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.
9,152
datasets available to search
ShareScore release 0.9.0
Dataset results
9,152 results for “Networking”
Simulated trajectories of city population: Levy walks along Utica, NY, street network
<p>Simulated trajectories of the 2000 census population of Utica, New York. Each of 53,971 simulated people was placed randomly along a road within his or her census tract of residence and then independently performed road-network-constrained, truncated Lévy walks for 8 hours of simulated time, moving at 4 km per hour. The trajectories were then sampled at 30 minute intervals. The original dataset was created for studying indexes of activity-space segregation. It is archived at <a href="https://zenodo.org/record/2865830#.XpYviKsza00">https://zenodo.org/record/2865830#.XpYviKsza00</a> and described more fully in Palmer (2013), Activity-Space Segregation: Understanding Social Divisions in Space and Time (http://arks.princeton.edu/ark:/88435/dsp01k643b130h).</p> <p>This version has been created to aid in testing contact-tracing apps and mobility analysis tools. The fields are:</p> <p>latitude: latitude</p> <p>longitude: longitude</p> <p>time: UNIX time in milliseconds</p> <p>ID: random ID assigned to each individual</p>
Artifacts related to "Using Informed Access Network Selection to Improve HTTP Adaptive Streaming Performance"
<p>This archive contains data related to in the following paper:</p> <p>"Using Informed Access Network Selection to Improve HTTP Adaptive Streaming Performance"</p> <p>(published at the ACM MMSys 2020 conference)</p> <p>Copyright (c) 2020, Theresa Enghardt <theresa@tenghardt.net>, Fachgebiet INET - TU Berlin.</p> <p><br> See https://github.com/fg-inet/MMSys2020_Informed-Access-Network-Selection for more information.</p> <p>This data is released under the Creative Commons Attribution 4.0 International license.</p>
Lifelong Learning of Graph Neural Networks for Open-World Node Classification
<p>Three temporal graph datasets for node classification under distribution shift.</p> <p>DBLP-Easy and DBLP-Hard are citation graph datasets. PharmaBio is a collaboration graph dataset.</p> <p>Vertices are scientific publications, edges are either citations (DBLP) or at-least-one-common-author relationships (PharmaBio).</p> <p>The task is to classify the vertices of the graph into the respective conference/journal venues (DBLP) or journal categories (PharmaBio). In the DBLP datasets, new classes may appear over time.</p> <p>Each dataset follows the structure:</p> <p>- adjlist.txt -- the graph structure encoded as adjacency lists: in each row, the first entry is the source vertex, the remaining entries are adjacent vertices</p> <p>- X.npy -- numpy serialized format for node features indexed by node id corresponding to adjlist.txt</p> <p>- y.npy -- numpy serialized format for node labels indexed by node id corresponding to adjlist.txt</p> <p>- t.npy -- numpy serialized format for time steps indexed by node id corresponding to adjlist.txt</p> <p>A paper describing our incremental training and evaluation framework is published in IJCNN 2021 (Pre-print on arXiv: <a href="https://arxiv.org/abs/2006.14422">https://arxiv.org/abs/2006.14422</a>).</p> <p>If you use these datasets in your research, please cite the corresponding paper:</p> <pre><code>@inproceedings{galke2021lifelong, author={Galke, Lukas and Franke, Benedikt and Zielke, Tobias and Scherp, Ansgar}, booktitle={2021 International Joint Conference on Neural Networks (IJCNN)}, title={Lifelong Learning of Graph Neural Networks for Open-World Node Classification}, year={2021}, volume={}, number={}, pages={1-8}, doi={10.1109/IJCNN52387.2021.9533412} }</code></pre> <p><br> </p>
SHYFEM set-up for model driven optimization of the tide gauge monitoring network in the Venice Lagoon
<p>This database include all configuration files, script and data for running the<br> simulations and elaborate the results presented in the work entitled "Model-driven<br> optimization of coastal sea observatories through data assimilation in a finite<br> element hydrodynamic model (SHYFEM v. 7_5_65)" to be submitted in Geoscientific Model<br> Development (GMD).</p>
Tagged original datasets for 'Genetically Optimized Massively Parallel Binary Neural Networks for Intrusion Detection Systems'
<p>Tagged, non-formatted, original datasets used in 'Genetically Optimized Massively Parallel Binary Neural Networks for Intrusion Detection Systems', T. Murovič, A. Trost.</p> <p>Available from the original authors:</p> <p>1. <a href="https://www.unsw.adfa.edu.au/unsw-canberra-cyber/cybersecurity/ADFA-NB15-Datasets/">https://www.unsw.adfa.edu.au/unsw-canberra-cyber/cybersecurity/ADFA-NB15-Datasets/</a> (UNWS-NB15 dataset)</p> <p>2. <a href="https://www.unb.ca/cic/datasets/nsl.html">https://www.unb.ca/cic/datasets/nsl.html</a> (NSL-KDD dataset)</p>
Code and data for: Network-based protein structural classification
<p>Code and data related to the research article titled, "Network-based protein structural classification".</p> <p>More information about the code and the data is available at https://nd.edu/~cone/NETPCLASS/</p>
Supplementary data for article 'Estimating and abstracting the 3D structure of feline bones using neural networks on X-ray (2D) images'
<p>3D DICOM volumes (CT scans) of feline femora, PNGs generated from them as DRRs using MeVisLab, and STLs generated from the DICOM volumes with MIMICS or MeshLab. Software to work with these files can be found at http://doi.org/10.5281/zenodo.3829423</p>
Aligning repository networks to support international sharing of COVID-19 resources and other current issues
<p>Recording of a panel "Aligning repository networks to support international sharing of COVID-19 resources", organized by COAR. This panel presented several national approaches to managing and sharing COVID-19 resources from around the world (Africa, Canada, Europe, Latin America, Asia), followed by a discussion about how we can work more closely across countries and regions to ensure that content can be integrated internationally. Participants: Kathleen Shearer - COAR, Paolo Manghi - OpenAIRE, Europe, Kazuhiro Hayashi, National Institution of Science and Technology Policy, Japan, Ansie Van de Wasthuizen, UNISA, South Africa, Cesar Olivares, CONCYTEC, Peru and LA Referencia, Latin America, Geoff Harder, Canadian Association of Research Libraries<br> <br> Organization Identifiers and Open Repositories: ROR-ing Together – Maria Gould, California Digital Library, University of California Office of the President.<br> <br> Research Data Management: a Stellenbosch University Journey – Samuel Simango, Stellenbosch University Library.<br> <br> Towards Open Data Metrics: enabling data repositories to demonstrate reuse – Kristian Garza, DataCite.</p> <p>DSpace-CRIS 7: What is Coming? – Susanna Mornati, 4Science</p>
Dataset The Lactate Receptor HCAR1 Modulates Neuronal Network Activity through the Activation of G(α) and G(βγ) Subunits
<p>This dataset is related to the study: </p> <p>"The Lactate Receptor HCAR1 Modulates Neuronal Network Activity through the Activation of G(α) and G(βγ) Subunits" by de Castro Abrantes H, Briquet M, Schmuziger C, Restivo L, Puyal J, Rosenberg N, Rocher AB, Offermanns S, Chatton JY. J Neurosci. 2019 Jun 5;39(23):4422-4433. doi: 10.1523/JNEUROSCI.2092-18.2019. Epub 2019 Mar 29. PubMed PMID: 30926749; PubMed Central PMCID: PMC6554634.</p>
Data from: The functional roles of species in metacommunities, as revealed by metanetwork analyses of bird-plant frugivory networks
<p>Understanding how biodiversity and interaction networks change across environmental gradients is a major challenge in ecology. We integrated metacommunity and metanetwork perspectives to test species' functional roles in bird-plant frugivory interactions in a fragmented forest landscape in Southwest China, with consequences for seed dispersal. Availability of fruit resources both on and under trees created vertical feeding stratification for frugivorous birds. Bird-plant interactions involving birds feeding only on the tree or both on and under the tree (shared) had a higher centrality and contributed more to metanetwork organization than interactions involving birds feeding only under the tree. Moreover, bird-plant interactions associated with large-seeded plants disproportionately contributed to metanetwork organization and centrality. Consequently, on-the-tree and shared birds contributed more to metanetwork organization whereas under-the-tree birds were more involved in local processes. We would expect that species' roles in the metanetwork will translate into different conservation values for maintaining functioning of seed-dispersal networks.</p>
Fluorescence Microscopy Data for Cellular Detection using Object Detection Networks.
<p>This data accompanies work from the paper entitled: </p> <p><strong>Object Detection Networks and Augmented Reality for Cellular Detection in Fluorescence Microscopy Acquisition and Analysis. </strong></p> <p>Waithe D1*,2,, Brown JM3, Reglinski K4,6,7, Diez-Sevilla I<sup>5</sup>, Roberts D<sup>5</sup>, Christian Eggeling1,4,6,8</p> <p>1 Wolfson Imaging Centre Oxford and 2 MRC WIMM Centre for Computational Biology and 3 MRC Molecular Haematology Unit and 4 MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, OX3 9DS, Oxford, United Kingdom. 5 Nuffield Division of Clinical Laboratory Sciences, Radcliffe Department of Medicine, John Radcliffe Hospital, University of Oxford, Headley Way, Oxford, OX3 9DU.<br> 6 Institute of Applied Optics and Biophysics, Friedrich-Schiller-University Jena, Max-Wien Platz 4, 07743 Jena, Germany.<br> 7 University Hospital Jena (UKJ), Bachstraße 18, 07743 Jena, Germany.<br> 8 Leibniz Institute of Photonic Technology e.V., Albert-Einstein-Straße 9, 07745 Jena, Germany.</p> <p>Further details of these datasets can be found in the methods section of the above paper.</p> <p><strong>Erythroblast DAPI (+glycophorin A):</strong> erythroblast cells were stained with DAPI and for glycophorin A protein (CD235a antibody, JC159 clone, Dako) and with Alexa Fluor 488 secondary antibody (Invitrogen). DAPI staining was performed through using VectaShield Hard Set mounting solution with DAPI (Vector Lab). Num. of images used for training: 80 and testing: 80. Average number of cells per image: 4.5.</p> <p><strong>Neuroblastoma phalloidin (+DAPI): </strong>images of neuroblastoma cells (N1E115) stained with phalloidin and DAPI were acquired from the Cell Image Library [26]. Cell images in the original dataset were acquired with a larger field of view than our system and so we divided each image into four sub-images and also created ROI bounding boxes for each of the cells in the image. The images were stained for FITC-phalloidin and DAPI. Num. of images used for training: 180, testing: 180. Average number of cells per image: 11.7.</p> <p><strong>Fibroblast nucleopore</strong>: fibroblast (GM5756T) cells were stained for a nucleopore protein (anti-Nup153 mouse antibody, Abcam) and detected with anti-mouse Alexa Fluor 488. Num. of images for training: 26 and testing: 20. Average number of cells per image: 4.8.</p> <p><strong>Eukaryote DAPI:</strong> eukaryote cells were stained with DAPI and fixed and mounted in Vectashield (Vector Lab). Num. of images for training: 40 and testing: 40. Average number of cells per image: 8.9.</p> <p><strong>C127 DAPI:</strong> C127 cells were initially treated with a technique called RASER-FISH[27], stained with DAPI and fixed and mounted in Vectashield (Vector Lab). Num. of images for training: 30 and testing: 30. Average number of cells per image: 7.1.</p> <p><strong>HEK peroxisome All</strong>: HEK-293 cells expressing peroxisome-localized GFP-SCP2 protein. Cells were transfected with GFP-SCP2 protein, which contains the PTS-1 localization signal, which redirects the fluorescently tagged protein to the actively importing peroxisomes[28]. Cells were fixed and mounted. Num. of images for training: 55 and testing: 55. Additionally we sub-categorised the cells as ‘punctuate’ and ‘non-punctuate’, where ‘punctuate’ would represent cells that have staining where the peroxisomes are discretely visible and ‘non-punctuate’ would be diffuse staining within the cell. The ‘HEK peroxisome All’ dataset contains ROI for all the cells: average number of cells per image: 7.9. The ‘HEK peroxisome’ dataset contains only those cells with punctuate fluorescence: average number of punctuate cells per image: 3.9.</p> <p><strong>Erythroid DAPI All: </strong>Murine embryoid body-derived erythroid cells, differentiated from mES cells. Stained with DAPI and fixed and mounted in Vectashield (Vector Lab). Num. of images for training: 51 and testing: 50. Multinucleate cells are seen with this differentiation procedure. There is a variation in size of the nuclei (nuclei become smaller as differentiation proceeds). The smaller, 'late erythroid' nuclei contain heavily condensed DNA and often have heavy ‘blobs’ of heterochromatin visible. Apoptopic cells are also present, with apoptotic bodies clearly present. The ‘Erythroid DAPI All’ dataset contains ROI for all the cells in the image. Average number of cells per image: 21.5. The subset ‘Erythroid DAPI’ contains non-apoptotic cells only: average number of cells per image: 11.9</p> <p><strong>COS-7 nucleopore. </strong>Slides were acquired from GATTAquant. GATTA-Cells 1C are single color COS-7 cells stained for Nuclear pore complexes (Anti-Nup) and with Alexa Fluor 555 Fab(ab’)2 secondary stain. GATTA-Cells are embedded in ProLong Diamond. Num. of images for training: 50 and testing: 50. Average number of cells per image: 13.2</p> <p><strong>COS-7 nucleopore 40x</strong>. Same GATTA-Cells 1C slides (GATTAquant) as above but imaged on Nikon microscope, with 40x NA 0.6 objective. Num. of images for testing: 11. Average number of cells per image: 31.6.</p> <p><strong>COS-7 nucleopore 10x.</strong> Same GATTA-Cells 1C slides (GATTAquant) as above but imaged on Nikon microscope, with 10x NA 0.25 objective. Num. of images for testing: 20. Average number of cells per image: 24.6</p> <p><strong>Dataset Annotation</strong></p> <p>Datasets were annotated by a skilled user. These annotations represent the ground-truth of each image with bounding boxes (regions) drawn around each cell present within the staining. Annotations were produced using Fiji/ImageJ [29] ROI Manager and also through using the OMERO [30] ROI drawing interface (<a href="https://www.openmicroscopy.org/omero/">https://www.openmicroscopy.org/omero/</a>). The dataset labels were then converted into a format compatible with Faster-RCNN (Pascal), YOLOv2, YOLOv3 and also RetinaNet. The scripts used to perform this conversion are documented in the repository (<a href="https://github.com/dwaithe/amca">https://github.com/dwaithe/amca</a>/scripts/).</p>
Dataset for: Generation of model tissues with dendritic vascular networks via sacrificial laser-sintered carbohydrate templates
<p>Published in:<br> Nature Biomedical Engineering. doi: 10.1038/s41551-020-0566-1.</p> <p>Generation of model tissues with dendritic vascular networks via sacrificial laser-sintered carbohydrate templates</p> <p>Ian S. Kinstlinger (1), Sarah H. Saxton (2), Gisele A. Calderon (1), Karen Vasquez Ruiz (1), David R. Yalacki (1), Palvasha R. Deme (1), Jessica E. Rosenkrantz (3), Jesse D. Louis-Rosenberg (3), Fredrik Johansson (2), Kevin D. Janson (1), Daniel W. Sazer (1), Saarang S. Panchavati (1), Karl-Dimiter Bissig (4), Kelly R. Stevens (2,5), and Jordan S. Miller (1)</p> <p>1 Department of Bioengineering, Rice University, Houston, TX, USA.<br> 2 Department of Bioengineering, University of Washington, Seattle, WA, USA.<br> 3 Nervous System, Palenville, NY, USA.<br> 4 Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA.<br> 5 Department of Pathology, University of Washington, Seattle, WA, USA</p> <p>Sacrificial templates for patterning perfusable vascular networks in engineered tissues have been constrained in architectural complexity, owing to the limitations of extrusion-based 3D-printing techniques. Here we show that cell-laden hydrogels can be patterned with algorithmically generated dendritic vessel networks and other complex hierarchical networks by using sacrificial templates made from laser-sintered carbohydrate powders. We quantified and modulated gradients of cell proliferation and cell metabolism emerging as a result of fluid convection through these networks and of diffusion of oxygen and metabolites out of them. We also show scalable strategies for the fabrication, perfusion culture and volumetric analysis of large tissue-like constructs with complex and heterogeneous internal vascular architectures. Perfusable dendritic networks in cell-laden hydrogels may help sustain thick and densely cellularized engineered tissues, and assist interrogations of the interplay between mass transport and tissue function.</p>
Supplementary videos for "Active flow network generates molecular transport by packets: case of the endoplasmic reticulum"
<p>Videos showing simulated motion on the active flow network for different switching timescales. In particular, compare <span class="math-tex">\(\tau_{\text{switch}} = 3 \text{ s}\)</span> to <span class="math-tex">\(\tau_{\text{switch}} = 30 \text{ ms}\)</span>. The red bubbles are proportional to the number of particles present in a node. Initially, all particles are placed in a central source node.</p>
Criminal Network: The Sicilian Mafia. "Montagna Operation"
<p>The datasets reported relate to criminal networks directly obtained from Court data:</p> <ul> <li>Meetings dataset, accounts for the physical meetings among suspected (police stakeout). It is composed by 101 nodes and 256 edges.</li> <li>Phone Calls dataset refers to phone calls among individuals (police eavesdropping). It is composed by 100 nodes and 124 edges.</li> <li>Roles dataset address the role of the suspected as well as their relationship with the other suspected, and the request from the judge (e.g. arrested/in jail/etc.).</li> </ul> <p>Meetings and Phone Calls datasets have in common 47 nodes (i.e., suspected).</p> <p><em>“Our datasets were derived from the pre-trial detention order issued by the Court of Messina’s preliminary investigation judge on March 14, 2007, which was towards the end of the major anti-mafia operation referred to as “Montagna Operation”. This operation was concluded in 2007 by the Public Prosecutor’s Office of Messina (Sicily) and was conducted by the Special Operations Unit of the Italian Police (the R.O.S. Reparto Operativo Speciale of the Carabinieri is specializing in anti-Mafia investigations). This particular investigation was a prominent operation focused on two Mafia clans, known as the “Mistretta” family and the “Batanesi clan”. From 2003 to 2007, these families were found to had infiltrated several economic activities including major infrastructure works, through a cartel of entrepreneurs close to the Sicilian Mafia.” (</em>From <a href="https://arxiv.org/abs/2003.05303">https://arxiv.org/abs/2003.05303</a>)</p> <p>For more details, please refer to:</p> <ul> <li>Journal publication PLoS ONE: <a href="https://journals.plos.org/plosone/article/citation?id=10.1371/journal.pone.0236476" target="_blank" rel="noopener">https://journals.plos.org/plosone/article/citation?id=10.1371/journal.pone.0236476</a></li> <li>Preliminary analysis in our conference paper: <a href="https://link.springer.com/chapter/10.1007/978-3-030-36683-4_36">https://link.springer.com/chapter/10.1007/978-3-030-36683-4_36</a></li> <li>Our pre-print on ArXiv: <a href="https://arxiv.org/abs/2003.05303">https://arxiv.org/abs/2003.05303</a></li> <li>Our GitHub Repository: <a href="https://github.com/lcucav/networkdistruption">https://github.com/lcucav/networkdistruption</a></li> </ul>
Data from: Phylogenetic comparative methods on phylogenetic networks with reticulations
The goal of Phylogenetic Comparative Methods (PCMs) is to study the distribution of quantitative traits among related species. The observed traits are often seen as the result of a Brownian Motion (BM) along the branches of a phylogenetic tree. Reticulation events such as hybridization, gene flow or horizontal gene transfer, can substantially affect a species' traits, but are not modeled by a tree. Phylogenetic networks have been designed to represent reticulate evolution. As they become available for downstream analyses, new models of trait evolution are needed, applicable to networks. One natural extension of the BM is to use a weighted average model for the trait of a hybrid, at a reticulation point. We develop here an efficient recursive algorithm to compute the phylogenetic variance matrix of a trait on a network, in only one preorder traversal of the network. We then extend the standard PCM tools to this new framework, including phylogenetic regression with covariates (or phylogenetic ANOVA), ancestral trait reconstruction, and Pagel's λ test of phylogenetic signal. The trait of a hybrid is sometimes outside of the range of its two parents, for instance because of hybrid vigor or hybrid depression. These two phenomena are rather commonly observed in present-day hybrids. Transgressive evolution can be modeled as a shift in the trait value following a reticulation point. We develop a general framework to handle such shifts, and take advantage of the phylogenetic regression view of the problem to design statistical tests for ancestral transgressive evolution in the evolutionary history of a group of species. We study the power of these tests in several scenarios, and show that recent events have indeed the strongest impact on the trait distribution of present-day taxa. We apply those methods to a dataset of Xiphophorus fishes, to confirm and complete previous analysis in this group. All the methods developed here are available in the Julia package PhyloNetworks.
DBLP Publications Network
<p>This dataset contains information about academic articles, their authors and venues of publication. The dataset has the form of a graph. It has been produced by the SmartDataLake project (<a href="https://smartdatalake.eu">https://smartdatalake.eu</a>), using data collected from Aminer (<a href="https://aminer.org">https://aminer.org</a>).</p>
Adjacency matrices of global atmospheric moisture networks during 2007-2016
<p>This dataset provides the adjacency matrices used to run Infomap to conduct community detection of global atmospheric moisture networks. A detailed description of file naming convention, dimension information and how to read the files can be found in 'Readme.txt'.</p>
MVCNN++: CAD model shape classification and retrieval using multi-view convolutional neural networks
<p>Deep neural networks have shown promising success towards the classification and retrieval tasks for images and text data. While there have been several implementations of deep networks in the area of computer graphics, these algorithms do not translate easily across different datasets, especially for shapes used in product design and manufacturing domain. Unlike datasets used in the 3D shape classification and retrieval in the computer graphics domain, engineering level description of 3D models do not yield themselves to neat distinct classes. The current study looks at an improved form of the 3D shape deep learning algorithm for classification and retrieval through the use of techniques such as relaxed classification, use of prime angled camera angles for capturing feature detail and transfer learning for reducing the amount of data and processing time needed to train shape recognition algorithms. The proposed algorithm (MVCNN++) builds on top of multi-view convolutional neural network (MVCNN) algorithm, improving its efficacy for manufacturing part classification by enabling use of part metadata, yielding an improvement of almost 6% over the original version. With the explosive growth of 3D product models available in publicly available repositories, search and discovery of relevant models is critical to democratizing access to design models.</p>
Dynamic shifts in social network structure and composition within a breeding hybrid population
1. Mating behavior and the timing of reproduction can inhibit genetic exchange between closely related species; however, these reproductive barriers are challenging to measure within natural populations. Social network analysis provides promising tools for studying the social context of hybridization, and the exchange of genetic variation, more generally. 2. We test how social networks within a hybrid population of California (Callipepla californica) and Gambel's quail (Callipepla gambelii) change over discrete periods of a breeding season. We assess patterns of phenotypic and genotypic assortment, and ask whether altered associations between individuals (association rewiring), or changes to the composition of the population (individual turnover) drive network dynamics. We use genetic data to test whether social associations and relatedness between individuals correlate with patterns of parentage within the hybrid population. 3. To achieve these aims, we combine RFID association data, phenotypic data, and genomic measures with social network analyses. We adopt methods from the ecological network literature to quantify shifts in network structure and to partition changes into those due to individual turnover and association rewiring. We integrate genomic data into networks as node-level attributes (ancestry) and edges (relatedness, parentage) to test links between social and parentage networks. 4. We show that rewiring of associations between individuals that persist across network periods, rather than individual turnover, drives the majority of the changes in network structure throughout the breeding season, and that the traits involved in phenotypic/genotypic assortment were highly dynamic over time. Social networks were randomly assorted based upon genetic ancestry, suggesting weak behavioral reproductive isolation within this hybrid population. Finally, we show that the strength of associations within the social network, but not levels of genetic relatedness, predict patterns of parentage. 5. Social networks play an important role in population processes such as the transmission of disease and information, yet there has been less focus on how networks influence the exchange of genetic variation. By integrating analyses of social structure, phenotypic assortment, and reproductive outcomes within a hybrid zone, we demonstrate the utility of social networks for analyzing links between social context and gene flow within wild populations. 08-Jul-2020
Hakea vegetation dataset for training and evaluating segmentation network
<p>This dataset is the version used for both training and evaluation of the models discussed the (in press) publication in Methods in Ecology and Evolution, "Detecting plant species in the field with deep learning and drone technology".</p> <p>Also included in this upload, results_inference_images.tar includes the output predictions for each of the trained models on the unseen test set.</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.