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867 results for “repositories”
FIGURE 103 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
FIGURE 103. Laticauda laticaudata. Photo © JT.
FIGURE 84 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
FIGURE 84. Oxyrhabdium modestum (Agusan del Norte Prov., Mindanao Id.) (KU 334388). Photo © RMB.
MAP 1 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
MAP 1. Topographic base map for the Philippine Archipelago.
FIGURE 101 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
FIGURE 101. Hydrophis [Leioselasma] spiralis. Photo © HV.
FIGURE 22 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
FIGURE 22. Dryophiops philippina (Zamboanga City Prov., Mindanao Id.) (KU 315167). Photo © RMB.
FIGURE 15 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
FIGURE 15. Ahaetulla prasina preocularis (Ilocos Prov., Luzon Id.) (KU 329698). Photo © RMB.
FIGURE 77 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
FIGURE 77. Myersophis alpestris (Holotype) (Mountain Prov., Luzon Id.) (KU 203012). Photo © JLW.
FIGURE 13 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
FIGURE 13. Cerberus schneideri (Guimaras Prov., Guimaras Id.) (KU 302979). Photo © CDS.
FIGURE 70 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
FIGURE 70. Sibynophis bivittatus (Brooke's Point, Palawan Id.) (KU 309608). Photo © RMB.
FIGURE 98 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
FIGURE 98. Hydrophis [Palemis] platuurus. Photo © JT.
FIGURE 69 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
FIGURE 69. Tropidonophis dendrophiops (Cagayan Prov., Luzon Id.) (KU 330031). Photo © RMB.
FIGURE 12 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
FIGURE 12. Aplopeltura boa (Zamboanga City Prov., Mindanao Id.) (KU 315147). Photo © RMB.
FIGURE 27 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
FIGURE 27. Pseudorabdion ater (male) (Zamboanga City Prov., Mindanao Id.) (KU 315197). Photo © RMB.
Compilation of existing underwater PAM repositories, libraries, and applications for sound processing
<p>Resources for passive acoustic monitoring (PAM) are continuously expanding and being developed, yet a major challenge for users is staying up-to-date and finding the best software or application for their acoustics investigation. We expand on previous efforts (Rhinehart & Nicholson, 2022; Felgate, 2023) with the aim of providing a current, comprehensive list of 1) underwater sound repositories of raw sound data without significant processing, 2) biological sound reference libraries, with species or taxa identification, and 3) sound processing tools for visualization, annotation, or analysis. This spreadsheet contains three pages, one dedicated to each of the aforementioned items, along with some descriptive information to help users identify the best resources for their needs.</p> <p>This work was done to support the Global Library of Underwater Biological Sounds (GLUBS) project and funded in part by the Richard Lounsbery Foundation and from funding to SCOR WG #169 (GLUBS) provided by national committees of the Scientific Committee on Oceanic Research (SCOR) and from a grant to SCOR from the US National Science Foundation (OCE--2140395), with support from the International Quiet Ocean Experiment.</p> <p> </p>
Issues of the Eclipse Platform Repository with Resolution set to FIXED
<p>In this dataset we can find all the issues of the Eclipse Platform repository where the Resolution attribute is set to FIXED. <br>The dataset contains information about the ID, Title, Description, StartDate( Date when the issue was asigned to its resolutor) and EndDate (Date when the issue was set to FIXED) of the issues in this repository.<br><br>This file does not include issues with a Duration ( EndDate-StartDate) is less than 5 minutes or issues that do not have its title or description set.</p>
Data repository - Bachelor thesis: mapping geodiversity
<p>This repository contains all data necessary to reproduce data of the BSc. thesis of Minqiu Korevaar [13576917]. Bsc. Future Planet Studies at the University of Amsterdam. Additionally, the thesis can be requested by contacting the author.</p>
Model and Data Repository_CLEWs 4 Zambia
<p><span>This repository for the research affiliated with the University of Edinburgh encompasses a comprehensive collection of data and model files, meticulously curated to facilitate detailed analysis and modelling using the CLEWs (Climate-Land-Energy-Water) framework. The repository includes the following essential files:</span></p> <ol> <li><strong><span>CLEWs Scenario Data Files</span></strong></li> <li><strong><span>CLEWs Reference Diagram for the Baseline</span></strong><span>:</span></li> <ul> <li><span>A comprehensive PDF diagram illustrating the baseline interconnections within the CLEWs framework for Zambia. This diagram serves as a visual aid to understand the foundational relationships and interactions between climate, land, energy, and water systems.</span></li> </ul> <li><strong><span>CLEWs Number Crunching File</span></strong><span>:</span></li> <ul> <li><span>An Excel file containing detailed numerical analyses and computations essential for the CLEWs modelling. This file includes various datasets, calculations, and results that form the backbone of the scenario analyses.</span></li> </ul> <li><strong><span>Signed Stakeholder Consent Forms</span></strong><span>:</span></li> <ul> <li><span>Documentation of consent from stakeholders who contributed to the research, ensuring ethical standards and transparency in data collection and usage.</span></li> </ul> <li><strong><span>Detailed Stakeholder Responses</span></strong><span>:</span></li> <ul> <li><span>Comprehensive documentation of feedback and insights from stakeholders, providing valuable qualitative data that complement the quantitative analyses. These responses are crucial for understanding local perspectives and validating model assumptions.</span></li> </ul> <li><strong><span>GEOCLEWs Inputs and Outputs for Zambia</span></strong><span>:</span></li> <ul> <li><span>A collection of files generated by the GeoCLEWs_ZM script, which automates data collection from sources such as GAEZ v4 and FAOSTAT. The outputs include agro-climatic potential yield, crop water deficit, precipitation, and land cover data, combined with electricity information for detailed CLEWs modelling. This dataset is vital for integrated analysis and visualization of the CLEWs components.</span></li> </ul> </ol> <p><span>By centralising these critical resources, the Zenodo repository provides an invaluable tool for researchers, policymakers, and stakeholders engaged in sustainable development and climate resilience efforts in Zambia. Each file has been meticulously prepared and uploaded to ensure ease of access, facilitating robust analysis and informed decision-making within the context of the CLEWs framework.</span></p>
Forging the Path to FAIR Data Through Data Repository and Journal Publication Community Partnerships
Open the record for dataset details and reuse information.
EU Biotransform - Repository on existing impact assessment methodologies
<p>A thorough review of already existing methodologies to assess environmental/social/economic impacts of fossil/bio-based and linear/circular economies, as well as their transitions, e.g. impact forecasting through theory of change, full or simplified LCAs, material flow analyses, and outlook like<br>automated data extraction with AI, at macro level (country or regional level).</p>
VasTexture: Vast repository of textures and PBR Materials extracted from images using unsupervised approach
<h2><strong>VasTexture: Vast repository of textures and SVBRDF/PBR Materials extracted from images using an unsupervised approach.</strong></h2> <p> </p> <p>This dataset contains hundreds of thousands of textures and PBR/SV-BRDF materials extracted from real-world natural images.</p> <p> </p> <p>The repository is composed of RGB images of textures given as RGB images (each image is one uniform texture) and folders of PBR/SVBRDF materials given as a set of property maps (base color, roughness, metallic, etc).</p> <p>Note that this contain subset of repository more could be found in the <a href="https://sites.google.com/view/infinitexture/home" target="_blank" rel="noopener">main project page</a>.</p> <p>Visualisation of sampled PBRs and Textures can be seen in: <a href="../records/11391127/files/PBR_examples.jpg?download=1" target="_blank" rel="noopener">PBR_examples.jpg</a> and <a href="../records/11391127/files/Textures_Examples.jpg?download=1" target="_blank" rel="noopener">Textures_Examples.jpg</a></p> <p><a href="https://sites.google.com/view/infinitexture/home" target="_blank" rel="noopener">Link to the main project page</a></p> <p><a href="https://www.arxiv.org/pdf/2403.03309" target="_blank" rel="noopener">Link to paper</a></p> <p> </p> <h2>File structure</h2> <p>Texture images are given in the <strong><a href="../records/11391127/files/Extracted_textures_1.zip?download=1" target="_blank" rel="noopener">Extracted_textures_</a>*.zip</strong> files.</p> <p>Each image in this zip file is a single texture, the textures were extracted and cropped from the <a href="https://storage.googleapis.com/openimages/web/index.html" target="_blank" rel="noopener">open images dataset</a>. </p> <p> </p> <p>PBR Materials are available in <strong><a href="../records/11391127/files/PBR_O0_1.zip?download=1" target="_blank" rel="noopener">PBR_*.zip</a></strong> files these PBRs were generated from the texture images in an unsupervised way (with no human intervention). Each subfolder in this file contains the properties map of the PBRs (roughness, metallic, etc, suitable for blender/unreal engine). Visualization of the rendered material appears in the file Material_View.jpg in each PBR folder.</p> <p>PBR materials and textures which are larger then 512x512 pixels contain '<strong>large' </strong>or<strong> 'larger' </strong>in their file name there about 40k in this repository but 100k more can be found in the <a href="https://sites.google.com/view/infinitexture/home" target="_blank" rel="noopener">main project page</a>.</p> <p>PBR materials and textures who are seamless marked as contain<strong> 'seamless'</strong> in their file name. </p> <p> </p> <p>PBR materials that were generated by mixing other PBR materials are available in files with the names<a href="../records/11391127/files/PBR_mix_O2_2.zip?download=1"> </a><strong><a href="../records/11391127/files/PBR_mix_O2_2.zip?download=1">PBR_mix*.zip</a> </strong></p> <p> </p> <p>Samples for each case can be found in files named: <strong> Sample_*.zip</strong></p> <p> </p> <p>File with the word <strong>Seamless </strong>contain tileable seamless textures this files also contain textures and PBR>512 size that were extracted from the Segment Anything Dataset.</p> <p>Since the textures were extracted fom natural images they were not natively seamless but were turned to seamless using the code at <strong><a href="https://github.com/sagieppel/convert-image-into-seamless-tileable-texture">this url</a></strong></p> <p> </p> <p> </p> <p><strong>Documented code used to extract the textures and generate the PBRs is available at: </strong></p> <p><strong><a href="../records/11391127/files/Texture_And_Material_ExtractionCode_And_Documentation.zip?download=1" target="_blank" rel="noopener">Texture_And_Material_ExtractionCode_And_Documentation.zip</a></strong></p> <h2>Details:</h2> <p>The materials and textures were extracted from real-world images using an unsupervised extraction method (code supplied). As such they are far more diverse and wide in scope compared to existing repositories, at the same time they are much more noisy and contain more outliers compared to existing repositories. This repository is probably more useful for things that demand large-scale and very diverse data, yet can use noisy and lower quality compared to professional repositories with manually made assets like ambientCG. It can be very useful for creating machine learning datasets, or large-scale procedural generation. It is less suitable for areas that demand precise clean and categorized PBR like CGI art and graphic design. For preview It is recommended to look at <a href="../records/11391127/files/PBR_examples.jpg?download=1" target="_blank" rel="noopener">PBR_examples.jpg</a> and <a href="../records/11391127/files/Textures_Examples.jpg?download=1" target="_blank" rel="noopener">Textures_Examples.jpg</a> or download the Sample files and look at the Material_View.jpg files to visualize the quality of the materials.</p> <h3>Scale:</h3> <p>Currently, there are a few hundred of thousands PBR materials and textures but the goal is to make this into over a million in the near future.</p> <h2>Data generation code:</h2> <p>The Python scripts used to extract these assets are supplied at: </p> <p><strong><a href="../records/11391127/files/Texture_And_Material_ExtractionCode_And_Documentation.zip?download=1" target="_blank" rel="noopener">Texture_And_Material_ExtractionCode_And_Documentation.zip</a></strong></p> <p>The code could be run in any folder of random images extract regions with uniform textures and turn these into PBR materials. </p> <h2>Alternative download sources:</h2> <p>Alternative download sources:</p> <p><a href="https://sites.google.com/view/infinitexture/home" target="_blank" rel="noopener">https://sites.google.com/view/infinitexture/home</a></p> <p><a href="https://e.pcloud.link/publink/show?code=kZON5TZtxLfdvKrVCzn12NADBFRNuCKHm70" target="_blank" rel="noopener">https://e.pcloud.link/publink/show?code=kZON5TZtxLfdvKrVCzn12NADBFRNuCKHm70</a></p> <p><a href="https://icedrive.net/s/jfY1xSDNkVwtYDYD4FN5wha2A8Pz" target="_blank" rel="noopener">https://icedrive.net/s/jfY1xSDNkVwtYDYD4FN5wha2A8Pz</a></p> <p> </p> <h2>Paper</h2> <p>This work was done as part of the paper "<a href="https://www.arxiv.org/pdf/2403.03309" target="_blank" rel="noopener">Learning Zero-Shot Material States Segmentation,</a></p> <p><a href="https://www.arxiv.org/pdf/2403.03309" target="_blank" rel="noopener">by Implanting Natural Image Patterns in Synthetic Data</a>".</p> <p>@article{eppel2024learning,</p> <p> title={Learning Zero-Shot Material States Segmentation, by Implanting Natural Image Patterns in Synthetic Data},</p> <p> author={Eppel, Sagi and Li, Jolina and Drehwald, Manuel and Aspuru-Guzik, Alan},</p> <p> journal={arXiv preprint arXiv:2403.03309},</p> <p> year={2024}</p> <p>}</p> <p> </p> <h2>License:</h2> <p>All the code and repositories are available on CC0 (free to use) licenses.</p> <p>Textures were extracted from the open images dataset which is an Apache license.</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.