RSS 1.0Datasets
Recent Submissions
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Young Red Sea Sediments: Formation Processes and Properties(KAUST Research Repository, 2023-01-22) [Dataset]This Repository compiles the experimental data obtained from the study "Young Red Sea Sediments: Formation Processes and Properties"
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Local beamforming and back-projection of induced earthquakes in Helsinki, southern Finland(Zenodo, 2023-01-16) [Dataset]This provides the synthetic simulation dataset and script of the GRL submission: Local beamforming and back-projection of induced earthquakes in Helsinki, southern Finland.
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Gaussian Approximation Potential for C-doped Boron Nitride(Zenodo, 2023-01-03) [Dataset]This is an GAP potential for amorphous boron nitride samples. It is trained based on datasets generated with ab-initio molecular dynamics and DFT. It can be used with pair_style quip command.
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Supplemental Material for Zuccolo et al., 2022(GSA Journals, 2023) [Dataset]Falcon2_CDS_omicsbox_gene.gff: description of the locations and structures of the predicted genes FALCON_TE_LIBRARY_V3_no_repbase.fa: multifasta file containing the TE library used in this work (excluding entries from Repbase)
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Street Sign Dataset(KAUST Research Repository, 2022-12-20) [Dataset]This paper presents a dataset of street signs collected from Creative Commons licensed sources. The dataset includes a total of 5630 images of street signs, which have been processed to remove the background and correct perspective distortion. The images in the dataset represent a diverse range of categories, including traffic control, shop, plaque, and house numbers. The dataset is intended for use in research on computer graphics, vision, and machine learning, with the images separated into folders based on their approximate real-world sizes. See the readme.txt file for additional information.
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Simulation of a dust-and-rain event across the Red Sea using WRF-Chem(KAUST Research Repository, 2022-12-14) [Dataset]Namelist file of WRF-Chem model configuration for the article titled "Simulation of a dust-and-rain event across the Red Sea using WRF-Chem" submitted to JGR.
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Electrically switchable anisotropic polariton propagation in a ferroelectric van der Waal semiconductor(Zenodo, 2022-12-04) [Dataset]Figure files including data for main text figures.
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Ultraliser: a framework for creating multiscale, high-fidelity and geometrically realistic 3D models for in silico neuroscience(Zenodo, 2022-10-01) [Dataset]Supplementary Data Supplementary Data 1 contains the input (non-watertight) surface meshes of the block (shown in Figure 2a) reconstructed within the context of the EPFL-KAUST collaboration, and the corresponding output (watertight) meshes generated by Ultraliser. Supplementary Data 2 contains a set of 20 non-watertight meshes that were randomly selected from the block shown in Supplementary Figure S54 and another set of the their watertight counterparts. Supplementary Data 3 contains a set of 25 neuronal morphologies with different morphological types and their corresponding watertight meshes. Supplementary Data 4 contains a set of 25 synthetic astroglial morphologies 15 and their corresponding watertight meshes. Supplementary Data 5 contains the vascular morphology (shown in Supplementary Fig. S83) and a corresponding multi-partitioned watertight mesh. Supplementary Data 6 contains the datasets used for the comparative analysis shown in Supplementary Section 13. Neuronal, astrocytic and vascular morphologies are stored in SWC, H5 and VMV file formats respectively. The file structures of the SWC and VMV formats are publicly available online. The H5 files of the complete astrocyte cells can be made available from corresponding authors upon request. All the surface meshes are stored in Wavefront OBJ files. Additional STL meshes are generated to be used for TetGen to create corresponding tetrahedral meshes. All the input and generated data files are publicly available on Zenodo (10.5281/zenodo.7105941). Data Sources Cellular and subcellular NGV meshes segmented from the volume shown in Figure 2 are provided by the collaborating co-authors affiliated with KAUST. Neuronal meshes shown in Figure 3, Supplementary Figures S55 - S75 and Supplementary Figures S85 are publicly available from the MICrONS program. Neuronal morphologies shown in Figure 4, Supplementary Figures S80 - S81 and Supplementary Figure S86 are publicly available from NeuroMorpho.Org. Astrocytic morphologies (Figure 5 and Supplementary Figure S82) are provided by Eleftherios Zisis. Vascular morphologies (rat’s cerebral microvasculature) shown in Figure 6 and Supplementary Figures S83 - S84 are courtesy of Bruno Weber, University of Zürich (UZH). The vascular morphology of the arterial arborizations shown in Supplementary Figure S88 is available from the Brain Vasculature (BraVa) database (cng.gmu.edu/brava).
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Data for "The Second Competition on Spatial Statistics for Large Datasets"(KAUST Research Repository, 2022-08-11) [Dataset]The enclosed datasets have been generated by the internal spatial data generator tool included in the ExaGeoStat software (https://github.com/ecrc/exageostat). It was used for the 2022 KAUST Competition on Spatial Statistics for Large Datasets (https://cemse.kaust.edu.sa/stsds/2022-kaust-competition-spatial-statistics-large-datasets). The competition had six parts (Sub-competition 1a, Sub-competition 1b, Sub-competition 2a, Sub-competition 2b, Sub-competition 3a, and Sub-competition 3b). The main purpose of the competition was to reassess existing approximation methods on large spatial datasets in a uniform way that guarantees a fair comparison. More information about the datasets can be found in the manuscript "The Second Competition on Spatial Statistics For Large Datasets."
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Network-constrained stochastic unit commitment data sets: ACTIVSg200 and ACTIVSg2000(KAUST Research Repository, 2022-07-27) [Dataset]Input data files used in the computational experiments of the manuscript "An effective hybrid decomposition approach to solve the network-constrained stochastic unit commitment problem in large-scale power systems" by Ricardo M. Lima, Gonzalo E. Constante-Flores, Antonio J. Conejo, Omar M. Knio The data sets were adapted from the Texas A&M University Electric Grid Datasets. https://electricgrids.engr.tamu.edu. Two cases are considered: 1) ACTIVSg200: the Illinois 200-Bus System. 2) ACTIVSg2000: the 2000-bus synthetic grid on the footprint of Texas The input files are formatted for the GAMS (www.gams.com) model developed. There are csv and GAMS files with the input data: 1) 24 hours profile demand scenarios by node 2) 24 hours profile wind scenarios by wind farm 3) 24 hours profile solar scenarios by solar farm 4) scenarios probabilities 5) generators technical characteristics 6) network characteristics 7) GAMS sets 8) GAMS dynamic sets 9) other input data The solar power output scenarios were generated for each farm location based on their coordinates available in the case study in and on data obtained from the National Solar Radiation Database (https://developer.nrel.gov/docs/solar/nsrdb/). The wind power output scenarios were generated for each farm location based on their coordinates available in the case study and on data obtained from the Wind Integration National Dataset Toolkit (https://developer.nrel.gov/docs/wind/wind-toolkit/). These data was processed with the System Advisor Model scripts (https://sam.nrel.gov).
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Dataset_ metabolic scope performance and tolerance of juvenile European sea bass Dicentrarchus labrax upon acclimation to high temperatures(Zenodo, 2022-07-25) [Dataset]This dataset contains the data associated with the article 'Metabolic scope, performance and tolerance of juvenile European sea bass Dicentrarchus labrax upon acclimation to high temperatures' by Stavrakidis-Zachou et al. accepted for publication on Plos one in July 2022.
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Tables S1 - S3 of "LEAfing through literature: Late embryogenesis abundant proteins coming of age – achievements and perspectives "(Zenodo, 2022-07-06) [Dataset]The deposited excel file contains Tables S1-S3 of the review article "LEAfing through literature: Late embryogenesis abundant proteins coming of age – achievements and perspectives" submitted as an invited Darwin review to the Journal of Experimental Botany in April 2022. It contains comprehensive compilations of LEA protein in vivo studies.
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rspatialdata/rspatialdata.github.io: First release(Zenodo, 2022-06-29) [Dataset]No description provided.
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The relocated catalog of the 2021 Flores Sea earthquake(Zenodo, 2022-05-30) [Dataset]The relocated catalog of the 2021 Flores Sea earthquakes Please refer to: Supendi, P., Rawlinson, N., Prayitno, B.S., Widiyantoro, S., Simanjuntak, A., Palgunadi, K.H., Kurniawan, A., Marliyani, G.I., Nugraha, A.D., Daryono, D., Anugrah, S.D., Fatchurochman, I., Gunawan, M.T., Sadly, M., Adi, S.P., Karnawati, D., Arimuko, A. (2022). The Kalaotoa Fault: A newly identified fault that generated the Mw 7.3 Flores Sea Earthquake. The Seismic Record (2022) 2 (3): 176–185.
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Waveform Data for Long-Wavelength Propagation in Fractured Rock Masses (3D Stress Field)(KAUST Research Repository, 2022-05-29) [Dataset]The dataset includes all the waveforms used for isotropic, anisotropic, and creep analyses. The ReadMe.txt file details the contents and organization of each file.
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Waveform Data for Long-Wavelength Propagation in Fractured Rock Masses (3D Stress Field)(KAUST Research Repository, 2022-05-29) [Dataset]The dataset includes all the waveforms used for isotropic, anisotropic, and creep analyses.
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Datasets used on the analysis of Mediterranean Mass mortality events during the 2015-2019 period(Zenodo, 2022-05-28) [Dataset]This upload contains three datasets in CSV files and a PDF file with the specific description of the CSV files. These data was used for the analysis of the mass mortality events reported during the period 2015-2019 across the Mediterranean. The datasets are 1) a CSV file with the data used for the description of the spatial-temporal, depth and biological patterns of mortality observed in the Mediterranean Sea in the 2015-2019 period; 2) a CSV file with the data used to conduct the analyses on the relationship between marine heatwaves (MHW) days found on the surface (averaged per monitored area and year) and the corresponding mass mortality incidence of benthic organisms; 3) a CSV file with the data used to conduct the analyses on the relationship between in-situ MHW days (averaged per monitored area, depth and year) and the corresponding mass mortality incidence. Data were obtained through benthic community field surveys conducted by 33 research teams from 11 Mediterranean countries. Surveys covered thousands of kms of coastline, spanning 13º of latitude (32 °S to 45 °N) and 40º of longitude (-5°W to 35°E) in the Mediterranean Sea. The dataset provides the most updated inventory of mass mortality events records for benthic species between 2015-2019 in the region. The surveys were conducted in 142 monitoring areas. Monitoring areas were considered as geographic areas (10-25 km coastline, e.g., a marine protected area and the nearby coast) sharing common environmental features. In situ temperature conditions datasets base consists of high frequency (hourly) time series obtained using HOBO data loggers (accuracy ± 0.21°C) set-up at standard depths along rocky walls by divers, generally every 5 m from the surface to 40 m depth.This dataset as in the case of the mortality was assembled under the T-MEDNet initiative (www.t-mednet.org). Satellite derived sea surface temperature (SST) across the Mediterranean Sea was obtained from CMEMS (https://resources.marine.copernicus.eu/?option=com_csw&view=details&product_id=SST_MED_SST_L4_REP_OBSERVATIONS_010_021). The data consists of daily (night-time), gap free, optimally interpolated foundation SST at ~4 km resolution from AVHRR with improved accuracy and stability over the 1982-2019 period
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Geochemical and genomic data from the NEOM Brine Pool (Gulf of Aqaba)(Zenodo, 2022-05-22) [Dataset]This workbook contains the raw data acquired from the sampling of cores and water collected at 1,800 m depth in the NEOM Brine Pool, Gulf of Aqaba. The file captures the geochronology of the long core (S1-S2), X-ray fluorescence scanning (S3), X-ray diffraction (S4), geochemical analyses of the core sediments and overlying bine, plus associated uncertainties, and measurement precision (S5), and genomics (S6).
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Morphological traits and sex ratios of Acanthochromis polyacanthus F2 generation in present-day and elevated temperatures(James Cook University, 2022-05-18) [Dataset]Please see the associated publication on why and how this data was collected and analysed: Spinks, R.K., Donelson, J.M., Bonzi, L.C., Ravasi, T. & Munday, PL. (2022) Parents Exposed to Warming Produce Offspring Lower in Weight and Condition. Ecology and Evolution. This data publication contains the dataset and a R script for the above publication.
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Finding Nano-Ötzi: Cryo-Electron Tomography Visualization Guided by Learned Segmentations(KAUST Research Repository, 2022-05-09) [Dataset]Example data for research paper: - ts_16_annotations.zip ... The 4-class annotation volumes; - ts_16_predictions.zip ... The 4-class prediction volumes; - ts_16_predictions_256.zip ... A 256 x 256 x 448 crop of the 4-class prediction volumes; - ts_16_predictions_512.zip ... A 512 x 512 x 448 crop of the 4-class prediction volumes; - ts_16_predictions_768.zip ... A 768 x 768 x 448 crop of the 4-class prediction volumes; - ts_16_predictions_1024.zip ... A 1024 x 1024 x 448 crop of the 4-class prediction volumes.