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.
361
datasets available to search
ShareScore release 0.9.0
Dataset results
361 results for “January”
Simulation results from WRF-Chem without aerosol feedbacks in eastern China for January-March 2017
<p>Simulation results from WRF-Chem without aerosol feedbacks in eastern China for January-March 2017 including meteorology and air quality,which are in wrfout_YYYY-MM-DD_00_00_00 file on each day for January-March 2017. The file 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, PM2_5_DRY, o3, no2, so2, co, nh3, EXTCOF55 and ALT.</p>
Simulation results from WRF-Chem with enabling aerosol-radiation interactions in eastern China for January-March 2017
<p>Simulation results from WRF-Chem with enabling aerosol-radiation interactions in eastern China for January-March 2017 including meteorology and air quality,which are in wrfout_YYYY-MM-DD_00_00_00 file on each day for January-March 2017. The file 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, PM2_5_DRY, o3, no2, so2, co, nh3, EXTCOF55 and ALT.</p>
Simulation results from WRF-CMAQ without aerosol feedbacks in eastern China for January-April 2017
<p>Simulation results from WRF-CMAQ without aerosol feedbacks 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>
Simulation results from WRF-CHIMERE without aerosol feedbacks in eastern China for January-March 2017
<p>Simulation results from WRF-CHIMERE without aerosol feedbacks in eastern China for January-March 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-March 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_out.zip</p><p>Air quality file including out.YYYYMMDD00_24_PHD.nc on each day for January-March 2017, which contains these variables:</p><p>PM25, O3, SO2, NO2, CO and optdaero.</p>
Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China for January-March 2017
<p>Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China for January-March 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-March 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_out.zip</p><p>Air quality file including out.YYYYMMDD00_24_PHD.nc on each day for January-March 2017, which contains these variables:</p><p>PM25, O3, SO2, NO2, CO and optdaero.</p>
Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions in eastern China for January-March 2017
<p>Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions in eastern China for January-March 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-March 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_out.zip</p><p>Air quality file including out.YYYYMMDD00_24_PHD.nc on each day for January-March 2017, which contains these variables:</p><p>PM25, O3, SO2, NO2, CO and optdaero.</p>
The growth of ring current/SYM-H under northward IMF Bz conditions present during the 21-22 January 2005 geomagnetic storm
<p>Database for "The growth of ring current/SYM-H under northward IMF $B_z$ conditions present during the 21-22 January 2005 geomagnetic storm". This collection of the Solar wind, Interplanetary magnetic field, and other satellite data are used in the study to determine the causes of the sustained peak of the ring current indices under unfavorable conditions. The paper is submitted to the Space Weather Paper ( MS# 2023SW003489).</p>
OAEBUDT Community Consultation Dataset January 2023 - July 2023
<p>This work was made possible by the Mellon Foundation through the Advancing to Launch by Developing IDS Governance Building Blocks Grant, and by the 73 participants that contributed in anonymous online and in-person activities facilitated via Mentimeter during workshops, active sessions and presentations at conferences. Christina Drummond and Ursula Rabar designed and facilitated the processes that generated the input for this document. Ursula Rabar prepared this dataset.</p>
CSS-2: Temperature retrieval January 2006
<p>Simulated CAIRT retrieval results for temperatures from ECMWF-IFS 36h forward integration initilaized by ERA-5; Jan 2006</p>
Data Set of selected strong motion parameters and Fourier Amplitude Spectra for the East Anatolian Fault Zone, Türkiye (January 2019 - February 2024)
<p>This product represents a high-quality Data Set useful for seismological studies in the East Anatolian Fault Zone, Türkiye and is addressed to the community that study the seismic source and ground motion.</p> <p>The dataset considers 9,442 events in a magnitude range Ml from 2.0 to 5.5. The period covered by the dataset includes seismicity between January 1, 2019 and February 29, 2024 for a total of 270,704 seismic phases (148,223 P and 122,481 S). In addition to the earthquake catalog, the dataset includes selected strong motion parameters such as selected Peak Ground Acceleration (PGA), Peak Ground Velocity (PGV), as well as Fourier Amplitude Spectra (FAS).</p> <p>The dataset is distributed through the following tables, which are descrived in the "Table of contents" below.</p> <ul> <li><strong>events_catalog.csv</strong> is the file of earthquake;</li> <li><strong>stations.csv </strong>is the file of stations;</li> <li><strong>PGA_PGV.csv </strong>is the file of PGA and PGV;</li> <li><strong>FAS.tar.gz </strong>is the folder which contains (in .csv format) the 98 FAS from 0.05 to 47.20 Hz.</li> </ul> <p>For full details on the dataset and its scientific context, please refer to the paper:</p> <p><strong>L. Colavitti, D. Bindi, G. Tarchini, D. Scafidi, and D. Spallarossa (2025)</strong>. <br><em>"A high-quality Data Set for seismological studies in the East Anatolian Fault Zone, Türkiye"</em>, <br><em>Earth System Science Data</em>, <strong>17(6)</strong>, 3089-3108. <a href="https://doi.org/10.5194/essd-17-3089-2025">https://doi.org/10.5194/essd-17-3089-2025</a>.</p>
Genomic data for Tracing SARS-CoV-2 clusters across local scales: Greater Houston, January–October 2021
Open the record for dataset details and reuse information.
Mesoscale stereo retrievals from Hunga Tonga-Hunga Ha’apai Eruption of 15 January 2022
Open the record for dataset details and reuse information.
Data for continuous and discrete measurements of carbonate parameters in a productive coastal region in the Northwestern Pacific (36°09'13.5''N, 129°24'04.9''E) from January to September in 2019 and from March to December in 2020
Open the record for dataset details and reuse information.
Dodd Frank financial reform at the Commodity Futures Trading Commission (CFTC): Public comments, January 14th, 2010 – July 16th, 2014
Open the record for dataset details and reuse information.
CARTHE drifter trajectories acquired at Fruholmen domain in October 2017 to January 2018
<p>The dataset contains trajectories from 21 CARTHE drifters which were released in October 2017 near the Fruholmen island (northern Norway). Geographical coordinates for each drifter were acquired approximately every 5 minutes via GPS. The project was funded by Research Council of Norway grants 237906 (CIRFA) and 244262 (Retrospect).</p>
Historical quotation of Ibex 35 companies from January 2020 to November 2020
<p>The histogram shows the listing values of Ibex 35 companies from January 2020 to November 2020. There is a histogram for each Ibex 35 company.</p> <p> </p> <p> </p>
Exploits: All registered in exploit-db, from January 2019 to October 2020
<p>This dataset contains all exploits registered on the <a href="https://www.exploit-db.com/">exploit-db website</a>, from 02 January 2019 to 06 November 2020. 2,665 exploits were found in this time range, and stored in CSV file. The CSV fields are as follows:</p> <ul> <li><strong>Id:</strong> exploit-db identifier.</li> <li><strong>Link Exploit:</strong> Link to download exploit code source.</li> <li><strong>App: </strong>Link to download the application in case the exploit is an application, and if it isn't an app the field is empty.</li> <li><strong>Date: </strong>Publication date on the website.</li> <li><strong>Verification:</strong> Exploit verfication by website. </li> <li><strong>Title:</strong> Exploit title.</li> <li><strong>Type:</strong> Exploit type. Could be Local, Remote and Webapp.</li> <li><strong>Platform:</strong> Platform on which the exploit is based on.</li> <li><strong>Author:</strong> Name of exploit author.</li> </ul>
RAMP data subset, January 1 through May 31, 2019
<p>The data are a subset of data from RAMP, the Repository Analytics and Metrics Portal (<a href="http://ramp.montana.edu/">http://ramp.montana.edu/</a>), consisting of data from 35 (out of 50) participating institutional repositories (IR) from the period of January 1 through May 31, 2019. This subset represents data analyzed for a pending publication. For a description of the data collection, processing, and output methods, please see the "methods" section below.</p> <p>The 'RAMP Primer,' a Jupyter Notebook consisting of Python code for combining monthly data and generating some aggregate statistics is available from <a href="https://github.com/imls-measuring-up/ramp-documentation.git">https://github.com/imls-measuring-up/ramp-documentation.git</a>. The linked repository also includes data documentation similar to that provided in the "methods" section below, as well as a file of IR index names useful for subsetting and filtering the data.</p> <p><b>Update: </b>Version two of this dataset was uploaded on January 14, 2020. Thanks to RAMP participants, the RAMP administrators discovered an error in the daily data harvest that resulted in incomplete page-click data for roughly 15 RAMP participating repositories. Only page-click data as described below were affected, and the corrsponding CSV files have been replaced with corrected data. The country-device data were not affected and have not been changed from version 1.</p>
Data from: "De novo assembly transcriptome for the rostrum dace (Leuciscus burdigalensis, Cyprinidae: fish) naturally infected by a copepod ectoparasite" in Genomic Resources Notes accepted 1 December 2014 to 31 January 2015
The emergence of pathogens represents substantial threats to public health, livestock, domesticated animals, and biodiversity. How wild populations respond to emerging pathogens has generated a lot of interest in the last two decades. With the recent advent of high-throughput sequencing technologies it is now possible to develop large transcriptomic resources for non-model organisms, hence allowing new research avenues on the immune responses of hosts from a large taxonomic spectra. We here focused on a wild population of the rostrum dace (Leuciscus burgiladensis) that is infected by Tracheliastes polycolpus, an emerging freshwater ectoparasite copepod. We used next generation Illumina sequencing technology to sequence the transcriptome of eight L. burdigalensis adult individuals collected in natura from the same sampling site. Four individuals were non-infected and four individuals were infected by T. polycolpus. We specifically focused on the spleen, the head kidney and epithelial cells and mucus from the fins, three tissues known to be involved in the immune response of fish. We used the Trinity methodology to reconstruct a de novo full-length transcriptome for L. burdigalensis. The resulting transcriptome will serve as an important broad-scale genomic resource for further studying the response of local population of L. burdigalensis to T. polycolpus pressures.
FIGURE 1. African mammal species described between January 1 1989 and December 31 2008 in A synthesis of African and western Indian Ocean Island mammal taxa (Class: Mammalia) described between 1988 and 2008: an update to Allen (1939) and Ansell (1989)
FIGURE 1. African mammal species described between January 1 1989 and December 31 2008, per year. The spike in 2006 is due largely to Louis et al. (2006b).
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.