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13,117 results for “Maps”
Indicative distribution map for Ecosystem Functional Group T2.3 Oceanic cool temperate rainforests
<p>This archive contains indicative distribution maps and profiles for <strong>T2.3 Oceanic cool temperate rainforests</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Indicative distribution map for Ecosystem Functional Group T2.2 Deciduous temperate forests
<p>This archive contains indicative distribution maps and profiles for <strong>T2.2 Deciduous temperate forests</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Indicative distribution map for Ecosystem Functional Group T3.1 Seasonally dry tropical shrublands
<p>This archive contains indicative distribution maps and profiles for <strong>T3.1 Seasonally dry tropical shrublands</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Indicative distribution map for Ecosystem Functional Group T3.2 Seasonally dry temperate heath and shrublands
<p>This archive contains indicative distribution maps and profiles for <strong>T3.2 Seasonally dry temperate heath and shrublands</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Indicative distribution map for Ecosystem Functional Group T7.2 Sown pastures and fields
<p>This archive contains indicative distribution maps and profiles for <strong>T7.2 Sown pastures and fields</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Indicative distribution map for Ecosystem Functional Group T2.4 Warm temperate laurophyll forests
<p>This archive contains indicative distribution maps and profiles for <strong>T2.4 Warm temperate laurophyll forests</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Indicative distribution map for Ecosystem Functional Group S2.1 Anthropogenic subterranean voids
<p>This archive contains indicative distribution maps and profiles for <strong>S2.1 Anthropogenic subterranean voids</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Dataset: Rainbow color map distorts and misleads research in hydrology – guidance for better visualizations and science communication
<p>The rainbow color map is scientifically incorrect and hinders people with color vision deficiency to view visualizations in a correct way. Due to perceptual non-uniform color gradients within the rainbow color map the data representation is distorted what can lead to misinterpretation of results and flaws in science communication. Here we present the data of a paper survey of 797 scientific publication in the journal Hydrology and Earth System Sciences. With in the survey all papers were classified according to color issues. Find details about the data below.</p> <ul> <li><code>year</code> = year of publication (YYYY)</li> <li><code>date</code> = date (YYYY-MM-DD) of publication</li> <li><code>title</code> = full paper title from journal website</li> <li><code>authors</code> = list of authors comma-separated</li> <li><code>n_authors</code> = number of authors (integer between 1 and 27)</li> <li><code>col_code</code> = color-issue classification (see below)</li> <li><code>volume</code> = Journal volume</li> <li><code>start_page</code> = first page of paper (consecutive)</li> <li><code>end_page</code> = last page of paper (consecutive)</li> <li><code>base_url</code> = base url to access the PDF of the paper with <code>/volume/start_page/year/</code></li> <li><code>filename</code> = specific file name of the paper PDF (e.g. <code>hess-9-111-2005.pdf</code>)</li> </ul> <p>Color classification is stored in the <code>col_code</code> variable with:</p> <ul> <li><code>0</code> = chromatic and issue-free,</li> <li><code>1</code> = red-green issues,</li> <li><code>2</code>= rainbow issues and</li> <li><code>bw</code>= black and white paper.</li> </ul> <p> </p> <p>See more details (e.g., sample code to analyse the survey data) on https://github.com/modche/rainbow_hydrology</p> <p>Paper: Stoelzle, M. and Stein, L.: Rainbow color map distorts and misleads research in hydrology – guidance for better visualizations and science communication, Hydrol. Earth Syst. Sci., 25, 4549–4565, https://doi.org/10.5194/hess-25-4549-2021, 2021.</p> <p> </p> <p> </p>
COVID19 Flow-Maps Daily Cases Reports
<p>This repository contains COVID-19 data for Spain, including daily cases at the level of autonomous communities as well as provinces, and higher spatial resolution for several autonomous communities (eight out of the nineteen autonomous communities publish reports with local daily COVID-19 cases at the level of municipalities or Basic Health Areas).</p> <p>Each record has an identifier, the associated date, the corresponding identifier of the layer and code of the region and a set of COVID-19 related fields, which include the number of new cases (daily incidence) and total cases.</p> <ul> <li> <p><strong>Autonomous Communities</strong>: ES.covid_cca</p> </li> <li> <p><strong>Provinces</strong>: ES.covid_cpro</p> </li> <li> <p>Higher spatial resolution:</p> <ul> <li> <p><strong>Principado de Asturias</strong>: 03.covid_cumun</p> </li> <li> <p><strong>Cantabria</strong>: 06.covid_cumun</p> </li> <li> <p><strong>Castilla y Leon</strong>: 07.covid_abs</p> </li> <li> <p><strong>Cataluña/Catalunya</strong>: 09.covid_abs</p> </li> <li> <p><strong>Comunitat Valenciana</strong>: 10.covid_cumun</p> </li> <li> <p><strong>Comunidad de Madrid</strong>: 13.covid_abs</p> </li> <li> <p><strong>Comunidad Foral de Navarra</strong>: 15.covid_abs</p> </li> <li> <p><strong>País Vasco/Euskadi</strong>: 16.covid_abs</p> </li> </ul> </li> </ul> <p>For information about data sources, visit: <a href="https://flowmaps.life.bsc.es/flowboard/data">https://flowmaps.life.bsc.es/flowboard/data</a></p>
COVID19 Flow-Maps Mobility-Associated-Risk
<p><strong>The Mobility Associated Risk</strong></p> <p>The Mobility Associated Risk is a risk score combines mobility and COVID-19 incidence to estimate how many cases could theoretically be exported/imported between different origin-destination pairs of regions.</p> <p>For more information about how the MAR is calculated visit: <a href="https://flowmaps.life.bsc.es/flowboard/board_what_is_risk#what_is_risk">https://flowmaps.life.bsc.es/flowboard/board_what_is_risk#what_is_risk</a></p> <p>Dashboard The Mobility Associated Risk combines mobility and COVID-19 incidence to estimate how many cases could theoretically be exported/imported between different origin-destination pairs of regions.</p> <p>For more information about how the MAR is calculated visit: <a href="https://flowmaps.life.bsc.es/flowboard/board_what_is_risk#what_is_risk">https://flowmaps.life.bsc.es/flowboard/board_what_is_risk#what_is_risk</a></p> <p>Dashboard <a href="https://flowmaps.life.bsc.es/flowboard/">https://flowmaps.life.bsc.es/flowboard/</a></p>
COVID19 Flow-Maps Population data
<p><strong>Daily population and trips per person data from Spain 2020-2021</strong></p> <p>This repository contains daily population records based on a study conducted by the MITMA, that analysed the mobility and distribution of the population in Spain from February 14th 2020 to May 9th 2021. The study is based on a sample of more than 13 million anonymised mobile phone lines provided by a single mobile operator whose subscribers are evenly distributed.</p> <p>For more information on the data visit: <a href="https://www.mitma.gob.es/ministerio/covid-19/evolucion-movilidad-big-data">https://www.mitma.gob.es/ministerio/covid-19/evolucion-movilidad-big-data</a></p> <p>Data provided by MITMA is related to the layer mitma_mov. For the rest of the layers, the population was estimated using the population grid from GEOSTAT: <a href="https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/population-distribution-demography/geostat">https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/population-distribution-demography/geostat</a></p>
West Texas Lightning Mapping Array - KTaL 2015-2016
<p>West Texas Lightning Mapping Array data collected near Lubbock, Texas as part of the Kinematic Texture and Lightning (KTaL) field campaign in 2015-2016. Includes VHF source locations and clustered flashes and their physical properties. Data are a subset of the full record, corresponding to the storms studied in a forthcoming publication.</p>
Geological map of the southern Red Sea & western Gulf of Aden region
<p><strong>Content</strong></p> <p>This dataset contains a geological map of the southern Red Sea & western Gulf of Aden region (1:3’100’000), including all the associated data.</p> <p>This dataset includes:</p> <ul> <li>The map in JPEG, PDF, and GeoTIFF format</li> <li>The shapefiles of the map</li> <li>One document listing all sources used for the compilation of this map (<em>Source_Material_GmsRSwGoAr.pdf</em>)</li> </ul> <p> </p> <p>This database is an additional complement to the paper ‘Rime, V., Foubert, A., Ruch, J. & Kidane, T. (2023), Tectonostratigraphic evolution and significance of the Afar Depression, <em>Earth-Science Reviews</em>, 244, 104519, <a href="https://doi.org/10.1016/j.earscirev.2023.104519">https://doi.org/10.1016/j.earscirev.2023.104519</a> ’<em>.</em></p> <p>Note that a larger-scale map of the Afar Depression is available as 'Rime, V., Foubert, A., Atnafu, B. and Kidane, T. (2022) Geological map of the Afar Depression. <em>Zenodo</em>. <a href="https://doi.org/10.5281/zenodo.7351643">https://doi.org/10.5281/zenodo.7351643</a> '</p> <p> </p> <p><strong>References</strong></p> <p>The map was developed by compiling a large number of published maps, descriptions, datings and other studies, complemented by remote sensing. All sources and references are mentioned in the <em>Source_Material_GmsRSwGoAr</em>. Material and methods of mapping have been described in detail within the paper.</p> <p> </p> <p><strong>Citation</strong></p> <p>When using the data, please cite the data as ‘Rime, V., Foubert, A., Atnafu, B. & Kidane, T. (2022) Geological map of the southern Red Sea & western Gulf of Aden region. Zenodo’ and refer to the accompanying paper as ‘Rime, V., Foubert, A., Ruch, J. & Kidane, T. (2023), Tectonostratigraphic evolution and significance of the Afar Depression, <em>Earth-Science Reviews</em>, 244, 104519, <a href="https://doi.org/10.1016/j.earscirev.2023.104519">https://doi.org/10.1016/j.earscirev.2023.104519</a> ’<em>.</em></p> <p>The map and additional data are given without any guarantee of correctness. Any use of these are under the user’s full responsibility.The authors decline any responsibility.</p> <p> </p> <p><strong>Acknowledgements</strong></p> <p>This study was funded by the Swiss National Science Foundation (SNF project SERENA – SEdimentary REcord of the Northern Afar 200021_163114). We are grateful to the University of Fribourg (Switzerland), the University of Addis Ababa (Ethiopia), the Ethiopian Ministry of Mines and Energy, the Ethiopian Geological Survey, Circum Minerals, former Allana Potash and Yara Dallol for their support. We particularly acknowledge Samuel Getachew that helped us to access some of the geological maps. We thank David Jaramillo-Vogel, Jean-Charles Schaegis, Haileyesus Negga, Addis Endeshaw, Ermias Gebru, Eva de Boever, Juan-Carlos Braga, Pia Wyler, Xenia Haberditz, the Ethioder team as well as the regional and local administration of the Afar for their help and support during fieldwork.</p>
Global map of soil bacterial richness
<p>This repository contains global model estimates of soil bacterial richness (Fig.4) as described in:</p> <p>Bickel, Samuel, Xi Chen, Andreas Papritz, and Dani Or. “A Hierarchy of Environmental Covariates Control the Global Biogeography of Soil Bacterial Richness.” <em>Scientific Reports</em> 9, no. 1 (August 20, 2019): 1–10. <a href="https://doi.org/10.1038/s41598-019-48571-w">https://doi.org/10.1038/s41598-019-48571-w</a>.</p>
Geological map of the Afar Depression
<p><strong>Content</strong></p> <p>This dataset contains a geological map of the Afar Depression (1:1’000’000), including all the associated data.</p> <p>This dataset includes:</p> <ul> <li>The map in JPEG, PDF, and GeoTIFF format</li> <li>The shapefiles of the map</li> <li>One document listing all sources used for the compilation of this map (<em>Source_Material_Afar Depression.pdf)</em></li> <li>One document describing the uncertainty of the map (<em>Reliability_geol_map.pdf</em>)</li> <li>One dating database compiling published datings from the literature in .txt and shapefile formats. This database has been reviewed and mistakes in coordinates were corrected (see comments column). The precision of the position is also evaluated (1 = poor - possibly up to more than 10km uncertainty; 2 = average - no precise GPS measurement of the coordinates but good localisation on map or description of the outcrop; 3 = very good - most of the time GPS measurement or very precise descriptions/map).</li> </ul> <p> </p> <p>This database is an additional complement to the paper ‘Rime, V., Foubert, A., Ruch, J. & Kidane, T. (2023), Tectonostratigraphic evolution and significance of the Afar Depression, <em>Earth-Science Reviews</em>, 244, 104519, <a href="https://doi.org/10.1016/j.earscirev.2023.104519">https://doi.org/10.1016/j.earscirev.2023.104519</a> ’<em>.</em></p> <p>Note that a smaller-scale map of the region is available as 'Rime, V., Foubert, A., Atnafu, B. and Kidane, T. (2022) Geological map of the southern Red Sea & western Gulf of Aden region. <em>Zenodo</em>. <a href="https://doi.org/10.5281/zenodo.7351765">https://doi.org/10.5281/zenodo.7351765</a> '</p> <p> </p> <p><strong>References</strong></p> <p>The map was developed by compiling a large number of published maps, descriptions, datings and other studies, complemented by fieldwork and remote sensing. All sources and references are mentioned in the <em>Source_Material_Afar_Depression</em>. Material and methods of mapping have been described in detail within the paper.</p> <p> </p> <p><strong>Citation</strong></p> <p>When using the data, please cite the data as ‘Rime, V., Foubert, A., Atnafu, B. & Kidane, T. (2022) Geological map of the Afar Depression. Zenodo, https://doi.org/10.5281/zenodo.7351643’ and refer to the accompanying paper as ‘Rime, V., Foubert, A., Ruch, J. & Kidane, T. (2023), Tectonostratigraphic evolution and significance of the Afar Depression, <em>Earth-Science Reviews</em>, 244, 104519, <a href="https://doi.org/10.1016/j.earscirev.2023.104519">https://doi.org/10.1016/j.earscirev.2023.104519</a> ’<em>.</em></p> <p>The map and additional data are given without any guarantee of correctness. Any use of these are under the user’s full responsibility. The authors decline any responsibility.</p> <p> </p> <p><strong>Acknowledgements</strong></p> <p>This study was funded by the Swiss National Science Foundation (SNF project SERENA – SEdimentary REcord of the Northern Afar 200021_163114). We are grateful to the University of Fribourg (Switzerland), the University of Addis Ababa (Ethiopia), the Ethiopian Ministry of Mines and Energy, the Ethiopian Geological Survey, Circum Minerals, former Allana Potash and Yara Dallol for their support. We particularly acknowledge Samuel Getachew that helped us to access some of the geological maps. We thank David Jaramillo-Vogel, Jean-Charles Schaegis, Haileyesus Negga, Addis Endeshaw, Ermias Gebru, Eva de Boever, Juan-Carlos Braga, Pia Wyler, Xenia Haberditz, the Ethioder team as well as the regional and local administration of the Afar for their help and support during fieldwork.</p>
A three-dimensional map of the Milky Way using 66,000 Mira variable stars
<p>We provide here full Table 1 from Iwanek, P., et al., 2023, "A three-dimensional map of the Milky Way using 66,000 Mira variable stars", ApJS (accepted for publication, DOI: 10.3847/1538-4365/acad7a), which contains mean magnitudes, distances, extinction values, and photometric chemical types for 65,981 Galactic Miras (Iwanek2023_Table1_GalMirasDist.txt file). The corner plot, i.e., the two-dimensional projections of the multi-dimensional posterior parameter spaces fitted to the Galactic Miras distribution is presented in Figure Iwanek2023_corner_plot.png.</p> <p> </p> <p>Patryk Iwanek is partially supported by Kartezjusz program No. POWR.03.02.00-00-I001/16-00, founded by the National Centre for Research and Development, Poland. Szymon Kozłowski acknowledges the support from the National Science Centre, Poland, via grant OPUS 2018/31/B/ST9/00334. </p> <p>This publication makes use of data products from WISE, which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California Institute of Technology, funded by the National Aeronautics and Space Administration (NASA). This work is based in part on archival data obtained with the Spitzer Space Telescope, which was operated by the Jet Propulsion Laboratory, California Institute of Technology under a contract with NASA.</p>
Set of CFT files from EBSD maps
<p>Set of .ctf files from EBSD maps (treated data) used in the articles Demouchy et al., submitted at European Journal Mineralogy.</p> <p>Demouchy, S., Thieme, M., Barou F., Beausir B., Taupin V., Cordier P., (2022-2023). Dislocation and disclination densities in experimentally deformed polycrystalline olivine. Submitted to <em>Eur. J. Min</em>., in revision (minor revision), dec 2022.</p>
Tectonic Map and Compressional Feature Map of Mare Tranquillitatis, Moon
<p>ArcGIS shapefiles of the tectonic (Compressional_Tectonism and Extensional_Tectonism) and compressional feature (Feature_Map_Classes) maps of Mare Tranquillitatis. This is complementary data for "Timing and Origin of Compressional Tectonism in Mare Tranquillitatis" published on JGR: Planets by Frueh et al. (Available on <a href="https://doi.org/10.1029/2022JE007533">https://doi.org/10.1029/2022JE007533</a>). </p> <ul> <li>Compressional_Tectonism: Polylines of wrinkle ridges, lobate scarps, and unidentified features, as well as their geodesic length, coordinates, and bearing.</li> <li>Extensional_Tectonism: Polylines of large graben and normal faults, as well as their geodesic length, coordinates, and bearing.</li> <li>Feature_Map_Classes: Compressional tectonic feature map, including their assigned erosional states.</li> </ul> <p>For a detailed description of the mapping process, features, and erosional states, we currently refer to our publication (Frueh et al., 2023).</p> <p> </p> <p>Frueh, T., Hiesinger, H., van der Bogert, C. H., Clark, J. D., Watters, T. R., & Schmedemann, N. (2023). Timing and origin of compressional tectonism in Mare Tranquillitatis. <em>Journal of Geophysical Research: Planets</em>, 128, e2022JE007533. <a href="https://doi.org/10.1029/2022JE007533">https://doi.org/10.1029/2022JE007533</a></p>
Environmental Materiality Map:MSCI
<p>The dataset was collected from <a href="https://www.msci.com/our-solutions/esg-investing/esg-industry-materiality-map">MSCI Industry Materiality Map: </a> "MSCI ESG Ratings assess the resilience of companies to long-term, financially relevant environmental, social, and governance (ESG) risks. Our ESG Industry Materiality Map is a representation of the current ESG Key Issues and their contribution to companies' ESG Ratings. This map is part of our ESG Ratings transparency initiatives, through which we have made ESG Ratings of <a href="https://www.msci.com/esg-ratings">companies</a> and <a href="https://www.msci.com/esg-fund-ratings">funds</a> accessible to the public." - MSCI (2023)</p>
Social Materiality Map: MSCI
<p>The dataset was collected from <a href="https://www.msci.com/our-solutions/esg-investing/esg-industry-materiality-map">MSCI Industry Materiality Map: </a> "MSCI ESG Ratings assess the resilience of companies to long-term, financially relevant environmental, social, and governance (ESG) risks. Our ESG Industry Materiality Map is a representation of the current ESG Key Issues and their contribution to companies' ESG Ratings. This map is part of our ESG Ratings transparency initiatives, through which we have made ESG Ratings of <a href="https://www.msci.com/esg-ratings">companies</a> and <a href="https://www.msci.com/esg-fund-ratings">funds</a> accessible to the public." - MSCI</p> <p>We collected MSCI Materiality Map and structured. </p> <p>Further information regarding the data collection process and codebook will be published in the future.</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.