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261 results for “Research assessment”
Quantitative Assessment of Research Data Management Practices - 2023
<p>This survey investigates <strong>Research Data Management (RDM) practices across five Swiss higher education institutions</strong>, including EPFL, ETH Zürich, Eawag, FHNW, and DaSCH, with the goal of gathering insights into how researchers manage data and code throughout the lifecycle of their projects, as well as using such findings to inform academic services related to RDM for researchers. Previous surveys, conducted at EPFL in 2017, 2019, and 2021, primarily focused on the planning and publishing stages of the research data lifecycle, such as data management planning and open data dissemination. The 2023 edition expanded to other institutes and places a stronger emphasis on <strong>Active Data Management</strong>, particularly during research projects, including a range of topics such as:</p> <ul> <li>Storage and backup solutions</li> <li>Data and code sharing platforms</li> <li>Documentation and metadata usage</li> <li>Compliance with legal and ethical standards</li> <li>Long-term data preservation strategies</li> <li>Use of open formats and open-source software</li> <li>Adoption of Data Management Plans (DMPs)</li> </ul> <p>This dataset was collected using the SurveyHero platform in compliance with GDPR and Swiss FADP regulations. enuvo GmbH acted as the data processor under a signed Data Processing Agreement. No personal identifiable information was purposefully collected, and data has been aggregated to further ensure respondents’ privacy.</p> <p>Included in this dataset:</p> <ul> <li>A CSV and XLSX file with the aggregated, anonymized data from the survey.</li> <li>Two PDF files containing graphical representations of the survey results, automatically generated by the SurveyHero platform in portrait and landscape mode.</li> <li>A README file providing context.</li> </ul> <p>This dataset is made openly available under the CC-BY 4.0 license. Users are encouraged to reuse it with appropriate attribution.</p>
MiRoR15-P2-Development of ARCADIA: a tool for assessing the quality of peer-review reports in biomedical research
<p>Survey questionnaire, anonymised survey data, and codebook related to: Superchi C, Hren D, Blanco D, Rius R, Recchioni A, Boutron I, González JA. Development of ARCADIA: a tool for assessing the quality of peer-review reports in biomedical research. BMJ Open 2020;0:e035604. doi:10.1136/bmjopen-2019-035604</p>
GraspOS landscape survey on Reforming Research Assessment
<p><span>This dataset is related to GraspOS Deliverable D2.1 "OS-aware RRA approaches landscape report" (<a title="https://zenodo.org/records/11098095" href="../records/11098095" target="_blank" rel="noreferrer noopener">https://zenodo.org/records/11098095</a>), Annex 1. GraspOS landscape survey on Reforming Research Assessment.</span></p>
Quantitative assessment of research data management practice - University of Bordeaux
<p>This survey was run at the University of Bordeaux in January 2019 using the questionnaire "Quantitative assessment of research data management practice" :</p> <p>Teperek, M., Krause, J., Lambeng, N., Blumer, E., van Dijck, J., Eggermont, R., … der Velden, Y. T. (2019). Quantitative assessment of research data management practice. Retrieved from : <a href="https://osf.io/mz3fx/">https://osf.io/mz3fx/</a></p> <p>The questionnaire included all the primary and secondary common questions, institution-specific questions regarding services and file sharing (EPFL questions), institution-specific questions for profile information.</p> <p>Data from the 425 responses collected are published here.</p> <p>Details regarding data collection and curation are included in the README file.</p> <p> </p>
MiRoR7-P1- Disagreements in risk of bias assessment for randomised controlled trials included in more than one Cochrane systematic reviews: a research on research study using cross-sectional design
<p>dataset referring to </p> <p><strong>Disagreements in risk of bias assessment for randomised controlled trials included in more than one Cochrane systematic reviews: a research on research study using cross-sectional design</strong></p> <p> </p> <p> </p> <p>Lorenzo Bertizzolo<sup>1</sup>, Patrick M Bossuyt<sup>2</sup>, Ignacio Atal<sup>1, 5</sup>, Philippe Ravaud<sup>1, 3-6</sup>, Agnès Dechartres<sup>7</sup></p> <p> </p> <p><sup>1</sup> INSERM, U1153 Epidemiology and Biostatistics Sorbonne Paris Cité Research Center (CRESS), Methods of therapeutic evaluation of chronic diseases Team (METHODS), Paris, F-75004 France; Paris Descartes University, Sorbonne Paris Cité, France.</p> <p><sup>2</sup> Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Netherlands.</p> <p><sup>3</sup> Centre d’Épidémiologie Clinique, Hôpital Hôtel Dieu, AP-HP (Assistance Publique des Hôpitaux de Paris), Paris, France.</p> <p><sup>4</sup> Faculté de Médecine, Université Paris Descartes, Sorbonne Paris Cité, Paris, France.</p> <p><sup>5</sup> Cochrane France, Paris, France</p> <p><sup>6</sup> Columbia University, Mailman School of Public Health, Department of Epidemiology, New York, USA</p> <p><sup>7</sup> Sorbonne Université, INSERM, Institut Pierre Louis de Santé Publique, Département Biostatistique, Santé Publique et Information Médicale, AP-HP, Hôpitaux Universitaires Pitié Salpêtrière – Charles Foix, Paris, France</p>
Questionnaire for the self-assessment of digital preservation activities in institutional research repositories
<p>This dataset includes a questionnaire designed to enable institutional repository managers to conduct a self-assessment of their digital preservation strategies and activities. It consists of 46 evaluation criteria extracted and modified from the NDSA Levels of Digital Preservation and ISO 16363:2017 standards. The questionnaire is provided in queXML format, facilitating its import into various survey applications</p> <p> </p>
Mapping Building BioData.pt Indicators against the performance and impact assessment frameworks for research infrastructures of OECD, ESFRI and RI-PATHS project
<p>"Buiding BioData.pt" indicators observed in international frameworks for performance and impact assessment of research infrastructures, namely, OECD, ESFRI and RI-PATHS.</p>
Assessing Quality Variations in Early Career Researchers' Data Management Plans: Quantitative Data of the Content Analysis
<p>The data includes the numerical results of the ranking of the data management plans created during the Basics of Research Data Management (BRDM) courses worth 3 ECTS credits in the years 2020 - 2022. The ranking was made using the Finnish DMP Evaluation Guidance (https://doi.org/10.5281/zenodo.4729831). Additionally, the data contains the results of the analysis of the best RDM practices included in the DMPs.</p> <p>Note 1: The comma-separated coded CSV version 1 (5.2.2024) may not open correctly on MacOS. You can use the comma-delimited CSV file version 2 or 3 (31.5.2024).</p> <p>Note 2: Versions 1 (Quality_variations_in_ECRs_DMPs_data) and 3 (Quality_variations_in_ECRs_DMPs_data_ver_3) contain evaluations of DMPs, best practices for data management, as well as methods for data sharing, storage, and preservation. In version 2 (Quality_variations_in_ECRs_DMPs_data_ver_2), the methods for data sharing, storage, and preservation are missing.</p> <p>Data is related to the research article https://doi.org/10.2218/ijdc.v18i1.873.</p>
Research data for "Phase transitions in NiO during the Oxygen Evolution Reaction assessed via electrochromic phenomena through operando UV-Vis spectroscopy"
<p>This is the dataset supporting the publication "Phase transitions in NiO during the Oxygen Evolution Reaction assessed via electrochromic phenomena through operando UV-Vis spectroscopy", published by the authors in Electrochimica Acta (2024), 144626 under <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.electacta.2024.144626" target="_blank" rel="noreferrer noopener">doi.org/10.1016/j.electacta.2024.144626</a>.</p> <p>The data is ordered according to Figure numbers in the main manuscript and the electronic supplementary information.</p>
Spectral irradiance at Lammi Biological Station Research Forest 2015: for assessing scale-wise similarity of curves with a thick pen
<p>This dataset contains records of the solar spectral energy irradiance (W m<sup>-2</sup> nm<sup>-1</sup>) in the understorey of forest stands at Lammi Biological Station, southern Finland (61◦ 3.24’ N, 25◦ 118 2.23’ E) during the spring of 2015. These spectra allow the change in spectral energy irradiance to be followed through the period of canopy leaf flush. Records are the average of recorded spectra from four points recorded at 40-cm above the forest floor using a Maya 2000 Pro array spectrometer. Spectra were recorded from exactly the same location on three dates, 2015-04-25, 2015-05-22, and 2015-06-05, before, during and after leaf flush. Data were recorded from the understorey of a young Betula stand, an old Betula stand, an old mixed Betula stand, a Quercus stand, and a Picea stand, in three positions: shade, semi-shade from leaves, and full sun in a sunfleck. On each occasion control measurements of spectral energy irradiance in full sun of an open field were also recorded at the beginning, middle and end of each measurement period. All measurements were made during the 2 hours either side of solar noon, on clear-sky days. Details of the sampling method and interpretation are given in the paper, Hartikainen et al., (2018) in Ecology and Evolution, which showcases the use of Thick Pen Transform to compare spectra.</p>
Dataset: Publication cultures and Dutch research output: a quantitative assessment
<p>Dataset belonging to the report: <a href="https://doi.org/10.5281/zenodo.2643360">Publication cultures and Dutch research output: a quantitative assessment</a></p> <p> </p> <p>On the report:</p> <p>Research into publication cultures commissioned by VSNU and carried out by Utrecht University Library has detailed university output beyond just journal articles, as well as the possibilities to assess open access levels of these other output types. For all four main fields reported on, the use of publication types other than journal articles is indeed substantial. For Social Sciences and Arts & Humanities in particular (with over 40% and over 60% of output respectively not being regular journal articles) looking at journal articles only ignores a significant share of their contribution to research and society. This is not only about books and book chapters, either: book reviews, conference papers, reports, case notes (in law) and all kinds of web publications are also significant parts of university output.</p> <p>Analyzing all these publication forms and especially determining to what extent they are open access is currently not easy. Even combining some the largest citation databases (Web of Science, Scopus and Dimensions) leaves out a lot of non-article content and in some fields even journal articles are only partly covered. Lacking metadata like affiliations and DOIs (either in the original documents or in the scholarly search engines) makes it even harder to analyze open access levels by institution and field. Using repository-harvesting databases like BASE and NARCIS in addition to the main citation databases improves understanding of open access of non-article output, but these routes also have limitations. The report has recommendations for stakeholders, mostly to improve metadata and coverage and apply persistent identifiers.</p>
Quantitative assessment of research data management practice
<p>This survey aims to investigate research data management practices in academic institutions. The survey comprises questions common to all institutions as well as institution-specific ones. Common questions were drafted in the frame of a collaboration between several RDM services: Tu Delft (team effort), EPFL (team effort), University of Cambridge (notably Marta Busse) and University of Illinois (notably Heidi Imker). The first survey was run by TU Delft and EPFL only end of 2017. In total, 1263 responses where collected (680 from TU Delft, 235 from EPFL and 348 from the University of Cambridge) and are published here. The results of each institution are provided in Microsoft Excel 2007 (XLSX) format. Consolidated results are provided in CSV format</p> <p>The first lines of the CSV file contains the question asked to researchers. Each further line contains the response of a researcher; answers to institution-specific questions are set to N/A for researchers of the other institutions. Column delimiters are commas(,), quote chars are double-quotes (") and subfield separators are semi-columns (;). The text encoding is UTF-8.</p> <p>More information about this survey as well as the exact survey questions and a detailed description how the survey might be re-used by other institutions is available on the project page on the Open Science Framework: htts://osf.io/mz3fx/ For any questions contact datastewards@tudelft.nl or researchdata@epfl.ch</p>
NOAA NCCOS Assessment: Prioritizing Areas for Future Seafloor Mapping, Research, and Exploration Offshore of California, Oregon, and Washington from 2019-03-01 to 2019-04-01
<p>Spatial information about the seafloor is critical for decision-making by marine resource science, management and tribal organizations. Coordinating data needs can help organizations leverage collective resources to meet shared goals. To help enable this coordination, the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) developed a spatial framework, process and online application to identify common data collection priorities for seafloor mapping, sampling and visual surveys offshore of the West Continental United States Coast (WCC). Twenty-six participants from NOAA’s West Coast Deep Sea Coral Initiative (WCDSCI) and Expanding Pacific Research and Exploration of Submerged Systems (EXPRESS) entered their priorities in an online application, using virtual coins to denote their priorities in 10x10 minute grid cells. Grid cells with more coins were higher priorities than cells with fewer coins. Participants also reported why these locations were important and what data types were needed. Results were analyzed and mapped using statistical techniques to identify significant relationships between priorities, reasons for those priorities and data needs. Ten high priority locations were broadly identified for future mapping, sampling and visual surveys. These locations were distributed throughout the WCC, primarily in depths less than 1,000 m. Participants consistently selected (1) Exploration, (2) Biota/Important Natural Area and (3) Research as their top reasons (i.e., justifications) for prioritizing locations, and (1) Benthic Habitat Map and (2) Bathymetry and Backscatter as their top data or product needs. This ESRI shapefile summarizes the results from this spatial prioritization effort. This information will enable NOAA WCDSCI, EXPRESS and other WCC organization to more efficiently leverage resources and coordinate their mapping of high priority locations along California, Oregon and Washington. </p> <p>This effort was funded by NOAA’s Deep Sea Coral Research and Technology Program (DSCRTP) through its WCDSCI. The overall goal of the project was to systematically gather and quantify suggestions for seafloor mapping, sampling and visual surveys for the WCDSCI and EXPRESS. The results are expected to help WCDSCI, EXPRESS and other organizations on the WCC to identify locations where their interests overlap with other organizations, to coordinate their data needs and to leverage collective resources to meet shared goals.</p> <p>There were four main steps in the WCC spatial prioritization process. The first step was to identify the technical advisory team, which included the 11 members of the DSCRTP WCDSCI Steering Committee and all of the participants involved in the EXPRESS campaign. This advisory team invited 37 participants for the prioritization. Step two was to develop the spatial framework and an online application. To do this, the WCC was divided into five subregions and 3,265 square grid cells approximately 10x10 minutes in size. Existing relevant spatial datasets (<em>e.g.</em>, bathymetry, protected area boundaries, etc.) were compiled to help participants understand information and data gaps and to identify areas they wanted to prioritize for future data collections. These spatial datasets were housed in the online application, which was developed using Esri’s Web AppBuilder. In step three, this online application was used by 26 participants to enter their priorities in each subregion of interest. Participants allocated virtual coins in the 10x10 minute grid cells to denote their priorities. Grid cells with more coins were higher priorities than cells with fewer coins. Participants also reported why these locations were important and what data types were needed. Coin values were standardized across the subregions and used to identify spatial patterns across the WCC region as a whole. The number of coins were standardized because each subregion had a different number of grid cells and participants. Standardized coin values were analyzed and mapped using statistical techniques, including hierarchical cluster analysis, to identify significant relationships between priorities, reasons for those priorities and data needs. This ESRI shapefile contains the 10x10 minute grid cells used in this prioritization effort and associated the standardized coin values overall, as well as by organization, justification and product. For a complete description of the process and analyses please see: Costa <em>et al</em>. 2019.</p>
Does size matter? Quality assessment of the size property in research data repositories
<p>Code and data for master's thesis on quality assessment of the size property in research data repositories. Research questions:</p> <ul> <li> <p> For what semantic concepts is the size property of repositories being used?</p> </li> <li> <p>What kind of quality factors can be detected when assessing the size property in a registry for research data repositories?</p> </li> <li> <p>Which automated and intellectual measures can improve the quality of the size property?</p> </li> </ul> <p>Method 1: Data analysis of size and related properties over all re3data records</p> <ul> <li> <p>Property selection</p> </li> <li> <p>Data extraction from API</p> </li> <li> <p>Data normalization</p> </li> <li> <p>Typing of patterns: mainly units of size</p> </li> <li> <p>Analysis: ~quantitative, mainly univariate, but also some multivariate / time</p> </li> </ul> <p>[Included in the publication:</p> <p>Method 2: Case Study of size in individual repositories</p> <ul> <li> <p>Repository selection: purposive sampling</p> </li> <li> <p>Data capture from GUI / API</p> </li> <li> <p>Analysis: ~qualitative]</p> </li> </ul>
Data for Research Assessment in the Transition to Open Science. 2019 EUA Open Science and Access Survey Results
<p>This database refers to the data collected by the European University Association (EUA) for its Open Science and Access Survey 2019, which gathered responses from universities and higher education institutions across Europe. The full report published by the association is available at <a href="https://eua.eu/resources/publications/888:research-assessment-in-the-transition-to-open-science.html">https://eua.eu/resources/publications/888:research-assessment-in-the-transition-to-open-science.html</a>.</p> <p>The data included in this database refers only to those universities and higher education institutions that accepted their data to be available in open access (n=174). All information that could lead to the identification of individual universities and higher education institutions was removed from the database (cf. cells highlighted in red). The following files are available:</p> <ul> <li>2019 EUA Open Science and Access Survey</li> <li>Database in the following formats: .xlsx (Microsoft Excel)</li> <li>Survey Codebook: includes information on all the variables and their coding.</li> </ul>
A Questionnaire to Assess the Research Practices and Services Related to the Academic and Research Staff at the Institutions of Higher Education in Palestine - Survey Data
<p>Data generated as part of a needs assessment survey conducted as part of ROMOR, a project funded by the Erasmus Plus Programme of the European Union in the period from October 2016 to October 2019. A questionnaire was prepared under the supervision of Palestinian Universities participating in the project. The results of the study will be used to create and develop institutional repositories to store the digital outputs of scientific research at the institutions of higher education in Palestine. The results will be also used to provide the vocational and academic training, and the institutional policies required to manage, organize the use, and populate the prospective repositories. This objective will contribute in promoting the access to and benefit of the results of scientific research in Palestine, and increase its impact at the local and international levels. This questionnaire was distributed to the representative of each institution, who in turn forwarded it to the suitable persons in the institution. Data was collected between January 4th and February 19th 2017. Paper and electronic versions of a questionnaire were prepared in both Arabic and English. The project coordinators at partner PS HEIs were requested to circulate the electronic questionnaire to all researchers and members of academic staff. Data was collected by ROMOR partners at:</p> ● The Islamic University of Gaza (IUG) ● Al-Quds Open University (QOU) ● Birzeit University (BZU) ● Palestine Technical University-Kadoori (KAD)
A Questionnaire to Assess the Research Practices and Services Related to the Academic and Research Staff at the Institutions of Higher Education in Palestine - Survey Data with Pie Charts
<p>Data generated as part of a needs assessment survey conducted as part of ROMOR, a project funded by the Erasmus Plus Programme of the European Union in the period from October 2016 to October 2019. A questionnaire was prepared under the supervision of Palestinian Universities participating in the project. The results of the study will be used to create and develop institutional repositories to store the digital outputs of scientific research at the institutions of higher education in Palestine. The results will be also used to provide the vocational and academic training, and the institutional policies required to manage, organize the use, and populate the prospective repositories. This objective will contribute in promoting the access to and benefit of the results of scientific research in Palestine, and increase its impact at the local and international levels. This questionnaire was distributed to the representative of each institution, who in turn forwarded it to the suitable persons in the institution. Data was collected between January 4th and February 19th 2017. Paper and electronic versions of a questionnaire were prepared in both Arabic and English. The project coordinators at partner PS HEIs were requested to circulate the electronic questionnaire to all researchers and members of academic staff. Data was collected by ROMOR partners at:</p> <p>● The Islamic University of Gaza (IUG)</p> <p>● Al-Quds Open University (QOU)</p> <p>● Birzeit University (BZU)</p> <p>● Palestine Technical University-Kadoori (KAD)</p> <p>[Data visualised as pie charts]</p> <p> </p>
The metadata of books submitted as research outputs to annual Lithuanian research assessments from 2008 to 2020
<p>This dataset contains ISBNs and below described metadata of 5199 books which Lithuanian universities and research institutions submitted as their best research outputs to get state funding after annual research evaluations from 2008 to 2020. The thorough explanation how this dataset was created provided in a preprint: Dagiene, Eleonora. 2023. "The Challenge of Assessing Academic Books: The UK and Lithuanian Cases Through the ISBN Lens." SocArXiv. <a href="https://doi.org/10.31235/osf.io/qpwxn">https://doi.org/10.31235/osf.io/qpwxn</a> </p><p>This dataset contains ISBNs and their metadata, gathered from the Global Register of Publishers <a href="https://grp.isbn-international.org/">https://grp.isbn-international.org/</a></p><p><strong>Description of data columns and remarks:</strong></p><p>ISBNs – unique identifiers – at least one author of the book identified by the ISBNs is affiliated with Lithuanian institution;</p><p>output_types – ['edited volumes', 'authored books'] – types of books eligible for research assessment;</p><p>years – 2008-2020 – book publishing years as reported by submitting institutions;</p><p>unified_title – titles of publishers – parent publishers (e.g. Springer Nature, Informa (Taylor & Francis)). Lithuanian institutions kept in Lithuanian;</p><p>primary_occupations_main – 'academic publishers', 'universities', 'intermediaries', 'other publishers', 'not publishers' – main types of institutions/companies which registered particular ISBNs;</p><p>primary_occupations_detailed – 'academic publishers', 'university presses', 'university departments', 'self-publishing', 'publishing services', 'specialised publishers', 'general publishers', 'societies', 'not publishing', 'research institutions', 'governmental institutions', 'libraries', 'museums', 'non-governmental organisations' – just more types of institutions/companies;</p><p>country – country name – countries where ISBNs were assigned, e.g. books authored or co-authored by Lithuanian researchers issued in 53 countries worldwide;</p><p>sciences – 'natural sciences', 'social sciences', 'agricultural sciences', 'technological sciences', 'medical and health sciences', 'humanities' – as brunches of sciences categorised by the Research Council of Lithuania.</p>
Lightning Assimilation in the Weather Research and Forecasting (WRF) Model: Technique Updates and Assessment of the Applications from Regional to Hemispheric Scales
<p>Figure 1. The data is proprietary, but it can be purchased from Vaisala Inc. (https:// <a href="http://www.vaisala.com/en/products/systems/lightning-detection">www.vaisala.com/en/products/systems/lightning-detection</a>), and the WWLLN raw data are also available for purchase at <a href="http://wwlln.net">http://wwlln.net</a>.</p> <p>Figure 2. Maps, data is not applicable.</p> <p>Figure 3. Data file: NLDN_WWLLN_Prism_Rainfall_Analysis.xlsx</p> <p>Figure 4. Data file: NLDN_WWLLN_METVARS_T2_Jul_2016.xlsx</p> <p>Figure 5. Data file: CONUSall_METOBS_q_Jul_2016.xlsx</p> <p>Figure 6. Data file: CONUSall_METOBS_ws_Jul_2016.xlsx</p> <p>Figure 7. Created using the R script: Hemi_Rain_ModelOnlyWGPM.R based on the R object files: AnnualRainFall_CFC_WRF_Hemi_BASE_*.rds, AnnualRainFall_CFC_WRF_Hemi_LTA_*.rds, and GPM_WRF_Paired_rain2Hemispheric_July2016.rds.</p> <p>Figure 8. Created using the R script: Hemi_Rain_Aanlysis.R based on the R object files: AnnualRainFall_CFC_WRF_Hemi_BASE_*.rds and AnnualRainFall_CFC_WRF_Hemi_LTA_*.rds.</p> <p>Figure 9. Data file: CPC_Model_Monthly_Prep_Hemi_Stats.xlsx</p> <p>Figure 10. Data file: CPC_Model_Monthly_Prep_Hemi_Stats.xlsx</p> <p>Figure 11. Data file: CPC_Model_Monthly_Prep_Hemi_Stats.xlsx</p> <p>Figure 12. Created using the R script: CreateCPCdataforUSdomain_vs_Prism.R based on the R oject files: Prism_CFC_WRF*.rds</p> <p>Figure 13. Data file: Hemi_lta_METOBS_T2_Jul_2016.xlsx</p> <p>Figure 14. Data file: Hemi_lta_METOBS_q_Jul_2016.xlsx</p> <p> </p>
Research data: Counterfactual assessment of protected area avoided deforestation in Cambodia version 4
<p>This dataset includes the data, the R scripts used for analysis and results that are the basis of the journal article: Black, B., Anthony, B. In review. Counterfactual assessment of protected area avoided deforestation in Cambodia: Trends in effectiveness, spillover effects and the influence of establishment date. Global Ecology and Conservation.</p> <p>Each folder includes a specific readme file in .txt format which includes metadata and instructions for reproducing the research.</p> <p> </p>
ScienceDex guides
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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.