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.
712
datasets available to search
ShareScore release 0.9.0
Dataset results
712 results for “mantle”
Occupancy of two Colombian endemic birds (Habia gutturalis) and White-Mantled Barbet (Capito hypoleucus) in fragmented forests of the Central Andes in Colombia
Open the record for dataset details and reuse information.
The mantle transition zone hosts the missing HIMU reservoir beneath eastern China
<p>Table S1. Geochemical and isotopic compositions of Cenozoic lavas from Wudi</p> <p>Table S2. LA-ICP-MS analyses of clinopyroxenes from Wudi lavas, clinopyroxenes from Xenoliths in Wudi lavas, and USGS basalt glass standards</p> <p>Table S3. The Pb isotopic data for clinopyroxene and groudmass from Wudi lavas, and clinopyroxenes from Xenoliths in WD lavas</p> <p>Table S4. The compositions of olivines from Wudi lavas</p> <p>Table S5. The compositions of Late Cenozoic lavas with SiO2 < 55 wt. % from eastern China.</p> <p>Table S6. Monte Carlo modeling for Pb isotope source composition from Paleo-Asian ocean crust.</p>
Dataset for Seismic waveform tomography of the Central and Eastern Mediterranean upper mantle
<p><strong>Dataset corresponding to the Seismic waveform tomography of the Central and Eastern Mediterranean upper mantle</strong></p> <p>This dataset belongs to the seismic waveform tomography of the Central and Eastern Mediterranean by Blom, Gokhberg and Fichtner, Solid Earth (Discussions), 2019. Seismic tomography is an inverse problem where the internal elastic structure of the Earth (the upper ~500 km) is determined from seismograms (the vibrations of the Earth as a result of earthquakes, as recorded by seismometers at the Earth's surface). This inverse problem is cast as an optimisation where the misfit between observed and synthetic seismograms is minimised: waveform tomography (often referred to as full waveform inversion or FWI). Synthetic seismograms are produced by simulating the elastic wavefield of earthquakes within the Earth. The optimisation problem is solved by iterative, deterministic, gradient-based inversion. Gradients are computed using the adjoint method, which requires one forward wavefield simulation and one adjoint wavefield simulation per earthquake used in the project.</p> <p>The inversion was carried out over several frequency bands, starting with the longest periods and including a progressively broader frequency band. Within each frequency band, ~10-20 iterations were carried out, totalling to a hundred iterations. Synthetic seismograms and iteration information are stored for a subset of iterations, notably those where human interaction (i.e. the selection of events / data windows) took place.</p> <p>Here, we describe:</p> <ul> <li>The contents of this package</li> <li>How to set up the package such that all the data can be accessed and used, and reproduce the figures.</li> </ul> <p><strong>Contents of this package</strong></p> <ul> <li>Data that was used for the seismic waveform inversion: raw and processed seismograms, station information, earthquake information, as well as the window selection (designating the parts of the data that were actually used at each stage in the inversion) and synthetic seismograms produced during various stages of the inversion. This information is gathered in the LASIF project "EMed_full.complete.tar".</li> <li>Models and misfit development across the iterations, as well as models relating to model testing, as carried out after the inversion. This information is gathered in the tarball "MODEL_FILES.tar". Model files are both given in the ses3d ascii format (text file drho, dvsv, dvsh, dvp and block_x, block_y, block_z) and in bundled .vtu format. Conversion to .vtu was done using the tools in SCRIPTS. These vtu files can be viewed using Paraview.</li> <li>information on the tools and code that was used to do the inversion: <ul> <li>ses3d: a seismic wave propagation spectral element code in spherical coordinates. This will run both forward and adjoint simulations. This is available publicly through the developers on <a href="https://cos.ethz.ch/software/production/ses3d.html">https://cos.ethz.ch/software/production/ses3d.html</a>. See Gokhberg & Fichtner, 2016.</li> <li>LASIF: a waveform inversion workflow managing package, where we have made small adaptations to make it suitable for our workflow. The original package is available via <a href="http://www.lasif.net">www.lasif.net</a> and on github (see Krischer et al, 2015), the modified version is added to this package as 'LASIF-master.zip'.</li> <li>LASIF_scripts: bespoke scripts in order to interact with the LASIF project and generate different types of analyses and plots that are used in the publication. This is included in the tarball 'LASIF_scripts.tar'</li> <li>SCRIPTS: containing some modified tools that were originally written for ses3d, as well as some additional tools - notably to interact with models converted to the VTK format. This is included in the tarball 'SCRIPTS.tar'</li> <li>A description of the conda environment named lasif_ext (which is used for all the data analysis), in the form of the yml file 'lasif_ext.yml'</li> </ul> </li> <li>An additional LASIF project which is used just to compute sensitivity kernels for different windows within the same trace: 'EMed_window_kernels.tar'. This is used as an example in one of the manuscript figures.</li> </ul> <p><strong>How to set up the data package</strong></p> <ol> <li>Download the entire data package. We will assume it is located in `~/Downloads/`.</li> <li>Get miniconda or anaconda if you don't have it.</li> <li>Install LASIF. This can be done using the instructions from the <a href="http://lasif.net">LASIF website</a>, but with a few adaptations, which are detailed in the lasif_ext.yml file. This amounts to the following: <ol> <li>Add the channel conda-forge to your standard channels</li> <li>Name the environment "lasif_ext"</li> <li>Manually replace the files in the LASIF source directory with those in LASIF-master.zip.</li> <li>Install the specific version of pyqt=4.11.</li> <li>Install the additional packages jupyter, vtk=7.0.0, pandas=0.23.4 (these are the ones that work for me).</li> </ol> </li> <li>Extract the LASIF_scripts.tar to the site-packages directory of your conda environment: <pre><code class="language-bash">tar -xf ~/Downloads/LASIF_scripts.tar -C [/path/to/conda/environments]/lasif_ext/lib/python2.7/site-packages/</code></pre> </li> <li>Make a project directory and extract all needed packages into it: <pre><code class="language-bash"># make project directory mkdir CEMed_project_Blometal cd CEMed_project_Blometal # extract data tarballs into it tar -xf ~/Downloads/EMed_full.complete.tar tar -xf ~/Downloads/EMed_window_kernels.tar tar -xf ~/Downloads/MODEL_FILES.tar # make scripts directory and extract scripts into it mkdir conda_stuff tar -xf ~/Downloads/SCRIPTS.tar -C conda_stuff # make data analysis directory mkdir data_analysis cd data_analysis # extract analysis tools tar -xf ~/Downloads/NPY_FILES.tar tar -xf ~/Downloads/FIGURE_SCRIPTS.tar tar -xf ~/Downloads/figs_png.tar</code></pre> </li> </ol> <p>Now the project should be ready for inspection. The following things can be done, for example:</p> <ul> <li>Reproduce the figures in the manuscript. All scripts for this are located in CEMed_project_Blometal/data_analysis/FIGURE_SCRIPTS/. <pre><code class="language-bash">conda activate lasif_ext cd CEMed_project_Blometal jupyter notebook</code></pre> <p>This should open up a browser tab that shows the directory structure. Navigate to data_analysis/FIGURE_scripts and click on one of the .ipynb files to open it. If you press 'Kernel' > 'Restart kernel and run all' at the top, all cells will be launched automatically. This should work out of the box.</p> </li> <li>Interact with the lasif project. For this, refer to the <a href="http://www.lasif.net">LASIF website</a>. Note that above jupyter notebooks do so extensively, using the lasif communicator.</li> <li>Build additional analysis tools, using the tools supplied in SCRIPTS and LASIF_scripts.</li> </ul> <p><strong>References:</strong></p> <ul> <li> <p>Blom, N., Gokhberg, A., and Fichtner, A.: <strong>Seismic waveform tomography of the Central and Eastern Mediterranean upper mantle</strong>, Solid Earth Discuss., <a href="https://doi.org/10.5194/se-2019-152">https://doi.org/10.5194/se-2019-152</a>, in review, 2019.</p> </li> <li> <p>Gokhberg, A., Fichtner, A., 2016. <strong>Full-waveform inversion on heterogeneous HPC systems</strong>. Comp. & Geosci. 89, 260-268. <a href="https://doi.org/10.1016/j.cageo.2015.12.013">https://doi.org/10.1016/j.cageo.2015.12.013</a></p> </li> <li> <p>Krischer, L., Fichtner, A., Zukauskaitė, S., and Igel, H. (2015),<strong> Large‐Scale Seismic Inversion Framework</strong>, Seismological Research Letters, 86(4), 1198–1207.<a href="http://dx.doi.org/10.1785/0220140248"> doi:10.1785/0220140248</a></p> </li> </ul>
Flat subduction versus big mantle wedge: contrasting modes for deep hydration and overriding craton modification - Dataset
<p>This is the dataset for the paper "Flat subduction versus big mantle wedge: contrasting modes for deep hydration and overriding craton modification" that has been submitted to "Journal of Geophysical Research: Solid Earth" for publication.</p>
Dataset (.esg files) of a multiphase aggregate representative of a lower mantle composition compressed at High P/T in an R rDAC
<p>A collection of .esg files for use in the software package Materials Analysis Using Diffraction (MAUD; Lutterotti et al., 1997). Seven files are included, spanning the range used in data analysis. All are post-conversion from San Carlos olivine. Files are named in the following format:</p> <p>MPBrgFp: Stands for Multiphase, primary phases bridgmanite and ferropericlase<br> ###: Number of the diffraction pattern taken during the experiment<br> ##GPa: Approximate temperature, rounded to the nearest whole number. This is to cross-correlate .esg files with experimental Pt pressures cited within the paper.</p>
Data for "Bayesian inference of mantle viscosity from whole-mantle density models"
<p><strong>Supplementary Data</strong><br> Rudolph, M.L., Moulik, P., and Lekic, V. (2020). Bayesian inference of mantle viscosity from whole-mantle density models. Geochemistry, Geophysics, Geosystems</p> <p>This data archive contains files needed to reproduce the figures from our 2020 G-Cubed paper, including the full ensemble solutions for mantle viscosity structure.</p>
Supporting data for "Water content of the dehydration melting layer in the topmost lower mantle" by H. Fei
<p>This is the EPMA and XRD data for "Water content of the dehydration melting layer in the topmost lower mantle" by H. Fei.</p>
FIGURES 2A–G. Pisidium dorbignyi, anatomy. A. Siphonal and mantle edge musculature. B. Inner radial mantle muscles, lateral view. C in Anatomical characteristics of two enigmatic and two poorly known Pisidium species (Bivalvia: Sphaeriidae) from Southern South America
FIGURES 2A–G. Pisidium dorbignyi, anatomy. A. Siphonal and mantle edge musculature. B. Inner radial mantle muscles, lateral view. C. Distribution of scars of inner radial mantle muscles. D. Inner view of inner demibranch showing the upper position of brood sac. E–G. Nephridium (11, 13: dorsal view of left and right portions; 12: lateral view). (al: ascending lamellae; as: anal siphon; bs: brood sac; dl: descending lamellae; dln: dorsal lobe of nephridium; irm: inner radial mantle muscles; irms: inner radial mantle muscle scars; ll: lateral loop of nephridium; pa: posterior adductor muscle; pl: pallial line; pss: pre-siphonal; sr1: anal siphon retractor; sr2: retractor muscles corresponding to lacking inhalant opening).
FIGURE 3 in Hypselodoris jacksoni, a new species from the south-western Pacific Ocean (Nudibranchia: Chromodorididae), with a discussion on intraspecific variation in mantle glands in Chromodoris willani Rudman, 1982
FIGURE 3. Hypselodoris jacksoni sp. nov. (A) Schematic arrangement of mantle glands; (B) Light micrograph of double row of posterior mantle glands (arrowed) (paratype QM, MO.71813).
FIGURE 1 in Hypselodoris jacksoni, a new species from the south-western Pacific Ocean (Nudibranchia: Chromodorididae), with a discussion on intraspecific variation in mantle glands in Chromodoris willani Rudman, 1982
FIGURE 1. Distribution map for Hypselodoris jacksoni sp. nov. Area shaded dark grey represents limits of observed occurrence.
FIGURE 2 in Hypselodoris jacksoni, a new species from the south-western Pacific Ocean (Nudibranchia: Chromodorididae), with a discussion on intraspecific variation in mantle glands in Chromodoris willani Rudman, 1982
FIGURE 2. Hypselodoris jacksoni sp. nov. (A) 35mm, Split Solitary Island, northern New South Wales, Australia, 1986. Photo C. Buchanan. (B) 39mm, "The Fireplace", Duncombe Bay, Norfolk Island, 22 March 1992. Photo R.C. Willan. (C) upper animal 35 mm, Flinders Reef, southern Queensland, Australia, 12 November 1983; lower animal 33 mm, Tangalooma, southern Queensland, Australia, 12 November 1983. Photo R.C. Willan. (D) Holotype. NTM P23398, 34 mm, "Shag Rocks", North Stradbroke Island, southern Queensland, Australia, 17 June 1981. Photo R.C. Willan.
FIGURE 6 in Hypselodoris jacksoni, a new species from the south-western Pacific Ocean (Nudibranchia: Chromodorididae), with a discussion on intraspecific variation in mantle glands in Chromodoris willani Rudman, 1982
FIGURE 6. Mantle gland variation between individuals of Chromodoris willani (n=10). Configuration A was displayed by two individuals, each other configuration represents a single animal. An additional animal displayed a pattern similar to G and H.
FIGURE 4 in Hypselodoris jacksoni, a new species from the south-western Pacific Ocean (Nudibranchia: Chromodorididae), with a discussion on intraspecific variation in mantle glands in Chromodoris willani Rudman, 1982
FIGURE 4. Hypselodoris jacksoni sp. nov. (SAM D19271) SEMs of radula and jaws (A) Central section of radula; note two denticles on inner face of innermost lateral (arrowed); (B) Middle section of half row of radula showing middle lateral teeth; (C) Outer edge of half row of radula showing detail of outermost lateral teeth; (D) Inner face of jaw showing detail of mandibular rodlets.
FIGURE 5 in Hypselodoris jacksoni, a new species from the south-western Pacific Ocean (Nudibranchia: Chromodorididae), with a discussion on intraspecific variation in mantle glands in Chromodoris willani Rudman, 1982
FIGURE 5. Hypselodoris jacksoni sp. nov. (SAM D19271) Reproductive system of a mature individual. Abbreviations: a, ampulla; bc, bursa copulatrix; ej, ejaculatory portion of vas deferens; fg, female gland mass; p, penial sac; pr, prostatic portion of vas deferens; rs, receptaculum seminis; u, uterine duct; v, vaginal duct; vg, vestibular gland.
FIGURE 4 in Taxonomy, distribution, natural history and conservation of the Russet-mantled Foliage-gleaner Syndactyla dimidiata (Pelzeln, 1859) (Aves: Furnariidae)
FIGURE 4. Range of Syndactyla dimidiata based on personally examined specimens (white squares), digital photographs of specimens (white circles) and published sight records (black circles). See Appendix 1. Black arrows indicate the type localities of Anabates dimidiatus Pelzeln, 1859, Philydor baeri Hellmayr, 1911, and Xenoctistes mirandae Snethlage, 1928. Grey shading indicates the limits of Cerrado vegetation (see Lopes 2008). See Fig. 2 for abbreviations of Brazilian states.
FIGURE 3 in Taxonomy, distribution, natural history and conservation of the Russet-mantled Foliage-gleaner Syndactyla dimidiata (Pelzeln, 1859) (Aves: Furnariidae)
FIGURE 3. Scatterplots of the first versus the second principal component scores of a Principal Component Analysis of the morphometric variables measured from male specimens of Syndactyla dimidiata (see Table 2). Given the small sample size, we did not perform a PCA analysis for females. Factor loadings are presented as a table in the upper left corner of the figure. The first principal component (PC1) accounted for 49.7% of the variation, and the second principal component (PC2) explained 24.9%.
FIGURE 1 in Taxonomy, distribution, natural history and conservation of the Russet-mantled Foliage-gleaner Syndactyla dimidiata (Pelzeln, 1859) (Aves: Furnariidae)
FIGURE 1. Extremes of chromatic variation in Syndactyla dimidiata. Above: male (DZUFMG 5859) collected at the type locality of Philydor baeri, state of Minas Gerais. Note its predominantly dull ochraceous tones. Below: female (DZUFMG 6165) collected in the Distrito Federal. Note its predominantly ochraceous rufous tones.
FIGURE 2 in Taxonomy, distribution, natural history and conservation of the Russet-mantled Foliage-gleaner Syndactyla dimidiata (Pelzeln, 1859) (Aves: Furnariidae)
FIGURE 2. Geographical distribution of chromatic variation in Syndactyla dimidiata. Numbers indicate the coloration of the specimens examined, being: 1—birds with predominantly dull ochraceous tones, such as the type of P. bae ri; 2—birds intermediate between the types of P. baeri and of A. dimidiatus; 3—rufescent-brown birds such as the type of A. dimidiatus and 4—birds with predominantly ochraceous rufous tones. Note that the chromatic variation observed in this species is continuous, and that the division presented here is somewhat arbitrary. Only definitive-plumaged specimens that were personally examined were included. Brazilian states are indicated as follows: TO—Tocantins, BA—Bahia, GO—Goiás, MT—Mato Grosso, MS— Mato Grosso do Sul, MG—Minas Gerais, SP—São Paulo, PR—Paraná.
Data for: Electrical Conductivity of Superionic Hydrous SiO2 and the Origin of Lower-mantle High Conductivity Anomalies Beneath Subduction Zones
<p><strong>Dataset S1.</strong> Experimental conditions and the measured resistance and conductivity of hydrous Al-bearing SiO2. </p>
Melting and Defect Transitions in FeO up to Pressures of Earth's Core-Mantle Boundary
<p>The tables here represent the Source Data for Figure 6 in the manuscript titled "Melting and defect transitions in FeO up to pressures of Earth's core-mantle boundary.</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.