads to significant delays and cost overruns. The DeepLynx ecosystem addresses these challenges through an open-source, modular data management platform that transforms fragmented project data into an integrated digital thread. Built on a federated microservice architecture, the ecosystem comprises seven specialized tools centered around DeepLynx Nexus, a unified data catalog with hierarchical organization and graph-based navigation capabilities. The ecosystem includes: DeepLynx Stream for real-time timeseries data ingestion from industrial sources; DeepLynx Ingest for governed data uploads with formal review workflows; DeepLynx Lattice for ontology-based entity and relationship extraction; DeepLynx Run for workflow orchestration and secure AI/ML compute; DeepLynx Visualize for 3D digital twin visualization; and DeepLynx Insight for AI-assisted document analysis with traceable, grounded responses. Deployable in cloud, on-premise, or hybrid environments using containerized Docker applications and Helm charts, the DeepLynx ecosystem provides flexible infrastructure that adapts to organizational requirements. By consolidating project data into a unified data lake with role-based access controls and OAuth2 authentication, DeepLynx enables digital thread and digital twin capabilities that improve decision-making, reduce risk, and support complex engineering workflows throughout the project lifecycle.

42 - ENGINEERING↗

NASA NTRSDate not supplied

Beyond Fair: Engagement, Data Usability, and Open Community Productivity through the NASA Open Science Data Repository

The FAIR principle (findable, accessible, interoperable, and reusable) governs the storage and sharing of NASA space biology and health data[1]. These guiding principles maximize reuse of data and the reproducibility of scientific findings. The NASA Open Science Data Repository (OSDR; an expansion of NASA GeneLab) was built on the FAIR principles and houses over 500 studies and close to 1000 datasets from decades of space life sciences experiments. OSDR embodies the FAIR principles through data governance that includes mediated, embargoed, and fully open access data. The FAIR data governance principles were recently proposed to be expanded to encompass a FAIREST framework for assessing research data repositories (FAIR + Engagement, Social connections, and Trust)[2]. FAIREST emphasizes the importance of data repositories engaging with the scientific community and gaining the trust of researchers regarding data quality. Trust also refers to the TRUST principles developed for assessment of digital repositories: Transparency, Responsibility, User Focus, Sustainability, Technology[3]. We present the “Open Science for Life in Space” Analysis Working Groups (AWGs) as evidence regarding the power of engagement, social connections, and trust which has enhanced OSDR’s capabilities and productivity. AWG members engage in two main activities. One, members provide feedback on OSDR scientific standards for data ingestion, curation, and reuse (study, subject and assay metadata; processing pipelines; dataset formats and uniformed structures for machine-readability). Two, AWG members collaborate to mine-reuse OSDR data to conduct scientific analysis. With nearly 800 active members, the AWGs have resulted in 32 publications re-using OSDR data and contributed many papers in two major special issues in Cell (2020) and Nature (2024). AWGs also serve as networking groups, facilitate social connections between researchers at all levels of experience, and also have a social online ‘Forum’ used to keep members informed on projects and opportunities. This community-centric, productive, and trustworthy data culture has resulted in a broader effect with international space agencies, academics, and the commercial space sector wanting to submit their data to OSDR. Ten studies of Inspiration 4 data were recently publicly released by OSDR, as were some JAXA human data. Coming up soon in OSDR are data submissions from the European Space Agency, Virgin Galactic PIs, and SpaceX Polaris Dawn. A major benefit of OSDR is the array of standardized and uniformly formatted data (which was developed through AWG member consensus), from which visualization tools, analysis tools, and machine learning models can be built or trained. This talk will cover the Multi-Study Visualization Tool, the Environmental Data Application, RadLab, and a UCSF-NSF funded knowledge graph biomedical health discovery tool ‘SPOKE’ currently being integrated with OSDR. OSDR also provides training programs in bioinformatics and machine learning to improve the scientific community’s awareness of data availability and to boost their ability to perform data analysis. The increasing engagement of the scientific community and the public with technologies powered by artificial intelligence (AI) heightens the need for data analysis to be transparent. The AI for Life in Space initiative leverages the data products provided in OSDR to train AI models, with an emphasis on explainable and trustworthy AI, which would not be possible without FAIR data and metadata. Overall, here we will demonstrate the importance for NASA life sciences data repositories to adhere to the FAIREST framework, by providing examples and success stories from different aspects of OSDR.

data↗

NASA NTRS1973

Parts, materials, and processes experience summary, volume 2

This summary provides the general engineering community with the accumulated experience from ALERT reports issued by NASA and the Government-Industry. Data Exchange Program, and related experience gained by Government and industry. It provides expanded information on selected topics by relating the problem area (failure) to the cause, the investigation and findings, the suggestions for avoidance (inspections, screening tests, proper part applications, requirements for manufacturer's plant facilities, etc.), and failure analysis procedures. Diodes, integrated circuits, and transistors are covered in this volume.

Source record↗

DOE OSTI2025

Multi-head physics-informed neural networks for learning functional priors and uncertainty quantification

In numerous applications, the integration of prior knowledge and historical information is essential, particularly for tasks requiring the solution of ordinary or partial differential equations (ODEs/PDEs) in data-sparse or noisy environments. For instance, achieving accurate solutions to time-dependent PDEs with limited initial condition measurements necessitates an effective strategy for embedding prior knowledge. Hard-parameter sharing architectures in neural networks (NNs) have demonstrated success in both traditional and scientific machine learning domains, facilitating the learning of informative representations. Here, in this study, we introduce a novel, yet efficient, method to enhance physics-informed neural networks (PINNs) by incorporating a multi-head structure that enables the learning of functional priors from both empirical data and governing physical laws. This prior information can then be used to address data sparsity and high-level noise in solving ODE/PDE problems with uncertainty quantification (UQ). The approach, termed Multi-Head PINN (MH-PINN), consists of a shared body NN and multiple head NNs, each corresponding to an individual PINN instance. Our framework for functional prior learning is carried out in two stages: (1) training the MH-PINNs to develop a shared body NN alongside multiple head NNs, and (2) employing these trained head NNs to estimate a prior distribution through a normalizing flow-based density estimator. The learned functional prior can then be applied as a regularization mechanism in deterministic contexts or as an informative prior within a Bayesian inference framework, aiding in the resolution of subsequent ODE/PDE tasks. We evaluate the efficacy of MH-PINNs across five benchmark problems, including a high-dimensional parametric PDE, all characterized by data sparsity or substantial noise levels. Our findings reveal that MH-PINNs deliver accurate solutions and robust UQ, demonstrating adaptability across a range of complex and challenging scenarios.

Bayesian inference↗

NASA NTRS2003

Cryogenic Information Center

The Cryogenic Information Center (CIC) is a not-for-profit corporation dedicated to preserving and distributing cryogenic information to government, industry, and academia. The heart of the CIC is a uniform source of cryogenic data including analyses, design, materials and processes, and test information traceable back to the Cryogenic Data Center of the former National Bureau of Standards. The electronic database is a national treasure containing over 146,000 specific bibliographic citations of cryogenic literature and thermophysical property data dating back to 1829. A new technical/bibliographic inquiry service can perform searches and technical analyses. The Cryogenic Material Properties (CMP) Program consists of computer codes using empirical equations to determine thermophysical material properties with emphasis on the 4-300K range. CMP's objective is to develop a user-friendly standard material property database using the best available data so government and industry can conduct more accurate analyses. The CIC serves to benefit researchers, engineers, and technologists in cryogenics and cryogenic engineering, whether they are new or experienced in the field.

Mohling, Robert A.↗

NASA NTRS2003

Cryogenic Information Center

Mohling, Robert A.↗

NASA NTRS1999

Using the World Wide Web for GIDEP Problem Data Processing at Marshall Space Flight Center

Since April 1997, Marshall Space Flight Center has been using electronic transfer and the web to support our processing of the Government-Industry Data Exchange Program (GIDEP) and NASA ALERT information. Specific aspects include: (1) Extraction of ASCII text information from GIDEP for loading into Word documents for e-mail to ALERT actionees; (2) Downloading of GIDEP form image formats in Adobe Acrobat (.pdf) for internal storage display on the MSFC ALERT web page; (3) Linkage of stored GRDEP problem forms with summary information for access from the MSFC ALERT Distribution Summary Chart or from an html table of released MSFC ALERTs (4) Archival of historic ALERTs for reference by GIDEP ID, MSFC ID, or MSFC release date; (5) On-line tracking of ALERT response status using a Microsoft Access database and the web (6) On-line response to ALERTs from MSFC actionees through interactive web forms. The technique, benefits, effort, coordination, and lessons learned for each aspect are covered herein.

McPherson, John W.↗

NASA NTRSDate not supplied

NASA's Commercial Smallsat Data Acquisition (CSDA) Program Enables Researchers to Take Advantage of This Rapidly Evolving Industry

The growth of commercial Earth Observation (EO) satellite industry is accelerating rapidly, bringing a diverse set of products to a wide range of EO research domains. NASA’s Commercial Smallsat Data Acquisition (CSDA) Program, established in 2017, identifies, evaluates, and acquires commercial data - products, including very high-resolution imagery spanning from visible to short-wave infrared wavelengths, synthetic aperture radar (SAR) imagery, as well as Global Navigation Satellite System (GNSS) data that support, augment, and complement NASA’s extensive catalog of Earth science data. The poster demonstrates how users can learn about the CSDA Program, access the data, and find results from publications and findings of NASA researchers. NASA-acquired commercial data are governed by an end user license agreement. This poster is intended as a practical guide to what the CSDA Program is, where to discover the data and types, and how to access and use the data for scientific purposes.

Stephan Klene↗

DOE OSTI2026

Adaptable Standards for Discovery, Access, and Usability of Oak Ridge National Laboratory’s Data Portals and Catalogs

Oak Ridge National Laboratory (ORNL) is leveraging its established capabilities and subject matter expertise in data curation, governance, management, national security, and risk assessment and mitigation to support the US Department of Energy (DOE) Grid Modernization Initiative. Using standards modeled by the National Institute of Standards and Technology (NIST), the Data Curation Network (DCN), the Oak Ridge Leadership Computing Facility (OLCF), and other leading organizations in the fields of energy research, high-performance computing, and national and homeland security, ORNL seeks to provide a federated approach to research data discovery, use, and interoperability.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

NASA NTRS2011

NASA Presentation to TechAmerica G12 Committee

This slide presentation reviews some of the actions that NASA is taking to address the issue of counterfeit electronic parts. While the emphasis is on electronic parts, the vision is broad enough to include materials and software. The effort includes coordination with other agencies, to identify and with the Government-Industry Data Exchange Program (GIDEP). An interim GIDEP Policy for suspected counterfeits was instituted. NASA's recommendation to the policy was for identification of the supplier and suggests allowing access to that information by government only. The issues with the General MIL specification, the testing requirements for radiation issues, the continuing development of Class Y standards for electronic equipment, status of package case isolation tests needed for 750 and 883,enhancement of 750 Internal Visual Inspection are reviewed. Further issues with consistent ESD control conditions across commodities, test methods, humidity limits, etc are briefly reviewed. The cost benefit analysis of film versus Real time radiography are also reviewed.

LaBel, Kenneth A.↗

NASA NTRS2018

JSC OCFO Cloud Integrated Budget Analytical Toolbox

The JSC OCFO analyst's job function relies heavily on analytics to provide every directorate customer with quality service in managing their respective budgets. This technology, configured on the Salesforce cloud platform, enhances the JSC OCFO customer user interface, provides state of the art data analytics and statistics, reduces IT costs, increases productivity, eliminates duplicate entry and errors, and utilizes machine learning and artificial intelligence to process day to day transactional tasks automatically without analyst manipulation. The unique configuration of the COTS technology allows for highly advanced analysis and reporting of government budget data. This provides the ability for complex budgets to be fully understood in detail by non-budget organizations and eliminates time consuming analysis on the OCFO analyst's behalf.

Robertson, Arden↗

DOE OSTI2026

WellPINN: Accurate Well Representation for Transient Fluid Pressure Diffusion in Subsurface Reservoirs With Physics‐Informed Neural Networks

Accurate representation of pumping wells is essential for reliable reservoir characterization and simulation of operational scenarios in subsurface flow models. Physics-informed neural networks (PINNs) are emerging as a promising alternative to numerical models for reservoir modeling, offering seamless integration of monitoring data and governing physical equations. However, existing PINN-based studies face major challenges in capturing fluid pressure near wells when using a source/sink term, particularly during the early stages after pumping begins. We address this problem by introducing WellPINN, a workflow in which an initially trained PINN infers fluid pressure across the entire reservoir domain using a large equivalent well radius. This initial PINN solution is then locally refined around the well by a set of subdomain PINNs that are trained for smaller equivalent well radii. Continuity across these subdomain interfaces as well as at the initial condition is ensured by hard-constraining each PINN on its subdomain boundary. Our results demonstrate WellPINN as the first workflow of its kind to focus on accurate inference of fluid pressure from pumping rates throughout the entire injection period, significantly advancing the potential of PINNs for inverse modeling and operational scenario simulations. All data and code for this paper are openly available at https://doi.org/10.20350/DIGITALCSIC/17260.

58 GEOSCIENCES↗

NASA NTRS1989

Aeroelastic analysis of prop fan blades with a semiempirical dynamic stall model

The time-history response of a propfan wind-tunnel model with dynamic stall was studied analytically. The response obtained from the analysis was compared with available experimental data. The governing equations of motion were formulated in terms of blade normal modes calculated using the COSMIC-NASTRAN computer code. The response analysis considered the blade plunging and pitching motions. The lift, drag, and moment coefficients for angles of attack below the static stall angle were obtained from a quasi-steady theory. For angles above static stall angles, a semiempirical dynamic stall model based on a correction to the angle of attack was used to obtain lift, drag, and moment coefficients. Using these coefficients, the aerodynamic forces were calculated at a selected number of strips, and integrated to obtain the total generalized forces. The combined momentum-blade element theory was used to calculate the induced velocity. The semiempirical stall model predicted a limit cycle oscillation near the setting angle at which large vibratory stresses were observed in an experiment. The predicted mode and frequency of oscillation also agreed with those measured in the experiment near this setting angle. The results also correlated well with the other published data that used a semiempirical dynamic stall model based on a synthesized procedure.

Reddy, T. S. R.↗