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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The Building Adapter: Automatic Mapping of Commercial Buildings for Scalable Building Analytics

This project creates new solutions for the manual metadata mapping problem: the costly process of creating a match between a building’s sensor data streams and the inputs of a building analytics engine. This goal is achieved by creating and improving techniques for metadata inference: automatically constructing new contextual information for sensing and control points based on the sensor point names and the raw time series values. The objective is to enable vendors to apply building analytics to 90% of buildings with no manual mapping, and to 10% of buildings with a 90% reduction in manual mapping. These targets are set for all types of metadata required by current analytics engines, including type, location, equipment type, and other relationships. The outcome of this project is a suite of solutions to the manual mapping problem collectively called the Building Adapter that allows vendors to apply analytics engines to new buildings at a significantly reduced cost.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

A Data Science and Machine Learning Platform Supporting Large Particle Accelerator Control and Diagnostics Applications Final Report: SBIR Initial Phase II DE-SC0022583

The Machine Learning Data Platform (MLDP) is a product providing full-stack support for data science, Machine Learning, and Artificial Intelligence (ML/AI) applications at particle accelerator and large experimental physics facilities. It supports ML/AI applications from front-end, high-speed acquisition of heterogeneous, time-series data, through data archiving and management, to back-end analysis. The MLDP embodies a “data-science ready” platform for data analysis and ML/AI applications in diagnosis, modelling, control, and optimization of these facilities. It provides data scientists and applications a consistent, datacentric interface to archive data standardizing implementation and deployment of ML/AI algorithms to different operations configurations within the same facility, or between facilities. Being an open-source, public-domain project, the MLDP is intended for broadest possible impact by increasing accessibility and minimizing the required expertise for installation and operation. The MLDP can also be deployed at user facilities for experimental data collection, archiving, and analysis. It is capable of acquisition and archiving of heterogeneous data from experimental equipment (e.g., images, arrays, structures, etc.) along with system hardware configurations (e.g., scalars, tables), control system process variables, and any metadata required for provenance. Thus, the MLDP can manage experimental data through its entire lifecycle, from acquisition and archiving, through analysis and investigation, to release and final publication.

43 PARTICLE ACCELERATORS↗
NASA NTRS2017

Extension of MBSE for Project Programmatics Management on the Asteroid Redirect Robotic Mission

Model-based Systems Engineering can be employed beyond management of the technical architecture development of a system to also manage the programmatics associated with Systems Engineering activities of a project. On NASA’s Asteroid Redirect Robotic Mission, MBSE has been successfully employed to manage, generate, and interact with the documentation-based deliverables associated with System Engineering activities. This has been involved in defining and tracking project document, milestone, and personnel metadata via the same modeling framework used for the technical architecture management. Additionally, it has focused on improving overall user experiences through linkage of documentation to technical content in the system model, automation of manually intensive tasks, and others stakeholderoriented features.

Mozafari, Tanaz↗
DOE OSTI2025

A standards perspective on genomic data reusability and reproducibility

Genomic and metagenomic sequence data provides an unprecedented ability to re-examine findings, offering a transformative potential for advancing research, developing computational tools, enhancing clinical applications, and fostering scientific collaboration. However, effective and ethical reuse of genomics data is hampered by numerous technical and social challenges. The International Microbiome and Multi’Omics Standards Alliance (IMMSA, https://www.microbialstandards.org/) and the Genomic Standards Consortium (GSC, https://gensc.org) hosted a 5-part seminar series “A Year of Data Reuse” in 2024 to explore challenges and opportunities of data reuse and reproducibility across disparate domains of the genomic sciences. Addressing these challenges will require a multifaceted approach, including common metadata reporting, clear communication, standardized protocols, improved data management infrastructure, ethical guidelines, and collaborative policies that prioritize transparency and accessibility. We offer strategies to enable responsible and technically feasible data reuse, recognition of data reproducibility challenges, and emphasizing the importance of cross-disciplinary efforts in the pursuit of open science and data-driven innovation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

DMTN-227: The Consolidated Database of Image Metadata

This document proposes a specification for what the content of an image metadata database should be, how it should be managed, how it could be implemented, and how it might be extended. A phased strategy for bringing it to production is also proposed.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1989

A rapid prototyping/artificial intelligence approach to space station-era information management and access

Applications of rapid prototyping and Artificial Intelligence techniques to problems associated with Space Station-era information management systems are described. In particular, the work is centered on issues related to: (1) intelligent man-machine interfaces applied to scientific data user support, and (2) the requirement that intelligent information management systems (IIMS) be able to efficiently process metadata updates concerning types of data handled. The advanced IIMS represents functional capabilities driven almost entirely by the needs of potential users. Space Station-era scientific data projected to be generated is likely to be significantly greater than data currently processed and analyzed. Information about scientific data must be presented clearly, concisely, and with support features to allow users at all levels of expertise efficient and cost-effective data access. Additionally, mechanisms for allowing more efficient IIMS metadata update processes must be addressed. The work reported covers the following IIMS design aspects: IIMS data and metadata modeling, including the automatic updating of IIMS-contained metadata, IIMS user-system interface considerations, including significant problems associated with remote access, user profiles, and on-line tutorial capabilities, and development of an IIMS query and browse facility, including the capability to deal with spatial information. A working prototype has been developed and is being enhanced.

Carnahan, Richard S., Jr.↗
NASA NTRS2015

Architectures Toward Reusable Science Data Systems

Science Data Systems (SDS) comprise an important class of data processing systems that support product generation from remote sensors and in-situ observations. These systems enable research into new science data products, replication of experiments and verification of results. NASA has been building systems for satellite data processing since the first Earth observing satellites launched and is continuing development of systems to support NASA science research and NOAAs Earth observing satellite operations. The basic data processing workflows and scenarios continue to be valid for remote sensor observations research as well as for the complex multi-instrument operational satellite data systems being built today. System functions such as ingest, product generation and distribution need to be configured and performed in a consistent and repeatable way with an emphasis on scalability. This paper will examine the key architectural elements of several NASA satellite data processing systems currently in operation and under development that make them suitable for scaling and reuse. Examples of architectural elements that have become attractive include virtual machine environments, standard data product formats, metadata content and file naming, workflow and job management frameworks, data acquisition, search, and distribution protocols. By highlighting key elements and implementation experience we expect to find architectures that will outlast their original application and be readily adaptable for new applications. Concepts and principles are explored that lead to sound guidance for SDS developers and strategists.

Data Processing↗
NASA NTRS1998

Emerging Network Storage Management Standards for Intelligent Data Storage Subsystems

This paper discusses the need for intelligent storage devices and subsystems that can provide data integrity metadata, the content of the existing data integrity standard for optical disks and techniques and metadata to verify stored data on optical tapes developed by the Association for Information and Image Management (AIIM) Optical Tape Committee.

OPTICAL DATA STORAGE MATERIALS↗
DOE OSTI2024

Conclusions and outlook

In this chapter, we provide notes on the state of metadata collection and organization practices and reflect on the achievements of the MetaCO task group. We also include an utility perspective on how to use this report in daily data management practice and a short guide is provided to show how metadata practices can be initiated. The chapter, and the report, is concluded within an outlook, sketching future progress and opportunities on the horizon.

Aguado, Daniel↗
DOE OSTI2020

Sandia National Laboratories Ecosystem for Open Science: Metadata Schema v0.2 Description.

The Ecosystem for Open Science (eOS) initiative was established in 2019. Its objective is improving openness and sharing of data and information across Defense Nuclear Nonproliferation (DNN) Research and Development (R&D) activities. To support this initiative, the eOS team at Sandia National Laboratories (SNL) developed metadata and data standards and proposed a machine-readable metadata schema. The nuclear explosion monitoring field was selected as a focus area due to its the wide range of pertinent phenomenologies.We developed the DCAT-eOS-AP metadata schema extending the Data Catalog Vocabulary version 2 (DCATv2) standard using an application profile (AP), to fit the needs of multi-disciplinary NA-22 projects. The DCAT-eOS-AP metadata schema describes data at different levels of granularity ranging from general descriptions to more domain-specific granular metadata. Its implementation and serialization is flexible with the ability to include new file or data types. Thus, it will scale with the ever-increasing data management needs of government research. Due to the multitude of phenomenologies represented in the DCAT-eOS-AP schema, we anticipate that it will be easily extensible to various projects across many DOE mission areas. This document describes data management challenges faced within the DNN R&D portfolio and provides insight on how metadata and data standards/guidelines combined with a comprehensive metadata schema can add value to programs throughout the Department of Energy (DOE). It reviews the importance of metadata standards, FAIR (Findability, Accessibility, Interoperability, and Reusability) data principles, and metadata schemas. Additionally, it summarizes input from subject matter experts (SME) at SNL and other National Laboratories that resulted in metadata and data standards/guidelines encompassing domains relevant to NA-22 projects. Finally, we discuss the DCAT-eOS-AP metadata development. Implementation recommendations and future development directions are included for those keen on adopting the DCAT-eOS-AP metadata schema.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

PoliMOR

PoliMOR is a scalable, automated, and customizable policy engine framework for multi-tiered parallel file systems. It is composed of single-purpose agents that handle tasks such as gathering file metadata, making policy decisions, and then executing actions based on those policies. These agents are designed to communicate using distributed message queues, allowing the number of individual agents to be scaled up as needed. PoliMOR automates the data management tasks by precluding the need for admin intervention. The agents in PoliMOR can be customized to integrate any utilities/tools that perform tasks like metadata scanning and data placement management.

Brumgard, Christopher↗
NASA NTRS2019

Design and Construction of a NASA Airborne and Field Investigation Inventory

NASA conducts airborne and field investigations that produce a wealth of valuable research data. Unfortunately, this data is often scattered across individual scientist hard drives or NASA Distributed Active Archive Centers and it can be difficult to locate and retrieve. Although satellite data has been successfully consolidated by tools such as EarthData Search, airborne and field investigation data present unique challenges stemming from the variability of temporal, spatial, platform, and instrument metadata. To address these difficulties with data retrieval and metadata variability, the Interagency Implementation and Concepts Team established an Airborne Data Management Group to improve airborne data search, understanding, access, and use. Surveys have been conducted of end users in order to build query lists that will drive the augmentation and standardization of existing metadata. Detailed metadata was then laboriously compiled from present and historic airborne and field investigations to build a database that will enable intelligent data search and retrieval. The inventory structure and function will be described and demonstrated. The purpose of this presentation is to bring awareness to this effort, to highlight and describe the issues and complications in development, and to increase user interest prior to public release in 2020.

Davis, Carson↗
DOE OSTI2020

Recent evolutions in the LTDP CDF project

In the latest years, CNAF (the national center of the Italian Institute for Nuclear Physics INFN dedicated to Research and Development on Information and Communication Technologies) has been working on the Long Term Data Preservation (LTDP) project for the CDF experiment, active at Fermilab from 1990 to 2011. The main aims of the project are to protect the most relevant part of the CDF RUN-2 data collected between 2001 and 2011 and already stored on tape at CNAF (4 PB), as well as to ensure the availability and the access to the analysis facility to those data over time. Lately, the CDF database, hosting information about CDF datasets such as their structure, file locations and metadata, has been imported from Fermilab to CNAF. Also, the Sequential Access via Metadata (SAM) station data handling tool for CDF data management, that allows to manage data transfers and to retrieve information from the CDF database, has been properly installed and configured at CNAF. This was a fundamental step in the perspective of a complete decommissioning of CDF services on Fermilab side. An access system has been designed and tested to submit CDF analysis jobs, using CDF software distributed via CERN Virtual Machine File System (CVMFS) and requesting delivery of CDF files stored on CNAF tapes, as well as data present only on Fermilab storage archive. Moreover, the availability and the correctness of all CDF data stored on CNAF tapes has been verified. This paper describes all these recent evolutions in detail, presenting the future plans for the LTDP project at CNAF.

Fornari, Federico↗
DOE OSTI2025

Label-based Virtual Directories In dCache

Traditional filesystems organize data in directories. These directories are typically a collection of files whose grouping is based on a single criterion, e.g., the starting date of an experiment, experiment name, beamline ID, measurement device, or instrument. However, each file in a directory can belong to several logical groups, such as a special event type, experiment condition, or a part of a selected dataset. dCache is a storage system developed to store large amounts of scientific data, used by many HEP and Photon Science experiments. With recent developments in dCache, we have introduced a concept of file tagging, which dynamically groups files with the same label into virtual directories. The file labels can be added, removed, renamed, and deleted through the admin interface or via REST API. The files in virtual directories are exposed through all protocols supported by dCache. This contribution will describe the details of the implementation for file tagging in dCache and present our future development plans on automatic metadata extractions, a feature that will significantly simplify data management. Additionally, we are exploring the future use of virtual directories as a way to translate scientific data catalogs into filesystem views for direct data analysis.

Sahakyan, Marina [DESY]↗
NASA NTRS2001

A Survey of Complex Object Technologies for Digital Libraries

Many early web-based digital libraries (DLs) had implicit assumptions reflected in their architecture that the unit of focus in the DL (frequently "reports" or "e-prints") would only be manifested in a single, or at most a few, common file formats such as PDF or PostScript. DLs have now matured to the point where their contents are commonly no longer simple files. Complex objects in DLs have emerged from in response to various requirements, including: simple aggregation of formats and supporting files, bundling additional information to aid digital preservation, creating opaque digital objects for e-commerce applications, and the incorporation of dynamic services with the traditional data files. We examine a representative (but not necessarily exhaustive) number of current and recent historical web-based complex object technologies and projects that are applicable to DLs: Aurora, Buckets, ComMentor, Cryptolopes, Digibox, Document Management Alliance, FEDORA, Kahn-Wilensky Framework Digital Objects, Metadata Encoding & Transmission Standard, Multivalent Documents, Open eBooks, VERS Encapsulated Objects, and the Warwick Framework.

Nelson, Michael L.↗
DOE OSTI2020

Metadata compression

A computer-executable method, system, and computer program product for managing a Parallel-Logged File System (PLFS) on a data storage system, wherein the data storage system is in communication with an application that updates the data storage system with checkpoint data, the computer-executable method, system, and computer program product comprising receiving a first checkpoint including data from the application; analyzing the data in the first checkpoint to determine whether a pattern exists in the checkpoint data; and upon a positive determination, adding the pattern into PLFS.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2013

GHRSST-14 DAS-TAG Report

The DAS-TAG provides the informatics and data management expertise in emerging information technologies for the GHRSST community. It provides expertise in data and metadata formats and standards, fosters improvements for GHRSST data curation, experiments with new data processing paradigms, and evaluates services and tools for data usage. It provides a forum for producer and distributor data management issues and coordination.

data processing↗