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557 results for “data reporting”
Supporting publication for 'Prevalence sample-based guidance for reporting 2021 data'
<p>The record is aimed at helping the reporting countries to submit their sample-based level data to the EFSA Data Collection Framework. We include here two excel files and one XML file, and we give below specific information on their use.</p> <p>The two Excel documents help in mapping terms from the matrix catalogue ZOO_CAT_MATRIX used in the aggregated prevalence data model to FoodEx2 codes, and offer examples on how prevalence data can be reported using SSD2 and how data are aggregated afterwards. The XML file is the same example as in the Excel file with similar title but in the XML format that allows for it be uploaded in the Data Collection Framework.</p>
Data for 17IND08 AdvanCT "report on the traceable measurement of freeform objects"
<p>Raw and evaluated data from 17IND08 AdvanCT's case study on freeforms, "report on the traceable measurement of freeform objects".</p> <p>Contains point clouds from CT (X-ray computed tomography) and tactile point clouds of two freeform workpieces made from titanium or polymer. Also includes data from registration spheres on both parts, and histogram data from nominal-actual comparisons between tactile and CT surfaces.</p>
Settings and data files from Silva et al (Scientific Reports 2022)
<p><strong>Neolithic Greece mtDNA sequences</strong></p> <p>The 47 mitochondrial sequences generated for this work are available in the .arp format for the program ARLEQUIN (http://cmpg.unibe.ch/software/arlequin35/).</p> <p><strong>Simulated Data and Simulation Program</strong></p> <p>This dataset permits to simulate the scenarios investigated in the article submitted by Silva et al, using the modified version of the program SPLATCHE2 provided here (http://www.splatche.com).</p> <p>There is a zipped folder Silva_et_al_SimulationSettings" that contains:</p> <p>i) SPLATCHE2 executable called "SPLATCHE2-VariableAdmixture".</p> <p>ii) a folder "DanubeRouteExpansion" including the settings used for the simulation of the four scenarios of the Neolithic expansion along the Danubian route.</p> <p>iii) a folder "GreeceContinuity" including the settings used to perform the structured population continuity test.</p> <p>A "ReadMe.txt" file is available in both settings folders with the instructions to launch the simulations.</p>
Excel mapping tools for 2021 AMR data reporting
<p>The main objective of the mapping tools is to provide a simple and useable platform for Member States and other reporting countries to map their country-specific standard terminology to that used by EFSA and to enable the production of an XML file for the submission of antimicrobial resistance data via the Data Collection Framework (DCF).</p> <p>The tools can be used to report antimicrobial resistance data within the framework of Directive 2003/99/EC and Decision 2020/1729/EU.</p> <p>The catalogues and the specific hierarchy of each data model (AMR and ESBL) are already inserted into each of the specific mapping tool. Specific Excel mapping tools corresponding to each of the two data models are available.</p> <p>Dynamic or manual version of the tool can be chosen for each data models.</p>
Data for "Measurement Report: A Multi-Year Study on the Impacts of Chinese New Year Celebrations on Air 1 Quality in Beijing, China."
<p>These are the datasets that have been used for the article "Measurement Report: A Multi-Year Study on the Impacts of Chinese New Year Celebrations on Air 1 Quality in Beijing, China," which is published in the journal <em>Atmospheric Chemistry and Physic</em><em>s</em>, by Foreback et al. (2022).</p>
Data from: The Subantarctic Rayadito (Aphrastura subantarctica), a new bird species on the southernmost islands of the Americas. Scientific Reports
<p><strong>Description of the dataset</strong><br> This dataset contains morphological and genetic information of Aphrastura populations in different sample sites in Chile and Argentina. This dataset was analysed in: Rozzi R, Quilodrán CS, Botero-Delgadillo E, Napolitano C, Torres-Mura JC, Barroso O, Crego RD, Bravo C, Ippi S, Quirici V, Mackenzie R, Suazo CG, Rivero-de-Aguilar J, Goffinet B, Kempenaers B, Poulin E and RA Vásquez. 2022. The Subantarctic Rayadito (<em>Aphrastura subantarctica</em>), a new bird species on the southernmost islands of the Americas. Scientific Reports.</p> <p>There are three files: </p> <ul> <li>Subantarctic_Rayadito_Morphology.txt: morphological information used for differentiating <em>Aphrastura subantarctica</em> from <em>Aphrastura spinicauda</em>. The former was sampled in the Diego Ramirez archipelago. The date of sampling is included in the last column. </li> <li>Subantarctic_Rayadito_Microsatellite.txt: all captured and genotyped adults from five populations. The band (ring) number is used as an ID for each individual bird. The matrix includes information regarding the locality of origin (MA: Manquehue; BA: Bariloche; TF: Tierra del Fuego; NI: Navarino Island; DR: Diego Ramírez Archipelago), and allele size (number of repeats) at 12 polymorphic microsatellite loci.</li> <li>Subantarctic_Rayadito_mtDNA.nex: mtDNA information for all <em>Aphrastura</em> individuals sequenced and used in our analysis. The labels denote the code number and location for each individual (DR: Diego Ramirez Archipelago; CH: Cape Horn Island ; Navarino : Navarino Island; TdelFuego : Tierra del Fuego; PtoNatales : Puerto Natales ; ElChalten : El Chalten; CalTortel : Caleta Tortel ; Coihayque : Coihayque ; Chaiten : Chaiten ; LosAlerces : Los Alerces ; Chiloe : Chiloé Island ; IslaMocha : Mocha Island ; Curacautin : Curacautin ; Rinihue : Rinihue ; Epulauquen : Epu Lauquen ; Constitucion : Constitución ; Manquehue : Manquehue ; FrayJorge : Fray Jorge National Park). </li> </ul> <p><strong>Acknowledgments </strong><br> This study was funded with Grants from the Sub-Antarctic Biocultural Conservation Program of the University of North Texas, University of Magallanes, the Cape Horn International Center (ANID CHIC-FB210018), the Institute of Ecology and Biodiversity of Chile (CONICYT PFB-23), and the Patagonia Mar y Tierra Working Group (The Pew Charitable Trust - Chile). We thank the support of the Omora Foundation, and FONDECYT 1140548 to RAV. C.N. thank support from ANID PAI 77190064, and ANID/BASAL FB210006. CSQ acknowledges support from the Swiss National Science Foundation (N° P400PB_183930 and P5R5PB_203169). We are grateful to Sylvia Kuhn and Alexander Girg from the Max Planck Institute for Ornithology for help in the laboratory, and to Jaime A. Cursach and Maximiliano Daigre during fieldwork and ornithological records in Gonzalo Island. Fieldwork in protected areas was possible thanks to people from Parque Nacional Bosque Fray Jorge, Minera Los Pelambres, Estación Biológica Senda Darwin, Parque Nacional Nahuel Huapi, and Parque Natural Karukinka. We also express our gratitude for logistical and personnel support from the 3rd Naval Zone of the Chilean Navy.</p> <p> </p>
Albanian SCL-90R data for cross-cultural SCL report
<p>Zip archive contains complete source data concerning the referred core part of the Albanian study in Tirana: <br> - selected socio-demographical variables, <br> - SCL-90-R global scales, subscales and items.</p> <p>Data is in SPSS SAV format (root format), CSV, XLSX and ODS.</p>
Statistical data collected in the case studies of the SPOT report - dataset
<p>Statistical data was collected for fifteen case studies in the context of the SPOT project, funded by the European Commission within the framework programme Horizon 2020.</p>
Replication data for measurement report: Evolution and distribution of NH3 over Mexico City from ground-based and satellite infrared spectroscopic measurements
<p>This dataset of atmospheric ammonia (NH3) has been generated from solar absorption spectra measured in central Mexico using ground-based Fourier-Transform Infrared (FTIR) spectrometers. The FTIR experiments have been operated by the “Spectroscopy and Remote Sensing” Research Group of the ICAyCC-UNAM (Instituto de Ciencias de la Atmósfera y Cambio Climático of the Universidad Nacional Autónoma de México, http://www.epr.atmosfera.unam.mx/)</p> <p>Related Publication:<br> Herrera, B., Bezanilla, A., Blumenstock, T., Dammers, E., Hase, F., Clarisse, L., Magaldi, A., Rivera, C., Stremme, W., Strong, K., Viatte, C., Van Damme, M., and Grutter, M.: Measurement report: Evolution and distribution of NH3 over Mexico City from ground-based and satellite infrared spectroscopic measurements, Atmos. Chem. Phys. https://doi.org/10.5194/acp-2022-217, Accepted, 2022.</p> <p>Abstract:<br> Ammonia (NH3) is the most abundant alkaline compound in the atmosphere, with consequences for the environment, human health, and radiative forcing. In urban environments, it is known to play a key role in the formation of secondary aerosols through its reactions with nitric and sulphuric acids. However, there are only a few studies about NH3 in Mexico City. In this work, atmospheric NH3 was measured over Mexico City between 2012 and 2020 by means of ground-based solar absorption spectroscopy using Fourier transform infrared (FTIR) spectrometers at two sites (urban and remote). Total columns of NH3 were retrieved from the FTIR spectra and compared with data obtained from the Infrared Atmospheric Sounding Interferometer (IASI) satellite instrument. The diurnal variability of NH3 differs between the two FTIR stations and is strongly influenced by the urban sources. Most of the NH3 measured at the urban station is from local sources, while the NH3 observed at the remote site is most likely transported from the city and surrounding areas. The evolution of the boundary layer and the temperature play a significant role in the recorded seasonal and diurnal patterns of NH3. Although the vertical columns of NH3 are much larger at the urban station, the observed annual cycles are similar for both stations, with the largest values in the warm months, such as April and May. The IASI measurements underestimate the FTIR NH3 total columns by an average of 32.2 ± 27.5 % but exhibit similar temporal variability. The NH3 spatial distribution from IASI shows the largest columns in the northeast part of the city. In general, NH3 total columns over Mexico City exhibited an average annual increase of 92 ± 3.9 x 1013 molecules/cm2 yr (urban) and 8.4 ± 1.4 x 1013 molecules/cm2 yr (remote) was observed in Mexico City at both FTIR stations and a decadal increase of 62 % with IASI data.</p> <p>Description UNAM_FTIRdata.csv:<br> Atmospheric composition measurements made at the Universidad Nacional Autónoma de Mexico Observatory on the rooftop of the Instituto de Ciencias de la Atmósfera y Cambio Climático (UNAM, 19.33°N, 99.18°W, 2280 m.a.s.l.) located at the south of Mexico City. <br> These are retrieved from Fourier Transfor InfraRed (FTIR) solar absorption spectra recorded with a Vertex 80 spectrometer from April 2012 to October 2019. <br> The dataset contains the local time (YYYY-MM-DD hh:mm:ss AM/PM), the total columns (molecules/cm2), total error (molecules/cm2), systematic error (molecules/cm2), random error (molecules/cm2), and Degrees of Freddom (DOF).</p>
Data for: Characteristics of Selected Open Infrastructures, 2024 State of Open Infrastructure Report
<p>The State of Open Infrastructure report provides an annual snapshot of general characteristics for open infrastructures (OIs) listed in Invest in Open Infrastructure’s (IOI) open infrastructure selection tool, Infra Finder (https://infrafinder.investinopen.org/).</p> <p>The data were summarized and reported in the “2024 State of Open Infrastructure Report” section “Characteristics of selected open infrastructures.” The full report is available at https://doi.org/10.5281/zenodo.10934089.</p> <p>A readme, data dictionary, and additional metadata definition file are provided with the dataset with additional detail.</p>
COVID-19 daily situation reports - partial data extracted to .csv
<p><span>Government of Nepal Ministry of Health and Population (MoHP) and World Health Organization’s Country Office in Nepal published daily situation reports monitoring the pandemic activity on a national level. Daily situation reports were published in a PDF format including up-to-date figures on the number of COVID-19 cases, the number of PCR-tests performed at each laboratory as well as the respective number of positive test results. The provided data contains parts of the data from these .pdf reports extracted to a .csv file. The data was extracted during a joint project between MoHP, WHO Country Office Nepal, WHO South East Asia Regional Office, Polytechnique Montréal, University of Amsterdam, and Karlsruhe Institute of Technology. </span></p>
FIGURE 8 in An analysis of fossil identification guides to improve data reporting in citizen science programs
FIGURE 8. Cluster analyses of all subjects as individuals. Subject labels denote which field guide the subject tested, a red 'C' for color photos, a black 'G' for grayscale photos, and a blue 'I' for illustrations. Author names are abbreviated "DaBu" for Dava Butler, "DoEs" for Donald Esker and "KrJu" for Kristopher Juntunen.
FIGURE 1 in An analysis of fossil identification guides to improve data reporting in citizen science programs
FIGURE 1. Map of the United States and surrounding regions, showing the location of the state of Florida and FMMS (Google 2017). 1B: Geologic map of the State of Florida, showing the geographic distribution of rocks and the location of the FMMS (Google 2017; Scott et al. 2001). 1C: Geologic map of the region around the FMMS, showing the distribution of rocks and location of the site (Google 2017; Scott et al. 2001). 1D: Photograph of FMMS, taken by Fred Mazza.
Data Report: Educational Pathway on Food and Nutrition in Amyotrophic Lateral Sclerosis on the AVASUS platform
<p><strong>Dataset name:</strong><em> nutri_als_dataset.csv </em></p> <p><strong>Version: </strong>1.0 </p> <p><strong>Dataset period:</strong> 06/01/2021 - 06/05/2024</p> <p><strong>Dataset Characteristics: </strong>Multivalued </p> <p><strong>Number of Instances: </strong>20967</p> <p><strong>Number of Attributes: </strong>9</p> <p><strong>Missing Values: </strong>Yes</p> <p><strong>Area(s): </strong>Health and education<strong> </strong></p> <p><strong>Sources: </strong></p> <ul> <li>Virtual Learning Environment of the Brazilian Health System (AVASUS) (Brasil, 2024a);</li> <li>Brazilian Occupational Classification (CBO) (Brasil, 2024b);</li> <li>National Registry of Health Establishments (CNES) (Brasil, 2024c); </li> <li>Brazilian Institute of Geography and Statistics (IBGE) (Brasil, 2024d). </li> </ul> <p><strong>Description</strong>:<strong> </strong>The “nutri_als_dataset.csv” dataset (see Table 1) originates from participants of the educational pathway on Food and Nutrition in Amyotrophic Lateral Sclerosis. The educational pathway is available on the AVASUS (Brasil, 2024a). This dataset provides elementary data to analyze the scope of the educational pathway courses and the profile of their participants.</p> <p><br><strong>Note</strong>: The content of the dataset is provided in Brazilian Portuguese (pt-br), as it originates from native speakers.</p> <p><strong>Table 1: </strong>Description of AVASUS dataset features. </p> <div> <table> <tbody> <tr> <td> <p><strong>Attributes </strong></p> </td> <td> <p><strong>Description </strong></p> </td> <td> <p><strong>Datatype </strong></p> </td> <td> <p><strong>Value</strong></p> </td> </tr> <tr> <td> <p><strong>user_id</strong></p> </td> <td> <p>Unique identifier for a person (anonymous).</p> </td> <td> <p>Categorical</p> </td> <td> <p>Person unique identifier.</p> </td> </tr> <tr> <td> <p><strong>course_enrollment</strong></p> </td> <td> <p>Course enrollment period.</p> </td> <td> <p>Datetime </p> </td> <td> <p>year-month-day.</p> </td> </tr> <tr> <td> <p><strong>course_name</strong></p> </td> <td> <p>Name in Portuguese referring to the course.</p> </td> <td> <p>Categorical</p> </td> <td> <ul> <li> <p>Alimentação por sonda na ELA;</p> </li> <li> <p>Alimentação e Nutrição na ELA;</p> </li> <li> <p>Orientações nutricionais específicas na ELA; or</p> </li> <li> <p>Modificações Dietéticas na ELA.</p> </li> </ul> </td> </tr> <tr> <td> <p><strong>certificate</strong></p> </td> <td> <p>The period in which the course participant obtained the right to a certificate.</p> </td> <td> <p>Datetime</p> </td> <td> <p>year-month-day hours, minutes, and seconds.</p> </td> </tr> <tr> <td> <p><strong>gender </strong></p> </td> <td> <p>Gender of the course participant. </p> </td> <td> <p>Categorical</p> </td> <td> <ul> <li> <p>Female;</p> </li> <li> <p>Male; or</p> </li> <li> <p>Not informed.</p> </li> </ul> </td> </tr> <tr> <td> <p><strong>region</strong></p> </td> <td> <p>Brazilian region in which the participant resides.</p> </td> <td> <p>Categorical</p> </td> <td> <ul> <li> <p>North;</p> </li> <li> <p>Northeast;</p> </li> <li> <p>Central-West;</p> </li> <li> <p>Southeast;</p> </li> <li> <p>South;</p> </li> <li> <p>Abroad; or</p> </li> <li> <p>Not reported.</p> </li> </ul> </td> </tr> <tr> <td> <p><strong>course_evaluation</strong></p> </td> <td> <p>A score given to the course by the participant. </p> </td> <td> <p>Numerical</p> </td> <td> <p>0, 1, 2, 3, 4, 5, or NaN.</p> </td> </tr> <tr> <td> <p><strong>evaluation_commentary</strong></p> </td> <td> <p>Comment made by the participant about the course.</p> </td> <td> <p>Categorical</p> </td> <td> <p>Free text or NaN.</p> </td> </tr> <tr> <td> <p><strong>CBO</strong></p> </td> <td> <p>Participant occupation.</p> </td> <td> <p>Categorical</p> </td> <td> <p>Text coded according to the Brazilian Classification of Occupations or “Indivíduo sem filiação formal.” (In English, “Individual without formal affiliation.”)</p> </td> </tr> </tbody> </table> </div> <p> </p> <p> </p> <p><strong>REFERENCES</strong></p> <p>Brasil (2024a). AVASUS - Virtual Learning Environment of the Brazilian Health System. Available from: <a href="https://avasus.ufrn.br/local/avasplugin/dashboard/transparencia.php">https://avasus.ufrn.br/local/avasplugin/dashboard/transparencia.php</a>. Accessed Jul 21, 2024.</p> <p>Brasil (2024b). CBO - classificação brasileira de ocupações. Available from: <a href="https://cbo.mte.gov.br/cbosite/pages/home.jsf">https://cbo.mte.gov.br/cbosite/pages/home.jsf</a>. Accessed Jul 21, 2024.</p> <p>Brasil (2024c). CNES - cadastro nacional de estabelecimentos de saúde. Available from: <a href="https://cnes.datasus.gov.br/">https://cnes.datasus.gov.br/</a>. Accessed Jul 21, 2024.</p> <p>Brasil (2024d). IBGE - Instituto Brasileiro de Geografia e Estatística. Estimativas da População. Available from: <a href="https://agenciadenoticias.ibge.gov.br/agencia-noticias/2012-agencia-de-noticias/noticias/39525-censo-2022-informacoes-de-populacao-e-domicilios-por-setores-censitarios-auxiliam-gestao-publica">https://agenciadenoticias.ibge.gov.br/agencia-noticias/2012-agencia-de-noticias/noticias/39525-censo-2022-informacoes-de-populacao-e-domicilios-por-setores-censitarios-auxiliam-gestao-publica</a>. Accessed Jul 21, 2024.</p> <p> </p> <p><strong>ARTICLE:</strong></p> <p>Data Report: Educational Pathway on Food and Nutrition in Amyotrophic Lateral Sclerosis on the AVASUS platform <br> </p> <p><strong>AUTHORS:</strong></p> <p>Karla M. D. Coutinho<sup>1,2</sup>, Felipe Fernandes<sup>2</sup>, Kelson C. Medeiros<sup>2,6</sup>, Karilany D. Coutinho<sup>2,4,5</sup>, Aline de Pinho Dias<sup>2,4</sup>, Ricardo A. M. Valentim<sup>2,4,5</sup>, Lúcia Leite-Lais<sup>3</sup>, Kenio Costa Lima1</p> <p> </p> <p><sup>1</sup>Postgraduate Program in Health Sciences, Federal University of Rio Grande do Norte, Natal, Brazil</p> <p><sup>2</sup>Laboratory of Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte (UFRN), Natal, Rio Grande do Norte, Brazil </p> <p><sup>3</sup>Department of Nutrition, Federal University of Rio Grande do Norte, Natal, Brazil</p> <p><sup>4</sup>Postgraduate Program in Management and Innovation in Health, Federal University of Rio Grande do Norte, Natal, Brazil</p> <p><sup>5</sup>Department of Biomedical Engineering, Federal University of Rio Grande do Norte, Natal, Brazil</p> <p><sup>6</sup>Federal Institute of Education, Science and Technology of Rio Grande do Norte, Natal, Brazil</p> <p> </p> <p> </p>
Figure 3 in New data on Ovalisia (Palmar) festiva (Linnaeus) (Coleoptera: Buprestidae) and its natural enemies reported from Bulgaria
Figure 3. Natural enemies of O. festiva: Metacolus unifasciatus, female (a); Pyemotes sp. parasitizing on O. festiva larva (b)
Figure 1 in New data on Ovalisia (Palmar) festiva (Linnaeus) (Coleoptera: Buprestidae) and its natural enemies reported from Bulgaria
Figure 1. Distribution range of Ovalisia festiva in Bulgaria: blue triangles – according to Sakalian (2003) and Djuleva & Stoeva (2015); red circles – new localities (2016-2019).
Fig. 3. Phylogenetic trees from reported 18S in Molecular systematics analysis of Lymantria dispar based on 18S rRNA and cox1 mtDNA sequence data
Fig. 3. Phylogenetic trees from reported 18S rRNA genes of insects according to NJ. A. Based on sequences of full-length. B. Based on second conserved region.
SUPER-G synthesis report & associated data - D3.6 Synergies & Tradeoffs
<p>A series of co-innovation workshops within 23 farm networks helped to identify PG management <br>options, innovations, and technologies to trial on commercial and experimental farms before being <br>road tested and demonstrated on a selection of pilot farms. A series of over 40 experiments were <br>conducted on commercial and research farms across the biogeographic regions on a wide range of <br>topics. </p> <p>The field trials and experiments have involved detailed integrated assessments on farms or <br>permanent grassland (PG) areas to investigate the synergies and trade-offs between productivity, <br>biodiversity, and delivery of other selected ecosystem services (ES). </p> <p>The investigations were placed into five overarching themes:<br>1. New Grassland Species / Diverse Species Swards<br>2. Precision Grassland Management<br>3. Nutrient Management<br>4. Agri-Environment Options<br>5. Miscellaneous</p>
Report of the Posidonia data set done at the CIEM wave flume on 2008
<p>The data set presents the results from experiments done in the CIEM large wave flume of Barcelona on wave and flow attenuation by a full-scale artificial Posidonia oceanica seagrass meadow in shallow water conditions. </p> <p>More information can be found on the published papers:</p> <p>Manca, E., I. Caceres, J. Alsina, V. Stratigaki, I. Townend, C.L. Amos., 2012. Wave energy and wave-induced flow reduction by full-scale model Posidonia oceanica seagrass. Continental Shelf Research, Vol. 50-51 ,pp. 100 - 116.</p> <p>Stratigaki, V., Manca, E., Prinos, P., Losada, I., Lara, J., Sclavo, M., Amos, C., Cáceres, I. and Sánchez-Arcilla, A., 2011. Large-scale experiments on wave propagation over Posidonia oceanica. Journal of Hydraulic Research, Vol. 49, pp. 31-43.</p> <p> </p>
Data providers package for reporting Chemical Contaminants (official data reporting phase) SSD2
<p>In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (<a href="http://registerofquestions.efsa.europa.eu/roqFrontend/mandateLoader?mandate=M-2010-0374">M-2010-0374</a>) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed.</p> <p>This data providers package provides the data collection configuration and supporting materials for reporting <strong>Chemical Contaminants in SSD2</strong>. These are to be used for the official data reporting phase.</p> <p>The package includes:</p> <p>CHECK advice on the values to be reported for the mandatory fields specified for this data collection.</p> <p>The Standard Sample Description Version 2 XSD schema definition for CONTAMINANTS reporting.</p> <p>The STX transformation file which automatically assigns sampEventId and sampAnId when this information is not provided.</p> <p>The general and CONTAMINANTS SSD2 specific business rules applied for the automatic validation of the submitted datasets.</p> <p>Excel Mapping tool to convert excel files after mapping into XML document.</p> <p>Guidance on how to use the Excel Mapping tool.</p> <p>Guidance on how to run the validation report after submitting data to the DCF.</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.