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13,117 results for “Maps”
SSHOC - National Gallery - Grounds Database CIDOC CRM Mapped Dataset
<p>In 2018 the <a href="https://doi.org/10.5281/zenodo.5838339">IPERION-CH Grounds Database</a> was presented to examine how the data produced through the scientific examination of historic painting preparation or grounds samples, from multiple institutions could be combined in a flexible digital form. Exploring the presentation of interrelated high resolution images, text, complex metadata and procedural documentation. The original <a href="https://research.ng-london.org.uk/iperion/">main user interface</a> is live, though password protected at this time. Work within the <a href="https://www.sshopencloud.eu/">SSHOC project</a> aimed to reformat the data to create a more <a href="https://www.go-fair.org/fair-principles/">FAIR</a> data-set, so in addition to mapping it to a standard ontology, to increase Interoperability, it has also been made available in the form of <a href="http://en.wikipedia.org/wiki/Linked_Data">open linkable data</a> combined with a <a href="http://en.wikipedia.org/wiki/SPARQL">SPARQL</a> end-point. A draft version of this live data presentation can been found <a href="https://rdf.ng-london.org.uk/sshoc/">Here</a>.</p> <p>This is a draft data-set and further work is planned to debug and improve its semantic structure.This deposit contains the CIDOC-CRM mapped data formatted in XML and an example model diagram representing some of the key relationships covered in the data-set.</p>
Cross-correlation coefficient maps generated in the paper "Correlation of Venusian Mesoscale Cloud Morphology Between Images Acquired at Various Wavelengths" by Narita et al. published in Journal of Geophysical Research - Planets
<p>This data archive contains the cross-correlation coefficient maps. Unzipping the compressed file, the following directories corresponding to different wavelength pairs appear. </p> <p> IR1_IR2/ : 0.9 micron & 2.02 micron<br> UVI283_UVI365/ : 283 nm & 365 nm<br> IR2_UVI365/ : 2.02 micron &. 365 nm<br> IR2_UVI283/ : 2.02 micron & 283 nm<br> IR2_LIR/ : 2.02 micron & 10 micron</p> <p>If usual unzip tools do not work, the use of 7zip is recommended:<br> https://www.7-zip.org/download.html</p> <p>Each directory contains CSV files for the longitude-latitude distribution of the correlation coefficient. The 2880 longitude grids cover the longitude range of 0 - 360 degrees, and the 1440 latitude grids cover the latitude range of -90 - +90 degrees, with a pixel resolution of 0.125 degree/pixel. Invalid regions are filled with the value of 1.1.</p> <p>Each filename is composed of the date, the instrument (wavelength), and the time. For example, for the file "20160720_ir2_150821_hp6_IR1_150209_hp6_sb24.csv":</p> <p> 20160720 : July 20, 2016<br> ir2 : 2.02 micron filter of IR2 camera<br> 150821 : IR2 exposure at 15:08:21<br> hp6: High-pass filtering size is 6 deg x 6 deg<br> IR1 : 0.9 micron filter of IR1 camera<br> 150209 : IR1 exposure at 15:02:09<br> sb24 : Sliding box size is 24 deg x 24 deg</p>
Area of habitat maps for amphibians and reptiles of Italy
<p>Area of Habitat (AOH) maps reveal the distribution of the habitat available to the species within their geographic range. Information on the distribution of species' habitats can help identify sites where viable populations of a species are found. We produced high resolution (100 m), freely accessible global area of habitat maps for 60 species of reptiles and amphibians distributed in Italy, which represent 60% of all Italian amphibian and reptile species. AOH maps can be used as a reference for conservation planning and can help monitoring habitat loss, which is known to be a major threat to many reptile and amphibian species in Europe.</p>
Distribution. Congo Basin in C Africa (S Cameroon, S Central African Republic, DR Congo, Equatorial Guinea, Gabon, and Republic of the Congo). Distribution of this recently recognized speciesis still not well known and the range map is only speculative. in Elephantidae
Distribution. Congo Basin in C Africa (S Cameroon, S Central African Republic, DR Congo, Equatorial Guinea, Gabon, and Republic of the Congo). Distribution of this recently recognized speciesis still not well known and the range map is only speculative.
Distribution. Discontinuous and limited to wetland environments in the Congo Basin N and W of the range of the Zambezi Sitatunga in S Benin (Porto Novo), S Nigeria, Cameroon, Central African Republic, Equatorial Guinea, Gabon, Republic of the Congo, N DR Congo; also several isolated populations in W Africa (Senegal, Gambia & Guinea-Bissau), NE Nigeria and W Chad, and perhaps extreme S Ghana. Maps and distributional information here are provisional pending future research. in Bovidae
Distribution. Discontinuous and limited to wetland environments in the Congo Basin N and W of the range of the Zambezi Sitatunga in S Benin (Porto Novo), S Nigeria, Cameroon, Central African Republic, Equatorial Guinea, Gabon, Republic of the Congo, N DR Congo; also several isolated populations in W Africa (Senegal, Gambia & Guinea-Bissau), NE Nigeria and W Chad, and perhaps extreme S Ghana. Maps and distributional information here are provisional pending future research.
Distribution. Discontinuous and limited to wetland environments in SE Sudan, perhaps the Rift Valley of Ethiopia, W Kenya surrounding Lake Victoria (two locations, very rare), Uganda, Burundi, Rwanda, NW Tanzania, and NE DR Congo. Maps and distributional information here are provisional pending future research. in Bovidae
Distribution. Discontinuous and limited to wetland environments in SE Sudan, perhaps the Rift Valley of Ethiopia, W Kenya surrounding Lake Victoria (two locations, very rare), Uganda, Burundi, Rwanda, NW Tanzania, and NE DR Congo. Maps and distributional information here are provisional pending future research.
Distribution. Discontinuous and limited to wetland environments in two areas of S Sudan: small swamps in SW Sudan near the DR Congo border, where the type specimen was collected, and the Sudd Swamps (Bahr-el-Ghazal) of the upper White Nile. Maps and distributional information here are provisional pending future research. in Bovidae
Distribution. Discontinuous and limited to wetland environments in two areas of S Sudan: small swamps in SW Sudan near the DR Congo border, where the type specimen was collected, and the Sudd Swamps (Bahr-el-Ghazal) of the upper White Nile. Maps and distributional information here are provisional pending future research.
Distribution. Discontinuous and limited to wetland environments from S Republic of the Congo through C DR Congo and SW Tanzania, S to Zambia, Angola, and Botswana. Maps and distributional information here are provisional pending future research. in Bovidae
Distribution. Discontinuous and limited to wetland environments from S Republic of the Congo through C DR Congo and SW Tanzania, S to Zambia, Angola, and Botswana. Maps and distributional information here are provisional pending future research.
Subspecies and Distribution. R.t.timorensisdeBlainville,1822—TimorI. R.t.djongaVanBemmel,1949-MunaandButonIs. R.t.flovesiensisHeude,1897—Flores1. R.t.macassaricaHeude,1896—Sulawesi. R.t.moluccensisQuoy&Gaimard,1830—MoluccanIs. R.t.renschiSody,1932—Bali. R. t. russa Muller & Schlegel, 1845 — Java. Possibly it is native only to Java and Bali islands, introduced into Lombok, Flores, Sumbawa, Sumba, Timor, Sulawesi, and Moluccan Islands in ancient times. It was introduced during the last centuries in many locations, including New Guinea, Aru Islands, New Britain Is, Australia, New Zealand, New Caledonia, Mauritius, and Comoro Is. The map represents the native range and the oldest introductions. in Cervidae
Subspecies and Distribution. R.t.timorensisdeBlainville,1822—TimorI. R.t.djongaVanBemmel,1949-MunaandButonIs. R.t.flovesiensisHeude,1897—Flores1. R.t.macassaricaHeude,1896—Sulawesi. R.t.moluccensisQuoy&Gaimard,1830—MoluccanIs. R.t.renschiSody,1932—Bali. R. t. russa Muller & Schlegel, 1845 — Java. Possibly it is native only to Java and Bali islands, introduced into Lombok, Flores, Sumbawa, Sumba, Timor, Sulawesi, and Moluccan Islands in ancient times. It was introduced during the last centuries in many locations, including New Guinea, Aru Islands, New Britain Is, Australia, New Zealand, New Caledonia, Mauritius, and Comoro Is. The map represents the native range and the oldest introductions.
Distribution. Formerly Anatolia, Turkey, then has been introduced into Europe from ancient times and later into many other countries in North and South America, South Africa, Australia, New Zealand, and Fiji Is. The distribution map includes both the native range in Anatolia and the European continent with its old introductions. in Cervidae
Distribution. Formerly Anatolia, Turkey, then has been introduced into Europe from ancient times and later into many other countries in North and South America, South Africa, Australia, New Zealand, and Fiji Is. The distribution map includes both the native range in Anatolia and the European continent with its old introductions.
Distribution. Iran and Israel (reintroduced). The map includes both the native relict population and the reintroduced ones. in Cervidae
Distribution. Iran and Israel (reintroduced). The map includes both the native relict population and the reintroduced ones.
The results of direct mappings of panama paper to RDF and RDF-star
<p>In the paper 'Converting Property Graphs to RDF: A Preliminary Study of the Practical Impact of Different Mappings', we have used mappings introduced by Nguyen et al. [1], and Hartig [2]. Data sets are the results of direct mappings of the real-world LPG with data about the Panama Papers[3]. </p> <p>Shahrzad Khayatbashi, Sebastián Ferrada, and Olaf Hartig. 2022. Converting Property Graphs to RDF: A Preliminary Study of the Practical Impact of Different Mappings. In Joint Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA) (GRADES & NDA’22), June 12, 2022, Philadelphia, PA, USA. ACM, New York, NY, USA, 8 pages. https://doi.org/10.1145/3534540.3534695</p> <p> </p> <p>References:</p> <p>[1] Vinh Nguyen, Hong Yung Yip, Harsh Thakkar, Qingliang Li, Evan Bolton, and Olivier Bodenreider. 2019. Singleton Property Graph: Adding A Semantic Web Abstraction Layer to Graph Databases. In Proceedings of the Blockchain enabled Semantic Web Workshop (BlockSW) and Contextualized Knowledge Graphs (CKG) Workshop.</p> <p>[2] Olaf Hartig. 2017. Foundations of RDF* and SPARQL*: An Alternative Approach to Statement-Level Metadata in RDF. In Proceedings of the 11th Alberto Mendelzon International Workshop on Foundations of Data Management and the Web (AMW).</p> <p>[3] https://offshoreleaks.icij.org/pages/database</p>
FIGURE 1. Fossil locality. A, Locality map. B in Fossil caddis cases from the lower Eocene Huachong Formation of the Sanshui Basin, Foshan City, Guangdong Province, South China with detrital zircon analyses
FIGURE 1. Fossil locality. A, Locality map. B, The outcrop (red arrow point where the fossils collected), with hammer indicating the layer for zircon sampling.
Dataset and code for : "Representing Vector Geographic Information As a Tensor for Deep Learning Based Map Generalisation"
<p>Dataset and code supporting the experiment about map generation in the article: "Representing Vector Geographic Information As a Tensor for Deep Learning-Based Map Generalisation"</p>
Data for paper "Graph Deep Learning Model for Mapping Mineral Prospectivity"
<p>Four prospecting information, namely, NE- and NW- trending faults, Agno Batholithic pluton margins, and porphyry intrusive contacts for mineral prospectivity mapping in Baguio district, Philippines.</p>
FIGURES 89–90. Distribution maps for Sadala spp. 89 S. tabatinga spec. nov., S. velox Simon, S. nanay spec. nov., S. punicea Simon 90 S in Revalidation of the genus Sadala Simon, 1880 with the description of a new genus of Neotropical huntsman spiders (Araneae, Sparassidae)
FIGURES 89–90. Distribution maps for Sadala spp. 89 S. tabatinga spec. nov., S. velox Simon, S. nanay spec. nov., S. punicea Simon 90 S. rufa (Keyserling), S. kaiabi spec. nov., S. keyserlingi Simon, S. nigristernis Simon, S. yuyapichis spec. nov.
A Cross-Domain Systematic Mapping Study on Software Engineering for Digital Twins
<p><strong>A Systematic Cross-Domain Mapping Study on the Software Engineering of Digital Twins</strong></p> <p>Manuela Dalibor, Nico Jansen, Bernhard Rumpe, David Schmalzing, Louis Wachtmeister, Manuel Wimmer, and Andreas Wortmann</p> <p>Digital Twins are currently investigated as the technological backbone for providing an enhanced understanding and management of existing systems as well as for designing new systems in various domains, e.g., ranging from single manufacturing components such as sensors to large-scale systems such as smart cities. Given the diverse application domains of Digital Twins, it is not surprising that the characterization of the term Digital Twin, as well as the needs for developing and operating Digital Twins are multi-faceted. Providing a better understanding what the commonalities and differences of Digital Twins in different contexts are, may allow to build reusable support for developing, running, and managing Digital Twins by providing dedicated concepts, techniques, and tool support. In this paper, we aim to uncover the nature of Digital Twins based on a systematic mapping study which is not limited to a particular application domain or technological space. We systematically retrieved a set of 1471 unique publications of which 529 were identified as potentially relevant and of which finally 356 were selected for further investigation. In particular, we analyzed the types of research and contributions made for Digital Twins, the expected properties Digital Twins have to fulfill, how Digital Twins are realized and operated, as well as how Digital Twins are finally evaluated. Based on this analysis, we also contribute a novel feature model for Digital Twins as well as several observations to further guide future software engineering research in this area.</p>
Barcoded Bulk QTL mapping reveals highly polygenic and epistatic architecture of complex traits in yeast
<p>Mapping the genetic basis of complex traits is critical to uncovering the biological mechanisms that underlie disease and other phenotypes. Genome-wide association studies (GWAS) in humans and quantitative trait locus (QTL) mapping in model organisms can now explain much of the observed heritability in many traits, allowing us to predict phenotype from genotype. However, constraints on power due to statistical confounders in large GWAS and smaller sample sizes in QTL studies still limit our ability to resolve numerous small-effect variants, map them to causal genes, identify pleiotropic effects across multiple traits, and infer non-additive interactions between loci (epistasis). Here, we introduce barcoded bulk quantitative trait locus (BB-QTL) mapping, which allows us to construct, genotype, and phenotype 100,000 offspring of a budding yeast cross, two orders of magnitude larger than the previous state of the art. We use this panel to map the genetic basis of eighteen complex traits, finding that the genetic architecture of these traits involves hundreds of small-effect loci densely spaced throughout the genome, many with widespread pleiotropic effects across multiple traits. Epistasis plays a central role, with thousands of interactions that provide insight into genetic networks. By dramatically increasing sample size, BB-QTL mapping demonstrates the potential of natural variants in high-powered QTL studies to reveal the highly polygenic, pleiotropic, and epistatic architecture of complex traits.</p>
FIGURE 20–21. Distribution map and habitat. 20 in On the taxonomy of genus Teliphasa Moore, 1888 (Lepidoptera: Pyralidae Epipaschiinae) with the description of two new species and two new species records from India
FIGURE 20–21. Distribution map and habitat. 20, distribution map of Teliphasa spp. 21, landscape view: India, Chirbatiya (Uttarakhand).
Processed Data 1 : Spatial multi-omic map of human myocardial infarction
<p>We provide here the processed snRNA-seq, snATAC-seq, and visium data for the manuscript: Kuppe, Ramirez Flores, Li et al. "Spatial multi-omic map of human myocardial infarction", 2022</p>
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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.