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DOE OSTI2025

An Open-Access Repository of Synchrophasor Data Quality Examples: Curation and Example Applications

Synchrophasor measurements are critical in providing wide-area situational awareness to power system operators. However, data artifacts may be introduced due to various issues such as loss of communication, loss of GPS signal, internal clock error, and vendor-specific implementation of phasor estimation algorithms. Tools designed to provide actionable insights from synchrophasor data, hence, must be designed to be robust to these data quality issues. In this work, two years of synchrophasor data sourced from multiple electric utilities in the United States were analyzed to identify examples of data quality problems. These examples were then labeled and published in the Grid Event Signature Library, a publicly available repository of power system measurements hosted by the Oak Ridge National Laboratory. This paper describes the data curation process, and illustrates two application use cases where the dataset can be valuable to the research community. In the first use case, a random forest classifier is trained to distinguish power system disturbance signatures from data anomalies introduced in synchrophasor measurements due to clock errors. The second use case studies the impact of data quality issues on an example synchrophasor application (specifically, event start time determination). The choice of data quality problems investigated is informed by the examples in the repository curated in this work.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Jackson, L., Johnson, M.B., Latrach, A., Grimes, D., Martinez, C., and Mclaughlin, J.F., 2024, Multidisciplinary geotechnical data collection, curation, and analysis for conformity with the regulatory framework for geologic carbon storage in Wyoming, USA: Geological Society of America Abstracts with Programs. Vol. 56, No. 5, 2024, doi: 10.1130/abs/2024AM-405024

Title: Multidisciplinary Geotechnical Data Collection, Curation, and Analysis for Conformity with the Regulatory Framework for Geologic Carbon Storage in Wyoming, USA. Text: Construction and operation of wells for geologic sequestration of carbon dioxide necessitate that they are permitted under the Environmental Protection Agency’s Underground Injection Control Class VI requirements. Class VI wells conform to stringent requirements to ensure long-term safety and integrity of the storage site and the protection of Underground Sources of Drinking Water. Entities pursuing Class VI permitting must provide comprehensive geologic site characterization, including regional geologic structure and stratigraphy, aquifer information, reservoir and confining unit geomechanical properties, geochemical analyses, assessment of trapping capacity and mechanisms, and a variety of other of multidisciplinary geotechnical data. The Wyoming Class VI Site Characterization Database Project is focused on developing a geologic site characterization database of geotechnical information, which has been compiled and verified from established, public databases/entities and scientific literature to expedite Class VI permitting in Sweetwater County within the Greater Green River Basin of southern Wyoming. The preliminary suite of compiled data from 14,000 wells includes 8,000 wells with logs and 7,250 wells with formation tops, ~70 wells with core data (e.g., X-Ray diffraction, petrographic, and petrophysical data), ~2,500 water analyses, ~740 seismic events data, and ~520 bottom-hole temperature measurements. Future work on—and stemming from—this project will include new core analyses, calculation and interpolation of subsurface temperature gradients, mechanical earth models, geochemical simulations, storage capacity estimation, stratigraphic column generation and correlation, and construction of subsurface maps. Finally, this work will help to inspire and facilitate subsurface data compilation and curation beyond Sweetwater County, Wyoming.

42 ENGINEERING↗

DOE OSTI2021

Auto-Curation of Seismic Event Data for Signal Denoising

Denoising contaminated seismic signals for later processing is a fundamental problem in seismic signals analysis. Neural network approaches have shown success denoising local signals when trained on short-time Fourier transform spectrograms. One challenge of this approach is the onerous process of hand-labeling event signals for training. By leveraging the SCALODEEP seismic event detector, we develop an automated set of techniques for labeling event data. Despite region specific challenges, training the neural network denoiser on machine curated events shows comparable performance to the neural network trained on hand curated events. We showcase our technique with two experiments, one using Utah regional data and one using regional data from the Korean peninsula.

58 GEOSCIENCES↗

DOE OSTI2022

DOE COVID-19 Data Curation Effort: Overview of Initial Data Collection Coverage (March - June 2020)

During the COVID-19 pandemic of 2020, major case reporting outlets quickly coalesced around two or three primary vendors. Johns Hopkins University and The New York Times were among the more prominent, and all were of great value to the nation, particularly during the uncertain early stages of the pandemic. They primarily focused on three major attributes: number of new cases, deaths, and recovery, but only at the state level. Recognizing that many states were reporting very detailed data sets (e.g., hospital beds) at a count level or finer, the ORNL Pandemic Modeling team embarked on a major data curation effort from March to June 2020 for the purpose of capturing this wealth of detailed data. The challenge of curating this data was daunting. The number of attributes reported by the states grew on almost on a weekly basis. States were routinely shifting their web tool strategies away from easily parsable HTML-based formatting to new Tableau and ArcGIS content. This growth in the sheer number of attributes combined with the unpredictable shifts in data format meant an aggressive and agile combination of automated scripting and manual scraping was required to capture new daily streams. To keep up, the team had to scale up staff and widen its approach for capture and storage. The DOE COVID-19 data collection effort resulted in over 11 million data points being collected, covering over 13,000 unique geographies and over 2,000 unique attributes that spanned predominantly from early March through the end of June 2020.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2024

Curating Carbon Storage Data for Reuse: Enabling Research and Modeling from Earth’s Surface to Subsurface

The volume of public geologic carbon storage (GCS) data resources has continued to increase in recent years as the result of an increase in funding from government, industry, and academia towards national, basin, regional and field scale studies to ensure carbon capture and storage becomes a commercially viable operation. Despite the increasing volume of data, GCS data applied towards analyses such as geologic, cost, and risk modeling continues to be multi-sourced and often disparate in nature, published across government agencies, websites, data repositories and buried in derivative reports and documents. Much of the time preparing for an analysis and derivative product development is spent collecting, aggregating, transforming and preparing input data. There have been significant efforts within the DOE National Energy Technology Laboratory’s Carbon Storage Program to optimize multi-source, multi-scale subsurface geologic data curation and aggregation to support data discovery, interoperability, and reuse. Methods include the use of artificial intelligence, machine learning, and data science techniques. This talk will discuss the workflows, best practices, and processes developed to support the aggregation and curation of data through the whole system – surface to subsurface data - that support multi-scale, multi-purpose analysis for carbon storage research.

Morkner, Paige↗

DOE OSTI2025

VA Determinants of Health Data Curation Documentation FY25-Q2

The U.S. Department of Veterans Affairs (VA) places the health and well-being of our nation’s veterans as its top priority. VA is dedicated to offering timely access to high-quality, evidence-based mental health care that meets the needs of veterans and supports their reintegration into society. One of our core missions is to prevent suicide among veterans through innovative approaches and resources. With funding from the VA Office of Mental Health and Suicide Prevention (OMHSP), the Determinants of Health (EDH) project has developed innovative datasets associated with specific health outcomes, a methodology for transforming spatiotemporal data from one spatial reference (e.g., a 1km grid) to another (e.g., US Census Tracts), and capabilities for modeling health outcomes. These datasets represent an enhancement of the Agency for Healthcare Research and Quality (AHRQ), addressing key gaps by introducing finer spatial resolution (Census Tract) and additional geographical covariates into existing data. The curation and standardization of these datasets is a complex task since they often originate from various sources and are measured at different spatial and temporal resolutions. For example, US Census data products typically use census blocks, block groups, or counties, while data like weather data are available on 1km grids. Some economic data may only be available at the zip code level. In this context, ‘standardized’ means that all datasets share the same spatial extent (e.g., US Census Tract and/or County), and ‘curated’ implies a repeatable process with data provenance and the use of appropriate methodologies for covariate conversion. The Determinants of Health datasets draw from multiple sources, resulting in variables with varying degrees of availability, patterns of missing data, and methodological considerations across different sources, geographies, and years.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

VA Determinants of Health Data Curation Documentation FY25-Q3

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

VA Community Determinants of Health Data Curation Documentation FY25-Q4

The U.S. Department of Veterans Affairs (VA) places the health and well-being of our nation’s veterans as its top priority. VA is dedicated to offering timely access to high-quality, evidence-based mental health care that meets the needs of veterans and supports their reintegration into society. One of our core missions is to prevent suicide among veterans through innovative approaches and resources. With funding from the VA Office of Mental Health and Suicide Prevention (OMHSP), the Determinants of Health (EDH) project has developed innovative datasets associated with specific health outcomes, a methodology for transforming spatiotemporal data from one spatial reference (e.g., a 1km grid) to another (e.g., US Census Tracts), and capabilities for modeling health outcomes. These datasets represent an enhancement of the Agency for Healthcare Research and Quality (AHRQ), addressing key gaps by introducing finer spatial resolution (Census Tract) and additional geographical covariates into existing data. The curation and standardization of these datasets is a complex task since they often originate from various sources and are measured at different spatial and temporal resolutions. For example, US Census data products typically use census blocks, block groups, or counties, while data like weather data are available on 1km grids. Some economic data may only be available at the zip code level. In this context, standardized’ means that all datasets share the same spatial extent (e.g., US Census Tract and/or County), and ‘curated’ implies a repeatable process with data provenance and the use of appropriate methodologies for covariate conversion. The Determinants of Health datasets draw from multiple sources, resulting in variables with varying degrees of availability, patterns of missing data, and methodological considerations across different sources, geographies, and years.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

VA Community Determinants of Health Data Curation Documentation FY26-Q1

The U.S. Department of Veterans Affairs (VA) places the health and well-being of our nation’s veterans as its top priority. VA is dedicated to offering timely access to high-quality, evidence-based mental health care that meets the needs of veterans and supports their reintegration into society. One of our core missions is to prevent suicide among veterans through innovative approaches and resources. With funding from the VA Office of Mental Health and Suicide Prevention (OMHSP), the Community Determinants of Health (EDH) Data project has developed innovative datasets associated with specific health outcomes, a methodology for transforming spatiotemporal data from one spatial reference (e.g., a 1km grid) to another (e.g., US Census Tracts), and capabilities for modeling health outcomes. These datasets represent an enhancement of the Agency for Healthcare Research and Quality (AHRQ), addressing key gaps by introducing finer spatial resolution (Census Tract) and additional geographical covariates into existing data. The curation and standardization of these datasets is a complex task since they often originate from various sources and are measured at different spatial and temporal resolutions. For example, US Census data products typically use census blocks, block groups, or counties, while data like weather data are available on 1km grids. Some economic data may only be available at the zip code level. In this context, ‘standardized’ means that all datasets share the same spatial extent (e.g., US Census Tract and/or County), and ‘curated’ implies a repeatable process with data provenance and the use of appropriate methodologies for covariate conversion. The Community Determinants of Health datasets draw from multiple sources, resulting in variables with varying degrees of availability, patterns of missing data, and methodological considerations across different sources, geographies, and years.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2026

VA Community Determinants of Health Data Curation Documentation FY26-Q2

The U.S. Department of Veterans Affairs (VA) places the health and well-being of our nation’s veterans as its top priority. VA is dedicated to offering timely access to high-quality, evidence-based mental health care that meets the needs of veterans and supports their reintegration into society. One of our core missions is to prevent suicide among veterans through innovative approaches and resources. With funding from the VA Office of Mental Health and Suicide Prevention (OMHSP), the Community Determinants of Health (EDH) Data project has developed innovative datasets associated with specific health outcomes, a methodology for transforming spatiotemporal data from one spatial reference (e.g., a 1 km grid) to another (e.g., U.S. Census Tracts), and capabilities for modeling health outcomes. These datasets represent an enhancement of the Agency for Healthcare Research and Quality (AHRQ), addressing key gaps by introducing finer spatial resolution (Census Tract) and additional geographical covariates into existing data. The curation and standardization of these datasets is a complex task since they often originate from various sources and are measured at different spatial and temporal resolutions. For example, U.S. Census data products typically use census blocks, block groups, or counties, while data like weather data are available on 1 km grids. Some economic data may only be available at the ZIP code level. In this context, ‘standardized’ means that all datasets share the same spatial extent (e.g., U.S. Census Tract and/or County), and ‘curated’ implies a repeatable process with data provenance and the use of appropriate methodologies for covariate conversion. The Community Determinants of Health datasets draw from multiple sources, resulting in variables with varying degrees of availability, patterns of missing data, and methodological considerations across different sources, geographies, and years.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2021

Expanding standards in viromics: in silico evaluation of dsDNA viral genome identification, classification, and auxiliary metabolic gene curation

Viruses influence global patterns of microbial diversity and nutrient cycles. Though viral metagenomics (viromics), specifically targeting dsDNA viruses, has been critical for revealing viral roles across diverse ecosystems, its analyses differ in many ways from those used for microbes. To date, viromics benchmarking has covered read pre-processing, assembly, relative abundance, read mapping thresholds and diversity estimation, but other steps would benefit from benchmarking and standardization. Here we use in silico-generated datasets and an extensive literature survey to evaluate and highlight how dataset composition (i.e., viromes vs bulk metagenomes) and assembly fragmentation impact (i) viral contig identification tool, (ii) virus taxonomic classification, and (iii) identification and curation of auxiliary metabolic genes (AMGs). The in silico benchmarking of five commonly used virus identification tools show that gene-content-based tools consistently performed well for long (≥3 kbp) contigs, while k -mer- and blast-based tools were uniquely able to detect viruses from short (≤3 kbp) contigs. Notably, however, the performance increase of k -mer- and blast-based tools for short contigs was obtained at the cost of increased false positives (sometimes up to ~5% for virome and ~75% bulk samples), particularly when eukaryotic or mobile genetic element sequences were included in the test datasets. Furthermore, for viral classification, variously sized genome fragments were assessed using gene-sharing network analytics to quantify drop-offs in taxonomic assignments, which revealed correct assignations ranging from ~95% (whole genomes) down to ~80% (3 kbp sized genome fragments). A similar trend was also observed for other viral classification tools such as VPF-class, ViPTree and VIRIDIC, suggesting that caution is warranted when classifying short genome fragments and not full genomes. Finally, we highlight how fragmented assemblies can lead to erroneous identification of AMGs and outline a best-practices workflow to curate candidate AMGs in viral genomes assembled from metagenomes. Together, these benchmarking experiments and annotation guidelines should aid researchers seeking to best detect, classify, and characterize the myriad viruses ‘hidden’ in diverse sequence datasets.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1998

Curation of US Martian Meteorites Collected in Antarctica

To date the ANSMET field team has collected five martian meteorites (see below) in Antarctica and returned them for curation at the Johnson Space Center (JSC) Meteorite Processing Laboratory (MPL). ne meteorites were collected with the clean procedures used by ANSMET in collecting all meteorites: They were handled with JSC-cleaned tools, packaged in clean bags, and shipped frozen to JSC. The five martian meteorites vary significantly in size (12-7942 g) and rock type (basalts, lherzolites, and orthopyroxenite). Detailed descriptions are provided in the Mars Meteorite compendium, which describes classification, curation and research results. A table gives the names, classifications and original and curatorial masses of the martian meteorites. The MPL and measures for contamination control are described.

Lindstrom, M.↗

NASA NTRS2000

Clean and Cold Sample Curation

Curation of Mars samples includes both samples that are returned to Earth, and samples that are collected, examined, and archived on Mars. Both kinds of curation operations will require careful planning to ensure that the samples are not contaminated by the instruments that are used to collect and contain them. In both cases, sample examination and subdivision must take place in an environment that is organically, inorganically, and biologically clean. Some samples will need to be prepared for analysis under ultra-clean or cryogenic conditions. Inorganic and biological cleanliness are achievable separately by cleanroom and biosafety lab techniques. Organic cleanliness to the <50 ng/sq cm level requires material control and sorbent removal - techniques being applied in our Class 10 cleanrooms and sample processing gloveboxes.

Allen, C. C.↗

NASA NTRS2001

JSC Curation and Future Sample Return Missions

Johnson Space Center is the NASA center charged with curation of extraterrestrial samples, and is currently participating on several missions. Our experience shows that curation efforts need to start early, during mission planning and mission design. Additional information is contained in the original extended abstract.

Cyr, K. E.↗

NASA NTRS2003

An Extraction and Curation Technique for Particles Captured in Aerogel Collectors

In 2006, the STARDUST mission will return samples of cometary, interplanetary and interstellar dust captured in aerogel collectors. The curation strategy (or strategies) for STARDUST remain to be defined. Here we present a technique for curation of particles captured in aerogel which will simultaneously preserve the entire particle track, and could allow for the elemental in situ analysis of both the particle residue at the terminus of the track and any particle residues located along the track. This builds on work that we have previously reported elsewhere.

Westphal, A. J.↗

NASA NTRS2007

Genesis Contingency Planning and Mishap Recovery: The Sample Curation View

Planning for sample preservation and curation was part of mission design from the beginning. One of the scientific objectives for Genesis included collecting samples of three regimes of the solar wind in addition to collecting bulk solar wind during the mission. Collectors were fabricated in different thicknesses for each regime of the solar wind and attached to separate frames exposed to the solar wind during specific periods of solar activity associated with each regime. The original plan to determine the solar regime sampled for specific collectors was to identify to which frame the collector was attached. However, the collectors were dislodged during the hard landing making identification by frame attachment impossible. Because regimes were also identified by thickness of the collector, the regime sampled is identified by measuring fragment thickness. A variety of collector materials and thin films applied to substrates were selected and qualified for flight. This diversity provided elemental measurement in more than one material, mitigating effects of diffusion rates and/or radiation damage. It also mitigated against different material and substrate strengths resulting in differing effects of the hard landing. For example, silicon crystal substrates broke into smaller fragments than sapphire-based substrates and diamond surfaces were more resilient to flying debris damage than gold. The primary responsibility of the curation team for recovery was process documentation. Contingency planning for the recovery phase expanded this responsibility to include not only equipment to document, but also gather, contain and identify samples from the landing area and the recovered spacecraft. The team developed contingency plans for various scenarios as part of mission planning that included topographic maps to aid in site recovery and identification of different modes of transport and purge capability depending on damage. A clean tent, set-up at Utah Test & Training Range to control the environment for processing the sample return capsule and cleanly installing a nitrogen purge to the canister, was used to control the environment for extracting collector fragments from the damaged canister and to document and package over 10,000 collector fragments.

Stansbery, E. K.↗

NASA NTRS2002

The Genesis Mission: Contamination Control and Curation

The Genesis mission, launched in August 2001, is collecting samples of the solar wind and will return to Earth in 2004. Genesis can be viewed as the most fundamental of NASA's sample return missions because it is expected to provide insight into the initial elemental and isotopic composition of the solar nebula from which all other planetary objects formed. The data from this mission will have a large impact on understanding the origins and diversity of planetary materials. The collectors consist of clean, pure materials into which the solar wind will imbed. Science and engineering issues such as bulk purity, cleanliness, retention of solar wind, and ability to withstand launch and entry drove material choices. Most of the collector materials are installed on array frames that are deployed from a clean science canister. Two of the arrays are continuously exposed for collecting the bulk solar wind; the other three are only exposed during specific solar wind regimes as measured by ion and electron monitors. Other materials are housed as targets at the focal point of an electrostatic mirror, or "concentrator", designed to enhance the flux of specific solar wind species. Johnson Space Center (JSC) has two principal responsibilities for the Genesis mission: contamination control and curation. Precise and accurate measurements of the composition of the solar atoms require that the collector materials be extremely clean and well characterized before launch and during the mission. Early involvement of JSC curation personnel in concept development resulted in a mission designed to minimize contaminants from the spacecraft and operations. A major goal of the Genesis mission is to provide a reservoir of materials for the 21 51 century. When the collector materials are returned to Earth, they must be handled in a clean manner and their condition well documented. Information gained in preliminary examination of the arrays and detailed surveys of each collector will be used to guide sample allocations to the scientific community. Samples allocated for analysis are likely to be small sections of individual collectors, therefore subdividing the materials must take place in a clean, well characterized way. A major focus of current research at JSC includes identifying and characterizing the contamination, waste, and alteration of the sample when using different subdividing, transport, and storage techniques and developing protocols for reducing their impact on the scientific integrity of the mission.

Stansbery, E. K.↗

NASA NTRS2011

Nuts and Bolts - Techniques for Genesis Sample Curation

The Genesis curation staff at NASA Johnson Space Center provides samples and data for analysis to the scientific community, following allocation approval by the Genesis Oversight Committee, a sub-committee of CAPTEM (Curation Analysis Planning Team for Extraterrestrial Materials). We are often asked by investigators within the scientific community how we choose samples to best fit the requirements of the request. Here we will demonstrate our techniques for characterizing samples and satisfying allocation requests. Even with a systematic approach, every allocation is unique. We are also providing updated status of the cataloging and characterization of solar wind collectors as of January 2011. The collection consists of 3721 inventoried samples consisting of a single fragment, or multiple fragments containerized or pressed between post-it notes, jars or vials of various sizes.

Burkett, Patti J.↗