Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
751
datasets available to search
ShareScore release 0.7.1
Dataset results
751 results for “geology”
Figure 6 from: Baker E, Johnson K, Young J (2011) The future of the past in the present: biodiversity informatics and geological time. ZooKeys 150: 397-405. https://doi.org/10.3897/zookeys.150.2350
Figure 6 - When there is no overlapping time periods the intersect is undefined.
Figure 4 from: Osikowski A, Georgiev D, Hofman S, Falniowski A (2015) Does the genetic structure of spring snail Bythinella (Caenogastropoda, Truncatelloidea) in Bulgaria reflect geological history? ZooKeys 518: 67-86. https://doi.org/10.3897/zookeys.518.10035
Figure 4 - Geographical distribution of COI clades. Compare with Figure 3.
Recurrence Time and Size of Chilean Earthquakes Influenced by Geological Structure
<p>Data related with the publication of "Recurrence Time and Size of Chilean Earthquakes Influenced by Geological Structure". Temperature model files are uploaded as .h5 .xdmf and .csv to visualize in paraview or your preferred software. The coseismic slip inversion for the Valdivia earthquake files are in .dat extension, please note that uncertainties are in the sigmainv.dat. Finally, we have uploaded all the input files necessary to run the quasi-dynamic model using Unicycle.</p>
(2019) Supplementary figures for "Depicting Grand Canyon’s rock layers: 150 years of visualizing and interpreting geology"
Open the record for dataset details and reuse information.
Data from: Re-evaluating the geological evidence for Late Holocene marine incursion events along the Guerrero Seismic Gap on the Pacific Coast of Mexico
Open the record for dataset details and reuse information.
Data from: Conserving evolutionary history does not result in greater diversity over geological timescales
Open the record for dataset details and reuse information.
SEDIMENT ANALYSIS NETWORK FOR DECISION SUPPORT (SANDS) MODIS GEOLOGICAL SURVEY OF AL (GSA) ANALYSIS V1
The Sediment Analysis Network for Decision Support (SANDS) MODIS Geological Survey of AL (GSA) Analysis dataset consists of geoTIFF images were analyzed for sediment redistribution after hurricanes on the Gulf of America. These are seasonal data for storms from September 14, 2000 to September 8, 2008. In addition to the analyzed files, the data files include the ESRI files for zipped bands and/or grids, metadata, and storm temporal information for the sediment analysis images. The Geological Survey of Alabama (GSA) generated this dataset from geoTIFF MODIS images as part of the Sediment Analysis Network for Decision Support (SANDS) project.
SEDIMENT ANALYSIS NETWORK FOR DECISION SUPPORT (SANDS) LANDSAT GEOLOGICAL SURVEY OF AL (GSA) ANALYSIS V1
The Sediment Analysis Network for Decision Support (SANDS) Landsat Geological Survey of AL (GSA) Analysis dataset analyzed changes in the coastal shoreline and sedimentation using Landsat GeoTiff images as part of the Sediment Analysis Network for Decision Support (SANDS) project. The daytime GeoTiffs images from Landsat 5 and Landsat 7 were analyzed for sediment re-distribution after a hurricane over the Gulf of America coastline in Alabama and part of the Florida area (coordinates 31 to 27 North latitude and 90 to 84.25 West longitude). These are seasonal data for storms from 2001-2008. In addition to the analyzed files, the data files include the ESRI files for zipped bands and grids, metadata, and storm temporal information for the sediment analysis images.
FIGURE 15. Stomatocysts ornamented with scabrae verrucae and conula. A. Stomatocyst 49 Pang & Wang. B. Stomatocyst 50 Pang & Wang. C–D. Stomatocyst 51 Pang & Wang. E–F. Stomatocyst 117 in Chrysophycean stomatocysts from the Aershan Geological Park (Inner Mongolia), China
FIGURE 15. Stomatocysts ornamented with scabrae verrucae and conula. A. Stomatocyst 49 Pang & Wang. B. Stomatocyst 50 Pang & Wang. C–D. Stomatocyst 51 Pang & Wang. E–F. Stomatocyst 117 Zeeb et al. Scale bar = 2 µm.
FIGURE 26. Stomatocysts ornamented with spines. A. Stomatocyst 1 Pang & Wang. B–C. Stomatocyst 2 Pang & Wang. D–E. Stomatocyst 77 Pang & Wang. F. Stomatocyst 78 in Chrysophycean stomatocysts from the Aershan Geological Park (Inner Mongolia), China
FIGURE 26. Stomatocysts ornamented with spines. A. Stomatocyst 1 Pang & Wang. B–C. Stomatocyst 2 Pang & Wang. D–E. Stomatocyst 77 Pang & Wang. F. Stomatocyst 78 Pang & Wang. Scale bar = 2 µm.
FIGURE 34. Stomatocysts ornamented with ridges. A. Stomatocyst 90 Pang & Wang. B. Stomatocyst 111 in Chrysophycean stomatocysts from the Aershan Geological Park (Inner Mongolia), China
FIGURE 34. Stomatocysts ornamented with ridges. A. Stomatocyst 90 Pang & Wang. B. Stomatocyst 111 Zeeb et al. C–D. Stomatocyst 133 Duff & Smol emend. Zeeb et al. subm. emend. Duff & Smol. E–F. Stomatocyst 337 Wilkinson & Smol. Scale bar = 2 µm.
Master_Thesis_Dataset: Hamburg Subsurface Geological data
Open the record for dataset details and reuse information.
Fig. 5 in The roles of niche divergence, dispersal, and geology on the diversification of Neotropical true frogs from the Rana palmipes species group (Amphibia, Anura, Ranidae) during the Great American Biotic Interchange
Fig. 5 Plots of disparity through time (DTT) for predictors (solid line) and data simulated under Brownian motion model of evolution (dashed line). Continuous lines represent the estimated values of disparity in relative time. Grey area represents the 95% confidence interval of simulated data in a dashed line. MDI, morphological disparity index. Negative values indicate niche conservatism, while positive values indicate niche divergence
Figure 5 in Tracking parallel adaptation of shell morphology through geological times in the land snail genus Pupilla (Gastropoda: Stylommatophora: Pupillidae)
Figure 5. Thin-plate splines illustrating (theoretical) transitions in shape, frontal view. A, fossil P. loessica → extant P. loessica. B, fossil P. pratensis (including P. m. densegyrata) → extant P. pratensis. C, fossil P. pratensis (including P. m. densegyrata) → extant P. alpicola. D, extant P. pratensis → P. alpicola. E, extant P. loessica→ P. alpicola. F, fossil P. muscorum → extant P. muscorum.
Figure 3 in Tracking parallel adaptation of shell morphology through geological times in the land snail genus Pupilla (Gastropoda: Stylommatophora: Pupillidae)
Figure 3. Landmarks for frontal (left) and lateral (right) aspects in geometric morphometric analyses.
Figure 2. Localities. A in Tracking parallel adaptation of shell morphology through geological times in the land snail genus Pupilla (Gastropoda: Stylommatophora: Pupillidae)
Figure 2. Localities. A, Eurasia with insets of detailed maps. B, European samples. C, Asian samples. Due to the large scale, single symbols may stand for several adjacent localities. In (B), 1 indicates the type locality of P. loessica (Předmostí at Přerov, Czech Republic), and 2 the type locality of Pupa muscorum var. pratensis (Dinkelscherben near Augsburg, Germany).
Museum Geologi
Museum Geologi Bandung Source: Objaverse 1.0 / Sketchfab
NEW HORIZONS GEOLOGY AND GEOPHYSICAL LORRI/MVIC MAPS V1.0
This data set contains derived data products from the New Horizons geology and geophysics science theme team. The products include mosaics, and topographic and bond albedo maps for Pluto and Charon. They are derived from observations taken by the LOng-Range Reconnaissance Imager instrument and the Multispectral Visible Imaging Camera instrument on the New Horizons mission during the Pluto Encounter mission phase. This is VERSION 1.0 of this data set.
CORONA Satellite Photographs from the U.S. Geological Survey
The first generation of U.S. photo intelligence satellites collected more than 860,000 images of the Earth’s surface between 1960 and 1972. The classified military satellite systems code-named CORONA, ARGON, and LANYARD acquired photographic images from space and returned the film to Earth for processing and analysis. The images were originally used for reconnaissance and to produce maps for U.S. intelligence agencies. In 1992, an Environmental Task Force evaluated the application of early satellite data for environmental studies. Since the CORONA, ARGON, and LANYARD data were no longer critical to national security and could be of historical value for global change research, the images were declassified by Executive Order 12951 in 1995. The first successful CORONA mission was launched from Vandenberg Air Force Base in 1960. The satellite acquired photographs with a telescopic camera system and loaded the exposed film into recovery capsules. The capsules or buckets were de-orbited and retrieved by aircraft while the capsules parachuted to earth. The exposed film was developed and the images were analyzed for a range of military applications. The intelligence community used Keyhole (KH) designators to describe system characteristics and accomplishments. The CORONA systems were designated KH-1, KH-2, KH-3, KH-4, KH-4A, and KH-4B. The ARGON systems used the designator KH-5 and the LANYARD systems used KH-6. Mission numbers were a means for indexing the imagery and associated collateral data. A variety of camera systems were used with the satellites. Early systems (KH-1, KH-2, KH-3, and KH-6) carried a single panoramic camera or a single frame camera (KH-5). The later systems (KH-4, KH-4A, and KH-4B) carried two panoramic cameras with a separation angle of 30° with one camera looking forward and the other looking aft. The original film and technical mission-related documents are maintained by the National Archives and Records Administration (NARA). Duplicate film sources held in the USGS EROS Center archive are used to produce digital copies of the imagery. Mathematical calculations based on camera operation and satellite path were used to approximate image coordinates. Since the accuracy of the coordinates varies according to the precision of information used for the derivation, users should inspect the preview image to verify that the area of interest is contained in the selected frame. Users should also note that the images have not been georeferenced.
1:100,000-scale Digital Line Graphs (DLG) from the U.S. Geological Survey
Digital line graph (DLG) data are digital representations of cartographic information. DLG's of map features are converted to digital form from maps and related sources. Intermediate-scale DLG data are derived from USGS 1:100,000-scale 30- by 60-minute quadrangle maps. If these maps are not available, Bureau of Land Management planimetric maps at a scale of 1: 100,000 are used. Intermediate-scale DLG's are sold in five categories: (1) Public Land Survey System; (2) boundaries (3) transportation; (4) hydrography; and (5) hypsography. All DLG data distributed by the USGS are DLG - Level 3 (DLG-3), which means the data contain a full range of attribute codes, have full topological structuring, and have passed certain quality-control checks.
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.