WFIP3 / WHOI ASIT Lidar / Standardized Data
This dataset contains standardized raw data from the WHOI ASIT deployed for WFIP-3. A ZX 300M is currently installed at the tower and has been deployed there since September 2021.
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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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Buoy 130 / Standardized Data
These are the standardized buoy data collected during the WFIP3 project period, initially deployed near the Martha's Vineyard region for validation and later deployed at the WFIP3 location. The NetCDF files contain the data for all of the *.csv files for a given day.
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Eddy Covariance Flux / Standardized Data
This dataset contains standardized Eddy Covariance Flux data.
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Tsdat: An Open-Source Data Standardization Framework for Marine Energy and Beyond: Preprint
Many organizations are tasked with the collection and processing of large quantities of data from various measurement devices. Data reported from these sources are often not interoperable with datasets and software used by analysts and other organizations in the same field, introducing barriers for collaboration on large-scale projects. This poses a particular problem for cross-device comparisons and machine learning applications. To address these challenges, the open source Time-Series Data Pipelines (Tsdat) software was developed by a joint collaboration between Pacific Northwest National Laboratory, the National Renewable Energy Laboratory, and Sandia National Laboratories to facilitate collaboration and accelerate advancements in the Marine Energy domain through the development of an open-source ecosystem of tools. This paper will describe the Tsdat software and the data standards within which the framework operates. A beta version of the framework has been released and is currently being used by several projects in marine energy, wind energy, and building energy systems.
big data↗
Including 238 U(n,f)/ 235 U(n,f) and 239 Pu(n,f)/ 235 U(n,f) NIFFTE fission TPC Cross-sections into the Neutron Data Standards Database
The primary purpose of this report is to document how the 238 U/ 235 U and 239 Pu/ 235 U neutron induced fission cross-section ratios, 238 U(n,f)/ 235 U(n,f) and 239 Pu(n,f)/ 235 U(n,f), respectively, measured by the NIFFTE fission Time Projection Chamber (fissionTPC) were included in the most recent database (termed GMA) underlying Neutron Data Standards (NDS) evaluations. This report shows and discusses NDS input files, and underlying assumptions regarding the uncertainty estimate and necessary for including these data. This uncertainty estimate and the resulting files were based on information provided by fissionTPC experimentalists, R.J.Casperson, N.S. Bowden, L. Snyder and K.T. Schmitt for the 238 U ratio, and by L. Snyder for the 239 Pu ratio. The fissionTPC data were included twice, by D. Neudecker and V. Pronyaev, to counter-check results and exclude possible mistakes in their inclusion. It is shown in both evaluations that including fissionTPC 239 Pu(n,f)/ 235 U(n,f) data points to a lower evaluated 239 Pu(n,f) cross section above 10 MeV than the currently released NDS data. This raises the question whether a part of a previous dataset by Tovesson et al., that was previously rejected above 13 MeV for having low values, should be included in the NDS evaluation after all. The evaluated 238 U(n,f) cross section only changes significantly close to the threshold. The impact on the 235 U(n,f) cross section is minimal. fissionTPC data reduce evaluated uncertainties on both observables by 0–12% of the GMA evaluated uncertainties. However, the currently released NDS data contain in addition to these GMA evaluated uncertainties “Unrecognized Sources of Uncertainties” (USU) of 1.2%. It needs to be further discussed within the NDS project, whether the new fissionTPC data should also reduce USU.
238U(n,f)/235U(n,f)↗
Applying a Template of Expected Uncertainties to Updating 239 Pu(n,f) Cross-section Covariances in the Neutron Data Standards Database
Templates of uncertainties expected in specific measurement types were recently developed. One aim of these templates is to help evaluators in identifying (1) missing or suspiciously low uncertainties and (2) missing correlations between uncertainties of the same and different experiments, when estimating covariances for experimental data employed in their evaluations. These templates also provide realistic estimates of standard deviations and correlations for a particular uncertainty source and measurement type that can be used by evaluators in situations where they are not supplied by the experimenters. This information allows for a more comprehensive uncertainty analysis across all measurements considered in an evaluation and, thus, more realistic evaluated covariances. Here, in this work, we extend a template that is applicable to uncertainties expected in neutron-induced fission, (n,f), cross-section measurements. It is applied to improving covariances of 239 Pu(n,f) cross-section measurements in the database underlying the Neutron Data Standards evaluations. This particular example was chosen since this evaluation is primarily based on experimental information. Also, some uncertainties of individual 239 Pu(n,f) cross-section experiments in this database were suspected to be underestimated. The evaluated uncertainties obtained after updating the covariances in the database by means of the template indeed do increase compared to their original values. Even more importantly, the evaluated mean values change noticeably. These modified cross sections impact application calculations significantly, as is demonstrated by employing them in simulations of the effective neutron multiplication factor for a few selected critical assemblies. However, this updated evaluated 239 Pu(n,f) cross section should not be interpreted as the final one that should replace values of the current Neutron Data Standards project. Evaluations for the Neutron Data Standards of the 239 Pu(n,f) cross section must be linked to many other observables included in the associated database, most notably to cross sections for 235 U(n,f), but also to those for 10 B(n, α ), 6 Li(n,t), 238 U(n,f), and 238 U(n, γ ), because of included measurements of the 239 Pu(n,f) cross section that appear as ratios to these reactions. Some of these other reactions are correlated to further observables in the database. Hence, updating uncertainties of data sets of any of these observables can potentially impact the 239 Pu(n,f) cross section. Uncertainties for all measurements of these linked physical observables have to be updated before a comprehensive evaluation of the 239 Pu(n,f) cross section and its corresponding uncertainties can be provided.
239Pu Neutron-induced fission cross-section↗
Validation of standardized data formats and tools for ground-level particle-based gamma-ray observatories
Context. Ground-based γ-ray astronomy is still a rather young field of research, with strong historical connections to particle physics. This is why most observations are conducted by experiments with proprietary data and analysis software, as is usual in the particle physics field. However, in recent years, this paradigm has been slowly shifting toward the development and use of open-source data formats and tools, driven by upcoming observatories such as the Cherenkov Telescope Array (CTA). In this context, a community-driven, shared data format (the gamma-astro-data-format, or GADF) and analysis tools such as Gammapy and ctools have been developed. So far, these efforts have been led by the Imaging Atmospheric Cherenkov Telescope community, leaving out other types of ground-based γ-ray instruments. Aims. We aim to show that the data from ground particle arrays, such as the High-Altitude Water Cherenkov (HAWC) observatory, are also compatible with the GADF and can thus be fully analyzed using the related tools, in this case, Gammapy. Methods. We reproduced several published HAWC results using Gammapy and data products compliant with GADF standard. We also illustrate the capabilities of the shared format and tools by producing a joint fit of the Crab spectrum including data from six different γ-ray experiments. Results. We find excellent agreement with the reference results, a powerful confirmation of both the published results and the tools involved. Conclusions. The data from particle detector arrays such as the HAWC observatory can be adapted to the GADF and thus analyzed with Gammapy. A common data format and shared analysis tools allow multi-instrument joint analysis and effective data sharing. To emphasize this, a sample of Crab nebula event lists is made public with this paper. Because of the complementary nature of pointing and wide-field instruments, this synergy will be distinctly beneficial for the joint scientific exploitation of future observatories such as the Southern Wide-field Gamma-ray Observatory and CTA.
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Evolving data standards for cryo-EM structures
Electron cryo-microscopy (cryo-EM) is increasingly being used to determine 3D structures of a broad spectrum of biological specimens from molecules to cells. Anticipating this progress in the early 2000s, an international collaboration of scientists with expertise in both cryo-EM and structure data archiving was established (EMDataResource, previously known as EMDataBank). The major goals of the collaboration have been twofold: to develop the necessary infrastructure for archiving cryo-EM-derived density maps and models, and to promote development of cryo-EM structure validation standards. We describe how cryo-EM data archiving and validation have been developed and jointly coordinated for the Electron Microscopy Data Bank and Protein Data Bank archives over the past two decades, as well as the impact of evolving technology on data standards. Just as for X-ray crystallography and nuclear magnetic resonance, engaging the scientific community via workshops and challenging activities has played a central role in developing recommendations and requirements for the cryo-EM structure data archives.
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Standardized Data to Improve Understanding and Modeling of Soil Nitrogen at Continental Scale
Abstract Nitrogen (N) is a key limiting nutrient in terrestrial ecosystems, but there remain critical gaps in our ability to predict and model controls on soil N cycling. This may be in part due to lack of standardized sampling across broad spatial–temporal scales. Here, we introduce a continentally distributed, publicly available data set collected by the National Ecological Observatory Network (NEON) that can help fill these gaps. First, we detail the sampling design and methods used to collect and analyze soil inorganic N pool and net flux rate data from 47 terrestrial sites. We address methodological challenges in generating a standardized data set, even for a network using uniform protocols. Then, we evaluate sources of variation within the sampling design and compare measured net N mineralization to simulated fluxes from the Community Earth System Model 2 (CESM2). We observed wide spatiotemporal variation in inorganic N pool sizes and net transformation rates. Site explained the most variation in NEON’s stratified sampling design, followed by plots within sites. Organic horizons had larger pools and net N transformation rates than mineral horizons on a sample weight basis. The majority of sites showed some degree of seasonality in N dynamics, but overall these temporal patterns were not matched by CESM2, leading to poor correspondence between observed and modeled data. Looking forward, these data can reveal new insights into controls on soil N cycling, especially in the context of other environmental data sets provided by NEON, and should be leveraged to improve predictive modeling of the soil N cycle.
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IHMCIF: An Extension of the PDBx/mmCIF Data Standard for Integrative Structure Determination Methods
Not Available
Vallat, Brinda (ORCID:0000000240768984)↗
Data Standards for Machine Learned Interatomic Potentials of Plasma Facing Materials
Explore the source record for details and available documents.
Wood, Mitchell Anthony [Sandia National Laboratori↗
Laser Disdrometer / Standardized Data
This dataset contains raw data from the laser disdrometer at Nantucket. The disdrometer measures droplet size distribution, hydrometer type, and precipitation rate.
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TTP - WREF LLNL Streamline Scanning Lidar / Standardized Data
These data are from a deployment of the LLNL Halo Streamline scanning lidar in Summer 2025. The scanning lidar was deployed in a clearing area 880 m south of the NEON tower.
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Laser Disdrometer / Standardized Data
The Parsivel2 Laser Disdrometers provide accurate measurements of precipitation, hail and snow. They also provide droplet size distributions.
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Laser Disdrometer / Standardized Data
The Parsivel2 Laser Disdrometers provide accurate measurements of precipitation, hail and snow. They also provide droplet size distributions.
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Laser Disdrometer / Standardized Data
The Parsivel2 Laser Disdrometers provide accurate measurements of precipitation, hail and snow. They also provide droplet size distributions.
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Laser Disdrometer / Standardized Data
The Parsivel2 Laser Disdrometers provide accurate measurements of precipitation, hail and snow. They also provide droplet size distributions.
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Laser Disdrometer / Standardized Data
The Parsivel2 Laser Disdrometers provide accurate measurements of precipitation, hail and snow. They also provide droplet size distributions.
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