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3,101 results for “Historical”
A new approach to geostatistical synthesis of historical records reveals capuchin spatial responses to climate and demographic change
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Downscaled climate grids of California at 90m for a variety of bioclimatic variables from 1971-2000, derived from historical climate grids
This dataset is comprised of 90 Geotiff images of selected bioclimatic variables for the state of California (extended past state lines to river basin boundaries). Originally created to model plant species distributions in California (Franklin et al. 2013. Modeling plant species distributions under future climates: how fine-scale do climate projections need to be? Global Change Biology 19: 473-483).
Historical Human Causes and Uses of Fire in Alaska
Although wildfire has been central to the ecological dynamics of interior Alaska for 5000 years, the role of humans in this dynamic is not well known. As a multidisciplinary research team, together with Native community partners, we analyzed patterns of human-fire interaction in two contiguous areas of Interior Alaska occupied by different Athabaskan groups. The Koyukon Athabascans in the western Interior considered fire a destructive force and had no oral history or stories suggesting use of fire for landscape management. Low lightning strike density and moist climate constrained occurrence of lightning fires, and a subsistence dependence on a predictable resource (salmon) resulted in a relatively sedentary settlement pattern. In this environment wildfire near communities might have negatively impacted hunting opportunities. In contrast, the Gwich'in Athabascans of the eastern Interior actively used fires to manage the landscape. Lightning fires occurred more frequently here because of greater lightning strike density and warmer summer temperatures. The Gwich'in showed greater mobility in hunting their less spatially predictable subsistence base (moose and caribou), which enabled them to move when wildfires altered local habitat. These striking contrasts between two neighboring Athabaskan groups sharing a contiguous boundary indicated different use and views of fire that were consistent with cultural adaptation to local biophysical and ecological settings. This contrasts with the commonly held view that Native peoples of North America pervasively modified landscapes through use of fire.
Pond diatom communities from the McMurdo Sound region of Antarctica, assessed from modern samples (2012-2016) and from historical samples collected during Shackleton’s Nimrod Expedition (1908-1909)
We performed a field survey to characterize diatom communities living in the benthic microbial mats of ponds across the McMurdo Sound region of Antarctica. Samples were collected during the Austral summers of 2012-13, 2013-14, and 2015-16 from the McMurdo Dry Valleys, Cape Royds, and from Hut Ridge near McMurdo Station. We also characterized pond diatom communities in samples collected on various dates from 1908-1909 during Ernest Shackleton’s Nimrod Expedition to compare against modern samples. Historical samples were taken from Cape Royds and the Stranded Moraines, and were analyzed from slides stored at the Natural History Museum, London. This data package includes relative abundance data for diatom species found in these modern and historical samples.
SGS-LTER Historical LTER Soil water - neutron probe: field data (1983-1992) in ungrazed ESA (Ecosystem Stress Area) on the Central Plains Experimental Range, Nunn, Colorado, USA, ARS Study Number 10
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Long-term (1985-1992) dynamics and spatial variations in soil water below the evaporative zone were evaluated for a shortgrass steppe with a low and variable precipitation regime. Each of sandy loam, clay loam, and two sandy clay loam sites compromised a toposequence with upland, midslope, and lowland positions. Soil water was monitored at 15cm intervals providing estimates covering 22.5 to 97.5 cm depths. Soil water throughout the profile was highest in the clay loam and lowest in the sandy loam. However, stored soil water did not vary systematically among slope positions. Additional information and referenced materials can be found: http://hdl.handle.net/10217/82912
SGS-LTER Historical LTER Soil water - neutron probe: lysimeter field data (1983-1992) on the Central Plains Experimental Range, Nunn, Colorado, USA, ARS Study Number 10
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Long-term (1985-1992) dynamics and spatial variations in soil water below the evaporative zone were evaluated for a shortgrass steppe with a low and variable precipitation regime. Each of sandy loam, clay loam, and two sandy clay loam sites compromised a toposequence with upland, midslope, and lowland positions. Soil water was monitored at 15cm intervals providing estimates covering 22.5 to 97.5 cm depths. Soil water throughout the profile was highest in the clay loam and lowest in the sandy loam. However, stored soil water did not vary systematically among slope positions. Additional information and referenced materials can be found: http://hdl.handle.net/10217/82912
SGS-LTER Historical LTER Soil water - neutron probe: field data (1985-1992) in Owl Creek on the Central Plains Experimental Range, Nunn, Colorado, USA, ARS Study Number 10
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Long-term (1985-1992) dynamics and spatial variations in soil water below the evaporative zone were evaluated for a shortgrass steppe with a low and variable precipitation regime. Each of sandy loam, clay loam, and two sandy clay loam sites compromised a toposequence with upland, midslope, and lowland positions. Soil water was monitored at 15cm intervals providing estimates covering 22.5 to 97.5 cm depths. Soil water throughout the profile was highest in the clay loam and lowest in the sandy loam. However, stored soil water did not vary systematically among slope positions. Additional information and referenced materials can be found: http://hdl.handle.net/10217/82912
SGS-LTER Historical LTER Soil water - neutron probe: field data (1984-1992) in Section 15, Sandy on the Central Plains Experimental Range, Nunn, Colorado, USA, ARS Study Number 10
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Long-term (1985-1992) dynamics and spatial variations in soil water below the evaporative zone were evaluated for a shortgrass steppe with a low and variable precipitation regime. Each of sandy loam, clay loam, and two sandy clay loam sites compromised a toposequence with upland, midslope, and lowland positions. Soil water was monitored at 15cm intervals providing estimates covering 22.5 to 97.5 cm depths. Soil water throughout the profile was highest in the clay loam and lowest in the sandy loam. However, stored soil water did not vary systematically among slope positions. Additional information and referenced materials can be found: http://hdl.handle.net/10217/82912
SGS-LTER Historical LTER Soil water - neutron probe: field data (1984-1992) in Section 25, Shale on the Central Plains Experimental Range, Nunn, Colorado, USA, ARS Study Number 10
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Long-term (1985-1992) dynamics and spatial variations in soil water below the evaporative zone were evaluated for a shortgrass steppe with a low and variable precipitation regime. Each of sandy loam, clay loam, and two sandy clay loam sites compromised a toposequence with upland, midslope, and lowland positions. Soil water was monitored at 15cm intervals providing estimates covering 22.5 to 97.5 cm depths. Soil water throughout the profile was highest in the clay loam and lowest in the sandy loam. However, stored soil water did not vary systematically among slope positions. Additional information and referenced materials can be found: http://hdl.handle.net/10217/82912
SGS-LTER Historical LTER Soil water - neutron probe: field data (1983-1992) across topography on the Central Plains Experimental Range, Nunn, Colorado, USA, ARS Study Number 10
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. Long-term (1985-1992) dynamics and spatial variations in soil water below the evaporative zone were evaluated for a shortgrass steppe with a low and variable precipitation regime. Each of sandy loam, clay loam, and two sandy clay loam sites compromised a toposequence with upland, midslope, and lowland positions. Soil water was monitored at 15cm intervals providing estimates covering 22.5 to 97.5 cm depths. Soil water throughout the profile was highest in the clay loam and lowest in the sandy loam. However, stored soil water did not vary systematically among slope positions. Additional information and referenced materials can be found: http://hdl.handle.net/10217/82912
Historical shorelines on Wreck Island of the Virginia Coast Reserve 1888-2003
This dataset consists of two components. An ArcGIS "shapefile" containing digitized boundary lines for the shoreline of Wreck Island for the years 1888 (partial), 1911 (partial), 1942, 1959, 1980 obtained from a NOAA coastal change map (1:24,000), 1994 (from USGS orthophotos) and October 2003 (after hurricane Isabel, from ETM+ Landsat 7 image). A mosaic of the 1994 orthophotos is also included as a GeoTIFF formated image. All data is in UTM zone 18N and uses the NAD83 datum.
Post-processed output from WACCM: historical simulation of 1957–2005 with medium energy electrons (compset B55TRWCN) and sensitivity studies (compset FW)
<p>This dataset contains post-processed monthly output from WACCM (version 4) simulations:</p> <ol> <li>historical simulation of 1957–2005 with medium energy electrons (compset B55TRWCN, B55TRWCN.zip)</li> <li>sensitivity study: 50-years experiments designed with different geomagnetic and solar conditions (compset FW, FW.zip)</li> </ol> <p>The postprocessing involved (1) zonal averaging, (2) Transformed Eulerian mean (TEM) budget calculation in log-pressure coordindates from model output (h0 files).</p> <p><strong>Contact</strong><br> Monika Szelag (monika.szelag@fmi.fi)</p> <p><strong>Raw data</strong><br> The raw, ungridded monthly data (2TB, h0 files) are currently available on FMI storage system, under path /ibrix/arch/waccm, and can be requested through the contact person. </p> <p><strong>Dataset contents</strong></p> <pre><code>B55TRWCN.zip files: vdk.zonal.002.1957-2005.nc vdk.zonal.003.1957-2005.nc vdk.zonal.004.1957-2005.nc tem.vdk.zonal.002.1957-2005.nc tem.vdk.zonal.003.1957-2005.nc tem.vdk.zonal.004.1957-2005.nc</code></pre> <p>WACCM output: historical simulations, zonal averages, 3 ensemble members of 49 years each (002,003,004).</p> <p>Variables are <strong>NOY, O3, OH, QJOULE, QRL_TOT, QRLNLTE, QRS_TOT, T, U</strong> (vdk.zonal.00[234].1957-2005.nc) and <strong>delf, fphi, fz, vres, wres, z3</strong> (tem.vdk.zonal.00[234].1957-2005.nc</p> <pre><code>FW.zip files: zonal_F2000_max.nc zonal_F2000_avg.nc zonal_F2000_min.nc tem_zonal_F2000_max.nc tem_zonal_F2000_avg.nc tem_zonal_F2000_min.nc</code></pre> <p>WACCM output: perpetual year 2000, zonal averages, 50 years experiments with 3 different solar and geomagnetic conditions (min, max, avg).</p> <p>Variables are <strong>NOY, NOX, O3, OH, QRL_TOT, QRS_TOT, T, U, V, CO, CO2, PS, TS</strong> (zonal_F2000_*.nc) and <strong>delf, fphi, fz, vres, wres, z3</strong> (tem_zonal_F2000_*.nc)</p> <p> </p>
International Labour Office Historical Studies and Reports English
<p>This is a collection of English texts based on historical reports from the International Labour Office from the 20th century. The original documents can be found at <a href="https://www.ilo.org/public/libdoc/ilo/ILO-SR/">https://www.ilo.org/public/libdoc/ilo/ILO-SR/</a></p> <p>This collection may be used and distributed provided that the International Labour Office is always duly acknowledged as the original source and that the use is non-commercial.</p> <p>The collection was created with the tools <a href="https://curl.haxx.se/">curl</a>, <a href="https://ocrmypdf.readthedocs.io/">OCRmyPDF</a>, <a href="https://poppler.freedesktop.org/">Poppler</a> and the following script on Debian GNU/Linux.</p> <pre><code class="language-bash">curl https://www.ilo.org/public/libdoc/ilo/ILO-SR/ | grep -o 'ILO[^"]*engl[^"><\/]*' | uniq | sed 's,ILO,https://www.ilo.org/public/libdoc/ilo/ILO-SR/ILO,g' > list_of_files.txt xargs -n 1 curl -O < list_of_files.txt rm list_of_files.txt find . -name '*.pdf' -exec ocrmypdf --language eng --deskew --clean '{}' '{}' \; && find . -name '*.pdf' -exec pdftotext '{}' '{}.txt' \; rm *.pdf</code></pre>
Figure 5 in A historical overview of the classification of the Neotropical tribe Zammarini (Hemiptera, Cicadidae) with a key to genera
Figure 5. Pronotal flange; bracket indicates width of pronotal flange.
Figure 3 in A historical overview of the classification of the Neotropical tribe Zammarini (Hemiptera, Cicadidae) with a key to genera
Figure 3. Presence of 2 (left) or 3 tarsomeres (right).
Figure 4 in A historical overview of the classification of the Neotropical tribe Zammarini (Hemiptera, Cicadidae) with a key to genera
Figure 4. Hind wing terminology following Moulds (2005).
Twitter historical dataset: March 21, 2006 (first tweet) to July 31, 2009 (3 years, 1.5 billion tweets)
<p><strong>Disclaimer: </strong>This dataset is distributed by Daniel Gayo-Avello, an associate professor at the Department of Computer Science in the University of Oviedo, for the sole purpose of non-commercial research and it just includes tweet ids.</p> <p>The dataset contains tweet IDs for <strong>all the published tweets</strong> (in any language) <strong>bettween March 21, 2006 and July 31, 2009</strong> thus comprising the first whole three years of Twitter from its creation, that is, about <strong>1.5 billion tweets</strong> (see file <em>Twitter-historical-20060321-20090731.zip</em>).</p> <p>It covers several defining issues in Twitter, such as the invention of hashtags, retweets and trending topics, and it includes tweets related to the 2008 US Presidential Elections, the first Obama’s inauguration speech or the 2009 Iran Election protests (one of the so-called Twitter Revolutions).</p> <p>Finally, it does contain tweets in many major languages (mainly English, Portuguese, Japanese, Spanish, German and French) so it should be possible–at least in theory–to analyze international events from different cultural perspectives.</p> <p>The dataset was completed in November 2016 and, therefore, the tweet IDs it contains were publicly available at that moment. This means that there could be tweets public during that period that do not appear in the dataset and also that a substantial part of tweets in the dataset has been deleted (or locked) since 2016.</p> <p>To make easier to understand the decay of tweet IDs in the dataset a number of representative samples (99% confidence level and 0.5 confidence interval) are provided.</p> <p>In general terms, <strong>85.5% ±0.5 of the historical tweets are available as of May 19, 2020</strong> (see file <em>Twitter-historical-20060321-20090731-sample.txt</em>). However, since the amount of tweets vary greatly throughout the period of three years covered in the dataset, additional representative samples are provided for 90-day intervals (see the file <em>90-day-samples.zip</em>).</p> <p>In that regard, the ratio of publicly available tweets (as of May 19, 2020) is as follows:</p> <ul> <li>March 21, 2006 to June 18, 2006: 88.4% ±0.5 (from 5,512 tweets).</li> <li>June 18, 2006 to September 16, 2006: 82.7% ±0.5 (from 14,820 tweets).</li> <li>September 16, 2006 to December 15, 2006: 85.7% ±0.5 (from 107,975 tweets).</li> <li>December 15, 2006 to March 15, 2007: 88.2% ±0.5 (from 852,463 tweets).</li> <li>March 15, 2007 to June 13, 2007: 89.6% ±0.5 (from 6,341,665 tweets).</li> <li>June 13, 2007 to September 11, 2007: 88.6% ±0.5 (from 11,171,090 tweets).</li> <li>September 11, 2007 to December 10, 2007: 87.9% ±0.5 (from 15,545,532 tweets).</li> <li>December 10, 2007 to March 9, 2008: 89.0% ±0.5 (from 23,164,663 tweets).</li> <li>March 9, 2008 to June 7, 2008: 66.5% ±0.5 (from 56,416,772 tweets; see below for more details on this).</li> <li>June 7, 2008 to September 5, 2008: 78.3% ±0.5 (from 62,868,189 tweets; see below for more details on this).</li> <li>September 5, 2008 to December 4, 2008: 87.3% ±0.5 (from 89,947,498 tweets).</li> <li>December 4, 2008 to March 4, 2009: 86.9% ±0.5 (from 169,762,425 tweets).</li> <li>March 4, 2009 to June 2, 2009: 86.4% ±0.5 (from 474,581,170 tweets).</li> <li>June 2, 2009 to July 31, 2009: 85.7% ±0.5 (from 589,116,341 tweets).</li> </ul> <p>The apparent drop in available tweets from March 9, 2008 to September 5, 2008 has an easy, although embarrassing, explanation.</p> <p>At the moment of cleaning all the data to publish this dataset there seemed to be a gap between April 1, 2008 to July 7, 2008 (actually, the data was not missing but in a different backup). Since tweet IDs are easy to regenerate for that Twitter era (source code is provided in <em>generate-ids.m</em>) I simply produced all those that were created between those two dates. All those tweets actually existed but a number of them were obviously private and not crawlable. For those regenerated IDs the actual ratio of public tweets (as of May 19, 2020) is 62.3% ±0.5.</p> <p>In other words, what you see in that period (April to July, 2008) is not actually a huge number of tweets having been deleted but the combination of deleted *and* non-public tweets (whose IDs should not be in the dataset for performance purposes when rehydrating the dataset).</p> <p>Additionally, given that not everybody will need the whole period of time the earliest tweet ID for each date is provided in the file <em>date-tweet-id.tsv</em>.</p> <p>For additional details regarding this dataset please see: <strong>Gayo-Avello, Daniel. "How I Stopped Worrying about the Twitter Archive at the Library of Congress and Learned to Build a Little One for Myself." <em>arXiv preprint arXiv:1611.08144</em> (2016)</strong>.</p> <p><strong>If you use this dataset in any way please cite that preprint </strong>(in addition to the dataset itself).</p> <p>If you need to contact me you can find me as <a href="https://twitter.com/pfcdgayo">@PFCdgayo</a> in Twitter.</p>
Data from: Historical demography and climate driven distributional changes in a widespread Neotropical freshwater species with high economic importance
The Neotropical region exhibits the greatest worldwide diversity and the diversification history of several clades is related to the puzzling geomorphologic and climatic history of this region. The freshwater Amazon ecoregion contains the main hydrographic basins of the Neotropical region that are highly dendritic and ecologically diverse. It contains a rich and endemic fish fauna, including one of its most iconic and economically important representatives, the bony-tongue Arapaima gigas (Teleostei, Osteoglossiformes). Here, we evaluated the projected distribution of the genus in different historical periods (Present, Last Glacial Maximum, Last Interglacial Maximum and Near Future) and interpreted these results in light of the genomic diversity and modeled historical demography. For that, we combined species distribution models, population genetic analysis using SNPs and deep learning model selection. We analyzed a representative sample of the genus from the two basins where it naturally occurs, four localities in the Amazon (Am) and three in the Tocantins-Araguaia (To-Ar) basin, as well as individuals from three fish farms. We inferred a potentially smaller distribution in the glacial period, with a possible refuge in central Am. Our genetic data agrees with this result, suggesting a higher level of genetic diversity in the Am basin, compared to that observed in To-Ar. Our deep learning model comparison indicated that the To-Ar basin was colonized by the population from the Am basin. Considering a global warming scenario in the near future, A. gigas could reach an even larger range, especially if anthropogenic related dispersal occurs, potentially invading new areas and impacting their communities.
Historical data of heroes and players of Dota 2
<p>This dataset contains historical data of heroes and players of Dota 2 and features to be used in win prediction models. More specifically, it includes:</p> <ul> <li>Changelog for all existing heroes of Dota 2</li> <li>Historical attribute values for all existing heroes of Dota 2 <ul> <li>Base strength</li> <li>Base agility</li> <li>Base intelligence</li> <li>Strength gain</li> <li>Agility gain</li> <li>Intelligence gain</li> <li>Base health</li> <li>Base health regeneration</li> <li>Movement speed</li> </ul> </li> <li>Historical statistics of heroes and players of Dota 2</li> <li>Historical statistics of heroes and players of Dota 2 organized by date</li> <li>Computed features useful for win prediction models</li> </ul>
Geopackage of data for Historical Archaeology and JOAD article
<p>This file is a Geopackage database that includes the following:</p> <p>For raster files, *Raw* indicates that data is the same as the previously archived version and "Rendered" indicates the visualization of that data. </p> <p>"DigitalElevationModelRaw" and "DigitalElevationModelRendered" are based upon Digital Elevation Model for Blue Mountain Charcoal Research Project. <a href="https://zenodo.org/record/1252441">https://zenodo.org/record/1252441</a></p> <p>"HillshadeRaw" and "HillshadeRendered" are based upon Hillshade Analysis of "Digital Elevation Model for Blue Mountain Charcoal Research Project". <a href="https://zenodo.org/record/1252520">https://zenodo.org/record/1252520</a></p> <p>"SlopeRaw" and "SlopeRendered" are based upon Slope Analysis of "Digital Elevation Model for Blue Mountain Charcoal Research Project". <a href="https://zenodo.org/record/1252977">https://zenodo.org/record/1252977</a></p> <p>"Hearths" = Identified Charcoal Hearths from "Slope Analysis of 'Digital Elevation Model for Blue Mountain Charcoal Research Project'". <a href="https://zenodo.org/record/1252985">https://zenodo.org/record/1252985</a></p> <p>"ResearchArea" = Blue Mountain Charcoal Project Research Area. <a href="https://zenodo.org/record/1252418">https://zenodo.org/record/1252418</a></p> <p>The collection of this data is described here:</p> <p>Description of Methods for Identifying Charcoal Hearths along the Blue Mountain of Pennsylvania. <a href="https://zenodo.org/record/1255101">https://zenodo.org/record/1255101</a></p> <p>And is published here:</p> <p>Carter, Benjamin P. 2019. “Identifying Landscape Modification Using Open Data and Tools: The Charcoal Hearths of the Blue Mountain, Pennsylvania.” <em>Historical Archaeology</em> 53 (2): 432–43. <a href="https://doi.org/10.1007/s41636-019-00171-1">https://doi.org/10.1007/s41636-019-00171-1</a>.</p> <p>Carter, Benjamin. 2019. “Data for ‘Identifying Landscape Modification Using Open Data and Tools: The Charcoal Hearths of the Blue Mountain, Pennsylvania.’” <em>Journal of Open Archaeology Data</em> 7 (July). <a href="https://doi.org/10.5334/joad.53">https://doi.org/10.5334/joad.53</a>.</p> <p>This data can be visualized here: NEEDED</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.