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13,117 results for “Maps”
Data Mapping Using dot15926 Editor
<p>This data set includes:</p> <ul> <li>Synthetic process plant data</li> <li>Processed version of the synthetic data (version to convert to RDF)</li> <li>Mapping scripts</li> <li>dot15926 data generated from the mapping process</li> </ul>
globalbioticinteractions/template-dataset: More examples and mappings.
<p>Template species interaction data repository compatible with globalbioticinteractions.org</p>
FIGURES 172–177. Distribution maps. 172 in Revision of the genus Acylophorus Nordmann, 1837 from Madagascar and Mascarene Islands (Coleoptera: Staphylinidae: Staphylininae: Acylophorina)
FIGURES 172–177. Distribution maps. 172, Acylophorus tristis Jarrige; 173, A. derougemonti sp. nov.; 174, A. muscorum Jarrige; 175, A. delphinus Fauvel (D), A. madecassus sp. nov. (Ŧ); 176, A. minutus Jarrige (D), A. hova sp. nov. (Ɨ), A. montanus sp. nov. (Δ); 177, A. sogai Jarrige.
Data Bundle for "Rapid electron backscatter diffraction mapping: Painting by numbers"
<p>This data is a release of EBSD data for "Rapid electron backscatter diffraction mapping: Painting by numbers"<br> Figure 5 and Figure 6 contain the EBSD data.<br> FFArgus.png = far field ARGUS image <br> NFArgus.png = near field ARGUS image<br> IPF = image data for the EBSD data<br> *.ctf = export of Bruker CTF data for full EBSD map to plot EBSD maps (e.g. in MTEX)<br> *.txt = reconstructed EBSD data in columns: euler1 euler 2 euler 3 euler 3 xpos ypos phaseID<br> *.prg = Bruker project file (use this to link the EBSD patterns to the NF Argus image)<br> EBSP folder = EBSPs as captured.</p> <p>The data bundle was prepared by Ben Britton (b.britton@imperial.ac.uk).</p> <p>The figures are presented in the powerpoint (which can be extracted as a zip if needed).</p>
Galactic dust absorption maps
<p>This dataset contains the 3D structure of interstelllar dust in the vicinity of the Sun, as well as its logarithmic spatial correlation power spectrum. It was computed from Gaia absorption data using Gaussian process regression.</p> <p>The simple_cube contains only mean and standard deviation while the full_cube contains 50 approximate posterior samples.</p> <p>The corresponding paper is available on arxiv:1901.05971</p> <p>In this version the documentation was corrected. The coordinate system does not have the half-pixel shift that is described in the previous data set versions, leading to an exactly centered box. Additionally, the description of the relation of power spectrum and dust realization was extended to include the a-priori mean of 0.001 e-folds of absorption per parsec.<br> The numerical content of the data set is identical to version 1.1</p>
Global liquefaction susceptibility map
<p>This is a global liquefaction susceptibility map (EPSG:4326) based on the geospatial liquefaction prediction models of Zhu et al.<sup>[1]</sup> .</p> <p>The coastal model was applied for areas <20km from the coast. The inland model was applied elsewhere. Refer to Zhu et al. <sup>[1]</sup> in the first instance for further methodology and descriptions.</p> <p>Input data used in part, or their entirety may comprise (amongst others):</p> <ul> <li>rivers <sup>[2-4]</sup></li> <li>depth to ground water <sup>[5]</sup></li> <li>precipitation <sup>[6] </sup></li> <li>land <sup>[7]</sup></li> <li><em>V<sub>s30</sub> </em><sup>[8]</sup></li> </ul> <p>Cell values are based on Zhu et al. <sup>[1]</sup> susceptibility classes where: </p> <ol> <li>very low,</li> <li>low,</li> <li>moderate,</li> <li>high,</li> <li>very high</li> </ol> <p>0 refers to no data -- typically water bodies.</p> <p>While this data may be useful as preliminary information for regional-scale planning, a PGV intensity term is required for probability maps. Again, see Zhu et al. <sup>[1]</sup> for a discussion here.</p> <p>An application using this dataset is seen in Koks et al. <sup>[9]</sup>.</p> <p> </p> <p><sup>[1] </sup><a href="https://doi.org/10.1785/0120160198">Zhu et al. (2017) An updated geospatial liquefaction model for global application. <em>Bull. Seismol. Soc. Am.</em> 107, 1365–1385.</a></p> <p><sup>[2]</sup> <a href="http://hydrosheds.cr.usgs.gov/">Lehner et al. (2006) HydroSHEDS: Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales, Version 1.0.</a></p> <p><sup>[3]</sup> <a href="http://inspire-geoportal.ec.europa.eu/demos/ccm/">Vogt et al. (2008) CCM River and Catchment Database, version 2.1.</a></p> <p><sup>[4]</sup> Wessel et al. (1992) Digital Chart of the World: Inland Water.</p> <p><sup>[5]</sup> <a href="http://10.1126/science.1229881">Fan et al. (2013) Global patterns of groundwater table depth. <em>Science </em>(80)339, 940–943.</a></p> <p><sup>[6]</sup> <a href="https://doi.org/10.1002/joc.5086">Fick et al. (2017) WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. <em>Int. J. Climatol. </em>37, 4302–4315.</a></p> <p><sup>[7]</sup> <a href="http://www.soest.hawaii.edu/wessel/gshhg/">Wessel et al. (2017) LGSHHG: A Global Self-consistent, Hierarchical, High-resolution Geography Database Version 2.3.7.</a></p> <p><sup>[8] </sup>Worden et al. (2017) <em>Development of an Open-Source Hybrid Global Vs30 Model,</em> Seismological Society of America Annual Meeting, 21-23 April, Pasadena, CA.</p> <p><sup>[9]</sup> <a href="https://www.nature.com/articles/s41467-019-10442-3">Koks et al. (2019) A global multi-hazard risk analysis of road and railway infrastructure assets <em>Nature Communications</em> 10 (2677)</a></p>
FIGURE 1. Map showing collection localities. A in Two new sponge-associated Branchiosyllis (Annelida: Syllidae: Syllinae) from Northeastern Brazil
FIGURE 1. Map showing collection localities. A, the two oceanic islands and a coastal region in Northeastern Brazil; B, Fernando de Noronha Island, 1: Buraco da Raquel; C, Rocas Atoll, 2 and 3: Canal da Barretinha and Piscina das Tartarugas, respectively; D, Todos os Santos Bay, 4: Ilha dos Frades. Colors of numbers and circles are just for a better view.
Inference of Feature Mappings from Class Mappings
<p>Provides mapping models as transformation definitions for two cases (Library2Library and UML2Component). In particular, the provided mappings models act as a reference for the inference of feature mappings from class mapping. The dataset also includes input and output models for the execution of transformations. </p>
FIGURES 23–24. Distribution maps. 23 in A new species of Polynoncus Burmeister, 1876 from Brazil (Coleoptera: Trogidae)
FIGURES 23–24. Distribution maps. 23, Omorgus triestinae Pittino, 1987; 24, Omorgus suberosus (Fabricius, 1775).
FIGURE 9 in The genus Bittacus Latreille (Insecta: Mecoptera) in Brazil: key to species, distribution maps, new synonym, and three new species
FIGURE 9. Bittacus cruzi sp. n. a) male holotype habitus; b) wings; c) head, frontal view; d) head and thorax, dorsal view; e) male terminalia, lateral view; f) male epandrium, dorsal view. Scale bars = 1 mm.
FIGURE 13. a in The genus Bittacus Latreille (Insecta: Mecoptera) in Brazil: key to species, distribution maps, new synonym, and three new species
FIGURE 13. a) Austromerope brasiliensis forewing; b) Pazius sp. head, frontal view; c) Issikiela sp. forewing; d) Nannobittacus sp. forewing. Cu = cubital; M = medial.
FIGURE 10 in The genus Bittacus Latreille (Insecta: Mecoptera) in Brazil: key to species, distribution maps, new synonym, and three new species
FIGURE 10. Bittacus ferreirai sp. n. a) wings; b) head, frontal view; c) head and thorax, dorsal view; d) male terminalia, lateral view; e) male terminalia, dorsal view; f) male terminalia, posterior view. Scale bars = 1 mm.
FIGURE 8. Brazilian Bittacus male epandria, dorsal view. a in The genus Bittacus Latreille (Insecta: Mecoptera) in Brazil: key to species, distribution maps, new synonym, and three new species
FIGURE 8. Brazilian Bittacus male epandria, dorsal view. a) B. angrensis; b) B. aripuanensis; c) B. blancheti; d) B. boraceiensis; e) B. brasiliensis; f) B. cruzi sp. n.; g) B. diversinervis; h) B. femoralis; i) B. ferreirai sp. n.; j) B. flavescens; k) B. froehlichi; l) B. genicutalus; m) B. latreillei; n) B. maculosus; o) B. omega; p) B. pintoi; q) B. varzeanus sp. n.
FIGURE 5. Bittacus wings. a in The genus Bittacus Latreille (Insecta: Mecoptera) in Brazil: key to species, distribution maps, new synonym, and three new species
FIGURE 5. Bittacus wings. a) B. brunipennis, holotype; b) B. froehlichi, holotype; c) B. omega, holotype. Scale bars = 1mm. Type specimen photos of B. brunipennis and B. froehlichi provided by Caleb Martins (LMED).
FIGURE 7. Generalized Bittacus male terminalia. a in The genus Bittacus Latreille (Insecta: Mecoptera) in Brazil: key to species, distribution maps, new synonym, and three new species
FIGURE 7. Generalized Bittacus male terminalia. a) posteroventral view; b) lateral view; c) lateral view, without epandrium. Bs = basistylus; C = cercus; E = epandrium; G = gonostylus; P = penisfilum; S = sternite; Sa = subanal plate; T = tergite.
FIGURE 12 in The genus Bittacus Latreille (Insecta: Mecoptera) in Brazil: key to species, distribution maps, new synonym, and three new species
FIGURE 12. Distribution records of Bittacus species in Brazil. a) B. angrensis, B. aripuanensis, B. blancheti, B. brasiliensis, B. brunipennis; b) B. boraceiensis, B. cruzi sp. n., B. diversinervis, B. femoralis; c) B. ferreirai sp. n., B. flavescens, B. froehlichi, B. latreillei; d) B. maculosus, B. omega, B. pintoi, B. varzeanus sp. n. Bittacus geniculatus is not represented because of its imprecise location.
FIGURE 11 in The genus Bittacus Latreille (Insecta: Mecoptera) in Brazil: key to species, distribution maps, new synonym, and three new species
FIGURE 11. Bittacus varzeanus sp. n. a) wings; b) head, frontal view; c) head and thorax, dorsal view; d) male terminalia, lateral view; e) male terminalia, dorsal view; f) male terminalia, posterodorsal view. Scale bars = 1 mm.
FIGURE 6. Bittacus wings. a in The genus Bittacus Latreille (Insecta: Mecoptera) in Brazil: key to species, distribution maps, new synonym, and three new species
FIGURE 6. Bittacus wings. a) B. diversinervis; b) B. boraceiensis, holotype forewing; c) B. femoralis, forewing; d) B. latreillei, forewing. A = anal; cc = costal crossvein; Cu = cubital; M = medial; pt = pterostigma; pt c = pterostigmal crossvein; R = radial; Rs = radial sector; Sc = Subcosta. Scale bars = 1 mm.
FIGURE 3. Bittacus adult habitus images. a in The genus Bittacus Latreille (Insecta: Mecoptera) in Brazil: key to species, distribution maps, new synonym, and three new species
FIGURE 3. Bittacus adult habitus images. a) B. diversinervis; b) B. femoralis; c) B. latreillei. Scale bars = 1 mm.
FIGURE 1. Bittacus adult habitus images. a in The genus Bittacus Latreille (Insecta: Mecoptera) in Brazil: key to species, distribution maps, new synonym, and three new species
FIGURE 1. Bittacus adult habitus images. a) B. angrensis; b) B. brasiliensis, lectotype; c) B. flavescens, holotype; d) B. geniculatus, holotype. Scale bars = 1 mm. Type specimen photos provided by Michael Ohl (ZMHB).
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.