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.
1,454
datasets available to search
ShareScore release 0.9.0
Dataset results
1,454 results for “large scale”
Figure 3 in Lessons learnt from large-scale eradication of Australian swamp stonecrop Crassula helmsii in a protected Natura 2000 site
Figure 3. Photo impressions of the large scale eradication of Crassula helmsii on the Island of Terschelling. A. The dominant infestation of C. helmsii in an artificial lake (location 5). B. Installing a mitigation fence in order to prevent entry by amphibians and reptiles (2.75 linear km). C. Drainage installation and steel road plates tracks. D. Excavation of 40 cm topsoil (Step 4 of the described eradication approach). E. Recolonization of characteristic native plant species in excavated area 2.5 years after the eradication of C. helmsii (March 2021). F. Guided tours in the study area to inform those concerned.
Figure 1 in Lessons learnt from large-scale eradication of Australian swamp stonecrop Crassula helmsii in a protected Natura 2000 site
Figure 1. Locations of the dune slacks (1–5) where measures for eradication of Crassula helmsii were taken.
Figure 2 in Lessons learnt from large-scale eradication of Australian swamp stonecrop Crassula helmsii in a protected Natura 2000 site
Figure 2. Flow chart of the process for large scale eradication of Crassula helmsii on the Island of Terschelling.
Linking the microarchitecture of neurotransmitter systems to large-scale MEG resting state networks
<p>Information processing and communication in neuronal circuits is enabled by dynamic networks of inter-areal coupling of neuronal oscillations in which hubs play a central role for regulation of communication. Oscillations are shaped by interactions between pyramidal cells and interneurons and are locally influenced by neuromodulatory systems. Here, we set out to investigate how sparial variability in neurotransmitter receptor and transporter density influences frequency-specific large-scale networks of phase-synchrony (PS) and amplitude-correlation (AC) in human magnetoencephalography data. We found that node centrality - indexing which individual brain regions function as hubs - covaried positively with GABA, NMDA, dopaminergic, and most serotonergic receptor and transporter densities in lower frequency bands (delta to low-alpha for PS, and delta for AC) and in the gamma band, but negatively in between. These results establish how local microarchitecture influences large-scale connectivity networks of neuronal oscillations in the human brain in frequency- and spatially-specific patterns.</p>
A Large-Scale Sensitivity Analysis on Latent Embeddings and Dimensionality Reductions for Text Spatializations
<p>Result Files for the Paper "A Large-Scale Sensitivity Analysis on Latent Embeddings and Dimensionality Reductions for Text Spatializations" to be published at IEEE Vis 2024</p>
Database: Influence of large-scale freestream turbulence on bypass transition in air and organic vapour flows
<p>This is an open-access database of numerical simulations of freestream-turbulence induced transitions of zero-pressure-gradient flat plates boundary layers. The data have been collected at Arts et Metiers Institute of Technology, at DynFluid laboratory, in the period 2021-2024 within the REGAL-ORC project- REal GAs effects on Loss mechanisms of ORC turbine flows, a project in collaboration with FH Münster in Germany.</p> <p>Work related to the database is published in Journal of Fluid Mechanics, under the title: "Influence of large-scale freestream turbulence on bypass transition in air and organic vapour flows". The aims of this work was to investigate freestream-turbulence induced transitions, in particular under relatively large integral length scale, of air and organic vapors boundary layers.</p> <p>This version contains evolutions of averaged quantities in the streamwise direction, along with profiles and spectra in the boundary layer for all the different simulations performed. This database is supplemented with python codes to read the data and descriptions of the data in the headers and README files.</p>
Multi-modal image analysis for large scale cancer tissue studies within IMMUcan: multiplex immunofluorescence images
<p>In cancer research, multiplexed imaging has enabled the in-depth characterization of the tumor microenvironment (TME) and how it relates to patient prognosis. However, standardized, multi-modal data from large numbers of patients to identify robust biomarkers is missing. To provide such data across five cancer indications, the IMMUcan consortium performs broad molecular and cellular spatial profiling of thousands of cancer samples. Two reproducible and scalable workflows have been developed for whole slide multiplexed immunofluorescence (mIF) and imaging mass cytometry (IMC) to overcome challenges of reproducibility and scalability. For mIF we developed IFQuant, a web-based tool optimized for user-friendliness and reproducibility. This Zenodo record contains the mIF images and IFQuant settings to reproduce the results presented in the referenced publication. The companion IMC dataset is available as a joint Zenodo record.</p>
Deprecated Dataset for "Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior"
<p>This dataset is deprecated. <strong>The updated version of this Dataset is here:</strong> <a href="https://zenodo.org/record/3678559#.Xl9-Ji97FhE">https://zenodo.org/record/3678559#.Xl9-Ji97FhE</a></p> <p>Dataset for the publication "Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior". Antigoni-Maria Founta, Constantinos Djouvas, Despoina Chatzakou, Ilias Leontiadis, Jeremy Blackburn, Gianluca Stringhini, Athena Vakali, Michael Sirivianos and Nicolas Kourtellis. International AAAI Conference on Web and Social Media (ICWSM), 2018.</p> <p>The dataset provided here includes an updated version of the original dataset, with ~100k tweets annotated using the CrowdFlower platform:</p> <ul> <li>hatespeech_labels.csv: contains ~100k rows, where every row consists of a unique Tweet ID and its associated majority annotation</li> </ul> <p><em>UPDATE</em>: It has come to our understanding that a number of the tweets are not available anymore for download on Twitter. Therefore, <strong>upon request</strong>, we can provide one more file with the full ~100k tweet text and their associated majority labels. The tweets are shuffled so that there is no connection between tweet IDs and texts (in order to be aligned with the T&C of Twitter).</p> <p>To obtain the file contact a.m.founta at gmail dot com <strong>AND </strong>antonis26papa at gmail dot com.</p> <p><em>Please cite the paper in any published work that uses any of these resources.</em></p> <blockquote> <p>@inproceedings{founta2018large,<br> title={Large Scale Crowdsourcing and Characterization of Twitter Abusive Behavior},<br> author={Founta, Antigoni-Maria and Djouvas, Constantinos and Chatzakou, Despoina and Leontiadis, Ilias and Blackburn, Jeremy and Stringhini, Gianluca and Vakali, Athena and Sirivianos, Michael and Kourtellis, Nicolas},<br> booktitle={11th International Conference on Web and Social Media, ICWSM 2018},<br> year={2018},<br> organization={AAAI Press}<br> }</p> </blockquote> <p>For any further questions contact a.m.founta at gmail dot com.</p> <p> </p> <p>Publication DOI: <a href="https://doi.org/10.5281/zenodo.1443348">https://doi.org/10.5281/zenodo.1443348</a></p> <p>Github: <a href="https://github.com/ENCASEH2020/hatespeech-twitter">https://github.com/ENCASEH2020/hatespeech-twitter</a></p>
Influence of storm sequencing and beach recovery on sediment transport and beach resilience data set at CIEM large scale wave flume.
<p>The Influence of storm sequencing and beach recovery on sediment transport and beach resilience (RESIST) experiments project proposes to study experimentally sequences of storm induced erosion and beach recovery, with a particular focus on the poorly known morphodynamic processes under low energy conditions. Series of large scale experimental tests were done to collect data on the cross-shore hydrodynamics, sediment transport and beach evolution. The main aim of this proposal is to investigate the influence of sequences of beach erosion-recovery in the overall beach profile evolution.</p> <p>The tested wave conditions (2 erosive and 3 Accretive bichromatic conditions) were combined to form three sequences of changing high/mild energy conditions. Each condition started from an initial beach 1/15 handmade profile.</p> <p>The experiments were carried out in the large scale wave flume CIEM at Universitat Politècnica de Catalunya (UPC), Barcelona within the program of Transnational Access of Hydralab+.</p> <p>Due to its size, the data set can not be placed on this repository and will be provided on demand. Please contact with the authors or with the data manager of the CIEM installation.</p>
Ripple Complex Experiments data set at CIEM large scale wave flume within Hydralab + project.
<p>The RIPCOM experiments (RIPple COMplex experiments) are presented in order to study the ripple growth conditions on large wave flume tests under fine unimodal, coarse unimodal and mixed sands conditions. The main objectives of the experiments is to improve and understand the protocols to perform mixed sediment experiments within the ripple regime and use/improve the equipment developed at Task 9.1 of the COMPLEX Joint Research Activity within Hydralab+. The experiments were carried out in the large scale wave flume CIEM at Universitat Politècnica de Catalunya (UPC), Barcelona.</p> <p>The experimental plan is divided in three steps:</p> <p>1. Find the optimum wave conditions that ensure ripples (based on measured velocities and previous literature studies) on the study area. Test the targeted waves with unimodal fine sediment (d 50 =0.250 mm) and measure the obtained ripples under the tested conditions. From the obtained measurements, the waves to be used on the next two steps are selected in order to fix the best conditions to produce ripples within the experimental constrains.</p> <p>2. The 13 upper cm of the fine sediment is removed and replaced by the coarser sediment (d 50 =0.545 mm). Once that is done the selected waves to be tested are reproduced and the bottom bedforms are measured.</p> <p>3. Mix both sediments fine and coarser sand homogeneously in order to repeat the selected wave conditions and measure the ripples growth and evolution under mixed sediment conditions.</p> <p>Due to its size, the data set can not be placed on this repository and will be provided on demand. Please contact with the authors or with the data manager of the CIEM installation.</p>
Large-scale and fine-grained phenological stage annotation of herbarium specimens datasets
<p>This upload is constituted of four datasets of specimens from American herbaria covering different levels of information precision and different floras - from temperate to equatorial.</p> <p>Three of these datasets consist of selected specimens from herbaria located in different geographic and environmental regions. Each specimen of these three datasets was annotated with the following fields: family, genus, species name, fertile / non-fertile, presence / absence of flower(s), presence / absence of fruit(s). The resulting dataset was composed of 163,233 herbarium specimens belonging to 7,782 species, 1,906 genera, and 236 families. Specimens were annotated as “fertile” if any reproductive structures were present, such as sporangia (ferns), cones (gymnosperms), flowers, or fruits (angiosperms). Non-fertile specimens were those that lacked any reproductive structures.</p> <p>The fourth dataset consists of 20,371 herbarium specimens from 11 genera in the sunflower family (<em>Asteraceae</em>). The main difference in this dataset is that it is annotated with fine-grained phenophase scores rather than presence/absence attributes (see description below).</p> <p>Each of these datasets is described below:</p> <ul> <li> <p>NEVP: this dataset of New England vascular plant (NEVP) specimens was produced by members of the Consortium of Northeastern Herbaria. The dataset comprises 42,658 digitized specimens that belong to 1,375 species and come from several North American institutions. Most of the specimens in this dataset are from the north-temperate region of the northeastern United States.</p> </li> <li> <p>FSU: this dataset was produced by the Florida State University's Robert K. Godfrey Herbarium (FSU), a collection that focuses on northern Florida and the U.S. Southeast Coastal Plain, one of North America's biodiversity hotspots. This dataset contains 54,263 digitized herbarium specimen records that belong to 3,870 species, making it the taxonomically richest dataset in this study. Most species in this dataset grow under subtropical or warm temperate conditions in the southeastern region of the United States.</p> </li> <li> <p>CAY: this dataset comes from the IRD’s Herbarium of French Guiana (CAY). CAY is dedicated to the Guayana Shield flora, with a strong focus on tropical tree species. This dataset is composed of 66,312 herbarium specimens that belong to 3,024 species. All digitized specimens of this herbarium are accessible online. Most specimens were collected in the tropical rainforests of French Guiana, with the remaining specimens coming mostly from Suriname and Guyana.</p> </li> <li> <p>PHENO: this dataset includes 20,371 herbarium specimens of 139 species in the <em>Asteraceae</em> produced in a study of phenological trends in the U.S. Southeast Coastal Plain. The dataset is composed of specimen records from 57 herbaria. Each recorded specimen was annotated for quartile percentages (0, 25, 50, 75, or 100%) of (i) closed buds, (ii) buds transformed into flowers, and (iii) fruits. According to the distribution of these three categories for each specimen, a phenophase code was computed.</p> </li> </ul> <p> </p> <p><strong>Datasets format</strong></p> <p>These datasets are grouped in 3 tasks:</p> <ol> <li>fertility detection</li> <li>flowers and/or fruit detection</li> <li>phenophase classification</li> </ol> <p>The first 2 tasks are carried on the first 3 previous datasets and thus are based on the same set of images, unlike the third task which has its own disjoint set of images. This is why the dataset is presented into two separated files, one for each set of images.</p> <p><em>Fertility detection & flower/fruit detection</em></p> <p>These tasks are contained into the <em>herbarium_fertility_annotations.zip</em> archive. It consists of 3 files:</p> <ul> <li><em>metadata.csv</em>: general information about all the herbarium specimens for these tasks <ul> <li><em>id</em>: specimen identifier</li> <li><em>collection</em>: which of NEVP, FSU or CAY does the specimen come from</li> <li><em>herbarium</em>: institution of origin of the specimen, especially for NEVP collection</li> <li><em>clade</em>,<em> family</em>,<em> genus</em>,<em> species</em>: classification of the specimen</li> <li><em>URL</em>: URL of the scan</li> </ul> </li> <li><em>fertility_task.csv</em>: specific information regarding the fertility detection task <ul> <li><em>id</em>: specimen identifier</li> <li><em>is_fertile</em>: <em>True</em> if the specimen has an expression of fertility, <em>False</em> otherwise</li> <li><em>train_test_set</em>: which subset does the specimen belong to; possible values are: <em>train</em>, <em>random_test</em>, <em>species_test</em> and <em>herbarium_test</em></li> </ul> </li> <li><em>flower_fruit_task.csv</em>: specific information regarding the flower/fruit detection task <ul> <li><em>id</em>: specimen identifier, note that in this case not all the specimen described in <em>metadata.csv</em> are included in this task</li> <li><em>has_flower</em>: <em>True</em> if the specimen has at least one flower, <em>False</em> otherwise</li> <li><em>has_fruit</em>: <em>True</em> if the specimen has at least one fruit, <em>False</em> otherwise</li> <li><em>train_test_set</em>: which subset does the specimen belong to; possible values are: <em>train</em>, <em>random_test</em>, <em>species_test</em> and <em>herbarium_test</em></li> </ul> </li> </ul> <p><em>Phenophase classification</em></p> <p>These tasks are contained into the <em>herbarium_asteraceae_phenophase_annotations.zip</em> archive. It consists of a single file:</p> <ul> <li><em>annotations.csv</em>: <ul> <li><em>id</em>: specimen identifier</li> <li><em>URL</em>: URL of the scan</li> <li><em>genus</em>: genus of the specimen</li> <li><em>phenophase</em>: integer from 1 to 9 describing the phenophase of the specimen</li> <li><em>train_test_set</em>: which subset does the specimen belong to; possible values are: <em>train</em> and <em>test</em></li> </ul> </li> </ul> <p> </p> <p><strong>Additional ressources</strong></p> <p>More information can be found in the related paper:<br> <em>Lorieul, T., K. D. Pearson, E. R. Ellwood, H. Goëau, J.-F. Molino, P. W. Sweeney, J. M. Yost, J. Sachs, E. Mata-Montero, G. Nelson, P. S. Soltis, P. Bonnet, and A. Joly. 2019. Toward a large-scale and deep phenological stage annotation of herbarium specimens: Case studies from temperate, tropical, and equatorial floras. Applications in Plant Sciences 7(3): e1233.</em></p> <p>For an example of usage of these datasets as well as a baseline, see: <a href="http://doi.org/10.5281/zenodo.2549996">http://doi.org/10.5281/zenodo.2549996</a></p> <p> </p>
FIG. 3. — Microphotina viridula n in Les mantes (Dictyoptera, Mantodea) du massif du Mitaraka (Guyane), in Touroult J. (ed.), "Our Planet Reviewed" 2015 large-scale biotic survey in Mitaraka, French Guiana.
FIG. 3. — Microphotina viridula n. sp., holotype mâle: A, vue dorsale; B, vue ventrale de l'avant-corps; C, étiquettes. Échelles: A, 1 cm; B, 5 mm. Photos M. Depraetere.
FIG. 4. — Microphotina viridula n in Les mantes (Dictyoptera, Mantodea) du massif du Mitaraka (Guyane), in Touroult J. (ed.), "Our Planet Reviewed" 2015 large-scale biotic survey in Mitaraka, French Guiana.
FIG. 4. — Microphotina viridula n. sp.: A, plaque sous-génitale d'un paratype; B, genitalia de l'holotype en vue ventrale avec en plus grand l'apex de l'épiphallus gauche (D) et sa variabilité chez un paratype (C). Échelles: A, B, 1 mm; C, D, 0,5 mm.
Large scale experiments for an alternative erosion control measure using sand-filled geosystems. Data set produced at the CIEM flume, Hydralab+
<p>Sand-filled geosystems have the potential to mimic aspects of natural and nature-based features that can enhance the resilience of coastal areas challenged by climate, with additional (structural) reinforcement.</p> <p>Knowledge gaps can be identified. For instance, (i) the sediment transport mechanisms around the geosystem; (ii) the amount of erosion in the leeside when the system is overtopped; (iii) quantitative contribution the geosystem for the wave overtopping reduction; and (iv) failure mechanisms of the geosystem under extreme conditions. Specific tests are proposed in order to fill the defined knowledge gap and answer the following research questions:</p> <ol> <li>How do nearshore coastal processes (wave transformation, sediment transport) and wave structure interactions during extreme events differ from those during more usual big storm conditions for situations with and without the geosystem?</li> <li>How do feedbacks between the hydrodynamics and morphology of natural and nature-based features affect flooding, erosion, and recovery of coastal areas when erosion is limited by the 'geosystem'?</li> <li>How to conceive a dynamic coastal protection that can easily adapt to climate change in areas experiencing coastal squeeze (i.e. dense urban environment and human infrastructure with sea encroaching land) and vulnerable to coastal erosion and flooding risks?</li> </ol> <p>The set of experiments, done at the large wave Flume (CIEM) in Barcelona, are here described in order to answer the previous questions. These experiments started on October 2018 and ended at the end of November 2018. These tests include different configurations:<br>an initial benchmark tests in order to test the wave conditions were no geosystem protection is used, a second layout with a geotube used as a geosystem protection and finally a third layout were geobags are used as a protection.</p>
Large scale experiments for an alternative erosion control measure using sand-filled geosystems. Data set produced at the CIEM flume, Hydralab+
<p>Sand-filled geosystems have the potential to mimic aspects of natural and nature-based features that can enhance the resilience of coastal areas challenged by climate, with additional (structural) reinforcement.</p> <p>Knowledge gaps can be identified. For instance, (i) the sediment transport mechanisms around the geosystem; (ii) the amount of erosion in the leeside when the system is overtopped; (iii) quantitative contribution the geosystem for the wave overtopping reduction; and (iv) failure mechanisms of the geosystem under extreme conditions. Specific tests are proposed in order to fill the defined knowledge gap and answer the following research questions:</p> <ol> <li>How do nearshore coastal processes (wave transformation, sediment transport) and wave structure interactions during extreme events differ from those during more usual big storm conditions for situations with and without the geosystem?</li> <li>How do feedbacks between the hydrodynamics and morphology of natural and nature-based features affect flooding, erosion, and recovery of coastal areas when<br> erosion is limited by the 'geosystem'?</li> <li>How to conceive a dynamic coastal protection that can easily adapt to climate change in areas experiencing coastal squeeze (i.e. dense urban environment and human infrastructure with sea encroaching land) and vulnerable to coastal erosion and flooding risks?</li> </ol> <p>The set of experiments, done at the large wave Flume (CIEM) in Barcelona, are here described in order to answer the previous questions. These experiments started on October 2018 and ended at the end of November 2018. These tests include different configurations: an initial benchmark tests in order to test the wave conditions were no geosystem protection is used, a second layout with a geotube used as a geosystem protection and finally a third layout were geobags are used as a protection.</p>
Pelvic arcade and vertebral structure of the second chief specimen of Tyrannosaurus rex, Amer. Mus. 5027, discovered in 1908. An orthogonal projection executed on a very large scale and reproduced one-twelfth natural size. C 1-C 10 cervical series, D 1-D 13 dorsal or thoracic series, S 1-S 5 sacral series, Cd 1- Cd 53 caudal series. The caudals actually preserved are shaded; those drawn in outline are conjectural and restored. The total number of caudals is conjectural. in Skeletal Adaptations of Ornitholestes, Struthiomimus, Tyrannosaurus
Pelvic arcade and vertebral structure of the second chief specimen of Tyrannosaurus rex, Amer. Mus. 5027, discovered in 1908. An orthogonal projection executed on a very large scale and reproduced one-twelfth natural size. C 1-C 10 cervical series, D 1-D 13 dorsal or thoracic series, S 1-S 5 sacral series, Cd 1- Cd 53 caudal series. The caudals actually preserved are shaded; those drawn in outline are conjectural and restored. The total number of caudals is conjectural.
Supplementary data to Schmiester et al. *Efficient parameterization of large-scale dynamic models based on relative measurements*
<p>This archive contains Supplementary data to the manuscript <em>Efficient parameterization of large-scale dynamic models based on relative measurements</em> by Leonard Schmiester, Yannik Schälte, Fabian Fröhlich, Jan Hasenauer and Daniel Weindl.</p>
Large scale experiments to improve monopile scour protection design adapted to climate change
<p>Offshore wind farms contribute significantly to contemporary renewable energy production. By installing these offshore structures, new technical design challenges arise, such as foundation optimisation. Present LCoE (Levelized Cost of Electricity) of offshore wind turbines amounts up to 170 Euro/MWh (Crown Estate, 2015), but the ambition is to reduce this by 2020 to 90 Euro/MWh (EY, 2015). Offshore wind turbine foundation costs are 20 % of the total costs in the case of a monopile (NREL, 2014). An important part of those costs is related to the foundation's scour protection. Therefore, optimisations in the design of the scour protection are indispensable.<br>Another promising track to reduce the costs of offshore wind turbines is their lifetime extension. Recent studies (Crown Estate, 2015) show that a 5 year lifetime extension can reduce the cost per kWh by 6 %. To check the feasibility of a lifetime extension, it will be necessary to diagnose or inspect the conditions of several core parts of the turbines, notably its foundation and scour protection. Therefore, more fundamental insight into the (longer term damage) behaviour of the scour protection around the monopile is needed.<br>Beside the interest in design optimisation and lifetime extension, the influence of climate change needs to be investigated in more detail. Climate change will increase the design storm conditions and influence the scour protection stability. Therefore, research towards a risk-based design will help to evaluate the functionality of scour protection already installed and improve the design of future scour protections adapted to climate change.<br>Based on the above motivations, the main research objective is to establish a basic benchmark dataset on the stability of scour protection around monopile foundations to serve as a basis for model tests in other flumes in the future (rather than to carry out a traditional sensitivity study with a fine resolution for all governing parameters). <br>To achieve the goals, scour researchers from several institutions are set to start work on a collaborative project at HR Wallingford's Fast Flow Facility (FFF) as part of PROTEUS, an EU-funded Hydralab+ project. Hydralab+ which is funded by the EU's Horizon 2020 Research and Innovation Programme brings together facilities and researchers in experimental hydraulic and hydrodynamics.<br>The research project aims to improve the design of scour protection around offshore wind turbine monopiles, as well as future-proofing them against the impacts of climate change. <br>PROTEUS, which stands for the 'PRotection of Offshore wind Turbine monopilEs against Scouring' will facilitate the conducting of a series of large scale experiments over a seven week period in the FFF flume at HR Wallingford's UK physical modelling facilities.<br>Partners involved in PROTEUS are: Department of Civil Engineering at Ghent University, HR Wallingford (UK), the Ludwig-Franzius Institute for Hydraulic, Estuarine and Coastal Engineering at the University of Hannover, the Faculty of Engineering at the University of Porto, the Geotechnics division of the Belgian Department of Mobility and Public Works, and International Marine and Dredging Consultants (IMDC nv).</p>
Text-fig. 4. Reteporella sp., deposited in NM Prague under number T 3318. A – Large colony suggesting very short transport. Scale bar 10 mm. Optic photography. B – the detail of branch showing the mode of preservation (no original skeleton preserved). Scale bar 1 mm. SEM photography (BSE detector). in The Priabonian Bryozoan-Decapod Association From The Borové Formation (The Ďurkovec Quarry, Ne Slovakia) And Its Palaeoecological Implications
Text-fig. 4. Reteporella sp., deposited in NM Prague under number T 3318. A – Large colony suggesting very short transport. Scale bar 10 mm. Optic photography. B – the detail of branch showing the mode of preservation (no original skeleton preserved). Scale bar 1 mm. SEM photography (BSE detector).
DATASET of Large-scale Neural Recordings for DENOISING Engine
<p><span>30 sec raw data (.brw) was recorded with BrainWave SW and detected LFP events and spikes were stored in (.bxr). These extracellular recordings were obtained from acute hippocampal-cortical slices and were collected at 14KHz/electrode sampling frequency.</span></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.