Skip to main content
Powered by ShareScore

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.

1,430

datasets available to search

ShareScore release 0.9.0

Reset

Dataset results

1,430 results for “Arabia”

Learn how ShareScore rates datasets ↗
zenodo48/100

Kingdom of Saudi Arabia. al-Ḥasāʾ, Jabal al-Qāra (جَبَل ٱلْقَارَة). Pottery production, kiln in operation, 1970.

<p>[KSA QAR 1970.13] Kingdom of Saudi Arabia. al-Ḥasāʾ, Jabal al-Qāra. Pottery production, kiln in operation, 1970.</p>

opencc-by-4.0Oct 2024View details →
zenodo44/100

National Checklists 2017: Saudi Arabia Species List

Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>A list of species from Saudi Arabia collected using effechecka and geonames polygons

opencc-zeroAug 2024View details →
zenodo44/100

National Checklists 2019: Saudi Arabia Species List

Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details.<p></p>A list of species from Saudi Arabia collected using effechecka and geonames polygons

opencc-zeroAug 2024View details →
zenodo44/100

Kingdom of Saudi Arabia. al-Ḥasāʾ, Jabal al-Qāra (جَبَل ٱلْقَارَة). Pottery production, kiln mouth being fed, 1970.

<p>[KSA QAR 1970.15] Kingdom of Saudi Arabia. al-Ḥasāʾ, Jabal al-Qāra. Pottery production, kiln mouth being fed, as documented 1970.</p>

opencc-by-4.0Oct 2024View details →
zenodo44/100

Kingdom of Saudi Arabia. al-Ḥasāʾ, Jabal al-Qāra (جَبَل ٱلْقَارَة). Pottery production, 1969.

<p>[KSA QAR 1969.24] Kingdom of Saudi Arabia. al-Ḥasāʾ, Jabal al-Qāra. Pottery production, as documented 1969.</p>

opencc-by-4.0Oct 2024View details →
zenodo44/100

Kingdom of Saudi Arabia. al-Ḥasāʾ, Jabal al-Qāra (جَبَل ٱلْقَارَة). Potter's wheel, 1968.

<p>[KSA QAR 1968.26] Kingdom of Saudi Arabia. al-Ḥasāʾ, Jabal al-Qāra. Potter's wheel, as documented 1968.</p>

opencc-by-4.0Oct 2024View details →
zenodo44/100

Kingdom of Saudi Arabia. al-Ḥasāʾ, Jabal al-Qāra (جَبَل ٱلْقَارَة). Pottery production, typology, 1970.

<p>[KSA QAR 1969.06] Kingdom of Saudi Arabia. al-Ḥasāʾ, Jabal al-Qāra. Pottery production, typology, 1970.</p>

opencc-by-4.0Oct 2024View details →
zenodo44/100

Kingdom of Saudi Arabia. al-Ḥasāʾ, Jabal al-Qāra (جَبَل ٱلْقَارَة). Pottery production in Dugha al-Gharāsh, 1969.

<p>[KSA QAR 1969.29] Kingdom of Saudi Arabia. al-Ḥasāʾ, <a href="https://www.wikidata.org/wiki/Q12204761">Jabal al-Qāra</a>. Pottery production in the cave known as<em> </em><a href="https://www.wikidata.org/wiki/Q99941895">Dugha al-Gharāsh</a>, as documented 1969.</p>

opencc-by-4.0Oct 2024View details →
zenodo44/100

Kingdom of Saudi Arabia. al-Ḥasāʾ, Jabal al-Qāra (جَبَل ٱلْقَارَة). Pottery production, 1969.

<p>[KSA QAR 1969.25] Kingdom of Saudi Arabia. al-Ḥasāʾ, Jabal al-Qāra. Pottery production as documented 1969.</p>

opencc-by-4.0Oct 2024View details →
zenodo44/100

Kingdom of Saudi Arabia. al-Ḥasāʾ, Jabal al-Qāra (جَبَل ٱلْقَارَة). Pottery production, 1969.

<p>[KSA QAR 1969.28] Kingdom of Saudi Arabia. al-Ḥasāʾ, Jabal al-Qāra (جَبَل ٱلْقَارَة). Pottery production, 1969.</p>

opencc-by-4.0Oct 2024View details →
zenodo44/100

Kingdom of Saudi Arabia. al-Ḥasāʾ, Jabal al-Qāra (جَبَل ٱلْقَارَة). Pottery production, kiln, 1968

<p>[KSA QAR 1968.25] Kingdom of Saudi Arabia. al-Ḥasāʾ, Jabal al-Qāra (جَبَل ٱلْقَارَة). Pottery production, kiln, empty and seen from above, 1968.</p>

opencc-by-4.0Oct 2024View details →
zenodo44/100

Kingdom of Saudi Arabia. al-Ḥasāʾ, Jabal al-Qāra (جَبَل ٱلْقَارَة). Fired ware being inspected.

<p>Kingdom of Saudi Arabia. al-Ḥasāʾ, Jabal al-Qāra (جَبَل ٱلْقَارَة). Fired ware being inspected, 1969.</p>

opencc-by-4.0Oct 2024View details →
zenodo44/100

Dataset for: Bedding scale correlation on Mars in western Arabia Terra

<p>Dataset for: Bedding scale correlation on Mars in western Arabia Terra</p> <p>A.M. Annex et al.</p> <p>Data Product Overview</p> <p>This repository contains all source data for the publication. Below is a description of each general data product type, software that can load the data, and a list of the file names along with the short description of the data product.</p> <p><strong>HiRISE Digital Elevation Models (DEMs).</strong></p> <p>HiRISE DEMs produced using the Ames Stereo Pipeline are in geotiff format ending with &lsquo;*X_0_DEM-adj.tif&rsquo;, the &ldquo;X&rdquo; prefix denotes the spatial resolution of the data product in meters. Geotiff files are able to be read by free GIS software like QGIS.</p> <p><strong>HiRISE map-projected imagery (DRGs).</strong></p> <p>Map-projected HiRISE images produced using the Ames Stereo Pipeline are in geotiff format ending with &lsquo;*0_Y_DRG-cog.tif&rsquo;, the &ldquo;Y&rdquo; prefix denotes the spatial resolution of the data product in centimeters. Geotiff files are able to be read by free GIS software like QGIS. The DRG files are formatted as COG-geotiffs for enhanced compression and ease of use.</p> <p><strong>3D Topography files (.ply).</strong></p> <p>Traingular Mesh versions of the HiRISE/CTX topography data used for 3D figures in &ldquo;.ply&rdquo; format. Meshes are greatly geometrically simplified from source files. Topography files can be loaded in a variety of open source tools like ParaView and Meshlab. Textures can be applied using embedded texture coordinates.</p> <p><strong>3D Geological Model outputs (.vtk)</strong></p> <p>VTK 3D file format files of model output over the spatial domain of each study site. VTK files can be loaded by ParaView open source software. The &ldquo;block&rdquo; files contain the model evaluation over a regular grid over the model extent. The &ldquo;surfaces&rdquo; files contain just the bedding surfaces as interpolated from the &ldquo;block&rdquo; files using the marching cubes algorithm.</p> <p><strong>Geological Model geologic maps (geologic_map.tif).</strong></p> <p>Geologic maps from geological models are standard geotiffs readable by conventional GIS software. The maximum value for each geologic map is the &ldquo;no-data&rdquo; value for the map. Geologic maps are calculated at a lower resolution than the topography data for storage efficiency.</p> <p><strong>Beds Geopackage File (.gpkg).</strong></p> <p>Geopackage vector data file containing all mapped layers and associated metadata including dip corrected bed thickness as well as WKB encoded 3D linestrings representing the sampled topography data to which the bedding orientations were fit. Geopackage files can be read using GIS software like QGIS and ArcGIS as well as the OGR/GDAL suite. A full description of each column in the file is provided below.</p> <table> <thead> <tr> <th>Column</th> <th>Type</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td>uuid</td> <td>String</td> <td>unique identifier</td> </tr> <tr> <td>stratum_order</td> <td>Real</td> <td>0-indexed bed order</td> </tr> <tr> <td>section</td> <td>Real</td> <td>section number</td> </tr> <tr> <td>layer_id</td> <td>Real</td> <td>bed number/index</td> </tr> <tr> <td>layer_id_bk</td> <td>Real</td> <td>unused backup bed number/index</td> </tr> <tr> <td>source_raster</td> <td>String</td> <td>dem file path used</td> </tr> <tr> <td>raster</td> <td>String</td> <td>dem file name</td> </tr> <tr> <td>gsd</td> <td>Real</td> <td>ground sampling distant for dem</td> </tr> <tr> <td>wkn</td> <td>String</td> <td>well known name for dem</td> </tr> <tr> <td>rtype</td> <td>String</td> <td>raster type</td> </tr> <tr> <td>minx</td> <td>Real</td> <td>minimum x position of trace in dem crs</td> </tr> <tr> <td>miny</td> <td>Real</td> <td>minimum y position of trace in dem crs</td> </tr> <tr> <td>maxx</td> <td>Real</td> <td>maximum x position of trace in dem crs</td> </tr> <tr> <td>maxy</td> <td>Real</td> <td>maximum y position of trace in dem crs</td> </tr> <tr> <td>method</td> <td>String</td> <td>internal interpolation method</td> </tr> <tr> <td>sl</td> <td>Real</td> <td>slope in degrees</td> </tr> <tr> <td>az</td> <td>Real</td> <td>azimuth in degrees</td> </tr> <tr> <td>error</td> <td>Real</td> <td>maximum error ellipse angle</td> </tr> <tr> <td>stdr</td> <td>Real</td> <td>standard deviation of the residuals</td> </tr> <tr> <td>semr</td> <td>Real</td> <td>standard error of the residuals</td> </tr> <tr> <td>X</td> <td>Real</td> <td>mean x position in CRS</td> </tr> <tr> <td>Y</td> <td>Real</td> <td>mean y position in CRS</td> </tr> <tr> <td>Z</td> <td>Real</td> <td>mean z position in CRS</td> </tr> <tr> <td>b1</td> <td>Real</td> <td>plane coefficient 1</td> </tr> <tr> <td>b2</td> <td>Real</td> <td>plane coefficient 2</td> </tr> <tr> <td>b3</td> <td>Real</td> <td>plane coefficient 3</td> </tr> <tr> <td>b1_se</td> <td>Real</td> <td>standard error plane coefficient 1</td> </tr> <tr> <td>b2_se</td> <td>Real</td> <td>standard error plane coefficient 2</td> </tr> <tr> <td>b3_se</td> <td>Real</td> <td>standard error plane coefficient 3</td> </tr> <tr> <td>b1_ci_low</td> <td>Real</td> <td>plane coefficient 1 95% confidence interval low</td> </tr> <tr> <td>b1_ci_high</td> <td>Real</td> <td>plane coefficient 1 95% confidence interval high</td> </tr> <tr> <td>b2_ci_low</td> <td>Real</td> <td>plane coefficient 2 95% confidence interval low</td> </tr> <tr> <td>b2_ci_high</td> <td>Real</td> <td>plane coefficient 2 95% confidence interval high</td> </tr> <tr> <td>b3_ci_low</td> <td>Real</td> <td>plane coefficient 3 95% confidence interval low</td> </tr> <tr> <td>b3_ci_high</td> <td>Real</td> <td>plane coefficient 3 95% confidence interval high</td> </tr> <tr> <td>pca_ev_1</td> <td>Real</td> <td>pca explained variance ratio pc 1</td> </tr> <tr> <td>pca_ev_2</td> <td>Real</td> <td>pca explained variance ratio pc 2</td> </tr> <tr> <td>pca_ev_3</td> <td>Real</td> <td>pca explained variance ratio pc 3</td> </tr> <tr> <td>condition_number</td> <td>Real</td> <td>condition number for regression</td> </tr> <tr> <td>n</td> <td>Integer64</td> <td>number of data points used in regression</td> </tr> <tr> <td>rls</td> <td>Integer(Boolean)</td> <td>unused flag</td> </tr> <tr> <td>demeaned_regressions</td> <td>Integer(Boolean)</td> <td>centering indicator</td> </tr> <tr> <td>meansl</td> <td>Real</td> <td>mean section slope</td> </tr> <tr> <td>meanaz</td> <td>Real</td> <td>mean section azimuth</td> </tr> <tr> <td>angular_error</td> <td>Real</td> <td>angular error for section</td> </tr> <tr> <td>mB_1</td> <td>Real</td> <td>mean plane coefficient 1 for section</td> </tr> <tr> <td>mB_2</td> <td>Real</td> <td>mean plane coefficient 2 for section</td> </tr> <tr> <td>mB_3</td> <td>Real</td> <td>mean plane coefficient 3 for section</td> </tr> <tr> <td>R</td> <td>Real</td> <td>mean plane normal orientation vector magnitude</td> </tr> <tr> <td>num_valid</td> <td>Integer64</td> <td>number of valid planes in section</td> </tr> <tr> <td>meanc</td> <td>Real</td> <td>mean stratigraphic position</td> </tr> <tr> <td>medianc</td> <td>Real</td> <td>median stratigraphic position</td> </tr> <tr> <td>stdc</td> <td>Real</td> <td>standard deviation of stratigraphic index</td> </tr> <tr> <td>stec</td> <td>Real</td> <td>standard error of stratigraphic index</td> </tr> <tr> <td>was_monotonic_increasing_layer_id</td> <td>Integer(Boolean)</td> <td>monotonic layer_id after projection to stratigraphic index</td> </tr> <tr> <td>was_monotonic_increasing_meanc</td> <td>Integer(Boolean)</td> <td>monotonic meanc after projection to stratigraphic index</td> </tr> <tr> <td>was_monotonic_increasing_z</td> <td>Integer(Boolean)</td> <td>monotonic z increasing after projection to stratigraphic index</td> </tr> <tr> <td>meanc_l3sigma_std</td> <td>Real</td> <td>lower 3-sigma meanc standard deviation</td> </tr> <tr> <td>meanc_u3sigma_std</td> <td>Real</td> <td>upper 3-sigma meanc standard deviation</td> </tr> <tr> <td>meanc_l2sigma_sem</td> <td>Real</td> <td>lower 3-sigma meanc standard error</td> </tr> <tr> <td>meanc_u2sigma_sem</td> <td>Real</td> <td>upper 3-sigma meanc standard error</td> </tr> <tr> <td>thickness</td> <td>Real</td> <td>difference in meanc</td> </tr> <tr> <td>thickness_fromz</td> <td>Real</td> <td>difference in Z value</td> </tr> <tr> <td>dip_cor</td> <td>Real</td> <td>dip correction</td> </tr> <tr> <td>dc_thick</td> <td>Real</td> <td>thickness after dip correction</td> </tr> <tr> <td>dc_thick_fromz</td> <td>Real</td> <td>z thickness after dip correction</td> </tr> <tr> <td>dc_thick_dev</td> <td>Integer(Boolean)</td> <td>dc_thick &lt;= total mean dc_thick</td> </tr> <tr> <td>dc_thick_fromz_dev</td> <td>Integer(Boolean)</td> <td>dc_thick &lt;= total mean dc_thick_fromz</td> </tr> <tr> <td>thickness_fromz_dev</td> <td>Integer(Boolean)</td> <td>dc_thick &lt;= total mean thickness_fromz</td> </tr> <tr> <td>dc_thick_dev_bg</td> <td>Integer(Boolean)</td> <td>dc_thick &lt;= section mean dc_thick</td> </tr> <tr> <td>dc_thick_fromz_dev_bg</td> <td>Integer(Boolean)</td> <td>dc_thick &lt;= section mean dc_thick_fromz</td> </tr> <tr> <td>thickness_fromz_dev_bg</td> <td>Integer(Boolean)</td> <td>dc_thick &lt;= section mean thickness_fromz</td> </tr> <tr> <td>slr</td> <td>Real</td> <td>slope in radians</td> </tr> <tr> <td>azr</td> <td>Real</td> <td>azimuth in radians</td> </tr> <tr> <td>meanslr</td> <td>Real</td> <td>mean slope in radians</td> </tr> <tr> <td>meanazr</td> <td>Real</td> <td>mean azimuth in radians</td> </tr> <tr> <td>angular_error_r</td> <td>Real</td> <td>angular error of section in radians</td> </tr> <tr> <td>pca_ev_1_ok</td> <td>Integer(Boolean)</td> <td>pca_ev_1 &lt; 99.5%</td> </tr> <tr> <td>pca_ev_2_3_ratio</td> <td>Real</td> <td>pca_ev_2/pca_ev_3</td> </tr> <tr> <td>pca_ev_2_3_ratio_ok</td> <td>Integer(Boolean)</td> <td>pca_ev_2_3_ratio &gt; 15</td> </tr> <tr> <td>xyz_wkb_hex</td> <td>String</td> <td>hex encoded wkb geometry for all points used in regression</td> </tr> </tbody> </table> <p><strong>Geological Model input files (.gpkg).</strong></p> <p>Four geopackage (.gpkg) files represent the input dataset for the geological models, one per study site as specified in the name of the file. The files contain most &nbsp;of the columns described above in the Beds geopackage file, with the following additional columns. The final seven columns (azimuth, dip, polarity, formation, X, Y, Z) constituting the actual parameters used by the geological model (GemPy).&nbsp;</p> <table> <thead> <tr> <th>Column</th> <th>Type</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td>azimuth_mean</td> <td>String</td> <td>Mean section dip azimuth&nbsp;</td> </tr> <tr> <td>azimuth_indi</td> <td>Real</td> <td>Individual bed azimuth</td> </tr> <tr> <td>azimuth</td> <td>Real</td> <td>Azimuth of trace used by the geological model</td> </tr> <tr> <td>dip</td> <td>Real</td> <td>Dip for the trace used by the geological mode</td> </tr> <tr> <td>polarity</td> <td>Real</td> <td>Polarity of the dip vector normal vector&nbsp;&nbsp;</td> </tr> <tr> <td>formation</td> <td>String</td> <td>String representation of layer_id required for GemPy models</td> </tr> <tr> <td>X</td> <td>Real</td> <td>X position in the CRS of the sampled point on the trace</td> </tr> <tr> <td>Y</td> <td>Real</td> <td>Y position in the CRS of the sampled point on the trace</td> </tr> <tr> <td>Z</td> <td>Real</td> <td>Z position in the CRS of the sampled point on the trace</td> </tr> </tbody> </table> <p><strong>Stratigraphic Column Files (.gpkg).</strong></p> <p>Stratigraphic columns computed from the Geological Models come in three kinds of Geopackage vector files indicated by the postfixes <code>_sc</code>, <code>rbsc</code>, and <code>rbssc</code>. File names include the wkn site name.</p> <p><strong>sc (_sc.gpkg).</strong></p> <p>Geopackage vector data file containing measured bed thicknesses from Geological Model joined with corresponding Beds Geopackage file, subsetted partially. The columns largely overlap with the the list above for the Beds Geopackage but with the following additions</p> <table> <thead> <tr> <th>Column</th> <th>Type</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td>X</td> <td>Real</td> <td>X position of thickness measurement</td> </tr> <tr> <td>Y</td> <td>Real</td> <td>Y position of thickness measurement</td> </tr> <tr> <td>Z</td> <td>Real</td> <td>Z position of thickness measurement</td> </tr> <tr> <td>formation</td> <td>String</td> <td>Model required string representation of bed index</td> </tr> <tr> <td>bed thickness (m)</td> <td>Real</td> <td>difference of bed elevations</td> </tr> <tr> <td>azimuths</td> <td>Real</td> <td>azimuth as measured from model in degrees</td> </tr> <tr> <td>dip_degrees</td> <td>Real</td> <td>dip as measured from model in degrees</td> </tr> <tr> <td>Dip corrected bed thickness (m)</td> <td>Real</td> <td>dip corrected bed thickness in meters</td> </tr> <tr> <td>lower_point</td> <td>Real</td> <td>lower bed elevation in meters</td> </tr> <tr> <td>upper_point</td> <td>Real</td> <td>upper bed elevation in meters</td> </tr> <tr> <td>_formation</td> <td>Real</td> <td>integer number of formation string</td> </tr> <tr> <td>layer_iid</td> <td>Integer64</td> <td>integer number of layer_id</td> </tr> <tr> <td>bascom_baryte_diff_bt</td> <td>Real</td> <td>diff. in thickness from geomodel measurements</td> </tr> <tr> <td>bascom_baryte_diff_dcbt</td> <td>Real</td> <td>diff. in dip cor. thicknesses &rsquo;&rsquo;</td> </tr> </tbody> </table> <p><strong>rbsc (rbsc.gpkg)</strong></p> <p>Geopackage vector file containing virtual boreholes with high resolution vertical sampling placed in a regular grid in the spatial extent of the DEM with the following columns.</p> <table> <thead> <tr> <th>Column</th> <th>Type</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td>formation</td> <td>String</td> <td>Model required string representation of bed index</td> </tr> <tr> <td>pred_z</td> <td>Real</td> <td>Z value of bedding plane</td> </tr> <tr> <td>layer_id</td> <td>Integer64</td> <td>Bed Index from Beds Geopackage file</td> </tr> <tr> <td>section</td> <td>Real</td> <td>section number</td> </tr> <tr> <td>thickness</td> <td>Real</td> <td>thickness of the layer predicted by model</td> </tr> <tr> <td>geom</td> <td>Point</td> <td>contains X,Y,Z of point in dem CRS</td> </tr> </tbody> </table> <p><strong>rbssc (rbssc.gpkg)</strong></p> <p>Geopackage vector file containing virtual boreholes with high resolution vertical sampling placed at the centroids for each section within the spatial extent of the DEM with the following columns.</p> <table> <thead> <tr> <th>Column</th> <th>Type</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td>formation</td> <td>String</td> <td>Model required string representation of bed index</td> </tr> <tr> <td>pred_z</td> <td>Real</td> <td>Z value of bedding plane</td> </tr> <tr> <td>layer_id</td> <td>Integer64</td> <td>Bed Index from Beds Geopackage file</td> </tr> <tr> <td>section</td> <td>Real</td> <td>section number</td> </tr> <tr> <td>thickness</td> <td>Real</td> <td>thickness of the layer predicted by model</td> </tr> <tr> <td>geom</td> <td>Point</td> <td>contains X,Y,Z of point in dem CRS</td> </tr> </tbody> </table> <p><strong>crescent_shapes.gpkg</strong></p> <p>Geopackage vector file containing the measurements of the crescent features.</p> <table> <thead> <tr> <th>Column</th> <th>Type</th> <th>Description</th> </tr> </thead> <tbody> <tr> <td>azimuth</td> <td>Real</td> <td>Azimuth of the crescent feature in degrees</td> </tr> </tbody> </table>

opencc-by-4.0Feb 2023View details →
zenodo44/100

Data Used for "Mapping Tribes: Ottoman Spatial Thinking in Iraq and Arabia, c. 1910"

<p>This repository contains data used for our article, &quot;Mapping Tribes: Ottoman Spatial Thinking in Iraq and Arabia, c. 1910&quot;. The README.md file explains the contents. This data can also be found at https://github.com/opengulf/ottoman-map.</p>

opencc-by-4.0Apr 2023View details →
zenodo40/100

Figs 41–50 in Contribution to the knowledge of selected genera of the tribe Opsiini (Hemiptera: Cicadellidae: Deltocephalinae) from the Kingdom of Saudi Arabia

Figs 41–50. Hishimonus phycitis (Distant, 1908). 41 – aedeagus, dorsal view; 42 – aedeagus, lateral view; 43 – connective; 44 – style; 45 – subgenital plate; 46 – valve; 47 – pygofer; 48 – female 7th sternite; 49–50 – ovipositor, lateral view.

opencc-by-4.0Jul 2018View details →
zenodo40/100

Figs 1–6. 1–2 in Contribution to the knowledge of selected genera of the tribe Opsiini (Hemiptera: Cicadellidae: Deltocephalinae) from the Kingdom of Saudi Arabia

Figs 1–6. 1–2 – Concavifer marmoratus Dlabola, 1960: 1 – dorsal view of male; 2– dorsal view of female. 3–4 – Phlepsopsius arabicus Dlabola, 1979: 3 – dorsal view; 4 – head and thorax. 5–6 – Hishimonus phycitis (Distant, 1908): 5 – dorsal view; 6 – head and thorax.

opencc-by-4.0Jul 2018View details →
zenodo40/100

Fig. 34. Disco-submarginal cell. A in The genus Enicospilus Stephens, 1835 (Hymenoptera, Ichneumonidae, Ophioninae) in Saudi Arabia, with twelve new species records and the description of five new species

Fig. 34. Disco-submarginal cell. A. Enicospilus psammus (after Gauld &amp; Mitchell 1978). B. E. perlatus (after Shestakov 1926).

opencc-by-3.0Nov 2017View details →
zenodo40/100

Fig. 31. Hind tarsal claw. A in The genus Enicospilus Stephens, 1835 (Hymenoptera, Ichneumonidae, Ophioninae) in Saudi Arabia, with twelve new species records and the description of five new species

Fig. 31. Hind tarsal claw. A. Enicospilus pacificus (Holmgren, 1868). B. E. pallidus (Taschenberg, 1875). C. E. pseudoculator Gadallah &amp; Soliman sp. nov. D. E. rundiensis Bischoff, 1915. E. E. senescens (Tosquinet, 1896). F. E. shadaensis Gadallah &amp; Soliman sp. nov.

opencc-by-3.0Nov 2017View details →
zenodo40/100

Fig. 33. A in The genus Enicospilus Stephens, 1835 (Hymenoptera, Ichneumonidae, Ophioninae) in Saudi Arabia, with twelve new species records and the description of five new species

Fig. 33. A. Mid tibial spurs of Enicospilus nervellator Aubert, 1966. B. Mid tibial spurs of E. splendidus Rousse, Soliman &amp; Gadallah sp. nov. C. Hind tibial spurs of E. splendidus Rousse, Soliman &amp; Gadallah sp. nov.

opencc-by-3.0Nov 2017View details →
zenodo40/100

Fig. 30. Hind tarsal claw. A in The genus Enicospilus Stephens, 1835 (Hymenoptera, Ichneumonidae, Ophioninae) in Saudi Arabia, with twelve new species records and the description of five new species

Fig. 30. Hind tarsal claw. A. Enicospilus grandiflavus Townes &amp; Townes, 1973. B. E. mirabilis Soliman &amp; Gadallah sp. nov. C. E. nervellator Aubert, 1966. D. E. oculator Seyrig, 1935. E. E. odax Gauld &amp; Mitchell, 1978. F. E. oweni Gauld &amp; Mitchell, 1978.

opencc-by-3.0Nov 2017View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record