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Dataset results
431 results for “register”
Database of local seismicity registered on ocean bottom seismometers (OBS). Database related to Bornstein et al. (accepted in Earth and Space Science), PICKBLUE
<p>We assembled a database of Ocean Bottom Seismometer (OBS) waveforms and manual P and S picks from local seismicity, on which we trained PickBlue, a deep-learning picker, using the seismometer data and the hydrophone channel. The dataset belongs to Bornstein et al. (accepted 2023 in Earth and Space Science). The picker and database are available in the SeisBench platform, allowing easy and direct application to OBS traces and hydrophone records.</p><p>The complete database is also accessible with SEISBENCH: <br><a href="https://seisbench.readthedocs.io">https://seisbench.readthedocs.io</a><br>SEISBENCH on github:<br><a href="https://github.com/seisbench">https://github.com/seisbench</a></p><p>Related paper:</p><p>Bornstein, T., Lange, D., Münchmeyer, J., Woollam, J., Rietbrock., A., Barcheck, G., Grevemeyer, I., Tilmann, F. (accepted 2023 in Earth and Space Science). PickBlue: Seismic phase picking for ocean bottom seismometers with deep learning, Earth and Space Science. </p>
Incriminations in the inquisition register of Bologna (1291-1310): network data and code
<p>Cross-sectional (synchronic) projection of network data on incriminations (nominations of people in the criminal context of heresy trials) in the medieval inquisition register of Bologna, 1291–1310 in TSV format (tabulator-separated values), and R code for the article: Zbíral, David, Katia Riccardo, Tomáš Hampejs, and Zoltán Brys. ‘Gender, Kinship, and Other Social Predictors of Incrimination in the Inquisition Register of Bologna (1291–1310): Results from an Exponential Random Graph Model’. PLOS One 20, no. 2 (11 February 2025): e0315467. https://doi.org/10.1371/journal.pone.0315467.</p> <p>The data and analysis are described in the related article.</p>
2023 EU Transparency Register - Meta-organizations
<p>For my Research Habilitation Dissertation, I extracted all information from the EU transparency Register</p> <p>There were 12,435 registered organizations as of January 2023 (Source: Transparency Register). On this basis, I attempted to distinguish between meta-organizations and non-meta-organizations. One should keep in mind that this database only concerns organizations and individuals that seek to lobby EU institutions. There are much more meta-organizations worldwide, and many are not concerned with lobbying the EU.</p> <p>I downloaded and organized the database. I added a year column and edited the database in order to identify meta-organizations. There are 13 different categories of organizations or individuals that can be registered: 1) “Academic institutions”, 2) “Associations and networks of public authorities”, 3) “Companies & groups”, 4), “Entities, offices or networks established by third countries”, 5) “Law firms”, 6) “Non-governmental organisations, platforms and networks and similar”, 7) “Organisations representing churches and religious communities”, 8) “Other organisations, public or mixed entities”, 9) “Professional consultancies”, 10) “Self-employed individuals”, 11) “Think tanks and research institutions”, 12) “Trade and business associations”, 13) “Trade unions and professional associations”. </p> <p>Sheet 1 shows the different tables I created for my habilitation. </p>
Co-registered U. Arizona HiRISE DTM and ORI over Sakarya Vallis, Gale Crater, Mars
<p>Local digital terrain model (DTM) and orthorectified image (ORI) of Sakarya Vallis, west of Aeolis Mons in Gale crater, Mars. The DTM was originally processed by the University of Arizona (DTEEC_006855_1750_007501_1750_A01, https://www.uahirise.org/dtm/dtm.php?ID=PSP_006855_1750); this product is co-registered to CTX DTMs which were themselves co-registered to HRSC DTMs (Persaud et al. 2021, https://doi.org/10.5281/zenodo.5808357) using Ames Stereo Pipeline. The ORI was processed using Ames Stereo Pipeline and adjusted with GDAL.</p> <p>Format: GeoTiff<br> Projection: Equidistant cylindrical<br> Datum: Spheroid (r = 3396.190 km)<br> Bit depth: Float32<br> DTM grid-spacing: 1 m/pixel<br> ORI resolution: 0.25 m/pixel</p> <p>Stereo pairs (from University of Arizona): PSP_006855_1750_RED, PSP_007501_1750_RED</p> <ul> </ul> <p>Image ID of the ORI: PSP_007501_1750_RED</p>
Country Compendium of the Global Register of Introduced and Invasive Species. Dataset.
<p>The Country Compendium of the Global Register of Introduced and Invasive Species (GRIIS) is a collation of data across 196 individual country checklists of alien species, along with a designation of those species associated with evidence of impact at a country level. </p>
Human Bony Labyrinth: Co-Registered CT and micro-CT Images, Surface Models and Anatomical Landmarks
<p>This data set consists of 23 specimens of the human bony labyrinth. For each specimen clinical CT (0.15×0.15×0.2 mm3, voxel size) and co-registered microCT (0.06 mm isotropic voxel size) images are available. Image labels for the bony labyrinth are provided for the same image coordinates. From the image labels, 3D surface models were generated. In addition, each specimen has a descriptor file containing the coordinates of anatomical landmarks as well as a cochlear coordinate system. The data set can be used to study the morphology of the inner ear or to evaluate (semi-)automated segmentation algorithms (e.g., for the preoperative planning of surgical procedures such as cochlear implantation).</p>
Final Dataset for the DIssemination of REgistered COVID-19 Clinical Trials (DIRECCT) Study
<p>The DIRECCT study is a multi-phase examination of clinical trial results dissemination during the COVID-19 pandemic.</p> <p>Interim data for trials completed during the first six months of the pandemic (i.e., 1 January 2020 – 30 June 2020) was previously deposited at https://doi.org/10.5281/zenodo.4669936.<br> This data deposit comprises the results of searches for trials completed during the first 18-months of the pandemic (i.e., 1 January 2020 – 30 June 2021).<br> The data structure for the final phase of the project is not identical to the interim data as it was substantially more complex.<br> The data include datatables (CSVs) that can be treated as relational and joined on the `id` or `trn` columns. See datamodel.png for an overview of the data.</p> <p>Details on data sources and methods for the creation and analysis of this dataset are available in a detailed protocol (Version 3.1, 19 July 2023) : https://osf.io/w8t7r</p> <p>Note: This repository will be updated with additional information including a codebook and archives of raw data.</p> <p>Additional information on the project is available at the project's OSF page: https://doi.org/10.17605/osf.io/5f8j2.</p>
S63 | UBADWGW | REACH Registered Substances Detected in Drinking (DW) or Groundwater (GW)
<p><strong>REACH Registered Substances Detected in Drinking (DW) or Groundwater (GW)</strong></p> <p>This is a literature review and a subsequent persistent, mobile and toxic/very persistent and very mobile (PMT/vPvM) assessment published by the German Environment Agency (UBA) in 2019. All substances are reported in literature to have been detected in drinking water and groundwater. This list contains only those substance that are registered under REACH (EC No 1907/2006). It is assessed whether a substance meets the PMT/vPvM criteria as proposed by the German Environment Agency (UBA) in 2019 <a href="https://www.umweltbundesamt.de/publikationen/reach-improvement-of-guidance-methods-for-the">(UBA TEXTE 126/2019)</a>.</p> <p><em>Reference</em>: Hans Peter H Arp and Sarah E Hale (2019). REACH: Improvement of guidance and methods for the identification and assessment of PMT/vPvM substances, Texte | 126/2019, German Environment Agency (UBA), Dessau-Roßlau, Germany. ISBN: 1862-4804, 131 pages.</p> <p><em>Acknowledgement:</em> Environmental Research of the Federal Ministry for the Environment, Nature Conservation and Nuclear Safety Project No. (FKZ) 3716 67 416 0 and Report No. FB000142/ENG</p> <p>This is the collection associated with list S63 UBADWGW on the <a href="https://www.norman-network.com/nds/SLE/">NORMAN Suspect List Exchange</a>.</p>
Three-dimensional arrangement of human bone marrow microvessels revealed by immunohistology in undecalcified sections - registered sections (input data)
<p>These are the 3500x3500 ROI data, selected from complete scans.</p> <p>Following procedure was applied:</p> <p>- Coarse registration (Ulrich et al, 2014)<br> - ROI selection, 4k x 4k regions<br> - Normalisation<br> - Fine-grain registration (Lobachev et al, 2016)<br> - Crop to the center to obtain 3500x3500 size.</p> <p>We estimated the slice thickness to be 7 µm.</p>
Global Register of Introduced and Invasive Species: GRIIS DwCA
Published via GBIF by the Invasive Species Specialist Group (ISSG). The Global Register of Introduced and Invasive Species (GRIIS) presents validated and verified checklists (inventories) of introduced (alien) and invasive alien species at the country, territory, and associated island level. Phase 1 of the project focused on developing validated and verified checklists of countries that are Party to the Convention on Biological Diversity (CBD). Phase 2 which is on-going, aims to achieve global coverage including non-party countries and all overseas territories of countries e.g. Netherlands, France and United Kingdom. Species belonging to all Kingdoms are covered as well as occurring in all Environment/systems. Country/ Territory/ Island checklists are reviewed and verified by networks of country or species experts. Verified checklists/ species records as well as those under review are presented on the online GRIIS website (www.griis.org). Individual species records are flagged with a __yes__ for verification. Only verified checklists/ species records are presented on the GBIF Portal. <p></p>https://www.gbif.org/dataset/search?publishing_org=cdef28b1-db4e-4c58-aa71-3c5238c2d0b5<p></p>
Country Compendium of the Global Register of Introduced and Invasive Species: Standardization to Records in World Flora Online or the World Checklist of Vascular Plants
<p>The <strong>Country Compendium of the Global Register of Introduced and Invasive Species (GRIIS)</strong> is a collation of data across 196 individual country checklists of alien species, along with a designation of those species associated with evidence of impact at a country level. This compendium is available via <a href="https://zenodo.org/records/6348164">Zenodo</a> and was described by Pagad et al. <a href="https://www.nature.com/articles/s41597-022-01514-z">2022</a>:</p><ul><li>Shyama Pagad, Stewart Bisset, & Melodie A. McGeoch. (2022). Country Compendium of the Global Register of Introduced and Invasive Species. Dataset. (V1_0) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.6348164">https://doi.org/10.5281/zenodo.6348164</a></li><li>Pagad, S., Bisset, S., Genovesi, P. <i>et al.</i> Country Compendium of the Global Register of Introduced and Invasive Species. <i>Sci Data</i> <strong>9</strong>, 391 (2022). <a href="https://doi.org/10.1038/s41597-022-01514-z">https://doi.org/10.1038/s41597-022-01514-z</a></li></ul><p> </p><p>Here I provide direct and fuzzy matches for species listed for the Plantae Kingdom in GRIIS with accepted plant names in <strong>World Flora Online</strong> (<a href="https://www.worldfloraonline.org/downloadData">version 2023.03</a>; Borsch et al. <a href="https://doi.org/10.1002/tax.12373">2020</a>) or the <strong>World Checklist of Vascular Plants</strong> (<a href="https://doi.org/10.34885/nswv-8994">version 10</a>; Govaerts et al. <a href="https://www.nature.com/articles/s41597-021-00997-6">2021</a>). Matching was done in <i>R</i> through the <a href="https://cran.r-project.org/package=WorldFlora">WorldFlora</a> package (Kindt <a href="https://bsapubs.onlinelibrary.wiley.com/doi/full/10.1002/aps3.11388">2020</a>). The taxonomic standardization process was similar to the one completed <a href="https://www.worldagroforestry.org/output/agroforestry-species-switchboard-30">during the preparation of the third major release</a> of the <a href="https://apps.worldagroforestry.org/products/switchboard">Agroforestry Species Switchboard</a> and when preparing the <strong>GlobalUsefulNativeTrees database</strong> (GlobUNT; <a href="https://worldagroforestry.org/output/globalusefulnativetrees">https://worldagroforestry.org/output/globalusefulnativetrees</a>) .</p><p>Where a matching species was found in GlobUNT, the species name in the GlobUNT database has been shown. GlobUNT has been described in the following publication: Kindt et al. (<a href="https://www.nature.com/articles/s41598-023-39552-1">2023</a>) <strong>GlobalUsefulNativeTrees, a database of 14,014 tree species, supports synergies between biodiversity recovery and local livelihoods in restoration</strong>. <i>Sci Rep</i> <strong>13</strong>, 12640. <a href="https://doi.org/10.1038/s41598-023-39552-1">https://doi.org/10.1038/s41598-023-39552-1</a>.</p><p>The developments of this dataset and GlobUNT were supported by the Darwin Initiative to project DAREX001 of <a href="https://www.darwininitiative.org.uk/project/DAREX001/"><i>Developing a Global Biodiversity Standard certification for tree-planting and restoration</i></a> and by Norway's International Climate and Forest Initiative through the Royal Norwegian Embassy in Ethiopia to the <a href="https://www.worldagroforestry.org/project/provision-adequate-tree-seed-portfolio-ethiopia"><i>Provision of Adequate Tree Seed Portfolio</i></a> project in Ethiopia. </p>
Estimated prevalence of chronic hepatitis B in Denmark on December 31, 2016 – an update based on nationwide registers
<p>Anonymised dataset analysed in the study "Estimated prevalence of chronic hepatitis B in Denmark on December 31, 2016 – an update based on nationwide registers". </p>
Data set for "Axonal and dendritic morphology of excitatory neurons in layer 2/3 mouse barrel cortex imaged through whole-brain two-photon tomography and registered to a digital brain atlas"
<p>Data set for: Liu Y, Foustoukos G, Crochet S and Petersen CCH (2022) Axonal and dendritic morphology of excitatory neurons in layer 2/3 mouse barrel cortex imaged through whole-brain two-photon tomography and registered to a digital brain atlas. Front Neuroanat 15: 791015. https://doi.org/10.3389/fnana.2021.791015</p> <p>There are 2 files in this upload:</p> <p>1. The file named "<strong>2022_Liu_FrontNeuroanat.pdf</strong>" is the Open Access pdf of the online publication in Frontiers in Neuroanatomy.</p> <p>2. The file named "<strong>Liu_data_code.zip</strong>" (~1 GB) is a zipped version of a folder ‘<em>Liu_data_code</em>’, which contains the data analyzed in the study along with the Python codes used to generate the published figures. The original high resolution image stacks obtained through whole-brain two-photon serial tomography are unfortunately too large for Zenodo, and only highly-downsampled data are included in this upload, which were used for registration with the Allen CCFv3. Instructions on how to view and analyse the anatomical data are provided in the 'README.docx' file, which you will find upon unzipping the folder.</p> <p> </p>
Historical Person Register, Tyrol 15th, 16th century
<p>The dataset consists of a file in CSV format (UTF 8). The historical person register contains late medieval / ENHG person names within the Tyrolean mining documents Hs. 37 and Hs. 1587 (15th and 16th century) as well as a modern standardisation of the names. The persons received unique Identifiers. The names are also split into title, first name, last name, occupation and descriptor. Furthermore, the year is added, provenance if available, and alternate writings of the names within the text.</p> <p>The project “Text Mining Medieval Mining Texts” (2019-2022) processed two historical mining sources: “Verleihbuch der Rattenberger Bergrichter” ( Hs. 37, 1460-1463) and “Schwazer Berglehenbuch” (Hs. 1587, approx. 1515) stored by the Tyrolean Regional Archive, Innsbruck (Austria). The central research objective of T.M.M.M.T. is the extraction and representation of the legal relationships between people, claims and mines over space and time. Furthermore it deals with the semantically opening and visualisation of the montanistic network of two tyrolean mining regions.</p> <p>Citeable Transcripts are online available:<br> Hs. 37 DOI: 10.5281/zenodo.6274562<br> Hs. 1587 DOI: 10.5281/zenodo.6274928</p> <p>View also the facsimiles and transcripts on Mining Hub: https://transkribus.eu/r/mining-hub/#/</p> <p>The research project (2019-2022) was carried out at the university of Innsbruck and funded by go!digital next generation programme of the Austrian Academy of Sciences.</p>
Historical Place Gazetteer and Historical Mine Register, Tyrol 15th, 16th century
<p>The dataset is split in two separated files in CSV format (UTF 8):</p> <p>1) Historical place gazetteer: It contains historical tyrolean names of places (core region: districts Kufstein, Schwaz; Austria) within the mining documents Hs. 37 and Hs. 1587 and their modern equivalents enriched with unique Identifiers. Furthermore, Places were localised and georeferenced as far as current scientific data and knowledge permit. A final column shows corresponding IDs between Hs. 37 and Hs. 1587.</p> <p>2) Historical mine register: The file contains historical Tyrolean names of mines and pits (core region: district Kufsten, Schwaz) within the mining documents Hs. 37 and Hs. 1587 as well as a modern standardisation of the names. The mines also received unique Identifiers.</p> <p>The registers were generated by the research team of the project “Text Mining Medieval Mining Texts” (2019-2022). Two historical mining sources were processed: “Verleihbuch der Rattenberger Bergrichter” ( Hs. 37, 1460-1463) and “Schwazer Berglehenbuch” (Hs. 1587, approx. 1515) stored by the Tyrolean Regional Archive, Innsbruck (Austria). The central research objective of T.M.M.M.T. is the extraction and representation of the legal relationships between people, claims and mines over space and time. Furthermore it deals with the semantically opening and visualisation of the montanistic network of two tyrolean mining regions.</p> <p>Citeable Transcripts are online available:<br> Hs. 37 DOI: 10.5281/zenodo.6274562<br> Hs. 1587 DOI: 10.5281/zenodo.6274928</p> <p>The research project (2019-2022) was carried out at the University of Innsbruck and funded by go!digital next generation programme of the Austrian Academy of Sciences.</p>
The Mining Register of Nejdek 1556/1581
<p>Transliteration of The Mining Register of Nejdek from years 1556/1581 with the database of the book records in MS Access.</p>
The Mining Register of Nejdek 1556/1581
<p>Transliteration of The Mining Register of Nejdek from years 1556/1581 with the database of the book records in MS Access.</p>
Montserrat Digital Surface Model (1 metre) - March 2019 - Pleiades Photogrammetry (raw, not co-registered)
<p>This tiff file contains a Digital Surface Model (DSM) of the southern portion of Montserrat, Eastern Caribbean, including the Soufrière Hills Volcano. This is the raw DSM, generated via leverage of Pleiades tri-stereo imagery using the DSM-OPT software platform; it has not been co-registered. </p>
Belham River Valley Digital Surface Model (1 metre) - March 2019 - Pleiades Photogrammetry (co-registered)
<p>This tiff contains a Digital Surface Model (DSM) of the Belham River Valley in Montserrat, Eastern Caribbean. This was generated via leverage of Pleiades tri-stereo imagery throught the DSM-OPT software platform. This DSM has been co-registered to a LiDAR DSM (generated in 2010, vertical error 0.15 m) and found to have a vertical error of 2.3 m.</p>
AI-related patents (WIPO, category G06N) and market capitalisation by companies registering at least 2 new ones in 2019, sorted into four global regions (China, USA, EEA, rest of the world)
<p>NOTE: for some reason the pptx and previews keep getting munged on this supposedly permanent arxiv, but the data is still there, unchanged, and you can see how the pptx should look in either the jpg, or the the article.</p> <p>Datasets and presentations concerning the strength of the EU and "the rest of the world" relative to China and the USA, for the purpose of illustrating and counteracting / better informing narratives concerning a "new AI cold war". The materials authored by us may be freely used under the terms of the MIT License, which appears in its entirety in both the dataset and the presentation. The other materials are only curated by us, taken from Twitter as examples of misinformation pertaining to this concern.</p> <p>As of 28 June, this work now also appears in a formal publication: Joanna J. Bryson, Helena Malikova; Is There an AI Cold War?. <em><em>Global Perspectives</em></em> 2021; 2 (1): 24803. doi: <a href="https://doi.org/10.1525/gp.2021.24803">https://doi.org/10.1525/gp.2021.24803</a></p> <p>Authors: The original analysis was conducted primarily by Malikova in collaboration with Bryson. An associated publication is anticipated where Bryson is the lead author.</p> <p>Contributors: independently followed Malikova's procedures to check her work. Inconsistencies were triple checked and resolved.</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.