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.
10,016
datasets available to search
ShareScore release 0.9.0
Dataset results
10,016 results for “Observation”
Data for AU Mic Flares Observed with HST/COS
<p>Data products and tables affiliated with "AU Microscopii in the FUV: Observations in Quiescence, During Flares, and Implications for AU Mic b and c" (Feinstein et al. 2022). This directory contains the following data products:</p> <ul> <li><strong>A demonstration Jupyter notebook on how to create the SED for AU Mic (</strong>panchromatic_spectrum_demo.ipynb<strong>) and all affiliated spectra and errors</strong> <ul> <li>X-ray -- XMM-Newton (xmm_newton_spectrum.npy)</li> <li>Differential Emission Measurement flux (au_mic_dem_quiescent_spectrum.fits)</li> <li>FUV -- FUSE (fuse_spectra.npy)</li> <li>FUV -- HST/COS (hst_cos_quiescent_spectrum.txt)</li> <li>NUV -- IUE (iue_spectra.npy)</li> <li>Optical -- HARPS-N (harps_spectra.npy)</li> <li>Optical/NIR -- PHOENIX model (phoenix_grid_3700_4.5_0.0.npy)</li> </ul> </li> <li><strong>A table of 176 measured emission lines from the HST/COS spectra of AU Mic (</strong>au_mic_full_emission_line_list.txt<strong>)</strong></li> <li><strong>The modeled transmission spectra for AU Mic b and c and a demonstration Jupyter notebook for how to read in the files</strong> (tp_profile_demo.ipynb): <ul> <li>Disequilibrium model for AU Mic b (au_mic_b_disequil_profile.dat)</li> <li>Disequilibrium model for AU Mic c (au_mic_c_disequil_profile.dat)</li> <li>Equilibrium model for AU Mic b (au_mic_b_equil_profile.dat)</li> <li>Equilibrium model for AU Mic c (au_mic_c_equil_profile.dat)</li> </ul> </li> </ul>
Model and observations used for Sigmond, M. et al, 'Large contribution of ozone-depleting substances to global and Arctic warming in the late 20th century", Geophysical Research Letters
<p>This dataset contains all the data used for the study "Large contribution of ozone-depleting substances to global and Arctic warming in the late 20th Century" by Sigmond et al, which was submitted to Geophysical Research Letters on July 26, 2022. It contains the following directories:</p> <p>- AR6: csv data files containing timeseries of Effective Radiative Forcing (ERF) as assessed by the IPCC Sixth Assessment Report (AR6).</p> <p>- CanESM5/DATA_siconc_canesm5_past_[expname] contain timeseries of September Sea Ice Extent (SSIE), where expname=historical (all forcing) or hist-noXXX (as historical, except that XXX is fixed to 1955 values)</p> <p>- CanESM5/DATA_tas_canesm5_past_[expname] contains timeseries of surface air temperature (am_: annual mean, arcam_: Arctic and annual mean, gmam_: Global and annual mean). expname as above </p> <p>- CanESM5/IN_TOA_COUPLED_CanESM5 contain timeseries of the global mean top of atmosphere net raditative flux. his=historical (all forcing) run, rms0056=fixed CFC run, rms0058=fixed CFC+stratospheric ozone run, rms0065: fixed CO2 run, and rms0066=fixed aerosol run.</p> <p>- CanESM5_uncoupled/DATA_rtmt_canesm5_YYYY: contains timeseries of RTMT (top of atmosphere radiative imbalance) in the uncoupled (fixed 1955 SST/SI) CanESM5 simulations. YYYY=fall: historical, faer: fixed aerosols, fco2: fixed CO2, fods: fixed CFC runs</p> <p>- OBSERVATIONS: contains timeseries of observational September Sea Ice Extent and surface air temperature used in the study</p> <p>- data_GSAT+ASAT+ERF+efficacies_2001-2005min1955.txt: contains the most import post-processed data </p> <p>Python code used to create these files from the raw model output are available at https://gitlab.com/michael.sigmond/cfc/</p>
Data from: Non-Adiabatic Acceleration of Injected Electrons in the Inner Magnetosphere: Joint Observations by the Van Allen Probe and the BeiDa Imaging Electron Spectrometer
<p>The dataset is associated with the study entitled "Non-adiabatic acceleration of injected electrons in the inner magnetosphere: Joint observations by the Van Allen Probe and the BeiDa Imaging Electron Spectrometer"</p> <p>The file includes directional electron flux data obtained by the BeiDa Imaging Electron Spectrometer and follows NASA's Common Data Format (CDF).</p>
Submesoscale motions driven by down-front wind around an anticyclonic eddy observed by gliders
<p>This datasets was used in the study named 'Submesoscale motions driven by down-front wind around an anticyclonic eddy observed by gliders'. It contains glider data. Please let me know if you need any more information.</p>
Direct observational evidence of an oceanic dual kinetic energy cascade and its seasonality
<p>Codes for the analysis and figure generation for drifter data</p>
Data for NHESS manuscript by Biass et al. (2022): Insights into the vulnerability of vegetation to tephra fallouts from interpretable machine learning and big Earth observation data
<p>This repository contains the data produced in the context of the following paper:</p> <blockquote> <p>Biass S, Jenkins SF, Aberhard WH, Delmelle P, Wilson T (2022): Insights into the vulnerability of vegetation to tephra fallouts from interpretable machine learning and big Earth observation data, Accepted in NHESS</p> </blockquote> <p>Naming convention is: `run_date`_`landcover`_`impact_metrics`_`VI`_`anomaly`_test.pkl, where:</p> <ul> <li>Landcover is either crops, shrubs, herbaceous vegetation (grass), forests (trees) or all together</li> <li>Impact metrics is either minV (impact magnitude) or minT (impact duration)</li> <li>VI is the vegetation index (here, EVI)</li> <li>Anomaly is the impact indicator (here, cumulative difference index)</li> </ul> <p>Refer to the associated paper for more information on the methodology.</p> <p>Files are saved as .pkl and were generated by the <a href="https://explainerdashboard.readthedocs.io/en/latest/">explainerdashboard</a> library. They are the result of <a href="https://xgboost.readthedocs.io/en/stable/">XGBoost</a> runs that were optimised with <a href="https://optuna.org">Optuna</a> and analysed with the <a href="https://shap.readthedocs.io/en/latest/">SHAP</a> library. They contain:</p> <ol> <li>The explanatory variables and observed and computed target variables for all features</li> <li>The SHAP values</li> </ol> <p>To load the files, use <a href="https://explainerdashboard.readthedocs.io/en/latest/cli.html?highlight=load#explainerdashboard.explainers.BaseExplainer.from_file">this method</a>.</p> <p> </p>
The MicroRESUS study: An observational study to examine the effects of circulatory shock and resuscitation on microcirculatory function and mitochondrial respiration after cardiovascular surgery.
<p>Post-cardiotomy shock (PCS) occurs in up to 5% of cardiovascular surgeries and has an in-hospital mortality rate as high as 75%. Physiologic derangements are often multifactorial, including ischemic-reperfusion injury leading to low cardiac output, vasoplegia, hemorrhage, or pericardial tamponade. Resuscitation strategies often target the normalization of systemic hemodynamics, however, practices to achieve standard macrocirculatory goals often fail to reverse microcirculation abnormalities or address cytopathic hypoxia. Perioperative shock may be the result of an imbalance between oxygen delivery and oxygen demand or could be the result of impaired oxygen utilization. This study will examine differences in microcirculatory function and mitochondrial respiration in patients with circulatory shock after cardiovascular surgery.</p>
The full-turn observational simulation: measured dual effects of the path difference and beam shifts
<p>This is part of work for the preprint entitled "1887 Michelson-Morley experiment: a new analysis with computer assistance".</p> <p>Each grouped Excel form and CAD drawing under the same filename presents the detailed process to simulate the full-turn observation of the apparatus, from which the dual effects of path difference between the two arms and lateral shifts of the two beams were measured for calculating the positioning of the fringes.</p>
Multi-instrument observations of the ionospheric response to the 26 December 2019 solar eclipse over Indian and Southeast Asian longitudes
<p>Here, the impact of the 26 December 2019 solar eclipse on the equatorial and low latitude ionosphere has been investigated using ground and space-based observations over Indian and Southeast Asian longitudes. The high-resolution Ionosonde observations at Tirunelveli, GPS TEC observations from a chain of GPS receivers along and across the eclipse path, TIMED-SABER, and Ionospheric Connection Explorer (ICON) satellites were utilized to investigate the eclipse-induced variations in electron density and thermospheric cooling. We noticed a tremendous increase and decrease in the base height of the F-layer, resembling the nighttime Pre-Reversal Enhancement (PRE). Near the eclipse maximum, a strong blanketing sporadic E layer was observed at Tirunelveli with a top frequency of ~18 MHz for 1 hour and 26 minutes. Satellite traces (STs) and ‘U’ shaped ionograms were noticed for the first time over Tirunelveli during eclipse maximum and end phases. The ‘STs’ and ‘U’ shaped traces indicate the presence of short-period gravity waves or TID type of wave perturbations over the Indian region. A maximum of ~5-7 TECU (30-40%) decrease in TEC is observed on the eclipse day for iisc, hyde, and tiru stations. Periodogram analyses of TEC data showed the presence of wavelike structures with periodicities of 18-24 minutes for different stations. Simultaneous observations from the ICON satellite showed an increase and decrease in hmF2 and NmF2 which matches well with the ionosonde observations from Tirunelveli. The temperature profiles from TIMED-SABER and ICON satellites showed a reduction and enhancement in the lower and upper E regions respectively.</p>
Simultaneous space-based observations of TGFs and lightning optical emission: Characteristics of lightning
<p>Raw data for figures for “Simultaneous space-based observations of TGFs and</p> <p>lightning optical emission: Characteristics of lightning”, Alnussirat et al., JGR-Atmospheres (submitted, 2022)</p>
Combined_ST_SM_Changes_Impacts soil temperature observations
<p>Observations of soil temperature used to evaluate ERA5-Land soil temperature</p>
Combined_ST_SM_Changes_Impacts Soil moisture observations
<p>In situ observations of soil moisture used in the paper.</p>
Observation data of a PV site and a Gobi site
<p>This is a supplementary file for the submitted paper "The characteristics and parameterizations of the surface albedo of utility-scale photovoltaic plant in the Gobi Desert".</p>
Observing flow of He II with unsupervised machine learning
<p>Data repository for observing flow in He II with unsupervised machine learning.</p>
Comprehensive assessment of postoperative mobility during the first days after mini-invasive lung surgery: A prospective observational study
<p><span>Study Objective</span><span>: </span><span>Postoperative physical therapy and early mobilization are major elements of </span><span>enhanced recovery after surgery. In contrast with supervised physical therapy sessions that can be monitored, self-mobilization is not easily quantifiable and has so far been estimated mainly through patient auto-reports. This study aimed to perform a comprehensive and objective evaluation of postoperative mobility.</span></p> <p><span>Design</span><span>: </span><span>Prospective observational study.</span></p> <p><span>Setting</span><span>: </span><span>Postoperative setting.</span></p> <p><span>Patients</span><span>: </span><span>Patients undergoing mini-invasive lung surgery.</span></p> <p><span>Interventions</span><span>: </span><span>Measurement of postoperative mobility during the five first postoperative days using an accelerometer (ActiGraph GT3X).</span></p> <p><span>Measurements</span><span>: </span><span>The primary outcome was the number of daily steps. Secondary outcomes included physical activity duration and intensity, sedentary time, number of breaks in sedentary time, sedentary patterns, daily evaluation by physiotherapists, postoperative complications, and acceptability of wearing the accelerometer. </span></p> <p><span>Main Results: </span><span>Sixty patients were included in the study, of whom 56 provided at least one day of valid accelerometry data. There was no significant change during the first four PODs concerning the number of daily steps nor the mean cadence. One-minute cadence peak, total activity counts, and duration of light-intensity physical activity increased over time (P = 0.032, P = 0.001 and P = 0.001, respectively). </span><span>Sedentary patterns changed favorably over time, with a decrease in prolonged sedentary bouts (≥ 60 consecutive min), and an increase in shorter bouts (< 10 min) (</span><span>P </span><span>< 0.001). Similar results were observed when analysis was adjusted for the day of the week when the surgery took place except for daily sedentary time (P = 0.055). The median acceptability of wearing the accelerometer was excellent (median 10 [9-10] on a 10-point Likert scale). Three patients had major complications. </span></p> <p><span>Conclusions: </span><span>Our findings suggest that daily steps may not be the most relevant indicator of early mobility following thoracic surgery and that accelerometry is suitable to follow patient's early postoperative activity.</span></p>
Dataset of Dipteran species observed along an elevational gradient from Ecuador.
<p>This dataset contains count data for Dipteran specimens collected at five elevations along an altitudinal gradient in the Eastern slope of tropical Andes, in Ecuador. Samples were collected to determine changes in forensically relevant Diptera community assembly as elevation changes.</p> <p>DipteraAltitudeEcuador_Data.csv is a file that contains the raw count data for species separated by both elevations of the identified specimens.</p> <p>DipteraAltitudeEcuador_Methods.docx is a summarized version of the sampling method relevant to interpreting the data.</p> <p>DipteraAltitudeEcuador_Descriptive.txt is a file describing the column headers in "DipteraAltitudeEcuador_Data.csv".</p>
Data used in "Observation of secondary ice production in clouds at low temperatures"
<p>To support open research, the data used in Korolev et al 2022 "Observation of secondary ice production in clouds at low temperatures" submitted to Atmospheric Chemistry and Physics has been provided here. <br> This in-situ data was collected by Environment and Climate Change Canada (ECCC) in collaboration with the National Research Council (NRC) on the NRC Convair-580 research aircraft on March 25 2017 between 11:00 and 12:00 UTC.<br> Radar data included was collected and processed by N. Cuong and M. Wolde of NRC Canada. <br> </p>
Water vapor vertical distribution on Mars during perihelion season of MY 34 and MY 35 with ExoMars-TGO/NOMAD observations [Dataset]
<p>1. Description of methods used for collection/generation of data:<br> NOMAD SO channel acquires transmittance spectra at different diffraction orders sounding the limb of the Martian atmosphere in solar occultation. It uses an echelle grating with a density of ∼4 lines/mm in a litrow configuration. An Acousto-Optical Tunable Filter (AOTF) is used to select different spectral windows (with a width that varies from 20 to 35 cm−1). Each window corresponds to the desired diffraction order to be used during the atmospheric scan. The spectral resolution of the SO channel is λ/∆λ=20,000.<br> After spectral calibration, the inversion problem is solved by fitting the data with a forward model and the vertical profiles are obtained.</p> <p>2. Methods for processing the data:<br> For the H2O inversion we use the Retrieval Control Program (RCP) developed at Institut für Meteoriologie und Klimaforschung (IMK), which incorporates the Karlsruhe Optimized and Precise Radiative transfer Algorithm (KOPRA) forward model. After providing an a priori, a first-guess and the measured spectra, RCP solves the inversion problem iteratively until the convergence of the solution. The IMK-IAA level-2 processor relies on multi-parameter non-linear least squares fitting of measured and modeled spectra (von Clarmann et al., 2003). Further information about RCP and the inversion problem can be found in (Jurado Navarro et al., 2016).<br> Retrievals of NOMAD diffraction orders 134 (3011-3035 cm−1) and 168 (3775-3805 cm−1) have been obtained and merged when collocated.</p>
IAA/CSIC Temperature and CO2 density profiles in Mars Year 34 retrieved from the 1st year of NOMAD/TGO solar occultation observations [dataset]
<p>Dataset associated to manuscript 2022JE007278, "Martian atmospheric temperature and density profiles during the 1st year of NOMAD/TGO solar occultation measurements", submitted on Feb 28th, 2022, to Journal of Geophysical Research - Planets (AGU) for the Special Issue "ExoMars Trace Gas Orbiter: One Martian Year of Science".</p> <p>Format and Number of datafiles: 1 README.txt and 1 tar file containing 325 ASCII files, one for each retrieved NOMAD scan. Each of these files contains one vertical profile of 7 parameters: altitude (km), Temperature in the last iteration (K), atmospheric pressure (mb), Temperature of First Guess (K), pressure of First Guess (mb), Temperature retrieval error (K) and diagonal element fo the Averaging Kernel matrix at that tangent altitude (normalized to 0-1). Also, the header of each file contains extra info, like the NOMAD "internal" data filename, and the ranges in latitude, longitude, Local time, Solar Longitude, tangent heights observed, and Line-of-Sight shift needed to obtain a good fit, together with the number of altitudes in the retrieval vector (usually around 100 km). See README file for more details.<br> </p>
Direct Observation of the Transitional Stage of Mixing-State- Related Absorption Enhancement for Atmospheric Black Carbon
<p>Data for article <em>Direct Observation of the Transitional Stage of Mixing-State-Related Absorption Enhancement for Atmospheric Black Carbon.</em></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.