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AI results complementing the Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - Bulgaria
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2019, which consisted of:</p> <ul> <li>Serological surveys to monitor the circulation of AIV subtypes H5 and H7 in poultry (active surveillance). These surveys should preferentially target poultry species or production systems with increased risk for introduction of avian influenza (AI).</li> <li>Passive surveillance aiming at the virological detection of AI in wild birds found dead or moribund.</li> </ul>
AI results complementing the Annual Report on surveillance for Avian Influenza in poultry and wild birds in Member States of the European Union - Cyprus
<p>This dataset contains the results of the EU co-funded surveillance activities conducted in 2019, which consisted of:</p> <ul> <li>Serological surveys to monitor the circulation of AIV subtypes H5 and H7 in poultry (active surveillance). These surveys should preferentially target poultry species or production systems with increased risk for introduction of avian influenza (AI).</li> <li>Passive surveillance aiming at the virological detection of AI in wild birds found dead or moribund.</li> </ul>
Dataset of results of the GraphQL-SMS
<p><strong>Dataset of results of the GraphQL-SMS</strong></p> <ul> <li><strong>02_1 RQ1_Mapping_DataSet_2020.xlsx</strong> contains the working data for the results of the question RQ1.</li> <li><strong>02 Mapping_DataSet_2020.xlsx</strong> contains the working data for the results of the questions: RQ2, RQ3, RQ4, RQ5 and RQ6.</li> </ul>
Tiny-ME early results
<p>Correctness and performance evaluation results produced with <a href="http://sisinflab.poliba.it/swottools/evowluator">evOWLuator</a> for the following OWL reasoners:</p><ul><li><a href="https://www.derivo.de/en/products/konclude/">Konclude</a> (version 0.6.2-544);</li><li><a href="http://swot.sisinflab.poliba.it/minime/">Mini-ME Java</a> (version 2.0);</li><li><a href="http://swot.sisinflab.poliba.it/minime-swift">Mini-ME Swift</a> (version 1.0);</li><li><a href="http://swot.sisinflab.poliba.it/tinyme">Tiny-ME C</a> (version 1.0.0);</li><li><a href="http://swot.sisinflab.poliba.it/tinyme">Tiny-ME Java</a> (version 1.0.0);</li><li><a href="http://swot.sisinflab.poliba.it/tinyme">Tiny-ME Objective-C</a> (version 1.0.0).</li></ul><p>Ontologies mentioned in the csv files are part of the <a href="https://zenodo.org/record/10791">ORE 2014 Reasoner Competition Dataset</a>.</p><p><strong>Publication:</strong> <a href="http://sisinflab.poliba.it/Publications/2022/RSBGLIP22">A multiplatform reasoning engine for the Semantic Web of Everything</a></p>
An Agent-Based Model to Predict Pedestrians Trajectories with an Autonomous Vehicle in Shared Spaces: Video Results
<p>A video illustrating the results presented in the paper: <em>"Prédhumeau M., Mancheva L., Dugdale J., and Spalanzani A. 2021. An Agent-Based Model to Predict Pedestrians Trajectories with an Autonomous Vehicle in Shared Spaces. In the Proc. of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021). IFAAMAS, Online."</em></p> <p> </p>
Underlying data - Results from the Open Call: How Citizens can participate in solar energy research?
<p>Underlying data to the "Results from the Open Call: How Citizens can participate in solar energy research?" @</p> <pre>https://zenodo.org/record/3554901#.YAgimxaCE2w</pre> <p>Answers to the online survey in "Call for ideas_answers online_survey.xlsx"</p> <p>Notes from the World Cafe and other meetings from the secretaries: "notes_MMLs_GRECO_2019.pdf</p> <p> </p>
Video Results of visual preprocessing module
<p>These videos titled ellip-detect show the ellipse detection results.</p> <p>The results are obtained by further detecting ellipses on the patches detected by the visual preprocessing module.</p> <p>These videos demonstrate the developed arc-based ellipse detector can handle the occlusion very well and perform robustly in real conditions.</p> <p> </p> <p>These videos titled tracking show the visual tracking results.</p> <p>Object, after initialization by template matching, will not be re-detected again.</p> <p>So this is a one-passing evaluation. </p> <p> </p> <p>These videos titled detect show the results of the visual preprocessing module.</p> <p>Object, after initialization by template matching, will be re-detected again if tracking fails.</p>
Results of the 10th Intl. Competition on Software Verification (SV-COMP 2021)
<p>Competition Results</p> <p>This file describes the contents of an archive of the 10th Competition on Software Verification (SV-COMP 2021).<br> <a href="https://sv-comp.sosy-lab.org/2021/">https://sv-comp.sosy-lab.org/2021/</a></p> <p>The competition was run by Dirk Beyer, LMU Munich, Germany.<br> More information is available in the following article:<br> Dirk Beyer. <em>Software Verification: 10th Comparative Evaluation (SV-COMP 2021).</em> In Proceedings of the 27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS 2021, Luxembourg, March 27 - April 1), 2021. Springer.</p> <p>Copyright (C) Dirk Beyer<br> <a href="https://www.sosy-lab.org/people/beyer/">https://www.sosy-lab.org/people/beyer/</a></p> <p>SPDX-License-Identifier: CC-BY-4.0<br> <a href="https://spdx.org/licenses/CC-BY-4.0.html">https://spdx.org/licenses/CC-BY-4.0.html</a></p> <p>To browse the competition results with a web browser, there are two options:</p> <ul> <li>start a local web server using php -S localhost:8000 in order to view the data in this archive, or</li> <li>browse https://sv-comp.sosy-lab.org/2021/results/ in order to view the data on the SV-COMP web page.</li> </ul> <p>Contents</p> <ul> <li><code>index.html</code>: directs to the overview web page</li> <li><code>LICENSE.txt</code>: specifies the license</li> <li><code>README.txt</code>: this file</li> <li><code>results-validated/</code>: results of validation runs</li> <li><code>results-verified/</code>: results of verification runs and aggregated results</li> </ul> <p>The folder <code>results-validated/</code> contains the results from validation runs:</p> <ul> <li><code>*.xml.bz2</code>: XML results from BenchExec</li> <li><code>*.logfiles.zip</code>: output from tools</li> <li><code>*.json.gz</code>: mapping from files names to SHA 256 hashes for the file content</li> </ul> <p>The folder <code>results-verified/</code> contains the results from verification runs and aggregated results:</p> <ul> <li><code>index.html</code>: overview web page with rankings and score table</li> <li><code>*.xml.bz2</code>: XML results from BenchExec</li> <li><code>*.merged.xml.bz2</code>: XML results from BenchExec, status adjusted according to the validation results</li> <li><code>*.logfiles.zip</code>: output from tools</li> <li><code>*.json.gz</code>: mapping from files names to SHA 256 hashes for the file content</li> <li><code>*.xml.bz2.table.html</code>: HTML views on the detailed results data as generated by BenchExec’s table generator</li> <li><code>*.All.table.html</code>: HTML views of the full benchmark set (all categories) for each tool</li> <li><code>META_*.table.html</code>: HTML views of the benchmark set for each meta category for each tool, and over all tools</li> <li><code><category>*.table.html</code>: HTML views of the benchmark set for each category over all tools</li> <li><code>iZeCa0gaey.html</code>: HTML views per tool</li> <li> <p><code>validatorStatistics.html</code>: Statictics of the validator runs</p> </li> <li><code>quantilePlot-*</code>: score-based quantile plots as visualization of the results</li> <li><code>quantilePlotShow.gp</code>: example Gnuplot script to generate a plot</li> <li> <p><code>score*</code>: accumulated score results in various formats</p> </li> </ul> <p>The hashes of the file names (in the files *.json.gz) are useful for</p> <ul> <li>validating the exact contents of a file and</li> <li>accessing the files from the witness store.</li> </ul> <p>Other Archives</p> <p>Overview over archives from SV-COMP 2021 that are available at Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.4459196">https://doi.org/10.5281/zenodo.4459196</a> Witness store (containing the generated verification witnesses)</li> <li><a href="https://doi.org/10.5281/zenodo.4458215">https://doi.org/10.5281/zenodo.4458215</a> Results (XML result files, log files, file mappings, HTML tables)</li> <li><a href="https://doi.org/10.5281/zenodo.4459126">https://doi.org/10.5281/zenodo.4459126</a> Verification tasks, version svcomp21</li> <li><a href="https://doi.org/10.5281/zenodo.4317433">https://doi.org/10.5281/zenodo.4317433</a> BenchExec, version 3.6</li> </ul> <p>All benchmarks were executed for SV-COMP 2021 <a href="https://sv-comp.sosy-lab.org/2021/">https://sv-comp.sosy-lab.org/2021/</a><br> by Dirk Beyer, LMU Munich, based on the following components:</p> <ul> <li><a href="https://gitlab.com/sosy-lab/sv-comp/archives-2021">https://gitlab.com/sosy-lab/sv-comp/archives-2021</a> svcomp21-0-g08c7a98</li> <li><a href="https://gitlab.com/sosy-lab/software/sv-benchmarks">https://gitlab.com/sosy-lab/software/sv-benchmarks</a> svcomp21-0-g4cc6b6d96a</li> <li><a href="https://gitlab.com/sosy-lab/software/benchexec">https://gitlab.com/sosy-lab/software/benchexec</a> 3.6-0-gb278ebbb</li> <li><a href="https://gitlab.com/sosy-lab/benchmarking/competition-scripts">https://gitlab.com/sosy-lab/benchmarking/competition-scripts</a> svcomp21-0-g8339740</li> <li><a href="https://gitlab.com/sosy-lab/sv-comp/bench-defs">https://gitlab.com/sosy-lab/sv-comp/bench-defs</a> svcomp21-0-ga57fe48</li> </ul> <p>Contact</p> <p>Feel free to contact me in case of questions: <a href="https://www.sosy-lab.org/people/beyer/">https://www.sosy-lab.org/people/beyer/</a></p>
Results of the 3rd Intl. Competition on Software Testing (Test-Comp 2021)
<p>Competition Results</p> <p>This file describes the contents of an archive of the 3rd Competition on Software Testing (Test-Comp 2021).<br> <a href="https://test-comp.sosy-lab.org/2021/">https://test-comp.sosy-lab.org/2021/</a></p> <p>The competition was run by Dirk Beyer, LMU Munich, Germany.<br> More information is available in the following article:<br> Dirk Beyer. <em>Status Report on Software Testing: Test-Comp 2021.</em> In Proceedings of the 24th International Conference on Fundamental Approaches to Software Engineering (FASE 2021, Luxembourg, March 27 - April 1), 2021. Springer.</p> <p>Copyright (C) Dirk Beyer<br> <a href="https://www.sosy-lab.org/people/beyer/">https://www.sosy-lab.org/people/beyer/</a></p> <p>SPDX-License-Identifier: CC-BY-4.0<br> <a href="https://spdx.org/licenses/CC-BY-4.0.html">https://spdx.org/licenses/CC-BY-4.0.html</a></p> <p>To browse the competition results with a web browser, there are two options:</p> <ul> <li>start a local web server using php -S localhost:8000 in order to view the data in this archive, or</li> <li>browse <a href="https://test-comp.sosy-lab.org/2021/results/">https://test-comp.sosy-lab.org/2021/results/</a> in order to view the data on the Test-Comp web page.</li> </ul> <p>Contents</p> <ul> <li><code>index.html</code>: directs to the overview web page</li> <li><code>LICENSE.txt</code>: specifies the license</li> <li><code>README.txt</code>: this file</li> <li><code>results-validated/</code>: results of validation runs</li> <li><code>results-verified/</code>: results of test-generation runs and aggregated results</li> </ul> <p>The folder <code>results-validated/</code> contains the results from validation runs:</p> <ul> <li><code>*.xml.bz2</code>: XML results from BenchExec</li> <li><code>*.logfiles.zip</code>: output from tools</li> <li><code>*.json.gz</code>: mapping from files names to SHA 256 hashes for the file content</li> </ul> <p>The folder <code>results-verified/</code> contains the results from test-generation runs and aggregated results:</p> <ul> <li><code>index.html</code>: overview web page with rankings and score table</li> <li><code>design.css</code>: HTML style definitions</li> <li><code>*.xml.bz2</code>: XML results from BenchExec</li> <li><code>*.merged.xml.bz2</code>: XML results from BenchExec, status adjusted according to the validation results</li> <li><code>*.logfiles.zip</code>: output from tools</li> <li><code>*.json.gz</code>: mapping from files names to SHA 256 hashes for the file content</li> <li><code>*.xml.bz2.table.html</code>: HTML views on the detailed results data as generated by BenchExec’s table generator</li> <li><code>*.All.table.html</code>: HTML views of the full benchmark set (all categories) for each tool</li> <li><code>META_*.table.html</code>: HTML views of the benchmark set for each meta category for each tool, and over all tools</li> <li><code><category>*.table.html</code>: HTML views of the benchmark set for each category over all tools</li> <li> <p><code>iZeCa0gaey.html</code>: HTML views per tool</p> </li> <li><code>quantilePlot-*</code>: score-based quantile plots as visualization of the results</li> <li><code>quantilePlotShow.gp</code>: example Gnuplot script to generate a plot</li> <li> <p><code>score*</code>: accumulated score results in various formats</p> </li> </ul> <p>The hashes of the file names (in the files <code>*.json.gz</code>) are useful for</p> <ul> <li>validating the exact contents of a file and</li> <li>accessing the files from the witness store.</li> </ul> <p>Other Archives</p> <p>Overview over archives from Test-Comp 2021 that are available at Zenodo:</p> <ul> <li><a href="https://doi.org/10.5281/zenodo.4459466">https://doi.org/10.5281/zenodo.4459466</a> Witness store (containing the generated test suites)</li> <li><a href="https://doi.org/10.5281/zenodo.4459470">https://doi.org/10.5281/zenodo.4459470</a> Results (XML result files, log files, file mappings, HTML tables)</li> <li><a href="https://doi.org/10.5281/zenodo.4459132">https://doi.org/10.5281/zenodo.4459132</a> Test tasks, version testcomp21</li> <li><a href="https://doi.org/10.5281/zenodo.4317433">https://doi.org/10.5281/zenodo.4317433</a> BenchExec, version 3.6</li> </ul> <p>All benchmarks were executed for Test-Comp 2021 <a href="https://test-comp.sosy-lab.org/2021/">https://test-comp.sosy-lab.org/2021/</a><br> by Dirk Beyer, LMU Munich, based on the following components:</p> <ul> <li><a href="https://gitlab.com/sosy-lab/test-comp/archives-2021">https://gitlab.com/sosy-lab/test-comp/archives-2021</a> testcomp21-0-gdacd4bf</li> <li><a href="https://gitlab.com/sosy-lab/software/sv-benchmarks">https://gitlab.com/sosy-lab/software/sv-benchmarks</a> testcomp21-0-gefea738258</li> <li><a href="https://gitlab.com/sosy-lab/software/benchexec">https://gitlab.com/sosy-lab/software/benchexec</a> 3.6-0-gb278ebbb</li> <li><a href="https://gitlab.com/sosy-lab/benchmarking/competition-scripts">https://gitlab.com/sosy-lab/benchmarking/competition-scripts</a> testcomp21-0-g8339740</li> <li><a href="https://gitlab.com/sosy-lab/test-comp/bench-defs">https://gitlab.com/sosy-lab/test-comp/bench-defs</a> testcomp21-0-g9d532c9</li> </ul> <p>Contact</p> <p>Feel free to contact me in case of questions: <a href="https://www.sosy-lab.org/people/beyer/">https://www.sosy-lab.org/people/beyer/</a></p>
Results for 2,230 UK Biobank binary and continuous traits
<p>Results for 2,230 UK Biobank binary and continuous traits. </p> <p>We applied the gene-based tests (Gene1D, Gene3D, GeneScan1D and GeneScan3D) to 1,403 UK Biobank binary phecodes and 827 continuous phenotypes (797 continuous traits + 30 biomarkers) using GWAS summary statistics on 28 million imputed variants. </p> <p>The results are in 3 different zipped folders: 'GeneScan3D_UKBB_1403binary_results.zip', 'GeneScan3D_UKBB_797continuous_results.zip' and 'GeneScan3D_UKBB_30biomarkers_results.zip'. A list of all 2,230 binary and continuous phenotypes is available in excel file 'UKBB_phenotype_description.xlsx'.</p> <p>Reference: Ma, S., Dalgleish, J. L ., Lee, J., Wang, C., Liu, L., Gill, R., Buxbaum, J. D., Chung, W., Aschard, H., Silverman, E. K., Cho, M. H., He, Z. and Ionita-Laza, I. "Improved gene-based testing by integrating long-range chromatin interactions and knockoff statistics", 2021</p>
Evaluation results for When a Computer Cracks a Joke: Automated Generation of Humorous Headlines
<p>Evaluation results for the paper:</p> <p>Alnajjar, K., & Hämäläinen, M. (2021) When a Computer Cracks a Joke: Automated Generation of Humorous Headlines. In<em> The Proceedings of the Twelfth International Conference on Computational Creativity, ICCC’21</em>.</p> <p>The table has the aggregated evaluation results for each evaluation question. The left and right columns are the title before and after the replacement word. The replacement column show the humorous word and original column the word that existed in the headline before the replacement. The system column indicates whether the humorous headline was produced by our system or by a human.</p>
Checkbot API raw results from Libraries, Archives and Museums websites for evaluating a data-driven Search Engine Optimization methodology
<p>Results from Checkbot API to measure and collect 341 websites compatibility on multiple SEO variables (34 variables). Checkbot API indexes the website's code to find features capable of impacting SEO performance. Each website has been tested with the maximum number of links allowed to be crawled equally to 10.000 per test. In this way, we retrieved data about the overall websites performance including their sub-pages, and not only the main domain names. A scale from 0 (lowest rate) to 100 (highest rate) was adopted for each examined variable. This constitutes a useful managerial indicator of dealing with the quantification of websites performance while avoiding complex measurement systems that are difficult to be adopted by administrators. Websites tested were also categorized by the CMS type used. More information about the variables and the meaning of the results can be found at https://www.checkbot.io/ </p>
OWL Reasoner Evaluation Results
<p>Correctness, performance and energy impact evaluation results produced with <a href="http://swot.sisinflab.poliba.it/evowluator">evOWLuator</a> for the following OWL reasoners:</p><ul><li><a href="https://bitbucket.org/dtsarkov/factplusplus">Fact++</a> (version 1.6.5);</li><li><a href="http://www.hermit-reasoner.com">HermiT</a> (version 1.3.8);</li><li><a href="http://jfact.sourceforge.net">JFact</a> (version 1.2.1);</li><li><a href="https://www.derivo.de/en/products/konclude/">Konclude</a> (version 0.6.2-544);</li><li><a href="http://swot.sisinflab.poliba.it/minime">Mini-ME</a> (version 2.0);</li><li><a href="http://swot.sisinflab.poliba.it/minime-swift">Mini-ME Swift</a> (version 1.0);</li><li><a href="https://github.com/stardog-union/pellet">Pellet</a> (version 2.3.1);</li><li><a href="http://trowl.org">TrOWL</a> (version 1.5).</li></ul><p>Ontologies mentioned in the csv files are part of the <a href="https://zenodo.org/record/10791">ORE 2014 Reasoner Competition</a> and <a href="https://bioportal.bioontology.org">BioPortal</a> datasets.</p><p><strong>Publication:</strong> <a href="http://sisinflab.poliba.it/Publications/2021/SBRGL21">A multiplatform energy-aware OWL reasoner benchmarking framework</a></p>
Archaeobotanical results from Mitchelstown 1, Cork, ireland
<p>.csv file with results of archaeobotanical analysis from Mitchelstown 1, Cork, Ireland</p>
Archaeobotanical results from Gortore , Cork, Ireland
<p>Dataset with results from identified charred plant remains from Gortore 1, Cork Ireland. These were from samples taken during the excavation of an Early Neolithic house, from a Bronze Age pit and from miscellaneous features which potentially date to a much later period, such as a ditch.See the plant remains report (http://dx.doi.org/10.6084/m9.figshare.928161) and the excavation report (http://eachtra.ie/new_site/wp-content/uploads/2010/07/E2119Gortore-N8RF.pdf) for more details.</p>
Archaeobotanical results from Caherdrinny 3, Co. Cork, Ireland
<p>Identified charred plant remains from a multi-period site in north Cork, Ireland saved as a .csv file.</p>
Archaeobotanical results from Ballynamona 2, Cork, Ireland
<p>.csv file containing the results of archaeobotanical analysis on samples from a Middle/Late Bronze Age site at Ballynamona, County Cork, Ireland. This dataset has been peer-reviewed and, as a result, has been subject to minor modifications. This version supersedes the version published at DOI:10.5281/zenodo.7701 (https://zenodo.org/record/7701#.UuUbjtJFDwc).</p> <p> </p>
Reconstruction Algorithms in Undersampled AFM Imaging - results
<p>This data set contains numerical simulation results from experiments for the paper "Review of compressed sensing reconstruction algorithms in AFM cell imaging", submitted to IEEE Journal of Selected Topics in Signal Processing.</p> <p>The data set consists of an HDF5 file containing the simulation results as well as MD5 and SHA checksums of the HDF5 database for validating the integrity of the data after download.</p> <p>The data set is licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/).</p> <p>Python scripts used for producing these results as well as Python scripts for extracting images and data used in the accompanying paper from the database can be found in the accompanying deposition http://doi.org/10.5281/zenodo.18745.</p> <p>The data set contains images, and reconstructed versions of these, originally published in the data set available at http://dx.doi.org/10.5281/zenodo.17573.</p>
Benchmark Hypergraphs and Detailed Experimental Results of "k-way Hypergraph Partitioning via n-Level Recursive Bisection"
<p>This dataset contains hypergraphs derived from three benchmark sets: The<br /> ISPD98 VLSI Circuit Benchmark Suite [1], the University of Florida Sparse Matrix Collec-<br /> tion [2] and the international SAT Competition 2014 [3]. From the latter, we randomly selected<br /> 100 instances from the application track and converted them into hypergraphs as follows:<br /> Each boolean variable (and its complement) is mapped to one vertex and each clause constitutes<br /> a net [41]. The Sparse Matrix Collection is organized into 172 groups and each group contains<br /> matrices of different application areas. From each group, we choose one matrix for each appli-<br /> cation area that has between 10 000 and 10 000 000 columns. In case multiple matrices fulfill<br /> our criteria, we randomly select one. In total, we include 192 matrices, which are translated into<br /> hypergraphs using the row-net model, i.e. each row is treated as a net and each column as<br /> a vertex. Empty rows are discarded. Both vertices and nets have unit weight. Together with the<br /> 18 ISPD98 VLSI instances , a total of 310 hypergraphs constitute our benchmark set. 4 Each of<br /> these hypergraphs is partitioned into k ∈ {2, 4, 8, 16, 32, 64, 128} blocks with ε = 0.03. For each<br /> value of k, a k-way partition is considered to be one test instance, resulting in a total of 2170<br /> instances.</p> <p>See the README for further information on the different files contained in this dataset.</p> <p>[1 ]C. J. Alpert. The ISPD98 Circuit Benchmark Suite. In Proc. of the 1998 Int. Symp. on Physical Design, ISPD ’98, pages 80–85, New York, 1998. ACM.<br /> [2] T. A. Davis and Y. Hu. The University of Florida Sparse Matrix Collection. ACM Trans. Math. Softw.,38(1):1:1–1:25, 2011.<br /> [3] A. Belov, D. Diepold, M. Heule, and M. Järvisalo. The SAT Competition 2014. http://www.satcompetition.org/2014/, 2014.</p>
Reconstruction Algorithms in Undersampled AFM Imaging - final results
<p>This data set contains numerical simulation results from experiments for the paper "Reconstruction Algorithms in Undersampled AFM<br /> Imaging", published in IEEE Journal of Selected Topics in Signal Processing.</p> <p>The data set consists of a set of HDF5 files containing the simulation results as well as MD5 and SHA checksums of the HDF5 databases for validating the integrity of the data after download.</p> <p>The data set is licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/).</p> <p>Python scripts used for producing these results as well as Python scripts for extracting images and data used in the accompanying paper from the database can be found in the accompanying deposition http://dx.doi.org/10.5281/zenodo.32959.</p> <p>The data set contains images, and reconstructed versions of these, originally published in the data set available at http://dx.doi.org/10.5281/zenodo.17573.</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.