Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
569
datasets available to search
ShareScore release 0.9.0
Dataset results
569 results for “APRIL”
Simulation results from WRF-CMAQ with enabling aerosol-radiation interactions in eastern China for January-April 2017
<p>Simulation results from WRF-CMAQ with enabling aerosol-radiation interactions in eastern China for January-April 2017 including meteorology and air quality:</p><p>YYYYMM_wrfout.zip:</p><p>Meteorological file including wrfout_YYYY-MM-DD_00_00_00 on each day for January-April 2017, which contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB</p><p>YYYYMM_CCTM_ACONC.zip:</p><p>Air quality file including CCTM_ACONC_v3852_YYYYMMDD.nc on each day for January-April 2017, which contains these variables:</p><p>ASO4I, ANO3I, ANH4I, ANAI, ACLI, AECI, ALVPO1I, ASVPO1I, ASVPO2I, ALVOO1I, ALVOO2I, ASVOO1I, ASVOO2I, AOTHRI, ASO4J, ANO3J, ANH4J, ANAJ, ACLJ, AECJ, AOTHRJ, AFEJ, ASIJ, ATIJ, ACAJ, AMGJ, AMNJ, AALJ, AKJ, ALVPO1J, ASVPO1J, ASVPO2J, AXYL1J, AXYL2J, AXYL3J, ATOL1J, ATOL2J, AXYL2J, AXYL3J, ATOL1J, ABNZ3J, AISO1J, AISO2J, AISO3J, ATRP1J, ATRP2J, ASQTJ, AALK1J, AALK2J, APAH1J, APAH2J, APAH3J, AORGCJ, AOLGBJ, AOLGAJ, ALVOO1J, ALVOO2J, ASVOO1J, ASVOO2J, ASVOO3J, APCSOJ, ASOIL, ACORS, ACLK, ASO4K, ANO3K, ANH4K, O3, SO2, NO2, CO, and NH3.</p><p>YYYYMM_CCTM_APMDIAG.zip:</p><p>Air quality file including CCTM_APMDIAG_v3852_YYYYMMDD.nc on each day for January-April 2017, which contains these variables:</p><p>PM25AT, PM25AC and PM25CO.</p><p>YYYYMM_CCTM_PHOTDIAG1.zip:</p><p>Air quality file including CCTM_PHOTDIAG1_v3852_YYYYMMDD.nc on each day for January-April 2017, which contains these variables:</p><p>OZONE_COLUMN, NO2_COLUMN, CO_COLUMN, SO2_COLUMN, HCHO_COLUMN, TROPO_O3_COLUMN and AOD_W550_ANGST.</p>
Analysis of the Ground Level Enhancement GLE 60 on April 15, 2001, and its Space Weather Effects: Comparison with Dosimetric Measurements - Data
<p>Computed data that was used within the "Analysis of the Ground Level Enhancement GLE 60 on April 15, 2001, and its Space Weather Effects: Comparison with Dosimetric Measurements" paper. Computations of cones were done by OTSO using TSY89 + IGRF13 magnetic field parameters. Contains the atmospheric yield functions used for radiation computation as well as the global radiation map at 35kft for GLE60. Data is provided in .csv format.</p>
coSIF Data Product for February, April, July, and October 2021
<p>The monthly, 0.05-degree resolution coSIF predictions and corresponding root-mean-squared prediction errors (RMSPEs) for each of February, April, July, and October 2021 over North America. Each NetCDF file corresponds to one of the four months and contains two variables: "cosif_prediction" and "cosif_rmspe." For example, "coSIF_202102.nc4" corresponds to February 2021. All units are Watts per square meter, per steradian, and per micrometer (W \ m^2 \ sr \ <span class="math-tex">\(\mu\)</span>m).</p> <p>As described in Jacobson et. al. (2023), predictions and RMSPEs for July 2021 were produced using cokriging. For all other months, predictions and RMSPEs were produced using kriging.</p>
IUCLID for pesticides filtering rule proposal for April 2024
<p>These are the draft filtering rules for pesticides dossiers in IUCLID proposed for implementation as from April 2024. The proposal is made by EFSA with the endorsement of the IUCLID PSN sub-group. These rules are up for public consultation until 20 September and any feedback can be provided through EU Survey where more details on the proposal can also be found: <a href="https://ec.europa.eu/eusurvey/runner/bae82a4d-e924-67e4-59fc-b1f3bcfdedb5">https://ec.europa.eu/eusurvey/runner/bae82a4d-e924-67e4-59fc-b1f3bcfdedb5</a></p>
Seismic records of the April 12, 2014 Solomon Islands (Mw = 7.6) earthquake (Sadeghi-Bagherabadi et al. 2023)
<p>Seismic records of the April 12, 2014 Solomon Islands (Mw = 7.6) earthquake (Sadeghi-Bagherabadi et al. 2023), recorded by the CIGSIP temporarry network in the western Arabia-Eurasia collision zone.</p> <p>Contact:<br> Amir Sadeghi-Bagherabadi (amir.sadeghi@hotmail.com)</p> <p>It is a supplement to:</p> <p><strong>Sadeghi-Bagherabadi, A., Margheriti, L., Aoudia, A., Baccheschi, P., Lucente, F. P., Sobouti, F., (2023). Anisotropic Gradients in Iran: Quasi-Love Waves Illuminate the Deep Structure and Deformation Style of the Zagros, Alborz and Kopet Dagh. Journal of Geodynamics, <a href="https://doi.org/10.1016/j.jog.2023.101989">https://doi.org/10.1016/j.jog.2023.101989</a></strong></p> <p>If you use this dataset, please cite the following paper:</p> <p><strong>Sadeghi-Bagherabadi, A., Margheriti, L., Aoudia, A., Baccheschi, P., Lucente, F. P., Sobouti, F., (2023). Anisotropic Gradients in Iran: Quasi-Love Waves Illuminate the Deep Structure and Deformation Style of the Zagros, Alborz and Kopet Dagh. Journal of Geodynamics, <a href="https://doi.org/10.1016/j.jog.2023.101989">https://doi.org/10.1016/j.jog.2023.101989</a></strong></p> <p>_________________________________________________________________</p> <p><br> Table of contents: </p> <p>SAC_files.tar.gz : includes seismic records of the April 12, 2014 Solomon Islands (Mw = 7.6) earthquake. The SAC file names are formatted as: YYYY.MM.DD-hh.mm.ss._SSSc.sac. For example '2014.04.12-20.14.39._E01e.sac' is the E-W component of station E01</p> <p>Resp_files.tar.gz : includes the station response files. The response file names are formatted as:MSSS-resp.txt. For example 'ME01-resp.txt' is the response file for station E01.</p> <p>_________________________________________________________________</p> <p>The CIGSIP project was a trilateral undertaking by the Institute for Advanced Studies in Basic Sciences (IASBS), Geological Survey of Iran, and Chinese Academy of Sciences. CIGSIP was funded and supported by the Strategic Priority Research Program (B) (Grant number XDB03010802) and the International Partnership Program (GJHZ1776) of the Chinese Academy of Sciences.</p>
AIS heatmap: North Sea and Dutch Inland Waterways for the months January, April, July, October in 2019
<p>This dataset contains information on vessel movements in the North Sea and Dutch Inland Waterways for the months January, April, July, and October in 2019. It provides a heatmap representation of vessel traffic density during these specific months, which can be useful for various maritime and environmental analyses.</p> <p>1. File Formats</p> <p>The dataset is provided in the following file formats:</p> <ul> <li>NetCDF : The primary data files are available in netcdf format. For each grid cell the variables sog (Speed Over Ground) and count (Number of AIS messages) are available</li> <li>GeoTIFF (Georeferenced Tagged Image File Format): Heatmap images are provided in GeoTIFF format, suitable for geographic visualization.</li> </ul> <p>The dataset is split into tiles. Each tile conforms to the <a href="https://wiki.openstreetmap.org/wiki/Tiles">OSM tiling</a> naming scheme.</p> <p>2. Variables </p> <p>The dataset includes the following key variables:</p> <ul> <li><strong>Speed Over Ground (SOG)</strong>: The average vessel's speed over the ground for all the messages.</li> <li><strong>Count</strong>: The number of AIS messages received in this location</li> </ul> <p>3. Data Collection Method </p> <p>The AIS data used in this dataset was collected from AIS transponders on vessels operating in the North Sea and Dutch Inland Waterways. These transponders transmit information such as vessel position, speed, and identification. The dataset aggregates this information to create heatmap images for analysis. We did this on all the messages. Some ships emit more messages than others. Ships emit messages at higher frequency when sailing than when stationary. </p> <p>4. Source of Original Data</p> <p>The original AIS data used to create this dataset was sourced from the AIS archive from Rijkswaterstaat. This dataset was analysed for the purpose of a <a href="https://ais-scrolly.netlify.app/">storymap</a>.</p> <p> </p> <p> </p>
Processed GPM-DPR Convective Profiles (April 2014 - November 2023)
Open the record for dataset details and reuse information.
HEartS Professional Survey: Charting the effects of COVID-19 lockdown 1.0 on working patterns, income, and wellbeing among performing arts professionals in the United Kingdom (April–June 2020)
Open the record for dataset details and reuse information.
High-frequency sensor data collected by Stroud Water Research Center in a recovery reach of White Clay Creek site ID WCC017 from April through December 2018
High-frequency sensor data at 5-min intervals using a s::can®oxy::lizer IITM and Solinst level logger, an Apogee SQ-212 sensor, and an s::can® field spectrophotometer in a recovery reach at White Clay Creek from April through December 2018. These data were collected as part of a study focused on baseflow dynamics of DOC and nitrate in White Clay Creek, Stroud Water Research Center. The parameters in this data package are water temperature, dissolved oxygen, depth, Photosynthetically Active Radiation (PAR), dissolved oxygen concentration, dissolved organic carbon concentration (DOC) and nitrate concentration. Data are presented in two tables. All the parameters and table are further explained in the metadata.
Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating Research (CiPEHR) Extended sites: winter ecosystem respiration chamber measurements using snow removal method. Oct-Nov 2009, Oct-Dec 2011, Oct-Nov; March-April 2012, Feb-May 2013.
The Carbon in Permafrost Experimental Heating Research (CiPEHR) project addresses the following questions: 1) Does ecosystem warming cause a net release of C from the ecosystem to the atmosphere?, 2) Does the decomposition of old C, that comprises the bulk of the soil C pool, influence ecosystem C loss?, and 3) How do winter and summer warming alone, and in combination, affect ecosystem C exchange? We are answering these questions using a combination of field and laboratory experiments to measure ecosystem carbon balance and radiocarbon isotope ratios at a warming experiment located in an upland tundra field site near Healy, Alaska in the foothills of the Alaska Range. This dataset contains point measurements of winter ecosystem respiration fluxes using the snow removal method and the soil temperature, air temperature, and snow depth associated with each flux.
Marsh water table height, logging data from the railroad Spartina marsh site on the Parker River for April-November 2012.
Measurements of water table height in the Parker River marsh located downstream of the railroad bridge. Measurements were taken every 5 minutes at each logger along a transect of water level loggers running perpendicular to the Parker River bank at the railroad site, MAR-PR-Wtable-RR for April-November 2012.
Marsh water table height, logging data from the Typha marsh site on the upper Parker River for April-November 2012.
Measurements of water table height in the upper Parker River Typha sp. marsh. Measurements were taken every 5 minutes at each logger along a transect of water level loggers running perpendicular to the Parker River bank at the Typha site, MAR-PR-Wtable-T, for April - November 2012
Marsh water table height, logging data from the Typha marsh site on the upper Parker River for April-November 2014.
Measurements of water table height in the upper Parker River Typha sp. marsh. Measurements were taken every 5 minutes at each logger along a transect of water level loggers running perpendicular to the Parker River bank at the Typha site, MAR-PR-Wtable-T, for April - November 2014
Marsh water table height, logging data from the railroad Spartina marsh site on the Parker River for April-November 2015.
Measurements of water table height in the Parker River marsh located downstream of the railroad bridge. Measurements were taken every 5 minutes at each logger along a transect of water level loggers running perpendicular to the Parker River bank at the railroad site, MAR-PR-Wtable-RR for April-October 2015.
Marsh water table height, logging data from the Typha marsh site on the upper Parker River for April-November 2015.
Measurements of water table height in the upper Parker River Typha sp. marsh. Measurements were taken every 5 minutes at each logger along a transect of water level loggers running perpendicular to the Parker River bank at the Typha site, MAR-PR-Wtable-T, for April - November 2015
Upper Phillips Creek soil organic content and bulk density April, 2017
Soil samples were taken in Phillips Creek Marsh (near Nassawadox, VA) and organic fraction and bulk density determined.
Vegetation and Building Heights for Accomack and Northampton Counties, Virginia, April 2015
This dataset gives the aboveground height of vegetation and buildings in Northampton and Accomack Counties, VA in April 2015. LiDAR data were collected April 11-24, 2015. A mosaiced DEM of ground elevations was assembled from DEM tiles from USGS. A LAS dataset of the classified LiDAR point cloud was assembled and a DEM of first-returns (representing the top of vegetation of buildings) created. The ground-elevation DEM was subtracted from the first-return DEM to yeild a difference layer that reflects the height of the vegetation or buildings above the ground level. Areas classified as Ponds, Lakes or Tidal areas were all set to 0 to avoid artifacts caused by waves etc. The resulting DEM was reprojected from State Plane to UTM coordinates and elevation units were changed from US Feet to Meters. The data contains some odd values in the seaside portion of the data. Heights > 10 meters in marsh areas are highly suspect.
TweetsKB (Part 7, April 2018 - April 2019)
<p><strong>TweetsKB</strong><strong> </strong>is a public RDF corpus of anonymized data for a large collection of <strong>annotated </strong>tweets. The dataset currently contains data for more than <strong>1.9 billion tweets</strong>, spanning more than 7 years (February 2013 - April 2020). Metadata information about the tweets as well as extracted <strong>entities</strong>, <strong>sentiments</strong>, <strong>hashtags</strong>, <strong>user mentions</strong> and <strong>URLs </strong>are exposed in RDF using established RDF/S vocabularies*. Example queries and more information are available through TweetsKB's home page: <a href="https://data.gesis.org/tweetskb/">https://data.gesis.org/tweetskb/</a>.</p> <p> </p> <p><em>* For the sake of privacy, we anonymize user IDs and we do not provide the text of the tweets.</em></p>
WRF v3.9 evaluation statistics, April and October 2015 Ireland
<p>Dataset related to Chapter 4 of PhD thesis "Modelling of accidental radioactive releases for Ireland" By Cillian Joy.<br> This folder contains a file for each statistic used. Time series data is aggregated for each month of the WRF v3.9 evaluation, April and October 2015.<br> Data is for each station (28), meteorology variable (wind speed, wind direction, and precipitation) for each statistic (7 for wind speed and precipitation, and 3 for wind direction.<br> For each location, the value provided is for the month. For example, Fractional Bias for one location for the month is an average of all time steps (1464).</p> <p>The seven statistic are:</p> <ol> <li>Factor of data within a factor (FAC 1.5)</li> <li>Factor of data within a factor (FAC 2.0)</li> <li>Fractional Bias (FB)</li> <li>Normalised Mean Square Error (NMSE)</li> <li>Correlation (R)</li> <li>Geometric Mean Bias (GMB)</li> <li>Geometric Mean Variance (GMV)</li> </ol> <p>21 May 2020, Cillian Joy, cillian.joy@nuigalway.ie</p>
Cloud radar, micro rain radar, parsivel and pluvio measurements at Ny-Ålesund for 7 Feb 2018, 16 March 2018 and 16 April 2018
<p>This data set contains netcdf files of the University of Cologne's cloud radar MiRAC-A, micro rain radar, parsivel and pluvio installed at the Arctic research site AWPIEV at Ny-Ålesund. Data are available for 3 days: 7 Feb 2018, 16 March 2018 and 16 April 2018.</p> <p>The MiRAC-A hourly files (“mirac-a_nya_compact_*_P01_ZEN.nc” include (among other variables):</p> <p>float Ze(time, range) ;</p> <p>Ze:long_name = "Equivalent radar reflectivity factor Ze" ;</p> <p>Ze:units = "mm^6/m^3" ;</p> <p>float vm(time, range) ;</p> <p>vm:long_name = "Mean Doppler velocity" ;</p> <p>vm:units = "m/s" ;</p> <p>vm:comment = "negative values indicate falling particles towards the radar" ;</p> <p>float sigma(time, range) ;</p> <p>sigma:long_name = "Spectral width of Doppler velocity spectrum" ;</p> <p>sigma:units = "m/s" ;</p> <p> </p> <p>The Micro Rain Radar daily files (“*_nya_mrr_improtoo_0-101.nc”) include (among other variables):</p> <p>float Ze(time, range) ;</p> <p>Ze:description = "reflectivity of the most significant peak" ;</p> <p>Ze:units = "dBz" ;</p> <p> </p> <p>The parsivel daily files (“sups_nya_dm00_l1_any_v00_*.nc”) include (among other variables):</p> <p>float N(dclasses, time) ;</p> <p>N:fill_value = NaN ;</p> <p>N:units = "log10(m-3 mm-1)" ;</p> <p>N:long_name = "particle concentration per diameter class" ;</p> <p>float dclasses(dclasses) ;</p> <p>dclasses:units = "mm" ;</p> <p>dclasses:long_name = "volume equivalent diameter class center" ;</p> <p> </p> <p>The pluvio daily files (“pluvio_nya_*.nc”) include (among other variables):</p> <p>r_accum_NRT(dim) ;</p> <p>r_accum_NRT:description = "accumulated precipitation NRT" ;</p> <p>r_accum_NRT:units = "mm" ;</p> <p> </p> <p>All available variables are listed and described in the header of the corresponding netcdf files.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.