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.
955
datasets available to search
ShareScore release 0.9.0
Dataset results
955 results for “Ocean data”
Thaliaceans data in the global ocean and the South China Sea
<p>This dataset contains two sheets, one is the global presence-absence records of some typical thaliacean species with environmental data and the other one is the abundance of thaliaceans with environmental data in the South China Sea.</p>
Data from: Distinctive microbial community and genome structure in coastal seawater from a human-made port and nearby offshore island in northern Taiwan facing the Northwestern Pacific Ocean
<p><span>Pollution in human-made fishing ports caused by petroleum </span><span>from</span><span> boats, dead fish, toxic </span><span>chemicals</span><span>, and effluent </span><span>poses</span><span> a challenge to the organisms in seawater. To decipher the impact of pollution on the microbiome, we collected surface water </span><span>from</span><span> a fishing port and a nearby offshore island in northern Taiwan facing the </span><span>Northwestern Pacific Ocean. By employing 16S </span><span>rRNA gene</span><span> amplicon sequencing and whole-genome shotgun sequencing, we discovered that </span><span>Rhodobacteraceae, Vibrionaceae, and Oceanospirillaceae emerged as the dominant species in the fishing port</span><span>,</span><span> where we found many genes harboring the functions of </span><span>antibiotic</span><span> resistance (</span><span>ansamycin, nitroimidazole, and aminocoumarin), metal tolerance (copper, chromium, iron and multimetal), virulence factors (chemotaxis, flagella, T3SS1), carbohydrate metabolism (biofilm formation and remodeling of bacterial cell </span><span>walls</span><span>), nitrogen metabolism (denitrification, N<sub>2</sub> fixation, and ammonium assimilation), and ABC transporters (phosphate, lipopolysaccharide, and branched-chain amino </span><span>acids</span><span>). The dominant bacteria at the nearby offshore island (</span><span>Alteromonadaceae, Cryomorphaceae, Flavobacteriaceae, Litoricolaceae, and Rhodobacteraceae) were partly similar to those in the South China Sea and the East China Sea. Furthermore, we inferred</span><span> that</span><span> the microbial community network of </span><span>the cooccurrence</span><span> of dominant bacteria </span><span>on the</span><span> offshore island was connected to dominant bacteria in </span><span>the </span><span>fishing port by mutual</span> <span>exclusion. By examining the assembled microbial genomes collected from the coastal seawater of the fishing port, we revealed four genomic islands containing large gene-containing sequences</span><span>,</span><span> including phage integrase, DNA</span> <span>invertase, restriction enzyme, DNA gyrase inhibitor, and antitoxin HigA-1.</span><span> In this study, </span><span>we provided </span><span>clues </span><span>for the possibility of genomic islands as the units of horizontal transfer and as the tools of microbes for facilitating adaptation in a human-made port environment.</span></p>
Data for: From rivers to ocean basins: The role of ocean barriers and philopatry in the genetic structuring of a cosmopolitan coastal predator
<p>The Bull Shark (Carcharhinus leucas) faces varying levels of exploitation around the world due to its coastal distribution. Information regarding population connectivity is crucial to evaluate its conservation status and local fishing impacts. In this study, we sampled 922 putative Bull Sharks from 19 locations in the first global assessment of population structure of this cosmopolitan species. Using a recently developed DNA-capture approach (DArTcap), samples were genotyped for 3,400 nuclear markers. Additionally, full mitochondrial genomes of 384 Indo-Pacific samples were sequenced. Reproductive isolation was found between and across ocean basins (eastern Pacific, western Atlantic, eastern Atlantic, Indo-West Pacific) with distinct island populations in Japan and Fiji. Bull Sharks appear to maintain gene flow using shallow coastal waters as dispersal corridors, whereas large oceanic distances and historical land-bridges act as barriers. Females tend to return to the same area for reproduction, making them more susceptible to local threats and an important focus for management actions. Given these behaviours, the exploitation of Bull Sharks from insular populations, such as Japan and Fiji, may instigate local decline that cannot readily be replenished by immigration, which can in turn affect ecosystem dynamics and functions. These data also supported the development of a <span>genetic panel to </span>ascertain the population of origin<span>, which will be useful in monitoring the trade of fisheries products and assessing population-level impacts of this harvest.</span></p>
Dataset for paper Pavel Perezhogin, Laure Zanna, Carlos Fernandez-Granda "Generative data-driven approaches for stochastic subgrid parameterizations in an idealized ocean model" submitted to JAMES.
<p>The dataset consists of the directory tree of .zarr archives. See <a href="https://github.com/m2lines/pyqg_generative/blob/master/Google-Colab/dataset.ipynb">Github repository</a> for the description of the dataset.</p> <p>The directory tree is:</p> <pre><code>├── eddy │ ├── 48 │ │ ├── gauss │ │ ├── hires-gauss │ │ ├── hires-sharp │ │ ├── lores │ │ └── sharp │ ├── 64 │ │ ├── gauss │ │ ├── hires-gauss │ │ ├── hires-sharp │ │ ├── lores │ │ └── sharp │ ├── 96 │ │ ├── gauss │ │ ├── hires-gauss │ │ ├── hires-sharp │ │ ├── lores │ │ └── sharp │ └── hires ├── jet │ ├── 48 │ │ ├── gauss │ │ ├── hires-gauss │ │ ├── hires-sharp │ │ ├── lores │ │ └── sharp │ ├── 64 │ │ ├── gauss │ │ ├── hires-gauss │ │ ├── hires-sharp │ │ ├── lores │ │ └── sharp │ ├── 96 │ │ ├── gauss │ │ ├── hires-gauss │ │ ├── hires-sharp │ │ ├── lores │ │ └── sharp │ └── hires</code></pre> <ul> <li>Every individual dataset is a <code>.zarr</code> <a href="https://zarr.readthedocs.io/en/stable/">archive</a></li> <li><code>eddy/jet</code> - configuration of the pyqg; eddy is default; See <a href="https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2022MS003258">Ross2022</a> for description</li> <li><code>hires.zarr</code> - high-resolution simulation at 256x256 grid</li> <li><code>48/64/96</code> - resolution of the coarse models</li> <li><code>lores.zarr</code> - low-resolution simulation</li> <li><code>gauss.zarr</code>, <code>sharp.zarr</code> - training datasets for prediction of subgrid forcing obtained with Gaussian or Sharp filters</li> <li><code>hires-gauss.zarr</code>, <code>hires-sharp.zarr</code> - high-resolution simulation projected onto coarse grid with Gaussian or Sharp filters</li> </ul> <p>The directory tree is split into small tar.gz files each representing a separate .zarr archive. Download any required parts of the dataset and unpack with:</p> <p><strong>tar -xf *.tar.gz </strong></p> <p><strong>The directory tree will be restored automatically!</strong></p>
Data for "Turbulent drag at the ice-ocean interface of Europa in simulations of rotating convection: Implications for nonsynchronous rotation of the ice shell"
<p>Data files and python Jupyter notebook to reproduce Figures 2 - 6 from the manuscript "Turbulent drag at the ice-ocean interface of Europa in simulations of rotating convection: Implications for nonsynchronous rotation of the ice shell".</p> <p>Contents:</p> <p>Package</p> <p>--EuropaOceanTorque.ipynb - Jupyter Notebook to load and analyse data. Reproduces figures 1-2 from the manuscript.<br> --cs510 - Grid info files<br> --mitgcm_vis - plotting and interpolation functions<br> --Results - directory for all data files<br> --Setup<br> ----runx - input files for running MITgcm<br> ----code - mods for compiling the MITgcm</p>
Ocean data
<p>Ocean model data.</p>
Ocean Model Data
<p>Experiments 4, 6, 8, and 10 rpm.</p>
Toward a Better Understanding of the Global Ocean Copper Distribution and Speciation through a Data-constrained Model
<p>MATLAB codes for a global marine copper model under the AWESOME OCIM framework. </p> <p>Prepared for manuscript submission.</p>
Compilation of the chemical composition data of pelagic clay around Minamitorishima Island in the western North Pacific Ocean
<p>A compilation of bulk chemical composition data of pelagic clay around Minamitorishima Island in the western North Pacific Ocean. Original data were published in the cited articles (shown in Data source column). This is a supplementary dataset for "High-dimensional chemostratigraphy of pelagic clay in western North Pacific Ocean revealed <em>via</em> unsupervised clustering approach" by Yasukawa et al.</p>
Supplementary data products for Ha et al. 'Assessing the biogeography of marine giant viruses in four oceanic transects'.
<p>Processed data products for Ha et al., "<strong>Assessing the biogeography of marine giant viruses in four oceanic transects</strong>".</p>
Data for "Satellite-observed strong subtropical ocean warming as an early signature of global warming"
<p>Data for “Satellite-observed strong subtropical ocean warming as an early signature of global warming”</p>
Data for "Diapycnal Upwelling over the Kyushu-Palau Ridge in the North Pacific Ocean"
<p>Data on manuscript entitled "Diapycnal Upwelling over the Kyushu-Palau Ridge in the North Pacific Ocean" in Matlab format. Details about the variables in the mat files are described in Readme.txt.</p>
Data supporting 'Modeling Antarctic ice shelf basal melt patterns using the one-Layer Antarctic model for Dynamical Downscaling of Ice--ocean Exchanges (LADDIE v1.0)'
<p>This data set contains the data produced for the paper 'Modeling Antarctic ice shelf basal melt patterns using the one-Layer Antarctic model for Dynamical Downscaling of Ice--ocean Exchanges (LADDIE v1.0)'</p> <p>The data set contains output from LADDIE simulations, including basal melt rates.</p> <p>The main simulations used in the man text are:</p> <p>- Crosson-Dotson: <a href="https://zenodo.org/api/files/0640a922-97a9-4ced-ad3d-dab66f05c696/CrossDots_0.5_tanh_Tdeep0.4_ztcl-500_050.nc">CrossDots_0.5_tanh_Tdeep0.4_ztcl-500_050.nc </a><br> - Filchner-Ronne: <a href="https://zenodo.org/api/files/0640a922-97a9-4ced-ad3d-dab66f05c696/FRIS_1.0_linear_S134.8_T1-2.3_720.nc">FRIS_1.0_linear_S134.8_T1-2.3_720.nc </a><br> </p> <p>The additional simulations included in the Appendix are:</p> <p>- 3D forcing of Crosson-Dotson: <a href="https://zenodo.org/api/files/0640a922-97a9-4ced-ad3d-dab66f05c696/CrossDots_0.5_mitgcm_2003_2008_100.nc">CrossDots_0.5_mitgcm_2003_2008_100.nc </a><br> - Tuning of Crosson-Dotson: XX_YY_ZZ.nc, where XX is the resolution in km, YY is the value for Cd,top, and ZZ is the value for Dmin<br> - Pine Island Ice Shelf: <a href="https://zenodo.org/api/files/0640a922-97a9-4ced-ad3d-dab66f05c696/PIG.nc">PIG.nc </a><br> </p>
compositional data for "Chromium isotope behavior during serpentinite dehydration in oceanic subduction zones"
<p>Table 1 refer to the Cr isotope results for the meta-serpentinite in this study. Table S1 shows the major and trace element compositions of the studied samples. Table S2 compiles the available Cr isotope compositions of low-grade serpentinites.</p>
Supporting data for manuscript: "Global-scale evaluation of coastal ocean alkalinity enhancement in a fully-coupled Earth system model"
<p>Supporting data for manuscript: "Global-scale evaluation of coastal<br> ocean alkalinity enhancement in a fully-coupled Earth system model"</p> <p>Authors: Julien Palmieri and Andrew Yool</p> <p>Institute: National Oceanography Centre, European Way, Southampton<br> SO14 3ZH, UK</p> <p>This repository consists of four main sets of files:</p> <p>1. Matlab scripts used for analysis, figure plotting and table<br> preparation</p> <p> Filenames of the format: Figure_??.m</p> <p>2. Raw netCDF output files from UKESM1 for six model experiments</p> <p> Filenames of the format: medusa_c*.nc</p> <p>3. BGCVal processed timeseries shelve files</p> <p> Filenames of the format: u-c*.shelve.txt</p> <p>4. CMM2 processed timeseries netCDF files</p> <p> Filenames of the format: c*_global.nc</p> <p>File sets 2-4 are read and processed by script files in file set 1<br> </p>
Elevation data for On the More Complex Wavelength Dependency of Airy Isostasy in Icy Shells of Ocean Worlds
<p>Elevations for surface and root topographies of simulated displacements. </p>
Late Cenozoic Sea Surface Temperature evolution of the South Atlantic Ocean (Data sets)
<p>Supplementary datasets affiliated with the Hoem et al., 2023 publication in Climate of the past: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-291/ </p> <p>Supplementary Table 3: GDGT results Site 696</p> <p>Supplementary Table 4: GDGT results SiteU1536</p>
Data for the figures of Sasaki et al. entitled "Turbulence across the Antarctic Circumpolar Current in the Indian Southern Ocean: Micro-Temperature Measurements and Finescale Parameterizations"
<p>1) Microstructure.nc includes profiles of epsilon and diapycnal diffusivity obtained from FP07 measurements.</p> <p>2) Fine_parameters.nc includes profiles of buoyancy frequency (N), shear-strain ratio, normalized internal wave energy, and polarization ratio of the counterclockwise (CCW) versus the clockwise (CW) component of the shear.</p> <p>3) epsilon_FineParam.nc includes profiles of epsilon calculated by finescale parameterizations. The subscript of each variable (eps_Fine_X) in this file corresponds to the row letter (a-l) of Table. 1.</p> <p>4) Fine_spectral_shape.nc includes profiles of Hstrain and spectral slope (s). </p>
Supplementary Data: An evaluation of the General Bathymetric Chart of the Ocean (GEBCO) in shoreline-crossing geomorphometric investigations of volcanic islands
<p>Supplementary data for the titular publication. Consists of .csv and .gpkg files with the results of geomorphometric parameter extraction of volcanic islands from shoreline-crossing DEMs of various resolution, the calculation of the deviation of these parameters depending on the source DEM, as well as basic statistical distribution of these parameters. See publication for more detailed information.</p>
Data for: Linking vertical movements of large pelagic predators with distribution patterns of biomass in the open ocean
<p>Many predator species make regular excursions from near-surface waters to the twilight (200-1,000 m) and midnight (1,000-3,000 m) zones of the deep pelagic ocean. While the occurrence of significant vertical movements into the deep ocean has evolved independently across taxonomic groups, the functional role(s) and ecological significance of these movements remain poorly understood. Here, we integrate results from satellite tagging efforts with model-predictions of deep prey layers in the North Atlantic Ocean to determine if prey distributions are correlated with vertical habitat use across 12 species of predators. Using 3D movement data for 344 individuals that traversed nearly 1.5 million km of pelagic ocean in >42,000 days, we found that nearly every tagged predator frequented the twilight zone and many made regular trips to the midnight zone. Using a predictive model, we found clear alignment of predator depth use with the expected location of deep pelagic prey for at least half of the predator species. We compared high-resolution predator data with shipboard acoustics and selected representative matches that highlight the opportunities and challenges in the analysis and synthesis of these data. While not all observed behavior was consistent with estimated prey availability at depth, our results suggest that deep pelagic biomass likely has high ecological value for a suite of commercially important predators in the open ocean. Careful consideration of the disruption to ecosystem services provided by pelagic food webs is needed before the potential costs and benefits of proceeding with extractive activities in the deep ocean can be evaluated.</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.