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.
151
datasets available to search
ShareScore release 0.7.1
Dataset results
151 results for “optical properties”
Quaver regressed light curves to accompany ApJ publication Optical Variability Properties of Southern TESS Blazars
<p>A collection of all Figures included in Appendix A of Optical Variability Properties of Southern TESS Blazars (Dingler & Smith 2024).</p>
Effect of substrate temperature on the optical and electrical properties of nitrogen-doped NiO thin films
<p>This file contains 2 figures. </p> <p>Fig.S1 Mott–Schottky plots of ITO coated glass.</p> <p>Fig.S2 Room temperature PL spectra of N-doped NiO thin films deposited at room temperature substrate temperature.</p>
Dataset for the article : Non-invasive estimation of in vivo optical properties and hemodynamic parameters of domestic animals: a preliminary study on horses, dogs, and sheep
<div> <div> <div> <div> </div> </div> </div> </div> <div> <div> <div> <div> <div> <div> <p>This dataset includes all the necessary data to understand and replicate the figures and tables presented in the article titled "Non-invasive Estimation of In Vivo Optical Properties and Hemodynamic Parameters of Domestic Animals: A Preliminary Study on Horses, Dogs, and Sheep." Specifically, it contains the raw measurement curves, along with the optical and hemodynamic parameters derived from the analysis of these raw data.</p> </div> </div> </div> </div> </div> </div>
Optical and chemical properties of brown carbon aerosols at Fukue Island in 2019-2020
Open the record for dataset details and reuse information.
Electronic Structure and Optical Properties of Tin Iodide Solution Complexes
<p>(TD)DFT+PCM study on the structural, electronic, and optical properties of 14 tin-iodide-solution complexes with the chemical formula SnI<sub>2</sub>M<sub>4</sub>, with M one of 14 common solvent molecules.</p>
Datasets for "Irradiance and cloud optical properties from solar photovoltaic systems" (final version)
<p>This dataset contains all the relevant data for the algorithms described in the paper "<a href="https://amt.copernicus.org/articles/16/4975/2023/">Irradiance and cloud optical properties from solar photovoltaic systems</a>", which were developed within the framework of the <a href="https://www.h-brs.de/de/satelliten-und-meteorologie-unterstuetzte-vorhersage-der-energieerzeugung-von-pv-anlagen-auf">MetPVNet</a> project.</p> <p><strong>Input data:</strong></p> <ol> <li><a href="http://www.cosmo-model.org/">COSMO</a> weather model data (DWD) as NetCDF files (cosmo_d2_2018(9).tar.gz) <ol> <li>COSMO atmospheres for <a href="http://www.libradtran.org/">libRadtran</a> (cosmo_atmosphere_libradtran_input.tar.gz)</li> <li>COSMO surface data for calibration (cosmo_pvcal_output.tar.gz)</li> </ol> </li> <li><a href="https://aeronet.gsfc.nasa.gov/">Aeronet</a> data as text files (MetPVNet_Aeronet_Input_Data.zip)</li> <li>Measured data from the <a href="https://www.h-brs.de/de/satelliten-und-meteorologie-unterstuetzte-vorhersage-der-energieerzeugung-von-pv-anlagen-auf">MetPVNet</a> measurement campaigns as text files (MetPVNet_Messkampagne_2018(9).tar.gz) <ol> <li>PV power data</li> <li>Horizontal and tilted irradiance from pyranometers</li> <li>Longwave irradiance from pyrgeometer</li> </ol> </li> <li>MYSTIC-based lookup table for translated tilted to horizontal irradiance (gti2ghi_lut_v1.nc)</li> </ol> <p><strong>Output data:</strong></p> <ol> <li>Global tilted irradiance (GTI) inferred from PV power plants (with calibration parameters in comments) <ol> <li>Linear temperature model: MetPVNet_gti_cf_inversion_results_linear.tar.gz</li> <li>Faiman non-linear temperature model: MetPVNet_gti_cf_inversion_results_faiman.tar.gz</li> </ol> </li> <li>Global horizontal irradiance (GHI) inferred from PV power plants <ol> <li>Linear temperature model: MetPVNet_ghi_inversion_results_linear.tar.gz</li> <li>Faiman non-linear temperature model: MetPVNet_ghi_inversion_results_faiman.tar.gz</li> </ol> </li> <li>Combined GHI averaged to 60 minutes and compared with COSMO data <ol> <li>Linear temperature model: MetPVNet_ghi_inversion_combo_60min_results_linear.tar.gz</li> <li>Faiman non-linear temperature model: MetPVNet_ghi_inversion_combo_60min_results_faiman.tar.gz</li> </ol> </li> <li>Cloud optical depth inferred from PV power plants <ol> <li>Linear temperature model: MetPVNet_cod_cf_inversion_results_linear.tar.gz</li> <li>Faiman non-linear temperature model: MetPVNet_cod_cf_inversion_results_faiman.tar.gz</li> </ol> </li> <li>Combined COD averaged to 60 minutes and compared with COSMO and APOLLO_NG data <ol> <li>Linear temperature model: MetPVNet_cod_inversion_combo_60min_results_linear.tar.gz</li> <li>Faiman non-linear temperature model: MetPVNet_cod_inversion_combo_60min_results_faiman.tar.gz</li> </ol> </li> </ol> <p><strong>Validation data:</strong></p> <ol> <li>COSMO cloud optical depth (cosmo_cod_output.tar.gz)</li> <li>APOLLO_NG cloud optical depth (MetPVNet_apng_extract_all_stations_2018(9).tar.gz)</li> <li>COSMO irradiance data for validation (cosmo_irradiance_output.tar.gz)</li> <li><a href="https://www.soda-pro.com/web-services/radiation/cams-radiation-service">CAMS</a> irradiance data for validation (CAMS_irradiation_detailed_MetPVNet_MK_2018(9).zip)</li> </ol> <p><strong>How to import results:</strong></p> <p>The results files are stored as text files ".dat", using Python multi-index columns. In order to import the data into a Pandas dataframe, use the following lines of code (replace [filename] with the relevant file name):</p> <p>import pandas as pd<br>data = pd.read_csv("[filename].dat",comment='#',header=[0,1],delimiter=';',index_col=0,parse_dates=True)</p> <p>This gives a multi-index Dataframe with the index column the timestamp, the first column label corresponds to the measured variable and the second column to the relevant sensor</p> <p><strong>Note:</strong></p> <p>The output data has been updated to match the latest version of the paper, whereas the input and validation data remains the same as in Version 1.0.0</p>
Measurement and modeling of the multi-wavelength optical properties of uncoated flame-generated soot: Data from the BC2, BC3, BC3+ and BC4 studies
Open the record for dataset details and reuse information.
Data from: Comprehensive first principles study on CO and NO gas adsorption effects on the structural, electronic, and optical properties of ASiSn nanoribbons
Open the record for dataset details and reuse information.
Data from: High-throughput screening of inorganic compounds for dielectric and optical properties to enable the discovery of novel materials
Dielectrics are an important class of materials that are ubiquitous in modern electronic applications. Even though their properties are important for the performance of devices, the number of compounds with known dielectric constant is on the order of a few hundred. Here, we use Density Functional Perturbation Theory as a way to screen for the dielectric constant and refractive index of materials in a fast and computationally efficient way. Our results form the largest database to date, containing the full dielectric tensor for 1,056 compounds. Details regarding the computational methodology and technical validation are presented along with the format of our publicly available data. In addition, we integrate our dataset with the Materials Project allowing users easy access to material properties. Finally, we explain how our dataset and calculation methodology can be used in the search for novel dielectric compounds.
Fractal geometry features of aerosol particle and its contribution to atmospheric optical property: development of Fractal Aerosol Cluster Model and its validation of atmospheric visibility during a heavy haze event
<p>-------------------------<br>Content of the dataset<br>-------------------------<br>****** the experiment case (EXP) ; the control case (CTR) ******</p> <p>1. Meteorological elements.tar contains observational and simulated data for T2, WS, RH, and PM2.5 time series, which can be used to plot Figure 4 and build Table 2</p> <p>2. Planar distribution.tar contains the horizontal spatial distribution data of aerosol extinction coefficients simulated by CTR and EXP for the four typical moments selected in this paper, which can be used to plot Figures 5, 6, and 7</p> <p>3. PM.rar contains the vertical profile data of simulated Particulate Matter concentrations by CTR and EXP during the study period in the paper, which can be utilized for drawing Fig. 11.</p> <p>4. Timeseries.tar contains observational and simulated data for time series of atmospheric visibility and surface shortwave radiation, which can be used to plot Figures 5, 6, 7, 8, S1, and build Table 3</p> <p>5. wrfbiochemi.rar contains the biogenic emissions data for simulation both for CTR and EXP.</p> <p>6. wrffirechemi.rar contains the biomass burning emissions data for simulation both for CTR and EXP.</p> <p>7. wrfchemi.rar contains the Anthropogenic emissions data for simulation both for CTR and EXP.</p> <p>8. The file module_optical_averaging.F contains the main code of the improved visibility model, the Fractal Aerosol Cluster Model</p> <p>(FACM), which is coupled to WRF-Chem and used by EXP. It is located in the chem/ directory and called by optical_driver.F.</p> <pre> </pre> <p> </p> <p>-------------------------</p> <p>Contact information</p> <p>-------------------------</p> <p> </p> <p>Zhenxin Liu</p> <p>liuzhenxin@nuist.edu.cn</p> <p> </p> <p> </p>
Black Gold Layers Preparation via Thermal Evaporation, Material and Optical Properties, Application Potential for Gas Sensors
Open the record for dataset details and reuse information.
Optical properties of small scatterers with high optical contrast
<p>Optical properties of small, spherical scatterers (r=100µm) with high optical contrast, representing melting ice hydrometeors.</p> <p>The dataset contains raw output as obtained with the discrete dipole approximation code ADDA (version 1.3b4) [1] and the T-matrix code MSTM (version 3.0) [2]. For an interpretation of the data see the corresponding documentations. Version 2.0 added additional calculations with hypothetical refractive indices.</p> <p>The manuscript describing this research was submitted to Optics Letters.</p> <p> </p> <p>ADDA (version 1.3b4): <a href="https://github.com/adda-team/adda/releases/tag/v1.3b4">https://github.com/adda-team/adda/releases/tag/v1.3b4</a></p> <p>MSTM )version 3.0): <a href="https://www.eng.auburn.edu/~dmckwski/scatcodes/">https://www.eng.auburn.edu/~dmckwski/scatcodes/</a></p>
A hyperspectral and multi-angular synthetic dataset of optical properties for waters with varying trophic levels and optical complexity
<p>This synthetic dataset encompasses inherent and apparent optical properties (IOPs-AOPs) alongside associated bio-geochemical constituents. The bio-optical modeling framework benefited from insights and data accumulated over the past three decades, resulting on a comprehensive dataset of in situ IOPs, including diverse water typologies, and enabling the imposition of rigorous quality standards.</p> <p>Employing the Hydrolight scalar radiative transfer equation solver, we generated above-surface and submarine light fields across the specified spectral range at a “true” hyperspectral resolution (1 nm), covering the ultraviolet down to 350 nm, therefore facilitating algorithm development and assessment for present and forthcoming hyperspectral satellite missions. A condensed version of the dataset tailored to twelve Sentinel-3 OLCI bands (400 nm to 753 nm) was crafted. Derived AOPs encompass an array of above- and below-surface reflectances, diffuse attenuation coefficients, and average cosines,</p> <p>A unique feature of our dataset lies in the calculation of AOPs across the complete range of solar and viewing zenith and azimuthal angles as per the Hydrolight default quadrants. This comprehensive directional coverage caters to studies investigating signal directionality, previously lacking sufficient reference data. The dataset is thus the result of 6500000 Hydrolight simulations, distributed in 5000 files, each file encapsulating a specific IOP scenario, ensuring sufficient data volume for each water type represented. In addition, angularly resolved AOPs are incorporated.</p>
Figure 8 in Morphological, optical and thermal properties of α- and γ-aluminum nanoparticles: Assessment of their biological activities against storage mites and mycotoxin producing fungi
Figure 8. Mortality (means ± SE) of C. mycophagus females, nymphs and larvae, concerning α- and γ-Al2O3 NPs at tested concentrations and exposure time.
HULIS and WSOC optical property data in cloud water collected at Taishan in 2021
Open the record for dataset details and reuse information.
Corneal Biomechanics, Optical Properties and Anterior Segment Structural Features in Patients With Pseudoexfoliation
ClinicalTrials.gov study NCT06731530. IPD Sharing: YES. Countries: 1. Publications: 0.
Data from: Holographic sol-gel monoliths: optical properties and application for humidity sensing
Open the record for dataset details and reuse information.
Data from: High-throughput screening of inorganic compounds for dielectric and optical properties to enable the discovery of novel materials
Open the record for dataset details and reuse information.
BOREAS TE-10 Leaf Optical Properties for SSA Species
The BOREAS TE-10 team collected several data sets in support of its efforts to characterize and interpret information on the reflectance, transmittance, gas exchange, oxygen evolution, and biochemical properties of boreal vegetation. This data set describes the spectral optical properties (reflectance and transmittance) of boreal forest conifers and broadleaf tree leaves as measured with a Spectron Engineering SE590 spectroradiometer at the SSA OBS, OJP, YJP, OA, OA-AUX, YA-AUX, and YA sites. The data were collected during the growing seasons of 1994 and 1996.
SNF Leaf Optical Properties: Cary-14
Knowledge of the optical properties of the components of the forest canopy is important to the understanding of how plants interact with their environment and how this information may be used to determine vegetation characteristics using remote sensing. During the summers of 1983 and 1984, samples of the major components of the boreal forest canopy (needles, leaves, branches, moss, litter) were collected in the Superior National Forest (SNF) of Minnesota and sent to the Johnson Space Center (JSC). At JSC, the spectral reflectance and transmittance characteristics of the samples were determined for wavelengths between .35 and 2.1 micrometers using the Cary-14 radiometer. This report presents plots of these data as well as averages to the Thematic Mapper Simulator (TMS) bands. There were two main thrusts to the SNF optical properties study. The first was to collect the optical properties of many of the components of the boreal forest canopy. The second goal of the study was to investigate the variability of optical properties within a species. The results of these studies allow a comparison of the optical properties of a variety of different species and a measure of the variability within species. These data provide basic information necessary to model canopy reflectance patterns.
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.