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1,580 results for “Vulnerabilities”
Replication Package: Vulnerably (Mis)Configured? Exploring 10 Years of Developers' Q&As on Stack Overflow
<p><strong>Welcome to the public repository for the additional content of the paper "Vulnerably (Mis)Configured? Exploring 10 Years of Developers' Q&As on Stack Overflow", accepted at the International Working Conference on Variability Modelling of Software-Intensive Systems (VAMOS) 2024.</strong></p><p>This repository provides additional information to the conducted exploratory study on configuration-related vulnerabilities, including the following files:</p><ul><li>README.txt</li><li>LICENSE.txt</li><li>DATASET_CONFIG_VULN_SO.csv: sheet containing data of 651 StackOverflow posts, including additional classifications based on manual analyses and automatic topic modeling</li></ul><p><strong>Instructions for using the dataset</strong></p><ol><li>Download and open the dataset (platform-independent CSV file).</li><li>The dataset includes 16 columns (A – P):<br>- Columns A – J: Original data fetched from the BigQuery Stack Overflow dataset (<i>Question_ID, Year_Asked, Question_Title, Question_Body, Question_Tags, View_Count, Question_Rating, Favorite_Count, Status, Answer_Count</i>)<br>- Columns K – N: Manually extracted data from the Stack Overflow posts (<i>System, Configuration Context, Security Context, Topic</i>)<br>- Column O: Data based on the automated topic modeling (<i>Configuration Topic</i>)<br>- Column P: Additional data extracted from the Stack Overflow posts without further classifications (<i>Additional Comments</i>)</li></ol><p><strong>Requirements</strong></p><ul><li>No requirements</li></ul><p><strong>Further information</strong></p><ol><li>The dataset is based on a search string (SQL query; August 1, 2023) applied on the Google BigQuery Stack Overflow dataset:<i> </i><br><i>("secur*") AND ("vulnerabilit*" OR "weakness*" OR "breach*" OR "exposure*" OR "CVE*" OR "CWE*") AND ("config*")</i></li><li>Originally, the dataset included 1,235 post which were limited by the first and second authors to 651 posts (34 deleted posts, 550 posts out of scope) using the following selection criteria: <br>- The post has been created in the last decade (2013-2022).<br>- The post is still available on the Stack Overflow website.<br>- The post is directly connected to a vulnerability-related issue in the context of configuring.</li><li>Topic modeling algorithm used: Latent Dirichlet Allocation (LDA)<br>- Settings: 200 iterations (coherence value = 0.6 for k = 7 to 11), α = k, β = 0.01</li></ol>
Indicators used to calculate the Vulnerability of European wine PDOs to climate change
<p>Dataset of the indicators used to define the Vulnerability of European wine PDO to climate change. The database includes the values of Exposure, Sensitivity and Adaptive Capacity for each PDO region. In the case of Exposure we also included the values for the indicators of Cool Night Iindex, Dryness Index and Huglin index. In the case of Adaptive Capacity we also included all the fifteen indicators used for the assessment of financial, natural, physical, social and human capacity. The classification in one of the Vulnerability classes is included in the related field.</p> <p>Please refer to the following article when citing the dataset:</p> <p>Tscholl, S., Candiago, S., Marsoner, T., Fraga, H., Giupponi, C., & Egarter Vigl, L.Climate resilience of European wine regions. Nat Commun 15, 6254 (2024). https://doi.org/10.1038/s41467-024-50549-w</p>
Negative Complement of a Set of Vulnerability-Fixing Commits: Supplementary Material
<div> <div><span>EASE 2024 - Industry track</span></div> <br> <div><span>This archive contains accompanying materials for the paper: </span></div> <br> <div><span>Rocío Cabrera Lozoya, Antonino Sabetta, Tommaso Aiello. "Negative Complement of a Set of Vulnerability-Fixing Commits: Method and Dataset" </span></div> <br> <div><span>submitted to the Industry track at EASE 2024 - https://conf.researchr.org/track/ease-2024/ease-2024-industry</span></div> <br> <div><span>It contains the following folders and files:</span></div> <br> <div><span>-</span><span> data</span></div> <div><span> </span><span>-</span><span> commit_pairs_final.csv : Dataset of 534 commit pairs corresponding to a positiive (security-relevant) commit and a negative sample obtained by the approach described in the paper.</span></div> <div><span> </span><span>-</span><span> single_positive.csv : Contains a single positive instance (taken from the MSR2019 dataset) which can be used to test the generate_negative_complement.py script.</span></div> <div><span>-</span><span> scripts</span></div> <div><span> </span><span>-</span><span> generate_negative_complement.py : Takes in a single .java file and obfuscates its developer-defined identifiers.</span></div> <div><span> </span><span>-</span><span> obfuscate_java_file.py : Generates a negative complement for a security-relevant dataset. The ouput is written to couple_dataset.csv.</span></div> <div><span> </span><span>-</span><span> requirements.txt : Requirements needed in the virtual environment to successfully run the previous scripts.</span></div> </div>
Just another copy and paste? Comparing the security vulnerabilities of ChatGPT generated code and StackOverflow answers
<div>Supplemental material for the paper "Just another copy and paste? Comparing the security vulnerabilities of ChatGPT generated code and StackOverflow answers" published in DLSP 2024.</div> <div> <div> </div> </div>
A deepened water table increases the vulnerability of peat mosses to periodic drought
<p>Here we address the combined impact of multiple stressors that are becoming more common with climate change. To study the combined effects of a lower water table (WT) and increased frequency of drought periods on the resistance and resilience of peatlands, we conducted a mesocosm experiment. This study evaluated how the photosynthesis of lawn Sphagnum mosses responds to and recovers from an experimental periodic drought after exposure to the stresses of a deep or deepened WT (naturally dry and 17-year-long water level drawdown in fen and bog environments. We aimed to quantify if deep WTs 1) support acclimation to drought, or 2) increase the base-level physiological stress of mosses, or 3) exacerbate the impact of periodic drought. There was no evidence of acclimation in mosses from drier environments; periodic drought decreased the photosynthesis of all Sphagnum mosses. Water level drawdown decreased the photosynthesis of bog-originating mosses before periodic drought, indicating that these mosses were stressed by the hydrological change. Deep WTs exacerbated Sphagnum vulnerability to periodic drought, indicating that the combination of drying habitats and increasing frequency of periodic drought will lead to a rapid transition in lawn vegetation. Water-retaining traits may increase Sphagnum resilience to periodic drought. Large capitula size was associated with a higher resistance; the bog-originating species studied here lacked large capitula or dense carpet structure and were more vulnerable to drought than the larger fen-originating species. Consequently, lawns in bogs may become threatened. Recovery after rewetting was significant for all mosses, but none completely recovered within three weeks. The most drought-resilient species had fen origin, indicating that fens are less likely to undergo a sudden transition due to periodic drought.</p> <p><strong>Synthesis:</strong> Water level drawdown associated with climate change increases the sensitivity of Sphagnum mosses to periods of drought and moves them closer to their tipping point as species on the edge of their ecological envelope rapidly shut down photosynthesis and recover poorly.</p>
Supplementary data for Development of Indicators of Social Vulnerability and Fishing Reliance in English Coastal Communities
<p>Supplementary data for Development of Indicators of Social Vulnerability and Fishing Reliance in English Coastal Communities by Tom Gibson, Chloe Lucas and Angela Muench. Full details are available via the publication and details of folder and file structures are available in the ReadMe file. </p>
VFDelta Vulnerability Fix Dataset
<p>The vulnerability fix dataset of VFDelta contains two datasets used in our study: VFM_2021 and VFM_2023. Refer to our paper for the detail of dataset. We are working on model publishing; please always check for the <strong>newer</strong> <strong>version</strong>.</p> <ul> <li>vfm_2021_train_val.parquet</li> <li>vfm_2021_test.parquet</li> <li>vfm_2023_train_val.parquet</li> <li>vfm_2023_test.parquet</li> <li>eval_vfdelta.ipynb</li> </ul> <p>The commit-level dataset provides meta information of "repo_name", "commit_id", "label". train_val file contains "partition" for the split of training and validation set, and test file contains "vfdelta_predict_proba" which is the predict probability of each commit by VFDelta. </p> <p>To evaluate VFDelta's performance on vfm_2021 and vfm_2023, run <code>eval_vfdelta.ipynb</code>, use the column vfdelta_predict_proba as our prediction result. You can also use them to compare the performance of your prediction results with VFDelta's.</p>
Flood protection and vulnerability estimates for Europe, 1950-2020
<p>This dataset provides estimates of flood protection levels and flood vulnerability at scale of 1422 subnational regions of 42 European countries over the period 1950–2020. Estimates are based on a set of vine-copula models quantified with data on flood impacts from the HANZE catalogue.</p> <p>The dataset contains two ZIP files with a total of five shapefiles, each containing a "Code" column with the code of the subnational region (based mainly on EU's NUTS3, v2010 classification) and other column estimates per each year between 1950 and 2020.</p> <ul> <li>NUTS3_Flood_Protection_coast: estimated flood protection level from coastal floods, as average return period in years between occurrence of significant flood impacts;</li> <li>NUTS3_Flood_Protection_riverine: as above, but for riverine floods;</li> <li>NUTS3_Vulnerability_Fat_comb: estimated actual fatalities from an hypothetical average flood, as % of potential impact under assumption of a static depth-fatality function and no flood protection within region (S-shaped function shown in Jonkman et al. 2008, <a title="Jonkman2008" href="https://doi.org/10.1007/s11069-008-9227-5">https://doi.org/10.1007/s11069-008-9227-5</a>)</li> <li>NUTS3_Vulnerability_Pop_aff: estimated actual population affected from an hypothetical average flood, as % of exposed population under assumption of no flood protection within region</li> <li>NUTS3_Vulnerability_Eco_less: estimated actual direct economic loss (damage to assets) from an hypothetical average flood, as % of potential impact under assumption of static depth-damage functions (from Huizinga et al. 2017, <a title="Huizinga2017" href="https://doi.org/10.2760/16510">https://doi.org/10.2760/16510</a>) and no flood protection within region.</li> </ul> <p>Detailed methodology is explained in the underlying publication. Code and data to reproduce the results are also available on Zenodo (see "Related works").</p> <p>Data can be also viewed on <a title="Natural Hazards" href="https://naturalhazards.eu/">https://naturalhazards.eu/</a></p>
Thesis data: Enhancing Vulnerability Detection: A Comparative Study of Change Identification Methods Across Granularity Levels
<p>Starting dataset used within the thesis; Enhancing Vulnerability Detection: A Comparative Study of Change Identification Methods Across Granularity Levels.</p> <p>Results of manual annotation of and extract of nonPatchTaggedCommitLinks within the NVD CVE dataset.</p>
Dataset for "Towards Centrality and Causality based Vulnerability Propagation Analysis"
<ul> <li> <p><strong><code>aggregated_data.json</code></strong>: This file contains the processed data generated after loading the Goblin Weaver tool. It includes all CVEs, CWEs, and other relevant attributes. Statistical analyses, particularly vulnerability analyses, are performed on this dataset.</p> </li> <li> <p><strong><code>graph_nodes_edges.pkl</code></strong>: This file stores the parsed GraphML-format graph, divided into chunks of nodes and edges to optimize memory usage during computations. All centrality-based measurements are conducted using this file.</p> </li> <li> <p><strong><code>cve_data.csv</code></strong>: This file captures features of nodes along with their one-hop neighbors. It includes attributes such as <code>whether_cve_exists</code>, <code>cve_exists</code>, and <code>cve_num</code>, as well as the source and target nodes involved.</p> </li> <li> <p><strong><code>cve_2_siblings_data.csv</code></strong>: This file documents features of nodes with their two-hop neighbors. It includes attributes like <code>whether_cve_exists</code>, <code>cve_exists</code>, and <code>cve_num</code>, along with details of source nodes and their two-hop neighbor nodes.</p> </li> <li><code><strong>fea_matrix.csv</strong>:</code><code>This file records the matrix of every node based on transformed five types of attributes, including missrelease (freshness missrelease), outdays(freshness outdatedTimeinMs), popularity, speed, and severity. It has been used for correlation analysis. </code></li> </ul>
Replication Package: Asking Security Practitioners: Did You Find the Vulnerable (Mis)Configuration?
<p><strong>Welcome to the public repository for the additional content of the paper "Asking Security Practitioners: Did You Find the Vulnerable (Mis)Configuration?", accepted at the International Working Conference on Variability Modelling of Software-Intensive Systems (VAMOS) 2025.</strong></p> <p>This repository provides additional information to the conducted survey study on configuration-related vulnerabilities, including the following files:</p> <ul> <li>QUESTIONNAIRE_VAMOS2025.csv: sheet containing all questionnaire data and answer options</li> <li>DATA_VAMOS2025.csv: sheet containing data of the 41 participants, including additional codings of free-text answers</li> <li>README.txt: readMe file</li> </ul> <p><strong>Requirements for using the data<br></strong></p> <ul> <li>No requirements</li> </ul> <p><strong>License for using the data<br></strong></p> <p>Creative Commons Attribution 4.0 International</p> <p>The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited.</p> <p>Further information: https://creativecommons.org/licenses/by/4.0/legalcode</p>
A Vulnerability Introducing Commit Dataset for Java: an Improved SZZ Based Approach
<p>This archive file contains the dataset generated from project-KB by applying our two-phase improved SZZ based algorithm for extracting vulnerability introducing commits. The package contains also the two tools (FilterBugIntroder, BugIntroducer) that automates the process.</p>
Database of vulnerability indicators used in the holistic characterization of vulnerability to flash floods in the region of Castilla y León (Spain)
<p>Database containing the vulnerability indicators used in the holistic analysis of vulnerability to flash floods in the region of Castilla y León (Spain), considering all its dimensions (social, economic, ecosystem, physical, institutional and cultural) and components (exposure, susceptibility and resilience). The database contains a total of 496 variables, of which 216 characterize social vulnerability, 180 economic vulnerability, 49 ecosystem vulnerability, 22 physical vulnerability, 23 institutional vulnerability and 6 cultural heritage vulnerability. The Excel file contains two sheets for each vulnerability dimension. The first sheet (whose name is composed with the name of the dimension and the suffix '_Variables') contains the information of the variables, i.e., the names of the municipalities, the province to which they belong and the values of the variables for each municipality. The variables on this sheet are identified as codes, whose definition and description (unit in which they are expressed, reference year of the information, information source and the link to the information) are found on the second sheet of each dimension (suffix '_Data_sources').</p>
World Risk Index - Vulnerability Component 2019
<p>Indicators for assessing human vulnerability to climatic hazards and natural hazards based on the most recent available international data in 2019. The overall indicator system is based on the concept of WRI methodology published in 2011 (https://weltrisikobericht.de/wp-content/uploads/2016/08/WorldRiskReport_2011.pdf). See also for conceptual understanding: https://doi.org/10.1142/S2345737615500037; https://doi.org/10.1142/S2345737616500056</p> <p>Data used in following publications:</p> <p>https://doi.org/10.1016/j.scitotenv.2021.150065</p> <p>https://doi.org/10.1088/1748-9326/ac1f43</p> <p> </p>
Safety of Vulnerable Road Users (VRU's) in Light-Rail Transit (LRT) Environment
<p>Light-rail transit (LRT), which includes modern streetcars, trolleys, and heritage trolleys, is one of the fastest growing modes of public transportation in the United States. To reduce the cost and complexity of construction, most LRT systems have their tracks placed on city streets, in medians, or in separate at-grade rights-of-way with at-grade crossings. Operating light-rail vehicles (LRVs) along these alignments introduces new conflicts and increases the risk of collisions with vulnerable road users (VRUs) including pedestrians, bicyclists, and electric scooter riders.<br> This study has two main objectives: (1) to review and evaluate the existing body of knowledge and the state of practice regarding safety of VRUs in LRT environments; and (2) to synthesize this information and package the results in a “Best Practices Resource Guide” and a companion “PowerPoint Presentation” for use in improving the safety of VRUs in existing LRT systems and advancing the professional capacity of transit workforce. Metropolitan Planning Organizations and State DOTs should also benefit from this resource information in the planning and design of new LRT systems.<br> This report presents a wide range of physical, educational, and enforcement treatments for improving the safety of VRUs in LRT environments. The selection of a particular treatment for use at an LRT grade crossing or station should be based on an engineering study whose scope and complexity depend on local conditions. Factors that should be considered during device selection include 1) pedestrian‐LRV collision experience, 2) pedestrian volumes and peak flow rates, 3) train speeds, frequency of trains, number of tracks, and railroad traffic patterns, 4) sight distances available to pedestrians and LRV operators approaching the crossing, and 5) skew angle, if any, of the crossing relative to the LRT tracks.</p>
Hotspots in the grid: Avian sensitivity and vulnerability to collision risk from energy infrastructure interactions in Europe and North Africa
<p>Wind turbines and power lines can cause bird mortality due to collision or electrocution. The biodiversity impacts of energy infrastructure (EI) can be minimised through effective landscape-scale planning and mitigation. The identification of high-vulnerability areas is urgently needed to assess potential cumulative impacts of EI while supporting the transition to zero-carbon energy.</p> <p>We collected GPS location data from 1,454 birds from 27 species susceptible to collision within Europe and North Africa and identified areas where tracked birds are most at risk of colliding with existing EI. Sensitivity to EI development was estimated for wind turbines and power lines by calculating the proportion of GPS flight locations at heights where birds were at risk of collision and accounting for species' specific susceptibility to collision. We mapped the maximum collision sensitivity value obtained across all species, in each 5x5 km grid cell, across Europe and North Africa. Vulnerability to collision was obtained by overlaying the sensitivity surfaces with density of wind turbines and transmission power lines.</p> <p>Results: Exposure to risk varied across the 27 species, with some species flying consistently at heights where they risk collision. For areas with sufficient tracking data within Europe and North Africa, 13.6% of the area was classified as high sensitivity to wind turbines and 9.4% was classified as high sensitivity to transmission power lines. Sensitive areas were concentrated within important migratory corridors and along coastlines. Hotspots of vulnerability to collision with wind turbines and transmission power lines (2018 data) were scattered across the study region with highest concentrations occurring in central Europe, near the strait of Gibraltar and the Bosporus in Turkey.</p> <p>Synthesis and Applications: We identify the areas of Europe and North Africa that are most sensitive for the specific populations of birds for which sufficient GPS tracking data at high spatial resolution were available. We also map vulnerability hotspots where mitigation at existing EI should be prioritised to reduce collision risks. As tracking data availability improves our method could be applied to more species and areas to help reduce bird-EI conflicts.</p>
A Review of Smart Contract Vulnerability Datasets
<p> Dataset of the studies included and excluded from a review of smart contracts vulnerability datasets.</p>
The metabolic hormone adiponectin affects the correlation between nutritional status and pneumococcal vaccine response in vulnerable indigenous children
<p class="MsoNoSpacing"><strong><span>Background:</span></strong><span> Almost 200 million children worldwide are either undernourished or overweight</span><span>. </span><span>Only a few studies have addressed the effect of variation in nutritional status on vaccine response</span><span>. </span><span>We previously demonstrated an association between stunting and an increased post-vaccination 13-valent pneumococcal conjugate vaccine (PCV13) response. In this prospective study, we assessed to what extent metabolic hormones may be a modifier in the association between nutritional status and PCV13 response.</span></p> <p class="MsoNoSpacing"><strong><span>Methods: </span></strong><span>Venezuelan children aged 6 weeks to 59 months were vaccinated with a primary series of PCV13. Nutritional status and serum levels of leptin, adiponectin and ghrelin were measured upon vaccination and their combined effect on serum post-vaccination antibody concentrations was assessed by generalized estimating equations multivariable regression analysis.</span></p> <p class="MsoNoSpacing"><strong><span>Results:</span></strong><span> A total of 210 children were included, of whom 80 were stunted, 81 had a normal weight and 49 were overweight. Overweight children had lower post-vaccination antibody concentrations than normal weight children </span><span>(regression coefficient -1.15, 95% CI -2.22 – -0.072)</span><span>. Additionally, there was a significant adiponectin-nutritional status interaction. In stunted children, higher adiponectin serum concentrations were associated with lower post-PCV13 antibody concentrations </span><span>(regression coefficient -0.19, 95% CI -0.24 – -0.14) </span><span>while the opposite was seen in overweight children </span><span>(regression coefficient 0.14, 95% CI 0.049 – 0.22)</span><span>. </span></p> <p><strong><span>Conclusion:</span></strong><span> Metabolic hormones, in particular adiponectin, may modify the effect of nutritional status on pneumococcal vaccine response. These findings emphasize the importance of further research to better understand the immunometabolic pathways underlying vaccine response and enable a future of optimal personalized vaccination schedules.</span></p>
Micro and macroclimatic constraints on the activity of a vulnerable tortoise: a mechanistic approach under a thermal niche view
<p>1. Thermal constraints imposed by the environment limit the activity time of ectotherms and have been a central issue in ecophysiology. Assessing these restrictions is key to determining the vulnerability of species to changing thermal niches and developing conservation strategies. 2. We generate an explicit tortoise model of thermal constraints at both micro and macroclimate scales based on thermophysiology parameters and environmental operative temperatures during a biologically significant period. As a study model, we use a vulnerable species of gopher tortoise (Gopherus evgoodei), whose primary habitat is the tropical dry forests in northwestern Mexico. 4. Our mechanistic model is based on a monitoring of 5-years of environmental operative temperatures (Te). Here, we use the hours of activity (ha) and hours of thermal restriction (hr), calculated from the voluntary temperature range of G. evgoodei with respect to Te, to project and compare the thermal constraints across space and time. In addition, this model was projected using a pessimistic climate change scenario for 2070 (RCP 8.5). 5. The results show that the period of activity of G. evgoodei, predicted by ha and hr, is limited by the frequency and availability of Te and differs significantly throughout the year and among years. In addition, under the RCP 8.5 scenario, we predict that hr will increase considerably and exceed the critical value (3.11 hr) placing this species as highly vulnerable. 6. We discuss and compare the period of potential activity, thermoregulation strategies, and costs and benefits with other Gopherus species. Finally, we identify critical areas to develop management strategies for protecting this Mexican endemic tortoise.</p>
Data for NHESS manuscript by Biass et al. (2022): Insights into the vulnerability of vegetation to tephra fallouts from interpretable machine learning and big Earth observation data
<p>This repository contains the data produced in the context of the following paper:</p> <blockquote> <p>Biass S, Jenkins SF, Aberhard WH, Delmelle P, Wilson T (2022): Insights into the vulnerability of vegetation to tephra fallouts from interpretable machine learning and big Earth observation data, Accepted in NHESS</p> </blockquote> <p>Naming convention is: `run_date`_`landcover`_`impact_metrics`_`VI`_`anomaly`_test.pkl, where:</p> <ul> <li>Landcover is either crops, shrubs, herbaceous vegetation (grass), forests (trees) or all together</li> <li>Impact metrics is either minV (impact magnitude) or minT (impact duration)</li> <li>VI is the vegetation index (here, EVI)</li> <li>Anomaly is the impact indicator (here, cumulative difference index)</li> </ul> <p>Refer to the associated paper for more information on the methodology.</p> <p>Files are saved as .pkl and were generated by the <a href="https://explainerdashboard.readthedocs.io/en/latest/">explainerdashboard</a> library. They are the result of <a href="https://xgboost.readthedocs.io/en/stable/">XGBoost</a> runs that were optimised with <a href="https://optuna.org">Optuna</a> and analysed with the <a href="https://shap.readthedocs.io/en/latest/">SHAP</a> library. They contain:</p> <ol> <li>The explanatory variables and observed and computed target variables for all features</li> <li>The SHAP values</li> </ol> <p>To load the files, use <a href="https://explainerdashboard.readthedocs.io/en/latest/cli.html?highlight=load#explainerdashboard.explainers.BaseExplainer.from_file">this method</a>.</p> <p> </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.