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3,172
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Dataset results
3,172 results for “Publications”
MULTIPLIERS_WP3/4/5_Science learning project on Clean water and sanitation_Public data_IREN_20241021_v1
<p><span>This dataset contains the following data related to</span><span> the science learning project on <em>Clean water and sanitation</em></span><span>:</span></p> <ul> <li><span>S</span><span>ummary of transcripts, quotes and translations, from interviews with teachers, OSC members, and students (</span><span>Pseudo-/Anonymised)</span></li> <li>Summary<span> of transcripts, quotes and translations, from focus group discussions with students (</span><span>Pseudo-/Anonymised)</span></li> </ul>
Linked collectors and determiners for: MPM Milwaukee Public Museum Invertebrate Zoology Collection.
Natural history specimen data linked to collectors and determiners held within, "MPM Milwaukee Public Museum Invertebrate Zoology Collection". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/c081d6d4-cb80-45b3-b9cd-dab5568b8c5e">https://bionomia.net/dataset/c081d6d4-cb80-45b3-b9cd-dab5568b8c5e</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/c081d6d4-cb80-45b3-b9cd-dab5568b8c5e">https://gbif.org/dataset/c081d6d4-cb80-45b3-b9cd-dab5568b8c5e</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: MPM Milwaukee Public Museum Herbarium.
Natural history specimen data linked to collectors and determiners held within, "MPM Milwaukee Public Museum Herbarium". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/9168f50d-350e-4af1-ba97-17274f1faeaf">https://bionomia.net/dataset/9168f50d-350e-4af1-ba97-17274f1faeaf</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/9168f50d-350e-4af1-ba97-17274f1faeaf">https://gbif.org/dataset/9168f50d-350e-4af1-ba97-17274f1faeaf</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: MPM Milwaukee Public Museum Paleobiology Collection.
Natural history specimen data linked to collectors and determiners held within, "MPM Milwaukee Public Museum Paleobiology Collection". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/900a5b09-234c-4c60-8422-87ecc61c01fb">https://bionomia.net/dataset/900a5b09-234c-4c60-8422-87ecc61c01fb</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/900a5b09-234c-4c60-8422-87ecc61c01fb">https://gbif.org/dataset/900a5b09-234c-4c60-8422-87ecc61c01fb</a>. Formatted as a Frictionless Data package.
Datasets underlying the publication "A new lineage nomenclature to aid genomic surveillance of dengue virus"
<p>These datasets are underlying the scientific publication titled "A new lineage nomenclature to aid genomic surveillance of dengue virus", published in the <a href="https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3002834#abstract0">PLOS Biology</a> journal. </p> <p>All sequences used to design the lineage system are from Genbank and GISAID, with accession numbers listed in the tables. Custom scripts and alignments of representative sequences from Genbank can be found on the github of the publication authors (<a href="https://github.com/DENV-lineages/lineages-paper">https://github.com/DENV-lineages/lineages-paper</a>).</p> <p>Sequences for the Vietnam case study can be found on Genbank under accession numbers PP269455-PP270050, in bioproject PRJNA1072696. For the case study from Tanzania, sequences can be found on Genbank under accession numbers OM920035-OM920066 for DENV-3 and OM920075-OM920415 for DENV-1. Sequences for the Brazil case study can be found on GISAID under accession numbers EPI_ISL_17733558 ‐ EPI_ISL_191469691.<br><br>The provided information in the datasets are further discussed and interpreted in detail, as well as their subsequent results, in the scientific publication.</p> <p>VIRTIGATION partner EMWEB contributed to this publication with findings from the VIRTIGATION project, a project which is part of the EU Open Research Data pilot. This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 101000570.</p>
MULTIPLIERS_WP5_Combined country data students interests_Public data_UL_ 20241025_v1
<p><span>This dataset contains combined data on interest, self efficacy and career awareness collected before and after TLS from all partner countries.</span></p>
MULTIPLIERS_WP3/4/5_Science learning project on Biodiversity and ecosystem services_Public data_UL_20241025_v1
<p><span>This dataset contains the following data related to</span><span> the science learning project on <em>Biodiversity and ecosystem services</em></span><span>:</span></p> <ul> <li> <p><span>S</span><span>ummary of transcripts from interviews with teachers, OSC members, and students (</span><span>Pseudo-/Anonymised)</span></p> </li> <li><span><span>Summary</span><span> of transcripts from focus group discussions with students (</span><span>Pseudo-/Anonymised)</span></span></li> </ul>
MULTIPLIERS_WP3/4/5_Science learning project on Forest use vs. forest protection_Public data_UMU_20241025_v1
<p><span>This dataset contains the following data related to</span><span> the science learning project on <em>Forest use vs. forest protection</em></span><span>:</span></p> <ul> <li><span>S</span><span>ummary of transcripts from interviews with teachers, OSC members, and students (</span><span>Pseudo-/Anonymised)</span></li> <li><span><span>Summary</span><span> of transcripts from focus group discussions with students (</span><span>Pseudo-/Anonymised)</span></span></li> <li><span><span><span>An indicative set of key messages and exemplary quotes from the teachers and researchers gathered from<span> </span>interviews conducted after the end of Implementation Round 2 and 3.</span></span></span></li> </ul>
MULTIPLIERS_WP5_Nature diaries_ Public data_UL_ 20241028_v1
<p><span>This dataset contains scanned students’ nature diaries. The scans have been anonymized for public use.</span></p>
Dataset for the publication: Metallic Impurities in Electrolysis: Catalytic Effect of Pb Traces in Reductive Amination and Acetone Reduction
<p>This dataset contains the experimental data of the publication "Metallic Impurities in Electrolysis: Catalytic Effect of Pb Traces in Reductive Amination and Acetone Reduction" that is published in Angewandte Chemie International Edition. </p>
Data supporting publication: All-dielectric structural coloration empowered by bound states in the continuum
<p>This repository includes the data corresponding to the figures shown in the journal article entitled</p> <p>"All-dielectric structural coloration empowered by bound states in the continuum"</p>
Metadata and georeferencing of the publications in the academic journal 'L'Espace Géographique' (1972-2020)
<p>The zip file contains two tab-separated files (.tsv):</p> <ul> <li>"netscity_espacegeo.tsv"</li> </ul> <p>29 columns, 1645 lines</p> <p>It contains the metadata of 1451 articles and "positions de recherche" issued in the academic journal 'L'Espace Géographique' between 1972 and 2020. The affiliations of the authors have been geocoded using the web application NETSCITY. This dataset combines the result of the geocoding process (geographical coordinates) for each publication with geographical enrichments (urban areas and countries from which the publications have been authored). Additionnal information are available: titles of the publications, sections of the journal in which the publications were published, publication year, authors names, affiliations.</p> <ul> <li>"metadata.tsv"</li> </ul> <p>7 columns, 29 lines</p> <p>It contains a description for each variable of the dataset: "netscity_espacegeo.tsv"</p> <p> </p>
Dataset for publication Electron-induced ligand loss from iron tetracarbonyl methyl acrylate
<p>Experimental dataset for the publication including readme files with description and all metadata.</p> <p><a href="https://doi.org/10.3762/bjnano.15.66">https://doi.org/10.3762/bjnano.15.66</a></p> <p> </p>
Dataset for publication "What does it take to stabilize a naphthalene anion?"
<p>Dataset for the publication What does it take to stabilize a naphthalene anion? </p> <div> <div><a href="https://doi.org/10.1063/5.0230131" target="_blank" rel="noopener">https://doi.org/10.1063/5.0230131</a></div> </div> <p> containing excel file with file assignments, raw data binaries (tfb), corresponding ascii files (asc) and metadata files in text format (tfa).</p> <p> </p>
Data Matrix Theme-Specific Analysis of the Recommendation on Science and Scientific Researchers (RSSR): Public and Stakeholder Engagement
<p>This Table sets out findings from the mapping exercise conducted as part of the objectives of subtask 6.1 of the RRING project.</p> <p>Aim: Alignment of RRI to advance the UN SDGs.</p> <p>Objectives:</p> <ul> <li>Mapping the RSSR to the SDGs </li> </ul> <p>Mapping the RSSR to the SDGs is aimed at providing new perspectives, ideas and approaches that can help to improve the operationalization and implementation of each SDG, <em>by facilitating the integration of RRI (or RRI-like) practices in the SDGs, to make them more achievable.</em> The impact of the new perspectives, ideas and approaches in SDG operationalization and implementation will be aimed at the level of <em>national and international policy (making); future research and innovation projects (in industry and academia); as well as education and training of researchers, policy makers and other stakeholders.</em></p> <p>Two documents were used for this task:</p> <ul> <li>2017 Recommendation on Science and Scientific Researchers ([RSSR], UNESCO), and</li> <li>the United Nations 2030 Agenda for Sustainable Development with the 17 Sustainable Development Goals (SDGs).</li> </ul>
Supplemental data of publication "Reactive Transport Model of Kinetically Controlled Celestite to Barite Replacement".
<p>Supplemental data of publication "Reactive Transport Model of Kinetically Controlled Celestite to Barite Replacement".</p> <p>Authors: Morgan Tranter, Maria Wetzel, Marco De Lucia, Michael Kühn</p> <p>Contact: mtranter@gfz-potsdam.de</p> <p>Submitted to Advances in Geosciences (31.06.2021).<br> Special Issue: European Geosciences Union General Assembly 2021, EGU Division Energy, Resources & Environment (ERE)</p> <p>EGU21 Abstract:<br> https://doi.org/10.5194/egusphere-egu21-9832</p> <p>Licensed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)</p>
Public Emails from Brazilian Smart Cities
<p>18,850 public available emails from 673 Brazilian smart cities featured in the 2020 <a href="https://ranking.connectedsmartcities.com.br/">Connected Smart Cities Ranking</a>.</p> <p>The public pages were scraped using UNINOVE LabCidades' opensource email scraper, available in GitHub as <a href="https://github.com/LabCidades/email-scraper">LabCidades/email-scraper.</a></p>
Pseudomonas aeruginosa predicted prophages from publicly available genomes
<p>Through the Genome Information by Organism section of the NCBI Genome database, <em>P. aeruginosa</em> bacterial genomic assemblies were downloaded (September 2020). Genome quality was assessed totaling 5,383 genomes total. All 5,383 genomes were then entered into VirSorter v.1 (https://github.com/simroux/VirSorter). The data set provided here includes all category 1 and category 4 predicted prophage sequences.</p>
Systematic Scoping Literature Review of Embryonic Stem Cells In Vitro Developmental Toxicity Tests: Included publications library
<p>The publications included in the systematic scoping review conducted according to the protocol:<a href="https://zenodo.org/record/2528920">https://zenodo.org/record/2528920</a></p> <p> </p>
Data for publication of "Determining the sensitive parameters of WRF model for the prediction of tropical cyclones in the Bay of Bengal using Global Sensitivity Analysis and Machine Learning"
<p>The data are made available as part of the paper "Determining the sensitive parameters of WRF model for the prediction of tropical cyclones in the Bay of Bengal using Global Sensitivity Analysis and Machine Learning", submitted to Geoscientific Model Development. This data set incorporates selected post-processed files needed to reproduce the results presented in the paper.</p> <p>The data contains six zip files, that are:</p> <ul> <li>Namelist.input files for the WRF model simulations of ten tropical cyclones</li> <li>WRF model simulation outputs using the default parameter values</li> <li>WRF model simulation outputs using the optimal parameter values (which give minimum RMSE value)</li> <li>IMDAA surface observations and IMERG precipitation data</li> <li>IMD observed tracks of ten tropical cyclones</li> <li>Ipython notebooks of sensitivity analysis and machine learning codes</li> </ul> <p>The remaining files are the ncl scripts that were used to obtain the figures. The ncl scripts used the data in the zip files.</p>
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.