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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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All sources NASA NTRS DOE OSTI

DOE OSTI2022

Best Practices for Energy Management Information Systems Metadata Schemas

The Federal Energy Management Program (FEMP) promotes best practices for impactful utilization of Energy Management Information Systems (EMIS) at federal facilities. This best practice document is part of a series of fact sheets created to help accelerate the market adoption and use of EMIS in the federal sector. The use of standard naming conventions and a metadata schema, which may be referred to as 'data tags,' improves the ability of the EMIS to consistently analyze, visualize, and derive value from operational data. To help address these issues, this fact sheet highlights best practices for use of metadata in an EMIS stack, which can significantly reduce the initial time required to deploy an EMIS.

EMIS↗

DOE OSTI2022

Best Practices for Energy Management Information Systems Metadata Schemas

Fact sheet highlights best practices for metadata schemas and standard naming conventions, which improve the ability of an energy management information system (EMIS) to consistently analyze, visualize, and derive value from operational data. This best practice document is part of a series of fact sheets created to help accelerate the market adoption and use of EMIS in the federal sector. It provides an overview of best practices for using metadata in an EMIS stack, which can significantly reduce the initial time required to deploy an EMIS.

data tags↗

DOE OSTI2022

Panel-Segmentation: A Python Package for Automated Solar Array Metadata Extraction Using Satellite Imagery

The NREL Python Panel-Segmentation package is a toolkit that automates the process of extracting accurate and valuable metadata related to solar array installations, using publicly available Google Maps satellite imagery. Previously published work includes automated azimuth estimation for individual solar installations in satellite images. Our continued research focuses on automated detection and classification of solar installation mounting configuration (tracking or fixed-tilt; rooftop, ground, or carport). Specifically, a Faster-RCNN Resnet-50 feature pyramid network (FPN) model was trained and validated on 862 manually labeled satellite images. This model was used to perform object detection on satellite imagery, locating and classifying individual solar installations' mounting configuration and type. Model results showed a mean average precision score (mAP) of 77.79%, with the model strongest at detecting fixed-tilt ground mount and fixed-tilt carport installations. The object detection model and its outputs have been incorporated into the Panel-Segmentation package's automated metadata extraction pipeline, which returns the mounting configuration and azimuth for individual solar arrays in satellite imagery. The complete image data set with labels has been released on the U.S. Department of Energy (DOE) DuraMAT DataHub, to encourage further research in this area.

deep learning↗

DOE OSTI2014

Data Bookkeeping Service 3 - Providing Event Metadata in CMS

The Data Bookkeeping Service 3 provides a catalog of event metadata for Monte Carlo and recorded data of the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) at CERN, Geneva. It comprises all necessary information for tracking datasets, their processing history and associations between runs, files and datasets, on a large scale of about 200, 000 datasets and more than 40 million files, which adds up in around 700 GB of metadata. The DBS is an essential part of the CMS Data Management and Workload Management (DMWM) systems [1], all kind of data-processing like Monte Carlo production, processing of recorded event data as well as physics analysis done by the users are heavily relying on the information stored in DBS.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Microbiome Metadata Standards: Report of the National Microbiome Data Collaborative’s Workshop and Follow-On Activities

Microbiome samples are inherently defined by the environment in which they are found. Therefore, data that provide context and enable interpretation of measurements produced from biological samples, often referred to as metadata, are critical. Important contributions have been made in the development of community-driven metadata standards; however, these standards have not been uniformly embraced by the microbiome research community. To understand how these standards are being adopted, or the barriers to adoption, across research domains, institutions, and funding agencies, the National Microbiome Data Collaborative (NMDC) hosted a workshop in October 2019. This report provides a summary of discussions that took place throughout the workshop, as well as outcomes of the working groups initiated at the workshop.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

Metadata management staging system

Django application providing a user-interface for building a file and metadata management system. An evolution of our Node.js and CouchDb metadata management system. This one focuses on server functionality and uses a well-documented, rational and REST-ful API for data access.

Source record↗

DOE OSTI2022

16S and ITS Amplicon Sequencing Fastq files and metadata from PARCHED Panama Tropical Forest soils, 2019-2020,

Model projections predict tropical forests will experience longer periods of drought and more intense precipitation cycles under a changing climate. Such transitions have implications for structure-function relationships within microbial communities. We examine how chronic drying might reshape prokaryotic and fungal communities across four lowland forests in Panama with a wide variation in mean annual precipitation and soil fertility. Four sites were established across a 1000 mm span in mean annual precipitation (2335 to 3300 mm). We expected microbial communities at sites with lower MAP to be less sensitive to chronic drying than sites with higher MAP; while fungal communities to be more resistant to disturbance than prokaryotes. At each location, partial throughfall exclusion structures were established over 10 x 10 m plots to reduce direct precipitation input. Raw demultiplexed sequences (bacteria, archaea, fungal) from soil samples taken from PARCHED Panama Tropical Forest throughfall exclusion experiments. Files that contain 16S are sequences from prokaryotes, ITS indicates sequences from fungi. Compressed fastq files are contained in Field_PARCHED_ITS_fastq_2020.zip, Field_PARCHED_ITS_fastq_2019.zip, Field_PARCHED_16S_fastq_2020.zip, Field_PARCHED_16S_fastq_2019.zip.There are four sites across the isthmus of Panama, each with 4 control and 4 exclusion plots. Throughfall exclusion shelters were built to intercept 50% of throughfall precipitation that hits the soil. Samples were taken on May 2019 and Jan 2020 from 0-10 cm and 10-20 cm depth approximately 9 and 18 months after shelter installation. Metadata and sample IDs for fastq files for 2019 sampling are within Field_PARCHED_Metadata_2019_ITS.csv and Field_PARCHED_Metadata_2019_16S.csv. The metadata for both 16S and ITS fastq files for January 2020 is included in Field_PARCHED_Metadata_2020.csv. No data processing or QA/QC was done on the raw data. Data processing example provided in R notebook file.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Applying Waveform Correlation and Waveform Template Metadata to Aftershocks in the Middle East to Reduce Analyst Workload

Organizations that monitor for underground nuclear explosive tests are interested in techniques that automatically characterize recurring events such as aftershocks to reduce the human analyst effort required to produce high-quality event bulletins. Waveform correlation is a technique that is effective in finding similar waveforms from repeating seismic events. In this study, we apply waveform correlation in combination with template event metadata to two aftershock sequences in the Middle East to seek corroborating detections from multiple stations in the International Monitoring System of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization. We use waveform templates from stations that are within regional distance of aftershock sequences to detect subsequent events, then use template event metadata to discover what stations are likely to record corroborating arrival waveforms for recurring aftershock events at the same location, and develop additional waveform templates to seek corroborating detections. We evaluate the results with the goal of determining whether applying the method to aftershock events will improve the choice of waveform correlation detections that lead to bulletin-worthy events and reduction of analyst effort.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2025

Metadata Standards for the NSE: Core Fields

This standard presents a core set of metadata fields required for each managed digital object within the Nuclear Security Enterprise (NSE). Metadata standardization is a critical enabler for two primary objectives: 1) effectively sharing data, documents, and other digital objects between NSE sites; and 2) supporting digital engineering through the digital thread at the object level. Standardization is necessary for both schemas and vocabularies, meaning that both field standards and value standards must be specified. This document serves as a foundational field standard, recommending a core set of fields that should be uniformly required for all managed digital objects within the NSE.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2023

Microbiome Metadata Management

Tremendous amounts of microbiome omics data have been generated in recent years, which holds great potential for large-scale studies and metaanalyses. The utility of these datasets is unfortunately limited by their lack of searchability and interoperability. Thorough, standardized metadata is essential for unlocking the scientific discovery potential of disparate datasets. Several national and international initiatives exist to gather and standardize microbiome omics data to improve accessibility and reusability. Continuing to improve consistency in metadata will allow advances in automation and reduction in manual mapping between databases.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Sample Identifiers and Metadata to Support Data Management and Reuse in Multidisciplinary Ecosystem Sciences

Physical samples are foundational entities for research across biological, Earth, and environmental sciences. Data generated from sample-based analyses are not only the basis of individual studies, but can also be integrated with other data to answer new and broader-scale questions. Ecosystem studies increasingly rely on multidisciplinary team-science to study climate and environmental changes. While there are widely adopted conventions within certain domains to describe sample data, these have gaps when applied in a multidisciplinary context. In this study, we reviewed existing practices for identifying, characterizing, and linking related environmental samples. We then tested practicalities of assigning persistent identifiers to samples, with standardized metadata, in a pilot field test involving eight United States Department of Energy projects. Participants collected a variety of sample types, with analyses conducted across multiple facilities. We address terminology gaps for multidisciplinary research and make recommendations for assigning identifiers and metadata that supports sample tracking, integration, and reuse. Furthermore, our goal is to provide a practical approach to sample management, geared towards ecosystem scientists who contribute and reuse sample data.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1993

User interface development and metadata considerations for the Atmospheric Radiation Measurement (ARM) archive

This paper will discuss user interface development and the structure and use of metadata for the Atmospheric Radiation Measurement (ARM) Archive. The ARM Archive, located at Oak Ridge National Laboratory (ORNL) in Oak Ridge, Tennessee, is the data repository for the U.S. Department of Energy's (DOE's) ARM Project. After a short description of the ARM Project and the ARM Archive's role, we will consider the philosophy and goals, constraints, and prototype implementation of the user interface for the archive. We will also describe the metadata that are stored at the archive and support the user interface.

Singley, P. T.↗

NASA NTRS2003

A Metadata Element Set for Project Documentation

Abstract NASA Goddard Space Flight Center is a large engineering enterprise with many projects. We describe our efforts to develop standard metadata sets across project documentation which we term the "Goddard Core". We also address broader issues for project management metadata.

Hodge, Gail↗

NASA NTRS2004

Metadata and Buckets in the Smart Object, Dumb Archive (SODA) Model

We present the Smart Object, Dumb Archive (SODA) model for digital libraries (DLs), and discuss the role of metadata in SODA. The premise of the SODA model is to "push down" many of the functionalities generally associated with archives into the data objects themselves. Thus the data objects become "smarter", and the archives "dumber". In the SODA model, archives become primarily set managers, and the objects themselves negotiate and handle presentation, enforce terms and conditions, and perform data content management. Buckets are our implementation of smart objects, and da is our reference implementation for dumb archives. We also present our approach to metadata translation for buckets.

Nelson, Michael L.↗

NASA NTRS2010

SPASE, Metadata, and the Heliophysics Virtual Observatories

To provide data search and access capability in the field of Heliophysics (the study of the Sun and its effects on the Solar System, especially the Earth) a number of Virtual Observatories (VO) have been established both via direct funding from the U.S. National Aeronautics and Space Administration (NASA) and through other funding agencies in the U.S. and worldwide. At least 15 systems can be labeled as Virtual Observatories in the Heliophysics community, 9 of them funded by NASA. The problem is that different metadata and data search approaches are used by these VO's and a search for data relevant to a particular research question can involve consulting with multiple VO's - needing to learn a different approach for finding and acquiring data for each. The Space Physics Archive Search and Extract (SPASE) project is intended to provide a common data model for Heliophysics data and therefore a common set of metadata for searches of the VO's. The SPASE Data Model has been developed through the common efforts of the Heliophysics Data and Model Consortium (HDMC) representatives over a number of years. We currently have released Version 2.1 of the Data Model. The advantages and disadvantages of the Data Model will be discussed along with the plans for the future. Recent changes requested by new members of the SPASE community indicate some of the directions for further development.

Thieman, James↗

NASA NTRS2019

Benchmarking CME Arrival Time and Impact: Progress on Metadata, Metrics, and Events

Accurate forecasting of the arrival time and subsequent geomagnetic impacts of coronal mass ejections (CMEs) at Earth is an important objective for space weather forecasting agencies. Recently, the CME Arrival and Impact working team has made significant progress toward defining communit yagreed metrics and validation methods to assess the current state of CME modeling capabilities. This will allow the community to quantify our current capabilities and track progress in models over time. First, it is crucial that the community focuses on the collection of the necessary metadata for transparency and reproducibility of results. Concerning CME arrival and impact we have identified six different metadata types: 3D CME measurement, model description, model input, CME (non)arrival observation, model output data, and metrics and validation methods. Second, the working team has also identified a validation time period, where all events within the following two periods will be considered: 1 January 2011 to 31 December 2012 and January 2015 to 31 December 2015. Those two periods amount to a total of about 100 hit events at Earth and a large amount of misses. Considering a time period will remove any bias in selecting events and the event set will represent a sample set that will not be biased by user selection. Lastly, we have defined the basic metrics and skill scores that the CME Arrival and Impact working team will focus on.

Verbeke, C.↗

DOE OSTI2013

Metadata management staging system

Source record↗

DOE OSTI2017

Distributed metadata in a high performance computing environment

A computer-executable method, system, and computer program product for managing meta-data in a distributed storage system, wherein the distributed storage system includes one or more burst buffers enabled to operate with a distributed key-value store, the co computer-executable method, system, and computer program product comprising receiving a request for meta-data associated with a block of data stored in a first burst buffer of the one or more burst buffers in the distributed storage system, wherein the meta data is associated with a key-value, determining which of the one or more burst buffers stores the requested metadata, and upon determination that a first burst buffer of the one or more burst buffers stores the requested metadata, locating the key-value in a portion of the distributed key-value store accessible from the first burst buffer.

97 MATHEMATICS AND COMPUTING↗