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.
11,198
datasets available to search
ShareScore release 0.9.0
Dataset results
11,198 results for “organs”
Figure 11 in New organic-walled Foraminifera (Protista) from the ocean's deepest point, the Challenger Deep (western Pacific Ocean)
Figure 11. Resigella bilocularis sp. nov. Transmission light micrographs of specimens on open slides in glycerol. A, holotype, reg. no. MPC-02697. B, paratype, reg. no. MPC-02696. C, D, general view and detail of specimen illustrated by SEM in Figure 12A–B. E, general view of specimen illustrated by SEM in Figure 13E–F. G, specimen with delicate partition in front of stercomata. H, paratype, reg. no. ZF 5171. I, small specimen with clearly developed neck between the two chambers. All scale bars = 50 Mm.
Figure 10 in New organic-walled Foraminifera (Protista) from the ocean's deepest point, the Challenger Deep (western Pacific Ocean)
Figure 10. Resigella laevis sp. nov. Scanning electron micrographs. A, B, aperture. C, D, surface of test near aperture showing relatively sparse development of finger-like projections. E, general view of test. F, aperture. G, broken section of wall.
Figure 9 in New organic-walled Foraminifera (Protista) from the ocean's deepest point, the Challenger Deep (western Pacific Ocean)
Figure 9. Resigella laevis sp. nov. Scanning electron micrographs. A, general view of test. B, proloculus. C, detail of interdigitated border between smooth organic surface of proloculus and highly ornamented organic surface of later chambers; boxes indicate areas shown in detail in D and F. D, E, surface of chamber immediately in front of proloculus showing mass of finger-like projections; the flat features are probably clay particles. F, G, surface of proloculus.
Figure 8 in New organic-walled Foraminifera (Protista) from the ocean's deepest point, the Challenger Deep (western Pacific Ocean)
Figure 8. Resigella laevis sp. nov. Transmission light micrographs of specimens on open slides in glycerol. A, holotype, reg. no. MPC-02710. B–G, paratypes, reg. nos. MPC-02711-02715. H, I, paratypes, reg. nos. ZF 5170. J–O, other specimens; M shows detail of final chamber with partition in front of stercomata; O shows detail of final chamber with mass of cytoplasm in front of stercomata. All scale bars = 50 Mm except where indicated otherwise.
Figure 7 in New organic-walled Foraminifera (Protista) from the ocean's deepest point, the Challenger Deep (western Pacific Ocean)
Figure 7. Nodellum aculeata sp. nov. Scanning electron micrographs. A, general view of test; area indicated by box is shown in detail in F. B, damaged region showing curved lines of fracture. C, D, broken sections of the wall showing probable agglutinated grain and lack of internal structure. E, inner surface of wall. F, G, surface of wall showing scale-like patches (probably clay particles) surrounded by masses of tiny, finger-like projections.
Figure 6 in New organic-walled Foraminifera (Protista) from the ocean's deepest point, the Challenger Deep (western Pacific Ocean)
Figure 6. Nodellum aculeata sp. nov. Scanning electron micrographs. A, general view of entire specimen; boxes indicate areas shown in detail in other images. B, C, progressively closer views of test surface near the aperture. D, E, progressively closer views of test surface near proloculus. Note the finger-like projections covering the surface of the wall in both areas.
Figure 5 in New organic-walled Foraminifera (Protista) from the ocean's deepest point, the Challenger Deep (western Pacific Ocean)
Figure 5. Nodellum aculeata sp. nov. Scanning electron micrographs of test apertures. A, C, D, specimens in which test tapers gently towards circular aperture. B, specimen with abruptly truncated apertural end (entire test shown in Fig. 3E). The specimen shown in D is probable dead (empty); those shown in A–C probably contain cytoplasm. All scale bars = 10 Mm.
Figure 3 in New organic-walled Foraminifera (Protista) from the ocean's deepest point, the Challenger Deep (western Pacific Ocean)
Figure 3. Nodellum aculeata sp. nov. Scanning electron micrographs. A, general view of entire specimen. B, proloculus with rounded end; boxes indicate areas shown in detail in C and D. C–D, details of proloculus; most of the surface is strewn with rod-like particles but the organic wall is exposed in irregular patches. E, oblique view of aperture. F, general view of entire specimen with pointed proloculus and abruptly truncated distal end.
Figure 4 in New organic-walled Foraminifera (Protista) from the ocean's deepest point, the Challenger Deep (western Pacific Ocean)
Figure 4. Nodellum aculeata sp. nov. Scanning electron micrographs. A, general view of entire specimen with somewhat crooked shape; box indicates area shown in detail in E. B, proloculus. C, pointed end of proloculus showing tip devoid of agglutinated particles. D, transition between surface of proloculus with agglutinated particles (to left) and predominately organic surface of the main tubular part of the test; note the interdigitation of the two areas. E, detail of surface. F, higher magnification showing tiny, finger-like projections covering test surface.
Figure 16 in New organic-walled Foraminifera (Protista) from the ocean's deepest point, the Challenger Deep (western Pacific Ocean)
Figure 16. Conicotheca nigrans gen. et sp. nov. Scanning electron micrographs of same specimen. A, general view; area indicated by box is shown in detail in C. B, aperture. C, detail of surface. D, proximal part of test with swollen 'proloculus'; areas indicated by boxes are shown in detail in E and F. E, smooth area on 'proloculus'. F, rough area with scale-like features, probably clay particles.
Figure 2 in New organic-walled Foraminifera (Protista) from the ocean's deepest point, the Challenger Deep (western Pacific Ocean)
Figure 2. Nodellum aculeata sp. nov. Scanning electron micrographs. A, proloculus; box indicates area shown in C. B, transition between surface of proloculus with obvious agglutinated particles (to left) and predominately organic surface of the main tubular part of the test. C–F, progressively closer views showing rod-like agglutinated particles strewn across the surface of the proloculus.
Figure 1 in New organic-walled Foraminifera (Protista) from the ocean's deepest point, the Challenger Deep (western Pacific Ocean)
Figure 1. Nodellum aculeata sp. nov. Transmission light micrographs of type specimens, on open slides in glycerol. A, holotype, reg. no. MPC-02705. B–H, paratypes, reg. nos. ZF 5169; F, detail of distal end showing mass of cytoplasm. I–O, paratypes, reg. nos. MPC-02706-02709; K, detail of proloculus with rounded end; M, detail of distal part of specimen showing abrupt decrease in width and truncated end. All scales bars = 100 Mm except where indicated otherwise.
Storage experiment for the analysis of dissolved organic matter in surface water and groundwater
<p>This dataset contains the data resulting from a storage experiment, whereby samples from surface water (<em>n</em>=3) and groundwater (<em>n</em>=1) were stored cooled (4°C) or frozen (-20°C) and analysed after 1, 2, 3, 7, 14, 30 and 90 days using fluorescence spectroscopy (Aqualog, Horiba Scientific, Edison, NJ, USA). For each sample, the absorbance spectrum (240–500 nm) and a fluorescence excitation-emission matrix (EEM) were obtained. EEMs were obtained for excitation wavelengths 240–500 nm (3 nm interval) and emission wavelengths 248–825 nm (~4.6 nm interval) with an integration time of 1 second. Five absorbance indicators and eight fluorescence indicators were calculated. The DOC concentration was estimated using the two-wavelength approach of Cook et al. (2017).</p> <p>The dataset consists of four files:</p> <ul> <li>Aqualog data processing and index calculation.R: R script with the code to process the Aqualog data and to calculate the indices.</li> <li>Aqualog.zip: Raw data obtained from the Aqualog, divided into subfolders corresponding to the day of measurement. For each sample, the absorbance spectrum (*ABS.dat) and EEMs of the sample (*SEM.dat) and corresponding blank measurement (*BEM.dat) are provided.</li> <li>Indices.xlsx: Table with index values for all samples.</li> <li>Samples.xlsx: Table with information about all samples (e.g. sampling site, storage duration, storage method)</li> </ul> <p>The geolocations of the sampling sites are:</p> <ul> <li>Site 102 - 50° 29' 6.09''N - 8° 33' 33.57''E</li> <li>Site 134 - 50° 28' 36.55''N - 8° 32' 39.56''E</li> <li>Site 175 - 50° 28' 34.05''N - 8° 32' 42.89''E</li> <li>Site 187 - 50° 28' 49.98''N - 8° 32' 35.12''E</li> </ul>
Grapevine Dataset for plant organ segmentation
<p><br>This is a dataset for Grapevine segmentation for the purposes of winter pruning, created in a joint work between Istituto Italiano di Tecnologia and Università Cattolica del Sacro Cuore, as part of the Vinum project. The work was also cofounded by Italian Ministry of University and Research PRIN 20172HHNK5 Project, under the supervision of Matteo Gatti, Claudio Semini and Darwin Caldwell.</p> <p>The images were captured in the simulated grapevine garden in Università Cattolica, located in Piacenza, Italy, and it is split in two parts, following agronomic trials being run on the university. The first part is a group of seven specimen that is the Control group, and the second group of eight specimens is being performed shoot thinning.</p> <p>Each plant has around 5 spurs, and the photos are taken from both sides of the grapevine specimen, meaning that there is one picture where the plant grows from left to right, and the other side where the plant grows from right to left. The resolution of the images is 4608x3456, and we have a total of 149 images. </p> <p> </p> <p>It is annotated using the COCO Segmentation format, and some of the statistics of the dataset such as the number of annotations and number of images can be seen next.</p> <p><strong>Control Complex</strong></p> <ul> <li>Total <ul> <li>Images: 69</li> <li>Annotated Images: 69</li> <li>Annotations: 1838</li> <li>Categories: 5</li> </ul> </li> <li>Annotations Per Category <ul> <li>Main Cordon: 79</li> <li>Cane: 440</li> <li>Node: 1100</li> <li>Arm: 103</li> <li>Spur: 116</li> </ul> </li> <li>Annotated Images Per Category <ul> <li>Main Cordon: 69</li> <li>Cane: 69</li> <li>Node: 69</li> <li>Arm: 62</li> <li>Spur: 68</li> </ul> </li> </ul> <p><strong>Shoot Thining Simple</strong></p> <ul> <li>Total <ul> <li>Images: 79</li> <li>Annotated Images: 79</li> <li>Annotations: 1635</li> <li>Categories: 5</li> </ul> </li> <li>Annotations Per Category <ul> <li>Main Cordon: 84</li> <li>Cane: 341</li> <li>Node: 912</li> <li>Arm: 154</li> <li>Spur: 144</li> </ul> </li> <li>Annotated Images Per Category <ul> <li>Main Cordon: 79</li> <li>Cane: 79</li> <li>Node: 79</li> <li>Arm: 79</li> <li>Spur: 77</li> </ul> </li> </ul> <p> </p>
Russian Index of the Research Organizations (RIRO)
<p>The RIRO dataset contains standardized official information, geodata, and various identifiers of research organizations in Russia, all interlinked via unified primary key. Currently covered data sources include ROR\GRID, WIkiData, Scopus\Scival IDs, InCites\Web of Science\eLIBRARY names, and the IDs assigned by the Russian Ministry of Science & Higher Education. RIRO lists not only the head organizations, but also their branches and last predecessors, which allows to build an hierarchy and analyze a history of mergers\liquidations using the linked IDs. RIRO is aimed to become a valuable tool for both research managers and academic scholars in the fields of science policy, scientometrics, science and technology studies.</p> <p>www: <a href="https://openriro.github.io/">RIRO Project site</a></p>
Dataset for "Fine-Tuning A Robust Metal–Organic Framework Towards Enhanced Clean Energy Gas Storage"
<p>Dataset covering the DFT simulations performed for the journal article "Fine-Tuning A Robust Metal–Organic Framework Towards Enhanced Clean Energy Gas Storage"</p>
Organizations—Crunchbase
<p>El conjunto de datos<strong> extraído de Crunchbase</strong> aplicando la técnica del <em>web scraping</em> contiene 1.000 observaciones de organizaciones, una muestra muy pequeña del conjunto de datos potencial. El límite establecido se debe a razones de practicabilidad.</p> <p>La información recogida de Crunchbase es información comercial, donde es posible consultar, entre otros campos, </p> <ul> <li> <p>las industrias en las que una organización opera «Industries», </p> </li> <li> <p>dónde se encuentra su sede «Headquarters Region», </p> </li> <li> <p>año de fundación «Founded Date», </p> </li> <li> <p>estado actual «Operating Status», </p> </li> <li> <p>email de contacto «Contact Email», </p> </li> <li> <p>teléfono de contacto «Phone Number», </p> </li> <li> <p>sus fundadores «Founders», </p> </li> <li> <p>si es un fondo en qué compañías y etapas invierte «Investment Stage», </p> </li> <li> <p>etc. </p> </li> </ul> <p>Los tipos de organizaciones que se pueden observar en los datos son:</p> <ul> <li> <p>Empresas</p> </li> <li> <p>Inversores</p> </li> <li> <p>Escuelas</p> </li> </ul> <p>El dataset se ha elaborado con el objetivo de ayudar a los fondos de capital riesgo a dedicar menos tiempo buscando información y más tiempo cerrando acuerdos.</p>
Dataset Literature Review Digital Forensic and Organization & Administration
<p>Bahwa data ini digunakan untuk membuat penelitian sesuai dengan tinjauan literatur dengan kata kunci digital forensik dan Organization & Administration</p>
FRidge GA13 Organic Ligands CSV data
<p>Competitive Ligand Exchange-Adsorptive Cathodic Stripping Voltammetry samples from 11 sites along the Mid-Atlantic Ridge. Samples were collected as part of the 2017-18 FRidge (GA 13) research expedition on board the RSS James Cook.</p>
CATH Structural domains in AlphaFold2 models for 21 model organisms
<p>CATH structural domain assignments for AlphaFold2 models in 21 model organisms.</p> <p>The table cath-v4_3_0.alphafold-v2.2022-11-22.tsv contains the domain assignments with information on model quality, CATH superfamily and Class, organism, average pLDDT, percentage of residues not in secondary structure, globularity and domain origin (CATH-PDB, CATH-HMM,Pfam,newfams).</p> <p>Organisms included:</p> <p>Arabidopsis thaliana</p> <p>Caenorhabditis elegans</p> <p>Candida albicans</p> <p>Danio rerio</p> <p>Dictyostelium discoideum</p> <p>Drosophila melanogaster</p> <p>Escherichia coli</p> <p>Glycine max</p> <p>Homo sapiens</p> <p>Leishmania infantum</p> <p>Methanocaldococcus jannaschii</p> <p>Mus musculus</p> <p>Mycobacterium tuberculosis</p> <p>Oryza sativa</p> <p>Plasmodium falciparum</p> <p>Rattus norvegicus</p> <p>Saccharomyces cerevisiae</p> <p>Schizosaccharomyces pombe</p> <p>Staphylococcus aureus</p> <p>Trypanosoma cruzi</p> <p>Zea mays</p> <p> </p> <p>The archive</p> <pre>cath-v4_3_0.alphafold-v2.2022-11-22.by_superfamily.tgz</pre> <p>contains all domains assigned by CATH in the dataset as PDB files, divided by superfamily.</p> <p>Alternatively, if you're interested in a particular organism, an individual tarball containing all CATH domains as PDB files is available</p> <p>e.g. cath-v4_3_0.alphafold-v2.2022-11-22.arabidopsis_thaliana.tgz</p> <p>All domains included in this release are named as af_[UniProt_ID]_[start]_[stop].</p> <p> </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.