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22,922 results for “collections as data”
Example structure of data sent from a collection management system to a citizen science platform, simple case
<p>Illustrative example of data format following Darwin Core to send from a collection management system to a citizen science platform. Simple case : http://coldb.mnhn.fr/catalognumber/mnhn/p/p03558024</p> <p>Illustration of the milestone28 document, worpackage 5.2 of the ICEDIG project.</p>
Single crystal diffraction images for a room temperature data collection on the LEF-PG co-crystal.
<p>A set of diffraction images collected on a Rigaku FRE+ diffractometer, equipped with HF Varimax confocal mirrors and an AFC12 goniometer and HG Saturn 724+ detector diffractometer.</p> <p>The sample is an organic co-crystal that forms part of a study of the LEF active pharmaceutical ingredient with a range of coformers. The structure with the PG coformer shows strong signs of modulation in the diffraction pattern and structure refinement. The model presented in the paper (submitted to Crystal Growth and Design) does not account for any modulation and serves the purpose of a suitable degree of characterisation precision for this article. </p> <p>The authors wish to make the raw data available so that those with interest and experise in handling modulated structures can perform more detailed modelling studies and/or use the data to test software or for training examples.</p>
Single-crystal X-ray diffractometry data for a sample of NiCl₂-dppe collected on beamline I19-2 at Diamond Light Source
<p>Single-crystal X-ray diffractometry data for a sample of [1,2-Bis(diphenylphosphino)ethane]dichloronickel(II) (NiCl<sub>2</sub>-dppe, [(C<sub>6</sub>H<sub>5</sub>)<sub>2</sub>PCH<sub>2</sub>CH<sub>2</sub>P(C<sub>6</sub>H<sub>5</sub>)<sub>2</sub>]NiCl<sub>2</sub>).</p> <p>Data collected at Diamond Light Source I19-2 on 2015-05-18, publicly available for users to test data reduction routines. Data are known to produce good merging statistics and final refinements.</p> <p>The sample was prepared as follows:<br> Nickel chloride (II) hexahydrate (1 g, 2 mmol) was heated under vacuum to produce anhydrous nickel chloride (II) with a visible colour change from green to yellow. The resulting solid was taken up in ethanol (5 ml) and added to 1,2-bis(dimethylphosphine)ethane (dppe) (0.837 g, 2 mmol) in ethanol (10 ml). The solution was refluxed for 3 hour after which the solvent was evaporated. The small red crystals were purified by recrystallisation in acetone (70% yield).</p> <p>The sample was held at an approximate temperature of 150 K and the illuminating beam had a wavelength of 0.68890 Å (17.997 keV). The detector was held at 2θ = 25° throughout.</p> <p>Inventory of data:<br> <strong>010_Ni_dppe_Cl_2_150K01</strong> — 130° ω scan, 0.4° images, 0.4s per image, 325 images; κ = 45°, φ = 160°.<br> <strong>010_Ni_dppe_Cl_2_150K02</strong> — 130° ω scan, 0.4° images, 0.4s per image, 325 images; κ = 45°, φ = 40°.<br> <strong>010_Ni_dppe_Cl_2_150K03</strong> — 130° ω scan, 0.4° images, 0.4s per image, 325 images; κ = 45°, φ = -80°.<br> <strong>010_Ni_dppe_Cl_2_150K04</strong> — 198° ω scan, 0.4° images, 0.4s per image, 495 images; κ = 0°, φ = -80°.</p>
Multicrystal data of proteinase K collected on the VMXi beamline at the Diamond Light Source, UK
<p>These are a series of datasets which have been collected on the VMXi beamline at the Diamond Light Source, UK. They were collected <em>in-situ</em> at room temperature using a Dectris 2X 4M detector. The datasets were collected in unattended mode using samples preselected using the SynchWeb interface to ISPyB. Each dataset is a 60 degree wedge of data, collected using 1% DMM (double multilayer monochromator) beam (at a wavelength of 0.979A) with an exposure time of 0.002 secs/ frame. These data were merged and have been used in the deposition of a structure to the protein databank.</p>
Lac Croche V-notch weir water flow data collected at the Station de biologie des Laurentides (SBL) de l'Université de Montréal, St-Hippolyte QC
<p>These datasets comprise hourly and daily water flow data collected at the Lac Croche v-notch weir at the Station de biologie des Laurentides (SBL) between 2014/04/01 and 2019/05/01.</p>
Supporting data: "How collective asperity detachments nucleate slip at frictional interfaces"
<p>This repository supports:</p> <p><strong>T.W.J. de Geus, M. Popović, W. Ji, A, Rosso, M. Wyart. How collective asperity detachments nucleate slip at frictional interfaces. Proc. Natl. Acad. Sci. U.S.A. 2019. <a href="https://dx.doi.org/10.1073/pnas.1906551116">doi: 10.1073/pnas.1906551116</a>, <a href="http://arxiv.org/abs/1904.07635">arXiv: 1904.07635</a></strong></p> <p>In particular, it provides all used data, all codes used to produce this data (including clones to all the used open-source libraries), and simple functions to plot the data. All data and code is free to use under the CC-BY-4 license, but: <em>Please cite the above research article</em> when using code or data (inspired) from this repository (or the open-source projects <a href="https://www.github.com/tdegeus/GooseFEM">GooseFEM</a> and <a href="https://www.github.com/tdegeus/GMatElastoPlasticQPot">GMatElastoPlasticQPot</a>), in addition to this dataset (<a href="https://dx.doi.org/10.5281/zenodo.3477938">doi: 10.5281/zenodo.3477938</a>).</p> <p>(c) T.W.J. de Geus | 2019 | contact: <a href="/Volumes/data/dataset/Geus_PNAS/tom%40gems.me">tom@geus.me</a>, <a href="http://www.geus.me">www.geus.me</a></p> <p>This work is licensed under a <a href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a>.</p> <p><strong>Contents</strong></p> <ol> <li>In brief</li> <li>Data files</li> <li>Code</li> <li>Plots</li> </ol> <p><strong>1. In brief</strong></p> <p>All codes (<code>codes/</code>) are written in C++ using a number of open-source libraries (<code>libraries/</code>). All data (<code>data/</code>) is stored in the HDF5 format. All plots (<code>data/</code>) are generated using Python and a number of open-source libraries.</p> <p>All codes are developed and tested on macOS and Linux. The notation used here is consistent with these Unix-based platforms. Windows based compilation and use might differ from the description here.</p> <p><strong>2. Data files ("data/")</strong></p> <p>The different ensembles (datasets) are included in different directories in <code>data/</code>. They are distinguished through their directory name that comprises the system size (denoted <code>nx=...</code>) and the shape factor of the Weibull distribution from which the yield strains are drawn (denoted <code>weibull=...</code>).</p> <p>Each ensemble consists of a number of realisations of the random yield strains at the frictional interface. Each realisation is stored in a separate file (<code>id=xxx.hdf5</code>). This file serves as input for the event-driven code (<code>code/Run/main.cpp</code>). This code stores the displacement field at the end of each event-driven step (for which it may take significant time for energy to be minimised). With these displacement fields, all other quantities (stress, strain, plastic strain, ...) can be reconstructed. The relevant reconstructed data for the entire ensemble is collected in <code>EnsembleInfo.hdf5</code>.</p> <p>For the manually triggered avalanches at different stresses (and fixed relative strain increment w.r.t. the last system spanning event) only selected output is stored to limit storage usage (<code>code/AvalancheAfterPush...</code>). Please note that the simulations are stopped when an event becomes system spanning to save on computation time, for this case the output thus does not correspond to a state of mechanical equilibrium. By contrast, any simulation that was not system-spanning does correspond to a state of mechanical equilibrium.</p> <p><strong>2a. Realisation ("data/.../id=xxx.hdf5")</strong></p> <p>See code <code>code/Run/main.cpp</code> and generation <code>code/Generate/generate.py</code></p> <ul> <li>Mesh (input)<br> <ul> <li><code>/coor</code>: Nodal coordinates <code>[nnode, ndim]</code> (<code>ndim == 2</code>)</li> <li><code>/conn</code>: Connectivity <code>[nelem, nne]</code> (<code>nne = 4</code>)</li> <li><code>/dofs</code>: Degrees-of-freedom (DOF) per node <code>[nnode, ndim]</code></li> <li><code>/iip</code>: Prescribed DOFs <code>[n_iip]</code><br> </li> </ul> </li> <li>Material model (input)<br> <ul> <li><code>/elastic/elem</code>: Elastic elements <code>[n_elasic]</code></li> <li><code>/elastic/G</code>: Shear modulus <code>[n_elasic]</code></li> <li><code>/elastic/K</code>: Bulk modulus <code>[n_elasic]</code></li> <li><code>/cusp/elem</code>: Elasto-plastic elements <code>[n_cusp]</code></li> <li><code>/cusp/G</code>: Shear modulus <code>[n_cusp]</code></li> <li><code>/cusp/K</code>: Bulk modulus <code>[n_cusp]</code></li> <li><code>/cusp/epsy</code>: Yield strains <code>[n_cusp, n_potentials]</code></li> <li><code>/uuid</code>: Unique identifier for the realisation<br> <br> Note that <code>n_elasic + n_cusp == nelem</code><br> </li> </ul> </li> <li>Simulation (input)<br> <ul> <li><code>/alpha</code>: Background damping coefficient <code>[nelem]</code> (homogeneous)</li> <li><code>/rho</code>: Mass density <code>[nelem]</code> (homogeneous)</li> <li><code>/run/dt</code>: Time-step</li> <li><code>/run/epsd/kick</code>: Size of the strain kick</li> <li><code>/run/epsd/max</code>: Local strain at which to stop<br> </li> </ul> </li> <li>Output<br> <ul> <li><code>/completed</code>: Completion signal, emitted when <code>/run/epsd/max</code> was reached locally</li> <li><code>/stored</code>: Stored event-driven step numbers <code>[n_event]</code></li> <li><code>/t</code>: Time at the end of each event-driven step <code>[n_event]</code></li> <li><code>/kick</code>: Strain kick (yes/no) per event-driven step <code>[n_event]</code></li> <li><code>/disp/...</code>: Nodal displacements per event-driven step <code>[nnode, ndim]</code></li> </ul> </li> </ul> <p><strong>2b. Simulation output ("data/.../EnsembleInfo.hdf5")</strong></p> <p>See code and help <code>code/EnsembleInfo/main.cpp</code>.</p> <p><strong>2c. Distribution P(x) ("data/.../EnsembleYieldDistance*.hdf5")</strong></p> <p>See code and help <code>code/EnsembleYieldDistance_stressControl/main.cpp</code> and <code>EnsembleYieldDistance_strainControl/main.cpp</code>.</p> <p><strong>2d. Manual triggering of events ("data/.../AvalancheAfterPush*.hdf5")</strong></p> <p>See code and help <code>code/AvalancheAfterPush_stressControl/main.cpp</code> and <code>code/AvalancheAfterPush_strainControl/main.cpp</code>.</p> <p><strong>3. Code ("code/")</strong></p> <p>The relevant codes to generate the datasets are referenced above. All non-standard libraries have been cloned under <code>libraries/</code>. Please note that they are subject to evolution: their cloned versions allow one to rerun the code in this dataset, however, for further development one is strongly encouraged to use the latest version. Please check out the development of:</p> <ul> <li><a href="https://github.com/tdegeus/GooseFEM.git">GooseFEM (v0.2.3)</a></li> <li><a href="https://github.com/tdegeus/GMatElastoPlasticQPot.git">GMatElastoPlasticQPot (v0.2.1)</a></li> <li><a href="https://github.com/tdegeus/cpppath.git">cpppath (v0.0.7)</a></li> <li><a href="https://github.com/xtensor-stack/xtensor.git">xtensor (v0.20.8)</a></li> <li><a href="https://github.com/xtensor-stack/xtensor-blas.git">xtensor-blas (v0.16.1)</a></li> <li><a href="https://github.com/xtensor-stack/xtl.git">xtl (v0.6.5)</a></li> <li><a href="https://github.com/xtensor-stack/xsimd.git">xsimd (v7.2.5)</a></li> <li><a href="https://github.com/BlueBrain/HighFive.git">highfive (master)</a></li> <li><a href="https://github.com/docopt/docopt.git">docopt (master)</a></li> <li><a href="https://github.com/fmtlib/fmt.git">fmt (master)</a></li> <li><a href="https://github.com/tdegeus/pyxtensor.git">pyxtensor (v0.0.5)</a></li> <li><a href="https://github.com/tdegeus/GooseMPL.git">GooseMPL (v0.2.24)</a></li> <li><a href="https://github.com/tdegeus/GooseEYE.git">GooseEYE (v0.2.0)</a></li> <li><a href="https://github.com/h5py/h5py.git">h5py (master)</a></li> </ul> <p>To compile code, follow the following structure:</p> <pre>cd code/... mkdir build cmake .. make</pre> <p>Then to run use:</p> <pre>./Run ...</pre> <p>(use <code>./Run --help</code> for help, and/or read the code). For some codes a support function generates commands. They can be generated and run as follows:</p> <pre>python makeJob.py source commands.txt</pre> <p><strong>4. Plots ("data/.../*.py")</strong></p> <p>Basic plot functions are included with the datasets. Note that all scripts require <code>numpy</code>, <code>matplotlib</code>, <code>h5py</code>, and <code>GooseMPL</code> to be installed. The latter two are included here, the other two are considered standard.</p>
Tracer gas (SF6 and Xe) migration data collected in 2018 as a part of the Diffusion experiment
<p>The dataset contains the results of the gas sampling performed following two injections of a mixture of the tracer gases (SF<sub>6</sub> and Xe). Two tracer gas injections were conducted in 2018 in Carroll, New Hampshire. Tracer gas injections were performed beneath the water table in two chemical-explosion generated cavities to compare the migration of sulfur hexafluoride (SF<sub>6</sub>) and xenon (Xe) through an explosion-generated fracture network and to study the influence of ground water on gas transport. A mixture of tracer gases (50% of SF<sub>6</sub> and 50% of Xe) was injected into each cavity. The first gas injection took place on September 8, 2018 and gas sampling continued until September 20, 2018. The second injection was performed on October 31, 2018 and gas sampling continued until November 8, 2018. The data were collected using an automatic sampling system. The data analysis was performed by using a gas chromatograph (Shimadzu GC-8A) with a Thermal Conductivity Detector (TCD). The gas concentrations measured at the surface from 4 sampling locations are provided.</p> <p>In addition, we provide measurements of the barometric pressure and temperature recorded using an Onset HOBO pressure transducer placed in the vicinity of the injection site approximately 1 m above ground and collecting pressure and temperature samples every 15 minutes for the duration of the experiment. The pressure and temperature data is provided in Tables S2 and S4.</p> <p> </p>
SNP data for the SwAsp collection
<p>DNP data for 94 individuals from the SwAsp collection, described in Luquez et al. (2008). Details about sequencing and SNP calling can be found in Wang et al. (2018). Data is mapped agains the <em>P. tremula </em>genome assembly v1.1(Lin et al. 2018).</p> <p><strong>References</strong></p> <p><strong><strong><strong>Lin Y-C</strong>, <strong>Wang J</strong>, <strong>Delhomme N</strong>, <strong>Schiffthaler B</strong>, <strong>Sundström G</strong>, <strong>Zuccolo A</strong>, <strong>Nystedt B</strong>, <strong>Hvidsten TR</strong>, <strong>de la Torre A</strong>, <strong>Cossu RM</strong>, <em>et al.</em></strong></strong> <strong>2018</strong>. Functional and evolutionary genomic inferences in Populus through genome and population sequencing of American and European aspen. <em>Proceedings of the National Academy of Sciences of the United States of America</em> <strong>115</strong>: E10970–E10978.</p> <p><strong><strong>Luquez V</strong>, <strong>Hall D</strong>, <strong>Albrectsen BR</strong>, <strong>Karlsson J</strong>, <strong>Ingvarsson P</strong>, <strong>Jansson S</strong></strong>. <strong>2008</strong>. Natural phenological variation in aspen (<em>Populus tremula</em>): the SwAsp collection. <em>Tree Genetics & Genomes</em> <strong>4</strong>: 279–292.</p> <p><strong><strong><strong>Wang J</strong>, <strong>Ding J</strong>, <strong>Tan B</strong>, <strong>Robinson KM</strong>, <strong>Michelson IH</strong>, <strong>Johansson A</strong>, <strong>Nystedt B</strong>, <strong>Scofield DG</strong>, <strong>Nilsson O</strong>, <strong>Jansson S</strong>, <em>et al.</em></strong></strong> <strong>2018</strong>. A major locus controls local adaptation and adaptive life history variation in a perennial plant. <em>Genome Biology</em> <strong>19</strong>: 72.</p>
TLS 1.3 Handshake Data Collected By Lumen
<p>The data file <code>ccr_tls_release.csv.xz</code> contains handshake records and extension information from the TLS connections from the Lumen dataset up to early November 2019.</p>
Text-fig. 5. Size comparison of lion p4 and m1 from Za Hájovnou Cave with close relative forms from European sites (black: Panthera fossilis, grey: Panthera cf. fossilis or Panthera fossilis – spelaea; f = female, old c. = old collection). Data source: Wojtusiak 1953, Thenius 1972, Schütt and Hemmer 1978, Argant 1988, 1991, García 2003, Baryshnikov and Tsoukala 2010). in Panthera Fossilis (Reichenau, 1906) (Felidae, Carnivora) From Za Hájovnou Cave (Moravia, The Czech Republic): A Fossil Record From 1987-2007
Text-fig. 5. Size comparison of lion p4 and m1 from Za Hájovnou Cave with close relative forms from European sites (black: Panthera fossilis, grey: Panthera cf. fossilis or Panthera fossilis – spelaea; f = female, old c. = old collection). Data source: Wojtusiak 1953, Thenius 1972, Schütt and Hemmer 1978, Argant 1988, 1991, García 2003, Baryshnikov and Tsoukala 2010).
Fig. 11. Plectanocotyle jeanloujustinei n in "Something old, something new, something borrowed, and the oioxeny is true": description of Plectanocotyle jeanloujustinei n. sp. (Polyopisthocotylea, Plectanocotylidae) from the MNHN Helminthology collection with novel molecular and morphological data for P. gurnardi (Van Beneden & Hesse, 1863) (sensu stricto) from Sweden
Fig. 11. Plectanocotyle jeanloujustinei n. sp. ex Chelidonichthys lastoviza from the western Mediterranean. Detail of the reproductive organs in the region of ovary, ventral view (HEL 1715).
Fig. 10. Plectanocotyle jeanloujustinei n in "Something old, something new, something borrowed, and the oioxeny is true": description of Plectanocotyle jeanloujustinei n. sp. (Polyopisthocotylea, Plectanocotylidae) from the MNHN Helminthology collection with novel molecular and morphological data for P. gurnardi (Van Beneden & Hesse, 1863) (sensu stricto) from Sweden
Fig. 10. Plectanocotyle jeanloujustinei n. sp. ex Chelidonichthys lastoviza from the western Mediterranean. Disposition of clamps sclerites. A, Dorsal jaw. B, Ventral jaw. C, Clamp, dorsal view (HEL 1713).
Fig. 9. Plectanocotyle jeanloujustinei n in "Something old, something new, something borrowed, and the oioxeny is true": description of Plectanocotyle jeanloujustinei n. sp. (Polyopisthocotylea, Plectanocotylidae) from the MNHN Helminthology collection with novel molecular and morphological data for P. gurnardi (Van Beneden & Hesse, 1863) (sensu stricto) from Sweden
Fig. 9. Plectanocotyle jeanloujustinei n. sp. ex Chelidonichthys lastoviza from the western Mediterranean. A, Body, holotype, ventral view (HEL 1721). B, Clamp, hologenophore, ventral view (HEL 1731). C, Clamp, paratype, dorsal view (HEL 1717). D, terminal lappet, paratype (HEL 1717). E, Anterior end showing male copulatory organ, paratype, ventral view (HEL 1720). F, Egg, paratype (HEL 1714).
Fig. 4 in "Something old, something new, something borrowed, and the oioxeny is true": description of Plectanocotyle jeanloujustinei n. sp. (Polyopisthocotylea, Plectanocotylidae) from the MNHN Helminthology collection with novel molecular and morphological data for P. gurnardi (Van Beneden & Hesse, 1863) (sensu stricto) from Sweden
Fig. 4. Tree inferred using the ML method based on the cox1 sequence data; only bootstrap values higher than 70 are indicated. The newly generated sequences of Plectanocotyle gurnardi sensu stricto are indicated in blue. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 8 in "Something old, something new, something borrowed, and the oioxeny is true": description of Plectanocotyle jeanloujustinei n. sp. (Polyopisthocotylea, Plectanocotylidae) from the MNHN Helminthology collection with novel molecular and morphological data for P. gurnardi (Van Beneden & Hesse, 1863) (sensu stricto) from Sweden
Fig. 8. Plectanocotyle gurnardi (Van Beneden and Hesse, 1863) sensu stricto ex Eutrigla gurnardus from the North Sea, Sweden, Detail of the reproductive organs in the region of ovary, ventral view (SMNH 216584).
Fig. 5 in "Something old, something new, something borrowed, and the oioxeny is true": description of Plectanocotyle jeanloujustinei n. sp. (Polyopisthocotylea, Plectanocotylidae) from the MNHN Helminthology collection with novel molecular and morphological data for P. gurnardi (Van Beneden & Hesse, 1863) (sensu stricto) from Sweden
Fig. 5. Tree inferred using the ML method based on the 28S rDNA sequence data; only bootstrap values higher than 70 are indicated. The newly generated sequences are indicated in bold. All sequences of Plectanocotyle gurnardi from the type-host Eutrigla gurnardus clustered in a single clade. * The polyopisthocotylean parasite annotated on GenBank as "Plectanocotyloides obscurum"; the host as "Aspitrigla obscura".
Fig. 3. Plectanocotyle jeanloujustinei n in "Something old, something new, something borrowed, and the oioxeny is true": description of Plectanocotyle jeanloujustinei n. sp. (Polyopisthocotylea, Plectanocotylidae) from the MNHN Helminthology collection with novel molecular and morphological data for P. gurnardi (Van Beneden & Hesse, 1863) (sensu stricto) from Sweden
Fig. 3. Plectanocotyle jeanloujustinei n. sp. ex Chelidonichthys lastoviza from the western Mediterranean (Algeria), hologenophores. A-E, Body lacking only the haptor. F. Body lacking a lateral part posterior part. G-H, anterior end of the body including the male copulatory organ. The missing parts were excised and used for DNA extraction. A, (HEL1729). B, (HEL1730). C, (HEL1732). D, (HEL1733). E, (HEL1734). F, (HEL1731). G, (HEL1727). H, (HEL17287).
Fig. 2 in "Something old, something new, something borrowed, and the oioxeny is true": description of Plectanocotyle jeanloujustinei n. sp. (Polyopisthocotylea, Plectanocotylidae) from the MNHN Helminthology collection with novel molecular and morphological data for P. gurnardi (Van Beneden & Hesse, 1863) (sensu stricto) from Sweden
Fig. 2. Plectanocotyle gurnardi (Van Beneden and Hesse, 1863) sensu stricto ex Eutrigla gurnardus from the North Sea, Sweden, hologenophores, body lacking only a lateral part; excised used for DNA extraction A, (SMNH 216644). B, (SMNH 216645). C, (SMNH 216646).
Fig. 1 in "Something old, something new, something borrowed, and the oioxeny is true": description of Plectanocotyle jeanloujustinei n. sp. (Polyopisthocotylea, Plectanocotylidae) from the MNHN Helminthology collection with novel molecular and morphological data for P. gurnardi (Van Beneden & Hesse, 1863) (sensu stricto) from Sweden
Fig. 1. One of the unstudied specimens of Plectanocotyle gurnardi (Van Beneden and Hesse, 1863) from the type-host Eutrigla gurnardus available for study before this paper, and that hinted the presence of Plectanocotyle gurnardi in Swedish waters of the North Sea. The slide containing two specimens of Plectanocotyle gurnardi labeled as "Phyllocotyle gurnardi": unstudied specimens collected by Theodor Odhner from the gills of Eutrigla gurnardus from Kristineberg, Sweden, Northeast Atlantic.
Fig. 6 in "Something old, something new, something borrowed, and the oioxeny is true": description of Plectanocotyle jeanloujustinei n. sp. (Polyopisthocotylea, Plectanocotylidae) from the MNHN Helminthology collection with novel molecular and morphological data for P. gurnardi (Van Beneden & Hesse, 1863) (sensu stricto) from Sweden
Fig. 6. Plectanocotyle gurnardi (Van Beneden and Hesse, 1863) sensu stricto ex Eutrigla gurnardus from the North Sea, Sweden. A, Body, ventral view (SMNH 216639). B, Clamp, ventral view (SMNH 216593). C, Anterior end showing male copulatory organ, ventral view (SMNH 216586). D, Egg, (SMNH 216594).
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.