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95 results for “research methods”

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zenodo48/100

Finite element method (FEM) models for translational research in non-invasive brain stimulation

<p>Finite element method (FEM) models for non-invasive brain stimulation modeling using SimNIBS or other compatible software.<br> The mouse and monkey models are described in detail in Alekseichuk et al., Comparative modeling of transcranial magnetic and electric stimulation in mouse, monkey, and human, NeuroImage 2019.<br> The Petri dish model follows a typical experimental setup for in-vitro TMS, similar to what is described in Lenz et al. Repetitive magnetic stimulation induces plasticity of inhibitory synapses, Nature Communications 2016.<br> <br> The following files are included:<br> 1. Brain tissue slice in a Petri dish.<br> 2. Normal adult male nude mouse &quot;Digimouse&quot; (brain volume of 0.38 cm3).<br> 3. Normal adult male capuchin monkey &quot;S&quot; (brain volume of 68.31 cm3).<br> <br> The models include the following tissues (coded with numbers):<br> 1. White matter volume<br> 2. Grey matter volume<br> 3. CSF volume<br> 4. Skull volume<br> 5. Soft tissues volume<br> 8. Eyeballs volume<br> 1001. White matter outer surfaces<br> 1002. Grey matter outer surfaces<br> 1003. CSF outer surfaces<br> 1004. Skull outer surfaces<br> 1005. Soft tissues outer surfaces<br> 1008. Eyeballs outer surfaces<br> <br> With any questions, please, contact the corresponding authors of the relevant papers or <a href="mailto:aopitz@umn.edu">aopitz@umn.edu</a> (Alexander Opitz).</p>

opencc-by-4.0May 2020View details →
zenodo44/100

The dataset for publication "Characterization of scintillating materials in use for brachytherapy fiber based dosimeters" by S. Commeti, et al., Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2022.

<p>This dataset is related to paper journal paper with DOI:&nbsp;<a href="http://dx.doi.org/10.1016/j.nima.2022.167083">10.1016/j.nima.2022.167083</a>.</p> <p>The dataset contains raw txt file and matlab files on the transmittance and the attenuation of Gadox and YVO specimens.&nbsp;</p> <p>Data files were prepared by agnieszka.gierej@vub.be</p>

opencc-by-4.0Sep 2022View details →
zenodo44/100

A decade of Semantic Web research through the lenses of a mixed methods approach (Resources)

<p>This work has been submitted to&nbsp;<a href="http://www.semantic-web-journal.net/content/decade-semantic-web-research-through-lenses-mixed-methods-approach">Semantic Web Journal</a>. We provide here resources to reproduce our approach.</p> <p>In this paper, we aim to provide a broader and more complete picture of Semantic Web topics and trends by adopting a mixed methods methodology, which allows a combined use of both qualitative and quantitative approaches. Concretely, we build on a qualitative analysis of the main seminal papers, which adopt a top-down approach, and on quantitative results derived with three bottom-up data-driven approaches (<a href="https://technologies.kmi.open.ac.uk/Rexplore/">Rexplore</a>, <a href="http://saffron.insight-centre.org/">Saffron</a>, <a href="https://www.poolparty.biz/">PoolParty</a>), on a corpus of Semantic Web papers published in the last decade. In this process, we both use the latter for &ldquo;fact-checking&rdquo; on the former and also to derive key findings in relation to the strengths and weaknesses of top-down and bottom-up approaches to research topic identification.</p> <p>Please access the full set of resources at:&nbsp;<a href="https://aic.ai.wu.ac.at/qadlod/SW/">https://aic.ai.wu.ac.at/qadlod/SW/</a></p>

opencc-by-4.0Nov 2018View details →
zenodo44/100

Global trends and collaborations in electrochemical methods: a dataset on etching and deposition research

<p><span>This dataset supports the study "Electrochemical Etching vs. Electrochemical Deposition: A Comparative Bibliometric Analysis," which examines scientific publications on electrochemical etching and electrochemical deposition from 1970 to 2023. The dataset is derived from the Science Citation Index Expanded (SCIE) database and includes bibliometric information on publication trends, leading contributors, research areas, and keyword co-occurrences in both fields.</span></p>

opencc-by-4.0Aug 2024View details →
zenodo44/100

Dataset from: Reporting of patient involvement: A mixed-methods analysis of current practice in health research publications

<p>This record includes the data associated with the study &quot;Reporting of patient involvement: A mixed-methods analysis of current practice in health research publications&quot;. In this study, we&nbsp;evaluated the extent and quality of patient involvement reporting in examples of current practice in health research. We used a targeted search strategy to&nbsp;identify publications that report on patient involvement using&nbsp;the following three samples:</p> <ul> <li>Publications published in 2019 in&nbsp;<em>The BMJ,&nbsp;</em>which requires&nbsp;reporting on patient involvement in research articles</li> <li>Publications listed in the PCORI database.&nbsp;We filtered for topic: example of engagement in health research; stakeholder involvement: patients; year: 2019</li> <li>Publications citing the <a href="https://www.bmj.com/content/358/bmj.j3453">GRIPP2 reporting checklist</a> or a <a href="https://onlinelibrary.wiley.com/doi/full/10.1111/j.1369-7625.2010.00607.x">critical appraisal guideline to assess the quality and impact of&nbsp;user involvement in research</a></li> </ul> <p>After applying our inclusion and exclusion criteria, the final sample consisted of 87 publications that reported on patient involvement.&nbsp;Included publications were coded according to three coding schemes.</p> <p>This deposit includes the following:</p> <ul> <li>Overview of publications that did not meet our inclusion criteria across all 3 samples&nbsp;(BMJ, PCORI, and citation)</li> <li>Overview of publications and additional documents (if applicable) that met our inclusion criteria across all 3 samples (BMJ, PCORI, and citation)</li> <li>Coded segments and analysis for the coding scheme&nbsp;&quot;Phase of involvement&quot; across all 3 samples&nbsp;(BMJ, PCORI, and citation). This includes the count of&nbsp;each sub-code&nbsp;across publications and the final results table.&nbsp;</li> <li>Coded segments and analysis&nbsp;for the coding scheme&nbsp;&quot;GRIPP2-SF reporting guidelines according to Staniszewska et al., 2017&quot; across all 3 samples&nbsp;(BMJ, PCORI, and citation).&nbsp;This includes the count of&nbsp;each sub-code&nbsp;across publications and the final results table.</li> <li>Coded segments and analysis for the coding scheme&nbsp;&quot;Critical appraisal tool according to Wright et al., (2010)&quot; across all 3 samples (BMJ, PCORI, and citation).&nbsp;This includes the count of&nbsp;each sub-code&nbsp;across publications and the final results table.</li> </ul>

opencc-by-4.0Feb 2022View details →
zenodo40/100

Payment Methods -research

<p>Consumer behavior, payment methods, payment technologies, applications, nfc, rfid, POI, Point of interaction</p>

opencc-by-4.0Feb 2020View details →
zenodo40/100

PIR data and EEG scoring for Wellcome Open Research methods paper (Brown et al 2016)

<p>PIR data and EEG-scored sleep in the Wellcome Open Research article:</p> <p>'COMPASS: Continuous Open Mouse Phenotyping of Activity and Sleep Status'</p> <p> </p> <p>1sensorPIRvsEEGdata.csv  -  PIR based actigraphy for mice to compare to EEG-scored sleep</p> <p>EEG_4mice10sec.csv  -  Manually scored sleep from EEG files (.edf) from 10.5281/zenodo.160118</p> <p>blandAltLandD.csv  -  paired estimates of sleep by PIR and EEG methods (sum of 4 mice over 1 day in 30min bins)</p> <p><br> 1monthPIRsleep.csv  - 1 month of activity for for figure 4</p> <p><br> 24mice_activity_LD1week.csv  - activity and sleep for 24 wt mice (for hierarchical clustering in figure 4)<br> 24mice_sleep_LD1week.csv </p> <p>     </p> <p> </p>

opencc-zeroOct 2016View details →
zenodo40/100

Рис. 1. ФиΛогенетические Αеревья хантавируса AMRV и его прироΑного носитеΛя восточноазиатской мыши Apodemus peninsulae Thomas, 1906. А. ФиΛогенетическое Αерево восточноазиатской мыши Apodemus peninsulae, построенное метоΑом «максимаΛьного правΑопоΑобия» (ML) и поΛученное на основе анаΛиза участка гена цитохрома b мтΔНК (744 п.н.). В узΛах ветвΛения указаны бутстреп-поΑΑержки, рассчитанные ΑΛя 1000 повторов. Цветными Λиниями обозначены фиΛогенетические Λинии: Αве Китайские (зеΛеный), Корейская «Korea» (синий), Амурская «Amur» (красный). ПоΛужирным шрифтом выΑеΛены собственные образцы. Названия образцов из GenBank/NCBI быΛи сокращены; B. ФиΛогенетическое Αерево из работы Α. Н. Яшиной с ΑопоΛнениями, построенное метоΑом «бΛижайшего сосеΑа» (NJ) на основе посΛеΑоватеΛьностей фрагмента М-сегмента (2737–2980 н.п.) генома хантавирусов. В узΛах ветвΛения указаны бутстреппоΑΑержки, рассчитанные ΑΛя 1000 повторов. Жирным выΑеΛены иссΛеΑованные РНК изоΛяты (Яшина 2012; Яшина и Αр. 2019) Fig. 1. Phylogenetic trees of AMRV and its natural reservoir host — the Korean field mouse Apodemus peninsulae Thomas, 1906. A. Phylogenetic tree of the Korean field mouse Apodemus peninsulae constructed by the "maximum likelihood" method (ML). The data are obtained from the analysis of the cytochrome b mtDNA gene fragments (744 bp). Bootstrap supports calculated for 1,000 repeats are indicated in the branching nodes. Colored lines indicate phylogenetic lines: two Chinese (green), Korea (blue), and Amur (red). Own samples are highlighted in bold. The names of the samples from GenBank/NCBI have been shortened; B. Phylogenetic tree from L. N. Yashina's work with additions constructed by the neighbour joining method (NJ). It is based on the sequences of an M-segment fragment (2737–2980 bp) of the hantavirus genome. Bootstrap supports calculated for 1,000 repeats are indicated in the branching nodes. The researched RNA isolates are highlighted in bold (Yashina 2012; Yashina et al. 2019) in Variability of the gene cyt b in the Korean field mouse Apodemus peninsulae Thomas, 1906 - a reservoir host of AMRV in the Khasansky District of Primorsky Krai

Рис. 1. ФиΛогенетические Αеревья хантавируса AMRV и его прироΑного носитеΛя восточноазиатской мыши Apodemus peninsulae Thomas, 1906. А. ФиΛогенетическое Αерево восточноазиатской мыши Apodemus peninsulae, построенное метоΑом «максимаΛьного правΑопоΑобия» (ML) и поΛученное на основе анаΛиза участка гена цитохрома b мтΔНК (744 п.н.). В узΛах ветвΛения указаны бутстреп-поΑΑержки, рассчитанные ΑΛя 1000 повторов. Цветными Λиниями обозначены фиΛогенетические Λинии: Αве Китайские (зеΛеный), Корейская «Korea» (синий), Амурская «Amur» (красный). ПоΛужирным шрифтом выΑеΛены собственные образцы. Названия образцов из GenBank/NCBI быΛи сокращены; B. ФиΛогенетическое Αерево из работы Α. Н. Яшиной с ΑопоΛнениями, построенное метоΑом «бΛижайшего сосеΑа» (NJ) на основе посΛеΑоватеΛьностей фрагмента М-сегмента (2737–2980 н.п.) генома хантавирусов. В узΛах ветвΛения указаны бутстреппоΑΑержки, рассчитанные ΑΛя 1000 повторов. Жирным выΑеΛены иссΛеΑованные РНК изоΛяты (Яшина 2012; Яшина и Αр. 2019) Fig. 1. Phylogenetic trees of AMRV and its natural reservoir host — the Korean field mouse Apodemus peninsulae Thomas, 1906. A. Phylogenetic tree of the Korean field mouse Apodemus peninsulae constructed by the "maximum likelihood" method (ML). The data are obtained from the analysis of the cytochrome b mtDNA gene fragments (744 bp). Bootstrap supports calculated for 1,000 repeats are indicated in the branching nodes. Colored lines indicate phylogenetic lines: two Chinese (green), Korea (blue), and Amur (red). Own samples are highlighted in bold. The names of the samples from GenBank/NCBI have been shortened; B. Phylogenetic tree from L. N. Yashina's work with additions constructed by the neighbour joining method (NJ). It is based on the sequences of an M-segment fragment (2737–2980 bp) of the hantavirus genome. Bootstrap supports calculated for 1,000 repeats are indicated in the branching nodes. The researched RNA isolates are highlighted in bold (Yashina 2012; Yashina et al. 2019)

opencc-by-4.0Jul 2024View details →
zenodo40/100

Dataset for: Developing research data management services and support for researchers: a mixed methods study

<p><strong>Overview</strong></p> <p>This dataset contains the raw data for the manuscript:&nbsp;<br> Perrier L, Barnes L. Developing research data management services and support for researchers: a mixed methods study. Partnership. 2018;13(1). doi:&nbsp;doi.org/10.21083/partnership.v13i1.4115.</p> <p>Full-text available at:&nbsp;<a href="https://journal.lib.uoguelph.ca/index.php/perj/article/view/4115/4202">https://journal.lib.uoguelph.ca/index.php/perj/article/view/4115/4202</a></p> <p><strong>Data and Documentation Files</strong></p> <p>Five files make up the dataset:&nbsp;</p> <ol> <li>Coding Scheme:&nbsp;RDMServicesSupport_Codes.txt</li> <li>Transcript, Focus Group 01 (anonymized):&nbsp;RDMServicesSupport_FocusGroup01.pdf</li> <li>Transcript, Focus Group 02 (anonymized):&nbsp;RDMServicesSupport_FocusGroup02.pdf</li> <li>Transcript, Focus Group 03 (anonymized):&nbsp;RDMServicesSupport_FocusGroup03.pdf</li> <li>Transcript, Focus Group 04 (anonymized):&nbsp;RDMServicesSupport_FocusGroup04.pdf</li> </ol> <p>Contact: Laure Perrier: <a href="https://journal.lib.uoguelph.ca/index.php/perj/article/view/4115/4202">orcid.org/0000-0001-9941-7129</a></p>

opencc-by-4.0Mar 2018View details →
edi40/100

Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating Research (CiPEHR) Extended sites: winter ecosystem respiration chamber measurements using snow removal method. Oct-Nov 2009, Oct-Dec 2011, Oct-Nov; March-April 2012, Feb-May 2013.

The Carbon in Permafrost Experimental Heating Research (CiPEHR) project addresses the following questions: 1) Does ecosystem warming cause a net release of C from the ecosystem to the atmosphere?, 2) Does the decomposition of old C, that comprises the bulk of the soil C pool, influence ecosystem C loss?, and 3) How do winter and summer warming alone, and in combination, affect ecosystem C exchange? We are answering these questions using a combination of field and laboratory experiments to measure ecosystem carbon balance and radiocarbon isotope ratios at a warming experiment located in an upland tundra field site near Healy, Alaska in the foothills of the Alaska Range. This dataset contains point measurements of winter ecosystem respiration fluxes using the snow removal method and the soil temperature, air temperature, and snow depth associated with each flux.

openOpenNov 2013View details →
edi40/100

Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating Research (CiPEHR): Winter ecosystem respiration chamber measurements using on-plot method, Oct 2012-May 2013.

The Carbon in Permafrost Experimental Heating Research (CiPEHR) project addresses the following questions: 1) Does ecosystem warming cause a net release of C from the ecosystem to the atmosphere?, 2) Does the decomposition of old C, that comprises the bulk of the soil C pool, influence ecosystem C loss?, and 3) How do winter and summer warming alone, and in combination, affect ecosystem C exchange? We are answering these questions using a combination of field and laboratory experiments to measure ecosystem carbon balance and radiocarbon isotope ratios at a warming experiment located in an upland tundra field site near Healy, Alaska in the foothills of the Alaska Range. This dataset contains point measurements of winter ecosystem respiration fluxes using the on-plot method and the soil temperature, air temperature, and snow depth associated with each flux.

openOpenApr 2014View details →
edi40/100

Eight Mile Lake Research Watershed, Carbon in Permafrost Experimental Heating and Drying Research (DryPEHR): Winter ecosystem respiration chamber measurements using on-plot method, Oct 2012-May 2013.

This drying and warming experiment addresses the following questions: 1) Does ecosystem drying, warming and permafrost thaw cause a net release or uptake of C from the ecosystem to the atmosphere?, 2) Does the decomposition of old C that comprises the bulk of the soil C pool influence ecosystem C loss? 3) How do drying and warmign affect plant communities and ecosystem properties? We are answering these questions using a combined warming and drying experiment (DryPEHR), which is situated with the Carbon in Permafrost Experimental Heating Research (CiPEHR) project and located in an upland tundra field site near Healy, Alaska in the foothills of the Alaska Range. Warming treatment here refers to growing season air temperature warming (~1C) using open top chambers (OTC) combined with soil 'warming' using snow fences during the snow covered months. Drying is achieve using an automated pumping system that lowers the water table in the dry plots. Soil warming began in 2008; OTCs and drying in 2011. This dataset contains point measurements of winter ecosystem respiration fluxes using the on-plot method and the soil temperature, air temperature, and snow depth associated with each flux.

openOpenApr 2014View details →
zenodo36/100

Impact of Different Nesting Methods on the Simulation of a Severe Convective Event Over South Korea Using the Weather Research and Forecasting Model

<p>The data from various platforms (NCEP FNL, TRMM, ERA5, AWS) and WRF Model output utilised to generate the figures in the current study (https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020JD033084) are available at this Zenodo&nbsp;data repository.</p>

opencc-by-4.0Jan 2021View details →
zenodo36/100

Research Data supporting "Linear-Scaling Density Functional Theory using the Projector Augmented Wave Method"

<p>Research Data supporting "Linear-Scaling Density Functional Theory using the Projector Augmented Wave Method" by Nicholas D. M. Hine</p>

opencc-by-4.0Oct 2016View details →
zenodo36/100

Simulation Results of the Paper entitled "The Design of a Zone-Picking System with Cooperation Area between Neighboring Zones and Its Cooperation Methods" (submitted to International Journal of Production Research)

<p>Simulation Results of the Paper entitled &ldquo;The Design of a Zone-Picking System with Cooperation Area between Neighboring Zones and Its Cooperation Methods&rdquo; (submitted to International Journal of Production Research)</p>

opencc-by-4.0May 2022View details →
dryad36/100

Research methods and Comparative examination of pinniped craniofacial musculature and its role in aquatic feeding

<p>Secondarily aquatic tetrapods have many unique morphological adaptations for life underwater compared to their terrestrial counterparts. A key innovation during the land-to-water transition was feeding. Pinnipeds, a clade of air-breathing marine carnivorans that includes seals, sea lions, and walruses, have evolved multiple strategies for aquatic feeding (e.g., biting, suction feeding). Numerous studies have examined pinniped skull and dental specializations for underwater feeding. However, data on the pinniped craniofacial musculoskeletal system and its role in aquatic feeding are rare. Therefore, the objectives of this study were to conduct a comparative analysis of pinniped craniofacial musculature and examine the function of the craniofacial musculature in facilitating different aquatic feeding strategies. We performed anatomical dissections of 35 specimens across six pinniped species. We describe 32 pinniped craniofacial muscles—including facial expression, mastication, tongue, hyoid, and soft palate muscles. Pinnipeds broadly conform to mammalian patterns of craniofacial muscle morphology. Pinnipeds also exhibit unique musculoskeletal morphologies—in muscle position, attachments, and size—that likely represent adaptations for different aquatic feeding strategies. Suction feeding specialists (bearded and northern elephant seals) have a significantly larger masseter  than biters. Further, northern elephant seals have large and unique tongue and hyoid muscle morphologies compared with other pinniped species. These morphological changes likely help generate and withstand suction pressures necessary for drawing water and prey into the mouth. In contrast, biting taxa (California sea lions, harbor, ringed, and Weddell seals) do not exhibit consistent craniofacial musculoskeletal adaptations that differentiate them from suction feeders. Generally, we discover that all pinnipeds have well-developed and robust craniofacial musculature. Pinniped head musculature plays an important role in facilitating different aquatic feeding strategies. Together with behavioral and kinematic studies, our data suggest that pinnipeds' robust facial morphology allows animals to switch feeding strategies depending on the environmental context—a critical skill in a heterogeneous and rapidly changing underwater habitat.</p>

opencc-zeroMay 2022View details →
zenodo36/100

International Journal of Social Research Methods: 25th Anniversary Editorial bonus material (methods and data)

<p>This dataset accompanies the&nbsp;25th Anniversary Editorial bonus material (methods and data) of the&nbsp;International Journal of Social Research Methods.</p> <p>https://www.tandfonline.com/journals/tsrm20/collections/TSRM_25th_Anniversary_SI</p>

opencc-by-4.0Aug 2022View details →
zenodo36/100

Bibliometric appendices for the paper "Systematic mapping study on the systematic mapping study research method"

<p>Bibliometric appendices for the paper &quot;Systematic mapping study on the systematic mapping study research method&quot;</p>

opencc-by-4.0Nov 2018View details →
zenodo36/100

Research Compendium for Himes et al. (2023): "Towards 3D Retrieval of Exoplanet Atmospheres: Assessing Thermochemical Equilibrium Estimation Methods"

<p>This archive is the Reproducible Research Compendium for</p> <p>Towards 3D Retrieval of Exoplanet Atmospheres: Assessing Thermochemical Equilibrium Estimation Methods</p> <p>by Himes, Harrington, and Baydin (2023), published in The Planetary Science Journal.</p> <p>The compendium includes all the software, documentation, configuration files, plots, and data published in the paper.&nbsp; The compendium is under the Reproducible Research Software License; see LICENSE file.&nbsp; The README provides additional information and describes the contents of each compressed .tar.gz file.</p>

openother-atMar 2023View details →
dryad36/100

Data from: Novel methods to define invasive procedures at the end-of-life were developed to improve quality of end of life care research: A population-based cohort study in colorectal cancer

<p><strong>Background</strong></p> <p>Understanding the use of invasive procedures (IPs) at the end-of-life (EoL) is important to avoid under- and overtreatment, but epidemiologic analysis is hampered by limited methods to define treatment intent and EoL phase. This study applied novel methods to report IPs at the EoL using a colorectal cancer (CRC) case study.</p> <p><strong>Methods</strong></p> <p>An English population-based cohort of adult patients diagnosed between 2013 and 2015 was used with follow-up to 2018. Procedure intent (curative, non-curative, diagnostic) by cancer site and stage at diagnosis was classified by two surgeons independently. Joinpoint regression modelled weekly rates of IPs for 36 sub-cohorts of patients with incremental survival of 0-36 months. EoL phase was defined by a significant IP rate change before death. Zero-inflated Poisson regression explored associations between IP rates and clinical/sociodemographic variables.</p> <p><strong>Results</strong></p> <p>Of 87,731 patients included, 41,972 (48%) died. 9,492 procedures were classified by intent (interrater agreement 99.8%). Patients received 502,895 IPs (1.39 and 3.36 per person year for survivors and decedents). Joinpoint regression identified significant increases in IPs four weeks before death in those living 3-6 months, and eight weeks before death in those living 7–36 months from diagnosis. 7,908 (18.8%) patients underwent IPs at the EoL, with stoma formation the most common major procedure. Younger age, early-stage disease, men, lower comorbidity, those receiving chemotherapy and living longer from diagnosis were associated with IPs.</p> <p><strong>Conclusions</strong></p> <p>Methods to identify and classify IPs at the EoL were developed and tested within a CRC population. This approach can be now extended and validated to identify potential under- and overtreatment. </p>

opencc-zeroSep 2023View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record