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ShareScore release 0.9.0
Dataset results
32 results for “2013-2014”
Immunogenicity and Safety Study of GlaxoSmithKline (GSK) Biologicals' Trivalent Split Virion Influenza Vaccine Fluviral™ (2013-2014 Season) in Adults Aged 18 Years and Older
ClinicalTrials.gov study NCT01878825. IPD Sharing: YES. Countries: 1. Publications: 0.
WRF-STILT Particle Trajectories for Boston, MA, USA, 2013-2014
This dataset provides Weather Research and Forecasting (WRF) Stochastic Time-Inverted Lagrangian Transport (STILT) particle trajectory data and footprint products for two receptors located in Boston, Massachusetts, USA, for July 2013 - December 2014. Meteorological fields from version 3.6.1 of the Weather Research and Forecasting model are used to drive STILT. STILT applies a Lagrangian particle dispersion model backwards in time from a measurement location (the "receptor" location), to create the adjoint of the transport model in the form of a "footprint" field. The footprint, with units of mixing ratio (ppm) per surface flux (umol m-2 s-1), quantifies the influence of upwind surface fluxes on CO2 and CH4 concentrations measured at the receptor and is computed by counting the number of particles in a surface-influenced volume and the time spent in that volume. Footprints are provided for the two receptors at two temporal and spatial scales: three days of surface influence over the whole North American coverage area at 1-degree resolution and 24 hours of surface influence within a smaller region close to the measurement locations ('near field') at 0.1-degree resolution.
CO2 Observations, Modeled Emissions, and NAM-HYSPLIT Footprints, Boston MA, 2013-2014
This dataset reports continuous atmospheric measurements of CO2 from two receptor sites and three boundary sites in and around Boston, Massachusetts, USA, that were combined with high-resolution CO2 emissions estimates and the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to estimate regional CO2 emissions from September 2013 to December 2014. The HYSPLIT model followed an ensemble of 1,000 particles released at the urban CO2 measurement sites backward in time based on wind fields and turbulence from the North American Mesoscale Forecast System (NAM) at 12-km resolution to the boundary CO2 measurement sites to derive footprint values and CO2 enhancements expected from the prior emissions based on the Anthropogenic Carbon Emissions System (ACES) inventory and the urban-Vegetation Photosynthesis Respiration Model (urbanVPRM). This dataset contains three sets of data products: (1) observed hourly mean CO2 observations for two urban receptor sites in Boston, MA (Boston University (BU) and Copley Square (COP)), (2) observed hourly mean CO2 and calculated vertical profiles (50 - 5000 m) for three boundary sites around Boston including Harvard Forest at Petersham, MA (HF), Canaan, NH (CA), and Martha's Vineyard, MA (MVY), and modeled mean boundary CO2 concentrations for particles released from BU and COP, and (3) particle trajectory files including footprint values and CO2 enhancements above boundary CO2 concentrations from the HYSPLIT model.
MEaSUREs MODIS Mosaic of Antarctica 2013-2014 (MOA2014) Image Map, Version 1
This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program, includes two image maps - a snow grain size map and a surface morphology map - provided at two different resolutions of 125 m and 750 m. The maps were produced from composited image swath data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) over Antarctica for the 2013-2014 austral summer season.
WRF-STILT Gridded Footprints for Boston, MA, USA, 2013-2014
This dataset provides Weather Research and Forecasting (WRF) Stochastic Time-Inverted Lagrangian Transport (STILT) footprint data products for two receptors located in Boston, Massachusetts, USA, for July 2013 - December 2014. The data are gridded footprints on a 1-km grid congruent with the ACES emissions inventory. Meteorological fields from version 3.5.1 of the Weather Research and Forecasting model are used to drive STILT. STILT applies a Lagrangian particle dispersion model backwards in time from a measurement location (the "receptor" location), to create the adjoint of the transport model in the form of a "footprint" field. The footprint, with units of mixing ratio, quantifies the influence of upwind surface fluxes on CO2 and CH4 concentrations measured at the receptor and is computed by counting the number of particles in a surface-influenced volume and the time spent in that volume.
Measurements from the debris-covered Imja-Lhotse Shar Glacier (2013-2014)
<p>These data are from the debris-covered portion of Imja-Lhotse Shar Glacier (27.901N, 86.938E, ~5050 m a.s.l.) located in the Nepal Himalaya that were collected during three field expeditions between September 2013 and November 2014. The data includes debris thickness measurements derived primarily by manual excavation, debris temperature measurements from thermistors located at the surface or within the debris, ablation stakes, and high-resolution digital elevation models used to estimate the surface roughness. Below is a brief description of the various datasets:</p> <p>- 15.03743_rounce2014-hd.csv: debris thickness measurements (m) from Rounce and McKinney (2014) and Rounce et al. (2015).</p> <p>- 15.03743_rounce2014-ts.csv: debris temperature measurements (K) where the depth is reported in cm from Rounce and McKinney (2014).</p> <p>- 15.03743_rounce2015-melt.csv: ablation stake measurements from the period May 18 - Nov 9 2014 detailed in Rounce et al. (2015).</p> <p>- 15.03743_rounce2015-ts.csv: debris temperature measurements (K) where the depth is reported in cm from Rounce et al. (2015).</p> <p>- Site_XX_DEM_1cm.tif: digital elevation model used to estimate surface roughness from Rounce et al. (2015).</p> <p> </p> <p>----- Citing datasets -----</p> <p>If using the debris thickness measurements (15.03743_rounce2014-hd.csv) or temperature data from September 2013 (15.03743_rounce2014-ts.csv), please cite:</p> <p>Rounce, D.R. and McKinney, D.C. (2014). Debris thickness of glaciers in the Everest area (Nepal Himalaya) derived from satellite imagery using a nonlinear energy balance model, <em>Cryosphere</em>, 8:1317-1329, doi:10.5194/tc-8-1317-2014.</p> <p>For all other data please cite:</p> <p>Rounce, D.R., Quincey, D.J., and McKinney, D.C. (2015). Debris-covered glacier energy balance model for Imja-Lhotse Shar Glacier in the Everest region of Nepal, <em>Cryosphere</em>, 9:2295-2310, doi:10.5194/tc-9-2295-2015.</p>
Kongsfjorden 2013-2014 mooring diagram KROP mooring
<div> <p>As part of the KROP - Kongsfjorden Rijpfjorden Observatory Programme, UiT The Arctic University of Norway and The Scottish Association for Marine Science maintain a marine obervatory in the high-Arctic location Kongsfjorden, Svalbard, since 2002. The observatory consists of an array of CTDs, temperature loggers, ADCPs and a sediment trap, in addition to various other instruments or installations that change from year to year. This document contains the mooring diagram for the deployment year 2013-2014. CTD and ADCP data is published at the Arctic Data Centre (<a href="https://adc.met.no/" target="_blank" rel="noopener">https://adc.met.no/</a>). Some previous data is available from NIRD (<a href="https://archive.sigma2.no/">https://archive.sigma2.no/</a>). All metadata is indexed by the SIOS data access portal (<a href="https://sios-svalbard.org/" target="_blank" rel="noopener">https://sios-svalbard.org/</a>).</p> <p>The original diagram has been published together with the dataset in the NIRD data archive. DOI for data and original diagram: <a href="https://doi.org/10.11582/2022.00018" target="_blank" rel="noopener">https://doi.org/10.11582/2022.00018</a></p> <p>The purpose of this re-publication is ease of access to the entire series of mooring diagrams. </p> </div> <p> </p>
Rijpfjorden 2013-2014 mooring diagram KROP mooring
<p>As part of the KROP - Kongsfjorden Rijpfjorden Observatory Programme, UiT The Arctic University of Norway and The Scottish Association for Marine Science maintain a marine observatory in the high-Arctic location Rijpfjorden, Svalbard, since 2006. The observatory consists of an array of CTDs, temperature loggers, ADCPs and a sediment trap, in addition to various other instruments or installations that change from year to year. This document contains the mooring diagram for the deployment year 2013-2014. CTD and ADCP data is published at the Arctic Data Centre (<a href="https://adc.met.no/)">https://adc.met.no/)</a>. Some previous data is available from NIRD (<a href="https://archive.sigma2.no/">https://archive.sigma2.no/</a>). All metadata is indexed by the SIOS data access portal (<a href="https://sios-svalbard.org/">https://sios-svalbard.org/</a>).</p> <p>The original diagram has been published together with the dataset in the NIRD data archive. DOI for data and original diagram: <a href="https://doi.org/10.11582/2021.00023" target="_blank" rel="noopener">https://doi.org/10.11582/2021.00023</a></p> <p>The purpose of this re-publication is ease of access to the entire series of mooring diagrams. </p>
US EPA Twitter posts from 2013-2014 and 2017-2018
Open the record for dataset details and reuse information.
North-Central Namibia: RACD around index cases and controls 2013-2014
Open the record for dataset details and reuse information.
Near Surface Air Temperature Dataset for China with high temporal and spatial resolution generated using random forest and multi-source data (2013-2014)
<div> <p>The dataset presents the daily near surface air temperature of China with 1km spatial resolution, including daily average air temperature, maximum temperature and minimum air temperature. The dataset was generated using machine learning and multiple variables, the accuracy was:T<sub>ave</sub>, R<sup>2</sup> = 0.97, RMSE = 1.61℃ and rRMSE = 13.24%; T<sub>max</sub>, R<sup>2</sup> = 0.94, RMSE = 2.35℃ and rRMSE = 13.02%; T<sub>min</sub>, R<sup>2</sup> = 0.95, RMSE = 2.04℃ and rRMSE = 27.09%).</p> </div>
Partij-belangengroepenrelaties in Vlaanderen: inventaris van de persoonlijke contacten in het verkiezingsjaar 2013-2014 (ruwe data)
<p>Ruwe data van de inventaris van alle gerapporteerde persoonlijke contacten van de deelnemende partijtopleden van alle zes de vertegenwoordigde Vlaamse partijen in het verkiezingsjaar 2013-2014)</p>
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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.