cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15485/2319247
title: Timeseries Unlabeled and Labeled Photos, Modeled Stream Elevation, and (Meta)Data of Variably Inundated Streams Across The Yakima River Basin, Washington, United States (v2)

description: This dataset is associated with  the “River Monitoring Photos” (RMP) study and subsequent manuscript (Bao et al. 2025. Monitoring river flow status using low-cost wildlife camera and image segmentation artificial intelligence doi: 10.1016/j.envsoft.2025.106715). Game camera timeseries photos were collected to evaluate stream variable inundation via changes in width. A subset of photos was labeled for training the YOLOv8 and Mask2Former models and used to  segment water surface fractions from all the game camera photos.This data package was originally published in March 2024. It was updated in October 2025 (v2) to add additional photos and files associated with the manuscript (i.e., processed data, labeled photos, and trained models). For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About.In addition to a readme, this data package also includes two file-level metadata (FLMD) files that describes each file and two data dictionaries (DD) that describe all column/row headers and variable definitions. This dataset is comprised of (1) file-level metadata; (2) data dictionary; (3) readme; (4) field metadata; and (5) folders containing game camera photos and manuscript-associated files. Each Yakima River Basin site has a folder that contains subfolders for each month photos were collected. There is also a folder for files associated with the manuscript which has subfolders for labeled data, trained models, Yakima River Basin site water surface fractions, and USGS site water surface fractions.  All files are .csv, .json, .txt, .yaml, .pth, .pt, or .pdf.  We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.
DOI: 10.15485/2447442
title: Upper-air soundings collected during the CROCUS Urban Canyons 2024 campaign in Chicago, Illinois USA

description: Funded by the Department of Energy’s Office of Science, Biological and Environmental Research program, Community Research on Climate and Urban Science (CROCUS) studies urban climate change and the impact it has on communities, with particular focus on disinvested, under-resourced communities. This information leads to new insights on urban climate challenges and informs future actions for mitigating and adapting to climate change at the street, neighborhood and regional levels.As part of the CROCUS effort, the Urban Canyons 2024 project was undertaken to study conditions at unprecedented detail over various neighborhoods in Chicago, Illinois.  This dataset consists of upper air soundings that were collected as part of this effort.  Soundings were launched during two intensive observing periods, IOP1 occurred on 22-23 July 2024, while IOP2 occurred on 27-28 July 2024.  For IOP1, soundings were launched at coordinated times from three sites, Shedd Aquarium in Downtown Chicago, Abizu Campus High School in Humboldt Park, and Gary Comer Youth Center in West Woodlawn. For IOP2, the Gary Comer site was replaced by a neighborhood site in West Woodlawn, Chicago.  The Abizu Campos site was operated by Valparaiso University and used iMET-4 rawinsondes, the other sites were operated by the University of Illinois Urbana-Champaign and used GRAW DFM-19 sondes.This dataset contains netCDF files containing quality-controlled temperature, dewpoint, geopotential height, pressure, and vector wind measurements at 1 second intervals following launch. These files are readable by the open-source netCDF software libraries available in many software packages (i.e., python, R, fortran, C++, etc.). The dataset also contains quicklook plots of each launch on a skew-T log-p thermodynamic diagram.  These are in png format viewable by most web browsers.
DOI: 10.15485/2448101
title: Data and scripts associated with “Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics within Water-Tagging Enabled Hydrologic Models” (v3)

description: This data package is associated with the publication “Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics within Water-Tagging Enabled Hydrologic Models” submitted to Journal of Advances in Modeling Earth Systems (Butler et al. 2025). This study developed the Sequential Precipitation Input Tagging (SPIT) framework to tag input precipitation and estimate water transit times and hydrologic tracers. SPIT tags all precipitation events at regular intervals over an extended period (monthly tags over seven years) in a hydrologic model from 2016-2022. SPIT is applied at six National Ecological Observatory Network (NEON) sites across the continental United States to calculate transit time distributions (TTD) and derive from these mean transit times (MTT), fractions of young water (Fyw), and hydrologic tracer concentrations in stream water (δ18O) within a water-tagging enabled version of the Weather Research and Forecast (WT-WRF-Hydro) model with national water model (NWM) configurations. We go on to validate WT-WRF-Hydro estimates against Butler et al. (2023), who analyzed the same NEON sites using stable water isotope data to estimate water transit times. This new tracking method provides a detailed picture of water movement and helps improve predictions about water availability in the future.This data package was originally published in January 2025. It was updated May 2025 (v2; new and modified files) and October 2025 (v3; new and modified files). File and folder names were not revised to indicate changes. See the change history section in the readme for more details.This data package contains the data and scripts used to develop the SPIT framework WT-WRF-Hydro (Water Tagging Weather Research and Forecasting Hydrologic) model and is associated with the following GitHub repository: https://github.com/zbutler33/SPIT-Framework.This data package contains five parent folders: (1) “Manipulated_outputs”, (2) “Metadata”, (3) “Observed”, (4) “Outputs”, and (5) “Scripts”. Each of these parent folders contains additional subfolders and files. Please see the FLMD (“v*_Butler_2024_WT_WRF_Hydro_flmd.csv”) for a list of all the files contained in this data package and descriptions for each. See the data dictionary (“v*_Butler_2024_WT_WRF_Hydro_dd.csv”) for definitions and units of all of the tabular (files ending in “.csv” and ".tsv") column headers.
DOI: 10.5281/zenodo.17651231
title: Golden Horn Experiements

description: The data generated and analysed during the Golden Horn Experiments are publicly available and can be accessed by interested researchers.
DOI: 10.5281/zenodo.17651232
title: Golden Horn Experiements

description: The data generated and analysed during the Golden Horn Experiments are publicly available and can be accessed by interested researchers.
DOI: 10.7910/dvn/hgifxf
title: Replication Data for: Where to flee? Preferences for host communities among displaced people in Congo

description: This dataset contains the replication data and file for "Where to flee? Preferences for host communities among displaced persons in Congo". Please use the following data files and consult the codebook for variable clarifications: where2flee_conjoint.csv: Contains the conjoint attributes randomly assigned and the choices and outcomes; where2flee_data: Contains the survey data on individuals taking the survey. The script Stoop&VanDerWindt&Weber(2925)_PlosOne_Replication.R runs the full analysis and appendix. For information on the full sampling process, contact the authors.
DOI: 10.34740/kaggle/dsv/13792221
title: Cannabis Store Locations Across Canada
DOI: 10.5281/zenodo.17250202
title: Dimensionality of the reinforced superconductivity of UTe2
DOI: 10.5281/zenodo.17250203
title: Dimensionality of the reinforced superconductivity of UTe2
DOI: 10.15468/dl.ds6bcp
title: Occurrence Download

description: A dataset containing 1519633 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Nudibranchia"
 ]
}

 The dataset includes 1519633 records from 1043 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045514-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15485/2552999
title: CROCUS 3-D wind data from Argonne Deployable Mast during Urban Canyon IOP July 2024

description: During the Community Research on Climate and Urban Science (CROCUS) Urban Integrated Field Laboratory (UIFL) project, led by Argonne National Laboratory, this dataset was collected by METEK uSonic-3 Class A MP sonic anemometer at 10 meter height of the Argonne Deployable Mast (ADM) from July 26 to July 28, 2024, .As part of the CROCUS 2024 Urban Canyon Intensive Observation Period (IOP), 3-D sonic anemometer on the ADM was set up to provide continuous measurements of wind and temperature in Chicago during July 2024. These measurements cover winds in X-, Y- and Z- direction and sonic temperature at 30-Hz resolution. The data are formatted as NetCDF (.nc) files, making them easily accessible using common software such as MATLAB, R, and Python.
DOI: 10.15485/2335799
title: CROCUS Air Quality Data at Northeastern Illinois University Rooftop

description: This dataset is from the Department of Energy Office of Science funded project, Community Research on Urban and Climate Science (CROCUS) (https://crocus-urban.org/). The AQT (Vaisala AQT530) instrument provides observations on meteorological conditions, including particulate matter (PM2.5, PM10), gas species concentrations (NO, NO2, O3, CO), and environment temperature and moisture. These measurements are critical for understanding air quality. These measurements are useful for understanding changes in aerosol properties, air quality research, and comparing to model experiments especially in urban environments.Datasets are stored in the netCDF data format, and we we encourage users to make use the associated toolkits available from Unidata (https://www.unidata.ucar.edu/software/netcdf/), Project Pythia (https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html), and our “Instrument Cookbooks” (https://crocus-urban.github.io/instrument-cookbooks) for more information on how to process the metadata-rich datasets.
DOI: 10.7910/dvn/rhxwwv
title: Replication Data for: "Enhancing Public Support for International Sanctions: An Information Provision Experiment"

description: We examine whether different information frames affect how people perceive the domestic costs of sanctions and support sanctions. Using data from an information provision experiment in Germany and Poland, we demonstrate that people over-estimate the costs of sanctions (GDP loss due to an energy embargo) in sending countries. Yet, this perception can be corrected through the provision of actual in-formation, which in turn enhances the support for the sanction. Contrasting sanc-tions’ costs with other costs—COVID-19 costs and costs imposed on target coun-tries—has no additional effect.
DOI: 10.15485/2482512
title: CROCUS Air Quality Data at Chicago State University Prairie Site

description: The Air Quality Transmitter (AQT) (Vaisala AQT530) instrument provides observations on meteorological conditions, including particulate matter (PM2.5, PM10), gas species concentrations (Nitric Oxide (NO), Nitrogen Dioxide (NO2), Ozone (O3)), and environment temperature and moisture. These measurements are critical for understanding air quality. These measurements are useful for understanding changes in aerosol properties, air quality research, and comparing to model experiments especially in urban environments.This dataset is from the Department of Energy Office of Science funded project, Community Research on Urban and Climate Science (CROCUS) (https://crocus-urban.org/). Datasets are stored in the netCDF data format, and we we encourage users to make use the associated toolkits available from Unidata (https://www.unidata.ucar.edu/software/netcdf/), Project Pythia (https://foundations.projectpythia.org/core/data-formats/netcdf-cf.html), and our “Instrument Cookbooks” (https://crocus-urban.github.io/instrument-cookbooks) for more information on how to process the metadata-rich datasets.
DOI: 10.15485/2998332
title: CROCUS Optical All Precipitation Gauge Data at Argonne National Laboratory Prairie Site

description: The APG (Optical Scientific Inc. All-Precipitation Gauge 815-DS) dataset contains one-minute measurements of precipitation rate, precipitation accumulation, air temperature, and present weather detection, both in 4680 format and decoded. Data were collected at the Argonne Testbed for Multiscale Observational Science (ATMOS), a 20-acre prairie site at Argonne National Laboratory in Lemont, Illinois. The data is presented as daily NetCDF (.nc) files, each containing approximately 24 hours of observations. Files follow the naming convention of: the project (CROCUS), location (atmos), instrument name (apg), data level (raw, a1), and date (year, month, day). The NetCDF format can be accessed using common scientific software such as Python using xarray, netCDF4 or act-doe.
DOI: 10.15485/2283980
title: Model America: Data and Models for every U.S. Building

description: The 5-year goal of the “Model America” concept was to generate a model of every building in the United States. This data repository delivers on that goal with "Model America v1".Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (bit.ly/AutoBEM).There were 125,715,609 buildings detected in the United States. Of this number, 122,146,671 (97.2%) buildings resulted in a successful generation and simulation of a building energy model. This dataset includes the full 125 million buildings. Future updates may include additional buildings, data improvements, or other algorithmic model enhancements in "Model America v2".This dataset contains OSM and IDF zip files for every U.S. county. Each zip file contains the generated buildings from that county.The .csv input data contains the following data fields:1.	ID - unique building ID2.	Centroid - building center location in latitude/longitude (from Footprint2D)3.	Footprint2D - building polygon of 2D footprint (lat1/lon1_lat2/lon2_...)4.	State_abbr - state name5.	Area - estimate of total conditioned floor area (ft2)6.	Area2D - footprint area (ft2)7.	Height - building height (ft)8.	NumFloors - number of floors (above-grade)9.	WWR_surfaces - percent of each facade (pair of points from Footprint2D) covered by fenestration/windows (average 14.5% for residential, 40% for commercial buildings)10.	CZ - ASHRAE Climate Zone designation11.	BuildingType - DOE prototype building designation (IECC=residential) as implemented by OpenStudio-standards12.	Standard - building vintageThis data is made free and openly available in hopes of stimulating any simulation-informed use case. Data is provided as-is with no warranties, express or implied, regarding fitness for a particular purpose. We wish to thank our sponsors which include Oak Ridge National Laboratory (ORNL) Laboratory Directed Research and Development (LDRD), U.S. Dept. of Energy’s (DOE) Building Technologies Office (BTO), Office of Electricity (OE), Biological and Environmental Research (BER), and National Nuclear Security Administration (NNSA).Update (March 2025): Corrected the ID field in all state-level .csv input files to ensure one-to-one consistency with the corresponding .osm and .idf output files. The schema and file structure are unchanged; only the values in the ID column were modified. No files were added or removed, and the .zip bundles (containing .osm/.idf) are unchanged. The corrected .csv inputs were re-extracted in March 2025 from the original data generated ~2021 (Theta supercomputer runs), and published here to align input IDs with model outputs.
DOI: 10.15468/dl.w57esv
title: Occurrence Download

description: A dataset containing 510 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-112.4688 28.49913, -112.3188 28.49913, -112.3188 28.64913, -112.4688 28.64913, -112.4688 28.49913))"
 ]
}

 The dataset includes 510 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045574-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57745/5envnu
title: Elisa+PCR Wintzenheim JAE.xlsx

description: :unav
DOI: 10.57745/dl8kxr
title: Meteorological-records-Wintzenheim-2015-2023.tab

description: :unav
DOI: 10.57745/vs4ktl
title: MeteorologicalDataLegend.doc

description: :unav
DOI: 10.57745/szy3jn
title: StickyTraps-Wintzenheim-2019.tab

description: Dispersal study conducted in June-July 2019 with Parthenolecanium corni first instar nymphs (L1) hatched in the laboratory from freshly laid eggs. First, L1 from 10 females were sprayed with a yellow fluorescent powder, then were placed in a small cup attached to a stake at 1.2 m height near the release source vine R on the 24th of June 2019. P. corni L1 numbers were collected on 8 sticky traps set around the release vine R, and controlled after one week. The cup was refilled with new stained crawlers, after control and trap film replacement. Traps were monitored weekly during three successive weeks.
DOI: 10.57745/qishsl
title: ScaleInsects-records-Wintzenheim.tab

description: Soft scale insects counted yearly on vines of the experimental plot. R=row, P=Plant. Pc=Parthenolecanium corni, Hb=Heliococcus bohemicus, Pv=Pulvinaria vitis
DOI: 10.57745/jeiljc
title: Données de réplication pour : Elisa+PCR-Wintzenheim

description: Distribution of viruses in vines controlled by DAS-ELISA and RT-PCR. R=row, P=Plant. Position of vines around a source vine (I), on the row from East to West: I---, I--, I- , I , I+, I++, I+++
DOI: 10.57745/uclez7
title: Initial-state-hillside2007-2009before-experiment.pptx

description: Before dispersal experiment on the trial plot, all the hillside was inspected from 2007 to 2009 for scale insects and leaf samples from vine stocks were tested by DAS-ELISA for GLRaV-1, -3 and GVA on surrounding vine plots
DOI: 10.15468/dl.9svamc
title: Occurrence Download

description: A dataset containing 636543 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is Côte d’Ivoire"
 ]
}

 The dataset includes 636543 records from 816 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045522-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22002/w123g-hg171
title: Coxiella_ Verocells_28dpi

description: Coxiella burnetii Nine Mile phase II clone 4 (NMIIC4) strain. Coxiella cells purified from infected Vero cells.
description: <strong>Tilt Series Date:</strong> 2017-09-25</p>
<strong>Data Taken By:</strong> Debnath Ghosal</p>
<strong>Species / Specimen:</strong> Coxiella burnetii</p>
<strong>Strain:</strong> Nine Mile phase II clone 4</p>
<strong>Tilt Series Settings:</strong>  Single Axis, tilt range: (-60.0°, 60.0°), step: 2°, constant angular increment, dosage: 130.0 eV/Å²,  defocus: -7.0 μm,  magnification: 27500x. </p>
<strong>Microscope:</strong> Caltech Polara</p>
<strong>Acquisition Software:</strong> UCSFTomo</p>
<strong>Upload Method:</strong> pipeline</p>
<strong>Processing Software Used:</strong> Raptor</p>
<strong>Collaborators and Roles:</strong> Strain sent to us by Robert Heinzen. Data collected and processed by Debnath Ghosal using Caltech tomography pipeline.</p>
<strong>Purification / Growth Conditions / Treatment:</strong> Refer to Heinzen lab.</p>
<strong>Sample Preparation:</strong> Freezing: 100% humidity, 4µl sample, Blot force 6, blot time 4 sec. Wait time 0 sec. Drain time 1 sec. Ethane/propane mix. Grid: Quantifoil Cu 2/2 200. Add gold to cells prior to freezing: 1ul of gold to 4 ul of cells, freeze.T</p>
  dga2017-09-25-112_slicer19035.jpg: multilayer structure beneath the inner membrane
description: Files available via S3 at https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/dga2017-09-25-112/rawdata/</p>Cb_vero_201709250112.mrc,  Tilt Series (Pixel Size 0.39 nm), 1.7 GB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/dga2017-09-25-112/rawdata/Cb_vero_201709250112.mrc"
        > <i class="download icon"></i> Download </a></p>

        Cb_vero_201709250112_part61_3.rec,  Reconstruction (Pixel Size 1.56 nm), 445.4 MB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/dga2017-09-25-112/3dimage_88600/Cb_vero_201709250112_part61_3.rec"
        > <i class="download icon"></i> Download </a></p>
DOI: 10.22002/m4n7a-tbf51
title: perfusion_dcrp_fixed

description: This sample was fixed with 2.5% glutaraldehyde for 1 hour. The cells look sick, the outer membrane looks bad. Fixing for 1 hour turns out to be bad,need to fix for lesser time.
description: <strong>Tilt Series Date:</strong> 2015-08-18</p>
<strong>Data Taken By:</strong> Poorna Subramanian</p>
<strong>Species / Specimen:</strong> Shewanella oneidensis</p>
<strong>Strain:</strong> MR-1</p>
<strong>Tilt Series Settings:</strong>  Single Axis, tilt range: (-60.0°, 60.0°), step: 1.0°, constant angular increment, dosage: 150.0 eV/Å²,  defocus: -10.0 μm,  magnification: 18000x. </p>
<strong>Microscope:</strong> Caltech Polara</p>
<strong>Acquisition Software:</strong> UCSFTomo</p>
<strong>Upload Method:</strong> pipeline</p>
<strong>Processing Software Used:</strong> Batchruntomo</p>
<strong>Collaborators and Roles:</strong> Moh and Sahand</p>
<strong>Purification / Growth Conditions / Treatment:</strong> The sample was grown in perfusion chamber and fixed for 1hour with 2.5% glutaraldehyde. Then washed 3 times in distilled water for 1 minute each. The sample was blotted in a manual plunger with 1ul gold beads.</p>
<strong>Sample Preparation:</strong> The ice was too thick in the squares for which LM images were available, so could not correlate. Took tomograms of all bugs in a square.</p>
description: Files available via S3 at https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/psa2015-08-18-41/3dimage_60520/</p>perfusion_dcrp_atlas10042.rec,  Reconstruction (Pixel Size 2.4 nm), 889.0 MB  
        
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        > <i class="download icon"></i> Download </a></p>

        perfusion_dcrp_atlas10042.mrc,  Tilt Series (Pixel Size 0.6 nm), 3.4 GB  
        
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        > <i class="download icon"></i> Download </a></p>