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19 results for “regional geology”
Supplementary Data for Wueller et al. (2024): Geologic History of the Amundsen Crater Region Near the Lunar South Pole: Basis for Future Exploration
<p>Supplementary Data for Wueller et al. (2024): Geologic History of the Amundsen Crater Region Near the Lunar South Pole: Basis for Future Exploration</p> <p>Data contains the georeferenced map plate of our geologic map that can be used in any geoinformation system (GIS).</p> <p><strong>If you use these data, please cite BOTH the Planetary Science Journal publication and the Zenodo dataset.</strong></p> <p>Wueller, L., Iqbal, W., Frueh, T., van der Bogert, C. H., & Hiesinger, H. (2024). Geologic history of the Amundsen crater region near the Lunar South Pole: Basis for future exploration. <em>The Planetary Science Journal</em>, <em>5</em>(6), 147. <a href="https://iopscience.iop.org/article/10.3847/PSJ/ad2c04">https://iopscience.iop.org/article/10.3847/PSJ/ad2c04</a></p> <p>Wueller, L., Iqbal, W., Frueh, T., van der Bogert, C. H., & Hiesinger, H. (2024). Supplementary Data for Wueller et al. (2024): Geologic history of the Amundsen crater region near the Lunar South Pole: Basis for future exploration. <em>Zenodo Dataset</em>. <a href="https://doi.org/10.5281/zenodo.10693820" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10693820</a></p> <p>-----------------------------------------------------------------------------------------------------------------------------------------</p> <p>Mapping Scale is 1:100,000</p> <p>Print Scale is 1:1,000,000</p> <p>-----------------------------------------------------------------------------------------------------------------------------------------</p> <p>For further questions contact lwueller@uni-muenster.de</p> <p>Lukas Wueller, Institut für Planetologie, Universität Münster, Germany, June 2024</p>
Geological Maps in the Syrtis Major Region, Mars
<p>The dataset is an ArcGIS geodatabase for the geological maps within the Syrtis Major region illustrated in Voigt et al., 2024. The geodatabase includes contacts as line features and geologic units as point features. Related publication: J.R.C. Voigt, V.Z. Sun, C.E. Viviano,<span> </span>M. Stack (2024): Investigating Hydrated Silica in Syrtis Major, Mars: Implications for the Longevity of Water–Rock Interaction. Geophysical Research Letters. </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>
Geographical and geological GIS boundaries of the Tibetan Plateau and adjacent mountain regions
<p><strong>Introduction</strong></p> <p>Geographical scale, in terms of spatial extent, provide a basis for other branches of science. This dataset contains newly proposed geographical and geological GIS boundaries for the <strong>Pan-Tibetan Highlands </strong>(new proposed name for the High Mountain Asia), based on geological and geomorphological features. This region comprises the <strong>Tibetan Plateau</strong> and three adjacent mountain regions: the <strong>Himalaya</strong>, <strong>Hengduan Mountains</strong> and <strong>Mountains of Central Asia</strong>, and boundaries are also given for each subregion individually. The dataset will benefit quantitative spatial analysis by providing a well-defined geographical scale for other branches of research, aiding cross-disciplinary comparisons and synthesis, as well as reproducibility of research results.</p> <p>The dataset comprises three subsets, and we provide three data formats (.shp, .geojson and .kmz) for each of them. Shapefile format (.shp) was generated in ArcGIS Pro, and the other two were converted from shapefile, the conversion steps refer to 'Data processing' section below. The following is a description of the three subsets:</p> <p>(1) The GIS boundaries we newly defined of the Pan-Tibetan Highlands and its four constituent sub-regions, i.e. the Tibetan Plateau, Himalaya, Hengduan Mountains and the Mountains of Central Asia. All files are placed in the "Pan-Tibetan Highlands (Liu et al._2022)" folder.</p> <p>(2) We also provide GIS boundaries that were applied by other studies (cited in Fig. 3 of our work) in the folder "Tibetan Plateau and adjacent mountains (Others’ definitions)". If these data is used, please cite the relevent paper accrodingly. In addition, it is worthy to note that the GIS boundaries of Hengduan Mountains (Li et al. 1987a) and Mountains of Central Asia (Foggin et al. 2021) were newly generated in our study using Georeferencing toolbox in ArcGIS Pro.</p> <p>(3) Geological assemblages and characters of the Pan-Tibetan Highlands, including Cratons and micro-continental blocks (Fig. S1), plus sutures, faults and thrusts (Fig. 4), are placed in the "Pan-Tibetan Highlands (geological files)" folder.</p> <p>Note: <strong>High Mountain Asia</strong>: The name ‘High Mountain Asia’ is the only direct synonym of Pan-Tibetan Highlands, but this term is both grammatically awkward and somewhat misleading, and hence the term ‘Pan-Tibetan Highlands’ is here proposed to replace it. <strong>Third Pole</strong>: The first use of the term ‘Third Pole’ was in reference to the Himalaya by Kurz & Montandon (1933), but the usage was subsequently broadened to the Tibetan Plateau or the whole of the Pan-Tibetan Highlands. The mainstream scientific literature refer the ‘Third Pole’ to the region encompassing the Tibetan Plateau, Himalaya, Hengduan Mountains, Karakoram, Hindu Kush and Pamir. This definition was surpported by geological strcture (Main Pamir Thrust) in the western part, and generally overlaps with the ‘Tibetan Plateau’ <em>sensu lato</em> defined by some previous studies, but is more specific.</p> <p>More discussion and reference about names please refer to the paper. The figures (Figs. 3, 4, S1) mentioned above were attached in the end of this document.</p> <p> </p> <p><strong>Data processing</strong></p> <p>We provide three data formats. Conversion of shapefile data to kmz format was done in ArcGIS Pro. We used the <em>Layer to KML</em> tool in Conversion Toolbox to convert the shapefile to kmz format. Conversion of shapefile data to geojson format was done in R. We read the data using the <em>shapefile</em> function of the raster package, and wrote it as a geojson file using the <em>geojson_write</em> function in the geojsonio package.</p> <p> </p> <p><strong>Version</strong></p> <p>Version 2022.1.</p> <p> </p> <p><strong>Acknowledgements</strong></p> <p>This study was supported by the Strategic Priority Research Program of Chinese Academy of Sciences (XDB31010000), the National Natural Science Foundation of China (41971071), the Key Research Program of Frontier Sciences, CAS (ZDBS-LY-7001). We are grateful to our coauthors insightful discussion and comments. We also want to thank professors Jed Kaplan, Yin An, Dai Erfu, Zhang Guoqing, Peter Cawood, Tobias Bolch and Marc Foggin for suggestions and providing GIS files.</p> <p> </p> <p><strong>Citation</strong></p> <p>Liu, J., Milne, R. I., Zhu, G. F., Spicer, R. A., Wambulwa, M. C., Wu, Z. Y., Li, D. Z. (2022). Name and scale matters: Clarifying the geography of Tibetan Plateau and adjacent mountain regions. Global and Planetary Change, In revision</p> <p> </p> <p>Jie Liu & Guangfu Zhu. (2022). Geographical and geological GIS boundaries of the Tibetan Plateau and adjacent mountain regions (Version 2022.1). https://doi.org/10.5281/zenodo.6432940</p> <p> </p> <p><strong>Contacts</strong></p> <p>Dr. Jie LIU: E-mail: <a>liujie@mail.kib.ac.cn</a>;</p> <p>Mr. Guangfu ZHU: <a>zhuguangfu@mail.kib.ac.cn</a></p> <p>Institution: Kunming Institute of Botany, Chinese Academy of Sciences</p> <p>Address: 132# Lanhei Road, Heilongtan, Kunming 650201, Yunnan, China</p> <p> </p> <p><strong>Copyright</strong></p> <p>This dataset is available under the Attribution-ShareAlike 4.0 International (<a href="https://creativecommons.org/licenses/by-sa/4.0/">CC BY-SA 4.0</a>).</p>
Hazardous geological processes occurrence assessment for Transcarpathian region,_Ukraine
<p>Maps of hazardous geological processes specific occurrence by administrative districts for Transcarpathian region were produced by the Institute of Geological Sciences of the National Academy of Sciences of Ukraine based on the processing of materials from such institutions: State Service of Geology and Mineral Resources of Ukraine, Transcarpathian geological and hydrogeological center of the State Enterprise "Zakhidukrgeologiia" of the National Joint Stock Company "Nadra Ukrainy", Berehovo, State Geological Information Archive of Ukraine. In particular, maps of the distribution of hazardous geological processes with a scale of 1:100000 (by V. Barnychka, 1980) and a scale of 1: 200000 (by M. Gabor) for the period 1980-2010 were used, as well as data provided by V. Petryk ("Zakhidukrgeologiia", 1983-2001), and data from information yearbooks on the of hazardous exogenous geological processes activization for Ukraine territory according to monitoring of engineering and geological processes 2015-2018. The ranking principles for Transcarpathian region administrative districts due to the hazardous geological processes occurrence depended on type of process.</p>
Structural geology data for the Pelling region, Sikkim, India
<p>This is the structural data (foliation planes, stretching lineations, crenulation lineations and fold axes) for the region around the town of Pelling, Sikkim, India. </p>
Text–fig. 1. Geographical and geological situation in the James Ross Island region. The locality No. 32 and the position of the Johann Gregor Mendel Czech Antarctic Station (JGM) are indicated. Modified from Sakala and Vodrážka (2014). in Marattiopsis Vodrazkae Sp. Nov. (Marattiaceae) From The Campanian Of The Hidden Lake Formation, James Ross Island, Antarctica.
Text–fig. 1. Geographical and geological situation in the James Ross Island region. The locality No. 32 and the position of the Johann Gregor Mendel Czech Antarctic Station (JGM) are indicated. Modified from Sakala and Vodrážka (2014).
Text-fig. 2. Latest Albian – Late Cretaceous palaeobotanical-palaeogeographical subregions of the North Pacific Region (a); modern outline of North-eastern Asia is shown for the Coniacian (after Smith et al. 1981): 1 – the Verkhoyansk-Chukotka Subregion, 2 – the Okhotsk-Chukotka Subregion, 3 – the Anadyr-Koryak Subregion (modified from Herman 2013) and geographical and geological position of the Turonian – Coniacian floras (b) (present-day map, modified from Shczepetov and Herman 2013). in On The Likely Palaeoelevation Of The Turonian - Coniacian Arman Flora Site (North-Eastern Asia)
Text-fig. 2. Latest Albian – Late Cretaceous palaeobotanical-palaeogeographical subregions of the North Pacific Region (a); modern outline of North-eastern Asia is shown for the Coniacian (after Smith et al. 1981): 1 – the Verkhoyansk-Chukotka Subregion, 2 – the Okhotsk-Chukotka Subregion, 3 – the Anadyr-Koryak Subregion (modified from Herman 2013) and geographical and geological position of the Turonian – Coniacian floras (b) (present-day map, modified from Shczepetov and Herman 2013).
Map Shapefiles of Regional Geology of the Hypanis Valles System, Mars
<p>This dataset consists of shapefiles for the manuscript Regional Geology of the Hypanis Valles System, Mars by Adler et al. (under review). Inside the zipfile is a README explaining how to view the data and sort shape orders. The data represent a geomorphic map of the Hypanis Valles watershed and a geomorphic map of the Hypanis deposit region at its terminus. We mapped these two regions at different scales: 1:2,000,000 for the catchment map (-5-10°N, 300-315°E) and 1:500,000 for the Hypanis deposit map (10-13.0°N, 313-316.5°E). Our mapping provides new morphologic insights beyond previous efforts which used lower spatial resolution data. We defined units based on morphology, albedo, thermal inertia, elevation, and spectral parameters.</p>
3-D geological and petrophysical models with synthetic geophysics based on data from the Hamersley region (Western Australia)
<p>3-D geological and petrophysical models with synthetic geophysics based on data from the Hamersley region (Western Australia)</p> <p>M. Jessell<sup>1,2</sup>, J. Giraud<sup>1,2</sup>, M. Lindsay<sup>1,2 </sup></p> <p><sup>1</sup>Centre for Exploration Targeting (School of Earth Sciences), University of Western Australia, 35 Stirling Highway, 6009 Crawley, Australia</p> <p><sup>2</sup>Mineral Exploration Cooperative Research Centre, School of Earth Sciences, University of Western Australia, 35 Stirling Highway, WA Crawley 6009, Australia</p> <p>Contact author: Jeremie Giraud (jeremie.giraud@uwa.edu.au)</p> <p>Companion dataset to the paper:</p> <p>Structural, petrophysical and geological constraints in potential field inversion using the Tomofast-x open-source code, J. Giraud, V. Ogarko, R. Martin, M. Lindsay, M. Jessell, Geoscientific Model Development Discussions.</p> <p>This dataset contains models and data shown in the paper, in both 2D and 3D:</p> <p>1. Geological model</p> <ul> <li>Reference lithology voxet:</li> </ul> <p>The reference geological model was obtained using public data from the Geological Survey of Western Australia and modified subsequently (stretched vertically and flattened at surface level) for the purpose of this study.</p> <ul> <li>Probability voxet<br> The lithology probability voxet was derived using Monte Carlo simulations for uncertainty estimation as mentioned in the paper.</li> </ul> <p>2. True and inverted models for density and magnetic susceptibility</p> <p>Derivation is detailed in the paper; it uses fictitious density and magnetic susceptibility values.</p> <p>3. Bouguer and total magnetic field anomaly</p> <p>Calculation is detailed in the paper.</p> <p>The authors are supported, in part, by Loop – Enabling Stochastic 3D Geological Modelling (LP170100985) and the Mineral Exploration Cooperative Research Centre (MinEx CRC) whose activities are funded by the Australian Government's Cooperative Research Centre Program. This is MinEx CRC Document 2021/3. Mark Lindsay acknowledges funding from the ARC and DECRA DE190100431.</p> <p>It is a companion dataset to: <br> Vitaliy Ogarko, Jeremie Giraud, & Roland. (2021, February 5). Tomofast-x v1.0 source code (Version 1.0). Zenodo. <a href="http://doi.org/10.5281/zenodo.4452620">http://doi.org/10.5281/zenodo.4452620</a></p>
Fig. 1 Simplified geological map 1 in Oligocene - Lower Miocene Biostratigraphy And Sedimentology Of The Borşa Formation (N Romania, Maramureş Region)
Fig. 1 Simplified geological map 1:200.000 after Gherasi et al., 1967 and Patrulius et al., 1968.
Dataset of the paper titled Geological characteristics and high scientific interest targets of the Zhurong landing region on Mars
<p>This dataset contains the original data and crater counting data of the paper titled Geological characteristics and high scientific interest targets of the Zhurong landing region on Mars.</p>
Small craters population as a useful geological investigative tool: Apollo 17 region as a case study - Craters Data
<p>Crater coordinates for areas under investigation. Unit names ref. to paper.</p> <p>Data format: Lat,Lon,Diam_km,Diam_m and Area in Km^2</p>
Constraints on global mined geological resource production from limited regional water availability
<p>This depository provides the input dataset and codes/analytical procedures required to assess the sustainable capacity of mineral production considering local water resources as a constraint. The output dataset derived from the study are also provided.</p>
FIG UR E 3 (a) Dated phylogeny of the genus Theodoxus constructed in BEAST based on COI, 16S and ATPα. Node labels denote divergence times in millions of years ago (Ma); node bars indicate the 95% credibility interval around these dates. Small squares at nodes indicate significant support of divergence events found with BEAST and other phylogenetic analyses (see Figures S2.1 and S2.2), as explained through the key. Where MOTUs (A–R) show conspecifics among a number of morphospecies, species names are given in order of their year of description. Morphospecies, incorporated from GenBank, where determination was potentially dubious are highlighted by an asterisk. Clades (C) and subclades (SC) are demarcated by dashed lines between MOTUs. (b) LTT plots indicating the build‐up of lineages in Theodoxus over geological time. Dashed lines surrounding the solid LTT lines indicate the 95% confidence intervals. Where intra‐ and interspecific diversity diverge, interspecific diversity is highlighted in blue and intraspecific diversity in red. Transitions in geological ages are highlighted by narrow grey lines, while the grey bar marks the period of pronounced glacial cycles (last 900 kyr) [Colour figure can be viewed at wileyonlinelibrary.com] in Contributions of biogeographical functions to species accumulation may change over time in refugial regions
FIG UR E 3 (a) Dated phylogeny of the genus Theodoxus constructed in BEAST based on COI, 16S and ATPα. Node labels denote divergence times in millions of years ago (Ma); node bars indicate the 95% credibility interval around these dates. Small squares at nodes indicate significant support of divergence events found with BEAST and other phylogenetic analyses (see Figures S2.1 and S2.2), as explained through the key. Where MOTUs (A–R) show conspecifics among a number of morphospecies, species names are given in order of their year of description. Morphospecies, incorporated from GenBank, where determination was potentially dubious are highlighted by an asterisk. Clades (C) and subclades (SC) are demarcated by dashed lines between MOTUs. (b) LTT plots indicating the build‐up of lineages in Theodoxus over geological time. Dashed lines surrounding the solid LTT lines indicate the 95% confidence intervals. Where intra‐ and interspecific diversity diverge, interspecific diversity is highlighted in blue and intraspecific diversity in red. Transitions in geological ages are highlighted by narrow grey lines, while the grey bar marks the period of pronounced glacial cycles (last 900 kyr) [Colour figure can be viewed at wileyonlinelibrary.com]
Supplementary Data for Wueller et al. (2024): Geologic History of Deuteronilus Cavus in the Ismenius Lacus Region, Mars.
<p>Supplementary Data for Wueller et al. (2024): Geologic History of Deuteronilus Cavus in the Ismenius Lacus Region, Mars</p> <p>Data contains the georeferenced map plate of our geologic map that can be used in any geoinformation system (GIS).</p> <p><strong>If you use these data, please cite BOTH the Journal of Geophysical Research: Planets publication and the Zenodo dataset.</strong></p> <p>Wueller, L., Iqbal, W., Hiesinger, H., & Head III, J. W. (2024). Geologic History of Deuteronilus Cavus in the Ismenius Lacus Region, Mars. <em>Journal of Geophysical Research: Planets</em>, <em>129</em>(2), e2023JE008039. <a href="https://doi.org/10.1029/2023JE008039">https://doi.org/10.1029/2023JE008039</a></p> <p>Wueller, L., Iqbal, W., Hiesinger, H., & Head, J. (2023). Geologic History of Deuteronilus Cavus in the Ismenius Lacus Region, Mars. <em>Zenodo Dataset</em>. <a href="https://doi.org/10.5281/zenodo.8205276" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.8205276</a></p> <p>-----------------------------------------------------------------------------------------------------------------------------------------</p> <p>Mapping Scale is 1:200,000</p> <p>-----------------------------------------------------------------------------------------------------------------------------------------</p> <p>For further questions contact lwueller@uni-muenster.de</p> <p>Lukas Wueller, Institut für Planetologie, Universität Münster, Germany, January 2024</p>
Aphrodite Region of Venus (I-2476): base maps for geologic mapping.
<p>This data repository contains the base map for the geologic mapping of the Aphrodite Region of Venus (I-2476). Data for this study were provided by the U.S. Geological Survey (USGS) Astrogeology Team in the projection parameters (Mercator projection). The data are also available online from the USGS Map-a-planet website (<a href="https://astrocloud.wr.usgs.gov/">https://astrocloud.wr.usgs.gov/</a> ).</p> <p>The datasets include: (a) Cycle 1 (east-directed illumination, or left-looking) SAR images cover essentially the entire I-2476 map area; (b) Topography (Global Topographic Data Record 3; GTDR 3); (c) Slope data (Global Slope Data Record; GSDR); (d) Reflectivity (Global Reflectivity Data Record; GRDR); and (e) Emissivity (Global Emissivity Data Record; GEDR).</p>
Geologic history of the south circumpolar region (SCR) of the Moon (Supplementary material)
<p>Supplementary material of publication (Krasilnikov et al., 2023):</p> <ul> <li>SP_Geological_Map_v1.3.rar - ArcGIS project contain results of geological mapping of South Circumpolar Region</li> </ul> <p> </p> <ul> <li>Fig 13a. High-resolution geologic map.</li> <li>Fig 13b. High-resolution geologic map, description of map units.</li> <li>Fig. 2S. High-resolution map units divided by age: (a) Copernican, Eratosthenian and undifferentiated ages; (b) Imbrian period; (c) Nectarian period; (d) pre-Nectarian period.</li> <li>Fig. 3S. Process of geologic map creation.</li> </ul> <p>In the new version (v.1.3), minor geological map corrections were made.<br> Version corrections:<br> - Correction of Ilp2 layer color (now it is 28, 153, 246 RGB).<br> - Correction of the line width of linear objects.<br> - Maped about 582 km of lobate scarps based on the data from Mishra and Kumar, (2022)* and mapping at 1:300000 scale.</p>
Niobe Planitia Region (I-2467), Venus: base maps for geologic mapping.
<p>This data repository contains the base map for the geologic mapping of the Niobe Planitia Region (I-2467) of Venus. Data for this study were provided by the U.S. Geological Survey (USGS) Astrogeology Team in the projection parameters (Mercator projection). The data are also available online from the USGS Map-a-planet website (<a href="https://astrocloud.wr.usgs.gov/">https://astrocloud.wr.usgs.gov/</a> ).</p> <p>The datasets include: (a) Cycle 1 (east-directed illumination, or left-looking) SAR images cover essentially the entire I-2467 map area; (b) Topography (Global Topographic Data Record 3; GTDR 3); (c) Slope data (Global Slope Data Record; GSDR); (d) Reflectivity (Global Reflectivity Data Record; GRDR); and (e) Emissivity (Global Emissivity Data Record; GEDR).</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.