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2,373 results for “Platform”
Data from: The BumbleBox: An open-source platform for quantifying behavior in bumblebee colonies
Open the record for dataset details and reuse information.
Santa Barbara Channel fish and invertebrate surveys at oil and gas platforms
Dataset contains occurrences of fish and invertebrates at nine oil and gas platforms between 1995 and 2011 in the southern California (Pt. Arguello to Long Beach). Observations were collected using a manned submersible at depths ranging from 29 – 224 meters (95 - 739 feet). Data are organized into two tables: (1) the fish count (1995-2000) and (2) the invertebrate count (1997-2011). Fish surveys were conducted primarily at nine Platforms (Irene, Hidalgo, Harvest, Hermosa, Holly, Gilda, Grace, Gina, Gail) in the Santa Barbara Channel and Santa Maria Basin. Invertebrate surveys were collected at these nine platforms plus Platform Edith, located off Long Beach (1998) and partial submersible surveys were completed around Platforms C, B, A, Hillhouse, Henry, Houchin, Hogan, and Habitat (2000). See additional methods under “Methods” and citations therein. The Santa Barbara Channel and Santa Maria Basin are situated in a dynamic marine transition zone between the regional flow patterns of central and southern California. The Santa Barbara Channel is about 100 km long by about 50 km wide (60 x 20 miles) and is bordered on the south by the Northern Channel Islands (San Miguel, Santa Rosa, Santa Cruz, and Anacapa). The smaller Santa Maria Basin is located off Pt. Arguello to the northwest. The entire area is bathed in a complex hydrographic system of currents and water masses. The convergence of different water masses in the Santa Barbara Channel results in relatively large scale fluctuations in physical parameters (e.g., temperature, salinity, oxygen, and nutrient concentrations) and biotic assemblages (e. g., flora and fauna).
Santa Barbara Channel fish surveys at shallow regions of oil and gas platforms (SCUBA)
This dataset included fish counts that were surveyed in the shallow sections (0 – 40 meters) of the oil and gas platforms using Scuba. The oil and gas platforms are located in the Santa Barbara Channel, California, USA. Each of the eleven platforms (GILDA, GINA, HOLLY, IRENE, HERMOSA, HIDALGO, GAIL, GRACE, HARVEST, C, and HENRY) were surveyed multiple times a year from 1995 to 2000. This scuba project was conducted and reported under a cooperative agreement (Agreement 1445-CA09-95-0836) between the U. S. Geological Survey (Biological Resources Division) and the University of California, Santa Barbara. Citation of report: Love, M. S., D. M. Schroeder, and M. M. Nishimoto. 2003. The ecological role of oil and gas production platforms and natural outcrops on fishes in southern and central California: a synthesis of information. U. S. Department of the Interior, U. S. Geological Survey, Biological Resources Division, Seattle, Washington, 98104, OCS Study MMS 2003-032. http://www.lovelab.id.ucsb.edu/Report.pdf These fish surveys at platforms were conducted within a few days of surveys at rock outcrops; the data can be viewed at: https://portal.lternet.edu/nis/mapbrowse?scope=edi&identifier=112 The deeper sections of the oil platform were surveyed using the research submarine Delta; the data can be viewed at: https://portal.lternet.edu/nis/mapbrowse?scope=edi&identifier=111
Piveau: A Large-scale Open Data Management Platform based on Semantic Web Technologie
<p>This file contains the sources that were used to create the feature comparison in "Piveau: A Large-scale Open Data Management Platform based on Semantic Web Technologies".</p>
A Versatile Polymer‐Based Platform for Intracellular Delivery of Macromolecules
<p>The plasma membrane barrier greatly restricts intracellular delivery of macromolecules. Currently available methods suffer from various limitations, including low delivery efficiency, high cytotoxicity, or incompatibility with a wider range of macromolecules or cell types. To overcome these issues, stimuli‐responsive polymers such as the bio‐inspired, pH‐responsive poly(l‐lysine isophthalamide) grafted with l‐phenylalanine at a stoichiometric ratio of 50% (PP50) can be used. In mildly acidic environments, the pseudopeptidic polymer can permeabilize the plasma membrane overcoming the problem of payload entrapment in the endosomes and allowing for efficient intracellular delivery. It is demonstrated that PP50 is capable of intracellular delivery by simple co‐incubation at pH 6.5 with various macromolecules, including different‐sized Dextrans, green fluorescent protein (GFP), and an apoptotic peptide. The delivery process is fast, nontoxic, and compatible with multiple cell types, including adherent and suspension cell lines, primary human mesenchymal stem cells, and cells grown as spheroids. In addition, apoptotic peptide delivery by co‐incubation with PP50 is over three times more effective than delivery using other common methods, including poly(ethyleneimine) (PEI), cell penetrating peptides (CPPs), and electroporation. The findings suggest that payload delivery by co‐incubation with PP50 is a flexible, controllable method allowing delivery of various payloads to many different cell types in vitro.</p>
Are developers losing interest on my project? An initial study on unstar events on GitHub platform
<p>GitHub is the most popular social coding platform and the world's largest collection of open source software. In this platform, users can star repositories to manifest their interest or satisfaction with the hosted project. However, it is not possible to maintainers of these projects to know whether they are losing the interest of developers from this platform (i.e., developers are removing their stars). In this paper, we present an initial investigation on how often developers remove stars from GitHub projects and the impact on their popularity. Our results show that GitHub projects frequently lose stars, however these events do not have a major influence on their overall popularity since most of them gain more stars than lose stars. We also show that some programming languages retain the interest from developers for more time.</p>
Data file for paper: Javier Rubio-Garcia; Anthony R J Kucernak, Rutao Liu and Barun K Chakrabarti "Hydrogen/functionalized benzoquinone for a high-performance regenerative fuel cell as a potential large-scale energy storage platform"
<p>The data in this spreadsheet was used to produce the figures in the paperJavier Rubio-Garcia; Anthony R J Kucernak, Rutao Liu and Barun K Chakrabarti "Hydrogen/functionalized benzoquinone for a high-performance regenerative fuel cell as a potential large-scale energy storage platform"Journal of Materials Chemistry A, 2020, DOI: 10.1039/C9TA12396B</p> <p>Please cite the above reference if you wish to use this data</p>
Preprocessed data for find motives behind cross-platform forks from SWHGD dataset
<p>The fork-based development mechanism provides the flexibilityand the unified processes for software teams to collaborate easilyin a distributed setting without too much coordination overhead.Currently, multiple social coding platforms support fork-based de-velopment, such as GitHub, GitLab, and Bitbucket. Although thesedifferent platforms virtually share the same features, they havedifferent emphasis. As GitHub is the most popular platform and thecorresponding data is publicly available, most of the current stud-ies are focusing on GitHub hosted projects. However, we observedanecdote evidences that people are confused about choosing amongthese platforms, and some projects are migrating from one platformto another, and the reasons behind these activities remain unknown.With the advances of Software Heritage Graph Dataset (SWHGD),we have the opportunity to investigate the forking activities acrossplatforms. In this paper, we conduct an exploratory study on 10popular open-source projects to identify cross-platform forks andinvestigate the motivation behind. Preliminary result shows thatcross-platform forks do exist, for the 10 subject systems in thisstudy, we found 81,357 forks in total among which 179 forks areon GitLab. Based on our qualitative analysis we found that most ofthe cross-platform forks that we identified are mirrors of anotherplatform, but we still find cases that were created due to preferenceof using certain functionalities (e.g. Continuous Integration(CI))supported by different platforms. This study lays the foundation offuture research directions, such as understanding the differencesbetween platforms and supporting cross-platform collaboration.</p>
CCoDaMiC: A framework for Coherent Coordination of Data Migration and Computation platforms
<p>This dataset release supports the results presented in the paper</p> <p><strong>Chinmaya Kumar Dehury</strong>, Satish Narayana Srirama, Tek Raj Chhetri, CCoDaMiC: A Framework for Coherent Coordination of Data Migration and Computation Platforms. Future Generation Computer Systems</p> <p>URL: https://www.sciencedirect.com/science/article/pii/S0167739X19330924</p> <p> </p>
Analyzed papers in an open IoT platform systematic mapping study
<p>As part of our systematic mapping study related to Open IoT Platforms, here we present the overall included and analyzed papers for our study. As a process, the papers are classified into five categories, such as used, indicated, proposed, defined and no explanation studies.</p> <p>The result of the classification process is: -use: 134 papers, -indicate: 56 papers -propose: 28 papers, -define: 3 papers, and -no explanation: 59 papers</p>
Classificação of WADI events for different monitoring platforms
<p>Boolean classification of WADI leak events in SCP and EDIAs's water distribution network areas during 2019 against the type of remote platform: UAV and MAV.</p>
FUNCERT - Registration dynamics and course certification rates on a Massive Open Online Course (MOOC) platform
<p>The FUNCERT data set describes 1 million course registration events collected over a 2-year period from the MOOC platform FUN (France Université Numérique, fun-mooc.fr). Each registration event is associated with a timestamp and an indication of whether a completion certificate was ultimately awarded. It was used in the referenced manuscript to model the impact of multiple course registrations on certificate rates.</p> <p>The data set is provided as a single file (FUNCERT.csv) with the following fields.</p> <p><strong>Time (min)</strong> The time of the registration event reported in minutes elapsed since the beginning of data collection. The time stamp is reported as a relative time only, not an exact calendar date, to enhance anonymization.</p> <p><strong>User ID</strong> A unique ID number for each user of the platform during this period. The number has been generated specifically for this data set and does not correspond to user ID numbers used within the FUN platform.</p> <p><strong>Course ID</strong> Each of the 140 offered courses is assigned a unique and anonymous ID code. In some cases courses were offered multiple times within the data collection period. The same Course ID is used across multiple instances of the same course.</p> <p><strong>Certificate</strong> A boolean variable set to 1 if the registration event is associated with a course completion certificate. Of 140 offered courses, 91 awarded certificates during the study period.</p> <p><strong>Age</strong> User age in years at the time of registration. Field may be left blank if data was not provided.</p> <p><strong>Gender</strong> User gender as selected from the options m and f. Field may be left blank if data was not provided.</p>
The Alginate Immobilization of Metabolic Enzymes (AIME) platform retrofits an estrogen receptor transactivation assay with metabolic competence
The U.S. EPA Endocrine Disruptor Screening Program utilizes data across the ToxCast/Tox21 high-throughput screening (HTS) programs to evaluate the biological effects of potential endocrine active substances (EAS). A potential limitation to the use of in vitro assay data in regulatory decision-making is the lack of coverage for xenobiotic metabolic processes. Both hepatic- and peripheral-tissue metabolism can yield metabolites that exhibit greater activity than the parent compound (bioactivation) or are inactive (bioinactivation) for a given biological target. Interpretation of biological effect data for both putative EAS, as well as other chemicals, screened in HTS assays may benefit from the addition of xenobiotic metabolic capabilities to decrease the uncertainty in predicting potential hazards to human health. The objective of this study was to develop an approach to retrofit existing HTS assays with hepatic metabolism. The Alginate Immobilization of Metabolic Enzymes (AIME) platform encapsulates hepatic S9 fractions in alginate microspheres attached to 96-well peg lids. Functional characterization across a panel of reference substrates for phase I cytochrome P450 enzymes revealed substrate depletion with expected metabolite accumulation. Performance of the AIME method in the VM7Luc estrogen receptor (ER) transactivation assay was evaluated across 15 reference chemicals and 48 test chemicals that yield metabolites previously identified as ER active or inactive. The results demonstrate the utility of applying the AIME method for identification of false positive and false negative target assay effects, reprioritization of hazard based on metabolism-dependent bioactivity, and enhanced in vivo concordance with the rodent uterotrophic bioassay. Integration of the AIME metabolism method may prove useful for future biochemical and cell-based HTS applications.
ACloud platform
<p>The platform that has been implemented during EIT Manufacturing ACloud project</p> <p>http://acloudproject.eu/</p> <p> </p>
ABOME: A Multi-platform Data Repository of Artificially Boosted Online Media Entities
<p><strong>Motivation</strong></p> <p>The rise of online media has enabled users to choose various unethical and artificial ways of gaining social growth to boost their credibility (number of followers/retweets/views/likes/subscriptions) within a short time period. In this work, we present ABOME, a novel data repository consisting of datasets collected from multiple platforms for the analysis of blackmarket-driven collusive activities, which are prevalent but often unnoticed in online media. ABOME contains data related to tweets and users on Twitter, YouTube videos, YouTube channels. We believe ABOME is a unique data repository that one can leverage to identify and analyze blackmarket based temporal fraudulent activities in online media as well as the network dynamics.</p> <p><strong>License</strong></p> <p>Creative Commons License.</p> <p><strong>Description of the dataset</strong></p> <p>In this work, we focused on collecting data from credit-based freemium services. We divide the datasets into two parts:</p> <p><strong>- Historical Data (</strong><strong>historical_anon.zip</strong><strong>)</strong></p> <p>This consists of all the data for Twitter and YouTube from blackmarket services gathered via sequential querying of the website’s URLs between the period March-June, 2019. We collected the metadata of each entity present in the historical data.</p> <p><strong>Twitter:</strong></p> <p>We collected the following fields for retweets and followers on Twitter:</p> <p><code>user_details</code>: A JSON object representing a Twitter user.</p> <p><code>tweet_details</code>: A JSON object representing a tweet.</p> <p><code>tweet_retweets</code>: A JSON list of tweet objects representing the most recent 100 retweets of a given tweet.</p> <ol> <li> <p><a href="https://developer.twitter.com/en/docs/tweets/data-dictionary/overview/user-object">https://developer.twitter.com/en/docs/tweets/data-dictionary/overview/user-object</a><a href="#fnref1">↩︎</a></p> </li> <li> <p><a href="https://developer.twitter.com/en/docs/tweets/data-dictionary/overview/tweet-object">https://developer.twitter.com/en/docs/tweets/data-dictionary/overview/tweet-object</a><a href="#fnref2">↩︎</a></p> </li> </ol> <p><strong>YouTube:</strong></p> <p>We collected the following fields for YouTube likes and comments:</p> <p><code>is_family_friendly:</code> Whether the video is marked as family friendly or not.</p> <p><code>genre:</code> Genre of the video.</p> <p><code>duration:</code> Duration of the video in ISO 8601 format (duration type). This format is generally used when the duration denotes the amount of intervening time in a time interval.</p> <p><code>description:</code> Description of the video.</p> <p><code>upload_date:</code> Date that the video was uploaded.</p> <p><code>is_paid:</code> Whether the video is paid or not.</p> <p><code>is_unlisted:</code> The privacy status of the video, i.e., whether the video is unlisted or not. Here, the flag <em>unlisted</em> indicates that the video can only be accessed by people who have a direct link to it.</p> <p><code>statistics:</code> A JSON object containing the number of dislikes, views and likes for the video.</p> <p><code>comments:</code> A list of comments for the video. Each element in the list is a JSON object of the text (<em>the comment text</em>) and time (<em>the time when the comment was posted</em>).</p> <p>We collected the following fields for YouTube channels:</p> <p><code>channel_description:</code> Description of the channel.</p> <p><code>hidden_subscriber_count:</code> Total number of hidden subscribers of the channel.</p> <p><code>published_at:</code> Time when the channel was created. The time is specified in ISO 8601 format (YYYY-MM-DDThh:mm:ss.sZ).</p> <p><code>video_count:</code> Total number of videos uploaded to the channel.</p> <p><code>subscriber_count:</code> Total number of subscribers of the channel.</p> <p><code>view_count:</code> The number of times the channel has been viewed.</p> <p><code>kind:</code> The API resource type (e.g., <em>youtube#channel</em> for YouTube channels).</p> <p><code>country:</code> The country the channel is associated with.</p> <p><code>comment_count:</code> Total number of comments the channel has received.</p> <p><code>etag:</code> The ETag of the channel which is an HTTP header used for web browser cache validation.</p> <p>The historical data is stored in five directories named according to the type of data inside it. Each directory contains JSON files corresponding to the data described above. <strong>'historical_sample.zip'</strong> contains a small sample of the historical dataset.</p> <p>- <strong>Time-series Data (time_series_anon.zip)</strong></p> <p>This consists of time-series data (collected every 8 hours) of Twitter users and tweets collected from the blackmarket services between the period of March-June, 2019. We collect the following time-series data for retweets and followers on Twitter:</p> <p><code>user_timeline</code>: This is a JSON list of tweet objects in the user’s timeline, which consists of the tweets posted, retweeted and quoted by the user. The file created at each time interval contains the new tweets posted by the user during each time interval.</p> <p><code>user_followers</code>: This is a JSON file containing the user ids of all the followers of a user that were added or removed from the follower list during each time interval.</p> <p><code>user_followees</code>: This is a JSON file consisting of the user ids of all the users followed by a user, i.e., the followees of a user, that were added or removed from the followee list during each time interval.</p> <p><code>tweet_details</code>: This is a JSON object representing a given tweet, collected after every time interval.</p> <p><code>tweet_retweets</code>: This is a JSON list of tweet objects representing the most recent 100 retweets of a given tweet, collected after every time interval.</p> <p>The time-series data is stored in directories named according to the timestamp of the collection time. Each directory contains sub-directories corresponding to the data described above. <strong>'time_series_sample.zip'</strong> contains a small sample of the time series dataset.</p> <p><strong>Data Anonymization</strong></p> <p>The data is anonymized by removing all Personally Identifiable Information (PII) and generating pseud-IDs corresponding to the original IDs. A consistent mapping between the original and pseudo-IDs is maintained to maintain the integrity of the data.</p> <p> </p>
Data from: Genomic prediction accuracies in space and time for height and wood density of Douglas-fir using exome capture as the genotyping platform
Background Genomic selection (GS) can offer unprecedented gains, in terms of cost efficiency and generation turnover, to forest tree selective breeding; especially for late expressing and low heritability traits. Here, we used: 1) exome capture as a genotyping platform for 1372 Douglas-fir trees representing 37 full-sib families growing on three sites in British Columbia, Canada and 2) height growth and wood density (EBVs), and deregressed estimated breeding values (DEBVs) as phenotypes. Representing models with (EBVs) and without (DEBVs) pedigree structure. Ridge regression best linear unbiased predictor (RR-BLUP) and generalized ridge regression (GRR) were used to assess their predictive accuracies over space (within site, cross-sites, multi-site, and multi-site to single site) and time (age-age/ trait-trait). Results The RR-BLUP and GRR models produced similar predictive accuracies across the studied traits. Within-site GS prediction accuracies with models trained on EBVs were high (RR-BLUP: 0.79–0.91 and GRR: 0.80–0.91), and were generally similar to the multi-site (RR-BLUP: 0.83–0.91, GRR: 0.83–0.91) and multi-site to single-site predictive accuracies (RR-BLUP: 0.79–0.92, GRR: 0.79–0.92). Cross-site predictions were surprisingly high, with predictive accuracies within a similar range (RR-BLUP: 0.79–0.92, GRR: 0.78–0.91). Height at 12 years was deemed the earliest acceptable age at which accurate predictions can be made concerning future height (age-age) and wood density (trait-trait). Using DEBVs reduced the accuracies of all cross-validation procedures dramatically, indicating that the models were tracking pedigree (family means), rather than marker-QTL LD. Conclusions While GS models' prediction accuracies were high, the main driving force was the pedigree tracking rather than LD. It is likely that many more markers are needed to increase the chance of capturing the LD between causal genes and markers.
Data from: Marine communities on oil platforms in Gabon, West Africa: high biodiversity oases in a low biodiversity environment
The marine biodiversity of Gabon, West Africa has not been well studied and is largely unknown. Our examination of marine communities associated with oil platforms in Gabon is the first scientific investigation of these structures and highlights the unique ecosystems associated with them. A number of species previously unknown to Gabonese waters were recorded during our surveys on these platforms. Clear distinctions in benthic communities were observed between older, larger platforms in the north and newer platforms to the south or closer to shore. The former were dominated by a solitary cup coral, Tubastraea sp., whereas the latter were dominated by the barnacle Megabalanus tintinnabulum, but with more diverse benthic assemblages compared to the northerly platforms. Previous work documented the presence of limited zooxanthellated scleractinian corals on natural rocky substrate in Gabon but none were recorded on platforms. Total estimated fish biomass on these platforms exceeded one ton at some locations and was dominated by barracuda (Sphyraena spp.), jacks (Carangids), and rainbow runner (Elagatis bipinnulata). Thirty-four percent of fish species observed on these platforms are new records for Gabon and 6% are new to tropical West Africa. Fish assemblages closely associated with platforms had distinct amphi-Atlantic affinities and platforms likely extend the distribution of these species into coastal West Africa. At least one potential invasive species, the snowflake coral (Carijoa riisei), was observed on the platforms. Oil platforms may act as stepping stones, increasing regional biodiversity and production but they may also be vectors for invasive species. Gabon is a world leader in terrestrial conservation with a network of protected areas covering >10% of the country. Oil exploration and biodiversity conservation currently co-exist in terrestrial and freshwater ecosystems in Gabon. Efforts to increase marine protection in Gabon may benefit by including oil platforms in the marine protected area design process.
Data from: Trepostomate bryozoans from the upper Katian (Upper Ordovician) of Morocco: gigantism in high latitude Gondwana platforms
A study of the Upper Ordovician trepostomate bryozoans belonging to the families Amplexoporidae and Monticuliporidae, from the eastern Anti-Atlas of Morocco, is presented here. They occur in the marly to fine-grained limestone, intermediate unit of the Khabt-el-Hajar Formation, late Katian in age, representing outer-ramp depositional environments. They inhabited the highest paleolatitude known for a bryozoan fauna during the Ordovician, estimated at more than 65–70ºS. A total of 11 species of the genera Anaphragma, Atactoporella, Homotrypa, Monotrypa, Monticulipora, and Prasopora are described. Three species are already known from the equatorial-tropical paleocontinents of Baltica, Laurentia, and Siberia: Anaphragma mirabile, Monotrypa jewensis, and Prasopora falesi. Four new taxa are described:Anaphragma undulata, Atactoporella moroccoensis, Monticulipora globulata, and Monticulipora irregularis. The two species of Anaphragma and the one of Atactoporella display significantly larger zoarial sizes than congeneric species, representing gigantism among bryozoans. Polar gigantism is rejected for the two species of Anaphragma as is gigantism related to photosynthetic endosymbionts. An alternative proposal for their giant size is their long zoarial life span due to their well-balanced, robust branching form, with a relatively wide basal supporting surface, adapted to unconsolidated substrates in environments below wave base. Their great stability in outer-ramp environments, with infrequent storms, would allow the zoaria to grow for an extended time and reach large sizes before being overturned and buried. Atactoporella moroccoensis, has both zoaria and zooecia gigantic, suggesting a hypothesis of polar gigantism.
Data from: Massively parallel multiplex DNA sequencing for specimen identification using an Illumina MiSeq platform
Genetic information is a valuable component of biosystematics, especially specimen identification through the use of species-specific DNA barcodes. Although many genomics applications have shifted to High-Throughput Sequencing (HTS) or Next-Generation Sequencing (NGS) technologies, sample identification (e.g., via DNA barcoding) is still most often done with Sanger sequencing. Here, we present a scalable double dual-indexing approach using an Illumina Miseq platform to sequence DNA barcode markers. We achieved 97.3% success by using half of an Illumina Miseq flowcell to obtain 658 base pairs of the cytochrome c oxidase I DNA barcode in 1,010 specimens from eleven orders of arthropods. Our approach recovers a greater proportion of DNA barcode sequences from individuals than does conventional Sanger sequencing, while at the same time reducing both per specimen costs and labor time by nearly 80%. In addition, the use of HTS allows the recovery of multiple sequences per specimen, for deeper analysis of genetic variation in target gene regions.
Data from: An automated platform for high-throughput mouse behavior and physiology with voluntary head-fixation
Recording neural activity during animal behavior is a cornerstone of modern brain research. However, integration of cutting-edge technologies for neural-circuit analysis with complex behavioral measurements poses a severe experimental bottleneck for researchers. Critical problems include a lack of standardization for psychometric and neurometric integration, and lack of tools that can generate large, sharable datasets for the research community in a time and cost effective way. Here, we introduce a novel mouse behavioral-learning platform featuring voluntary head fixation and automated high throughput data collection for integrating complex behavioral assays with virtually any physiological device. We provide experimental validation by demonstrating behavioral training of mice in visual discrimination and auditory detection tasks. To examine facile integration with physiology systems, we coupled the platform to a two-photon microscope for imaging of cortical networks at single-cell resolution. Our behavioral learning and recording platform is a prototype for the next generation of mouse cognitive studies.
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.