cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12130980.v42
title: MOOD Maps of Google community mobility change during the COVID-19 outbreak

description: The MOOD project (MOnitoring Outbreak events for Disease surveillance in a data science context. H2020) has geo-referenced the data Google has published as a series of PDF files presenting reports on national and subnational human mobility levels relative to a baseline data of late January 2020. The details and the PDF files can be found at https://www.google.com/covid19/mobility/.<br>More detail on these files can be found at https://www.moodspatialdata.com/humanmobilityforcovid19 <br>The first set of data were released on April 2 2020 and have been revised weekly since then. The maps now utilise the CSV data released by Google. Please note that the maps figures use a mean of the previous three days, while the Google PDFs use a single days data so there will be differences between values in our maps when compare to the Google PDFs.<br>The authors have extracted the majority of these data into a series of excel spreadsheets. Each worksheet provides the data for % change in numbers of records at various types of location categories illustrated by: retail and recreation, grocery and pharmacy, parks and beaches, transit stations, workplaces and residential (columns f to K). A second set of columns calculates the difference of each value from the mean values for each category (columns L to P) Columns A to E contain geographical details. Column Q contains the names used to link to a mapping file.There are separate worksheets for the date of the data from each dated release (e.g. 2903, 0504 etc.) and separate worksheets calculating the changes between specific dates.<br>A second spreadsheet has been added calculating the 3 day moving mean of each day from the 15th of February. Each day is referenced by the Gregorian calendar day count. So day 48 = Feb 17th.<br>The maps (for EU & Global) display these data. We provide 600 dpi jpegs of the Global (“WD”) and European (“EU”) mapped values at the latest date available, for each of the mobility categories: retail and recreation (“retrec”) , grocery and pharmacy (“grocphar”) , parks (“parks”) , transit stations (“transit”), residential (“resid”) and workplaces (“work”). We also provide maps of the changes from the previous week (“ch”).<br>All data extracting and subsequent processing have been carried out by ERGO (Environmental Research Group Oxford) on behalf of the MOOD H2020 project. Data will be periodically updated. Additional maps can be obtained on request to the authors.
DOI: 10.6084/m9.figshare.12086724.v2
title: Supplementary Tables 1-7

description: One Word file explaining the content of Supplementary Tables and seven Excel files containing Supplementary Tables 1 to 7 of the MS by Donal MacGrogan et al entitled: " Identification of a peripheral blood gene signature predicting aortic valve calcification"<br><br>
DOI: 10.6084/m9.figshare.12612068.v1
title: Source Data and Code for "Determinants of genome-wide distribution and evolution of uORFs in eukaryotes"

description: This dataset contains the source data underlying all the data figures, and the custom scripts used to prepare data and perform analyses. See README.md for details.
DOI: 10.6084/m9.figshare.13055906.v2
title: R0160_20170527a_videos

description: Rat 0160, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.13055906.v1
title: R0160_20170527a_videos

description: Rat 0160, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.3761562.v1632
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.3761562.v1631
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.3761562.v1634
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.3761562.v1633
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.12130980.v45
title: MOOD Maps of Google community mobility change during the COVID-19 outbreak

description: The MOOD project (MOnitoring Outbreak events for Disease surveillance in a data science context. H2020) has geo-referenced the data Google has published as a series of PDF files presenting reports on national and subnational human mobility levels relative to a baseline data of late January 2020. The details and the PDF files can be found at https://www.google.com/covid19/mobility/.<br>More detail on these files can be found at https://www.moodspatialdata.com/humanmobilityforcovid19 <br>The first set of data were released on April 2 2020 and have been revised weekly since then. The maps now utilise the CSV data released by Google. Please note that the maps figures use a mean of the previous three days, while the Google PDFs use a single days data so there will be differences between values in our maps when compare to the Google PDFs.<br>The authors have extracted the majority of these data into a series of excel spreadsheets. Each worksheet provides the data for % change in numbers of records at various types of location categories illustrated by: retail and recreation, grocery and pharmacy, parks and beaches, transit stations, workplaces and residential (columns f to K). A second set of columns calculates the difference of each value from the mean values for each category (columns L to P) Columns A to E contain geographical details. Column Q contains the names used to link to a mapping file.There are separate worksheets for the date of the data from each dated release (e.g. 2903, 0504 etc.) and separate worksheets calculating the changes between specific dates.<br>A second spreadsheet has been added calculating the 3 day moving mean of each day from the 15th of February. Each day is referenced by the Gregorian calendar day count. So day 48 = Feb 17th.<br>The maps (for EU & Global) display these data. We provide 600 dpi jpegs of the Global (“WD”) and European (“EU”) mapped values at the latest date available, for each of the mobility categories: retail and recreation (“retrec”) , grocery and pharmacy (“grocphar”) , parks (“parks”) , transit stations (“transit”), residential (“resid”) and workplaces (“work”). We also provide maps of the changes from the previous week (“ch”).<br>All data extracting and subsequent processing have been carried out by ERGO (Environmental Research Group Oxford) on behalf of the MOOD H2020 project. Data will be periodically updated. Additional maps can be obtained on request to the authors.
DOI: 10.6084/m9.figshare.12130980.v44
title: MOOD Maps of Google community mobility change during the COVID-19 outbreak

description: The MOOD project (MOnitoring Outbreak events for Disease surveillance in a data science context. H2020) has geo-referenced the data Google has published as a series of PDF files presenting reports on national and subnational human mobility levels relative to a baseline data of late January 2020. The details and the PDF files can be found at https://www.google.com/covid19/mobility/.<br>More detail on these files can be found at https://www.moodspatialdata.com/humanmobilityforcovid19 <br>The first set of data were released on April 2 2020 and have been revised weekly since then. The maps now utilise the CSV data released by Google. Please note that the maps figures use a mean of the previous three days, while the Google PDFs use a single days data so there will be differences between values in our maps when compare to the Google PDFs.<br>The authors have extracted the majority of these data into a series of excel spreadsheets. Each worksheet provides the data for % change in numbers of records at various types of location categories illustrated by: retail and recreation, grocery and pharmacy, parks and beaches, transit stations, workplaces and residential (columns f to K). A second set of columns calculates the difference of each value from the mean values for each category (columns L to P) Columns A to E contain geographical details. Column Q contains the names used to link to a mapping file.There are separate worksheets for the date of the data from each dated release (e.g. 2903, 0504 etc.) and separate worksheets calculating the changes between specific dates.<br>A second spreadsheet has been added calculating the 3 day moving mean of each day from the 15th of February. Each day is referenced by the Gregorian calendar day count. So day 48 = Feb 17th.<br>The maps (for EU & Global) display these data. We provide 600 dpi jpegs of the Global (“WD”) and European (“EU”) mapped values at the latest date available, for each of the mobility categories: retail and recreation (“retrec”) , grocery and pharmacy (“grocphar”) , parks (“parks”) , transit stations (“transit”), residential (“resid”) and workplaces (“work”). We also provide maps of the changes from the previous week (“ch”).<br>All data extracting and subsequent processing have been carried out by ERGO (Environmental Research Group Oxford) on behalf of the MOOD H2020 project. Data will be periodically updated. Additional maps can be obtained on request to the authors.
DOI: 10.6084/m9.figshare.13077581.v1
title: On the status of Nycteris madagascariensis G. Grandidier, 1937, a reputed endemic to Madagascar

description: Cyt-b fasta file for Nycteris madagascariensis and tree files from Nycteris phylogenetic analyses.<br>
DOI: 10.6084/m9.figshare.12420968.v4
title: Benchmarking atlas-level data integration in single-cell genomics - integration task datasets

description: Pancreas, Lung atlas, human immune cell, and human and mouse immune cell integration tasks from the manuscript "Benchmarking atlas-level data integration in single-cell genomics". <br><br>These datasets were aggregated from public datasets, cell annotations were harmonized or reannotated, and the data was consistently preprocessed using scran pooling and log+1 transformation. In the immune cell datasets an erythrocyte development trajectory was also annotated. Details on dataset preprocessing can be found in the paper and in the accompanying Github at https://www.github.com/theislab/scib.<br><br>Please cite the paper and the papers the individual datasets were aggregated from when using this data.<br><br>Note: the "complexBatch" version of the pancreas data was used in the paper. This version contains a higher resolution batch covariate and all batches were normaled jointly.<br>
DOI: 10.6084/m9.figshare.3761562.v1639
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.3761562.v1638
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.13078883.v1
title: Soybean Crop Insect Processed (Cropped) Image Dataset_V1 for Classification

description: The dataset contains soybean crop adult insect raw Images ( a total of 3797 images) in JPG format. There were considered four kind of soybean crop insect’s images as: 1. A folder Cropped_Eocanthecona_Bug_A contains 1185 images of Eocanthecona Bug. 2. A folder Cropped_Tobacco_Caterpillar_B contains 980 images of Tobacco Caterpillar. 3. A folder Cropped_Red_Hairy_Catterpillar_C Contains 998 images of Red Hairy Caterpillar. 4. A folder Cropped_Larva_Spodoptera_D contains 634 images of Larva Spodoptera. 5. All the images were cropped from the original dataset (Tiwari, Vivek; Saxena, Ravi R; Ojha, Muneendra (2020): Soybean Crop Insect Raw Image Dataset_V1 with bounding boxes. figshare. Dataset. https://doi.org/10.6084/m9.figshare.13077221.v3 ). <br>This dataset contains more focused and localized soybean insect images and hence ideal for classification applications. The dataset was developed by the authors under collaborative work between Indira Gandhi Krishi Vishwavidyalaya (IGKV), Raipur (CG), and DSPM IIIT Naya Raipur (CG), India
DOI: 10.6084/m9.figshare.3761562.v1641
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.3761562.v1640
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.48370/ofd/g0qggr/g81ksp
title: Golovinomyces biocellatus (Ehrenb.) V.P. Heluta F-3088.tif

description: :unav
DOI: 10.6084/m9.figshare.3761562.v1643
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.48370/ofd/g0qggr
title: Golovinomyces biocellatus (Ehrenb.) V.P. Heluta, 3088

description: Fungarium Mikromycetes
DOI: 10.6084/m9.figshare.3761562.v1642
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.3761562.v1647
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.3761562.v1646
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.13103288.v1
title: Arctic Reanalysis COSMO-CLM 1980

description: COSMO-CLM climatological data archive
DOI: 10.6084/m9.figshare.13107791.v1
title: Explaining the Variability of Community Smells: A Statistical Perspective

description: This appendix contains four folders:<br>1)Data Analyzed. The first folder contains the CSV file with all the projects analyzed. There are information about the commit range, time windows, etc.<br>2) Data Ready for R. This folder contains four CSV files ready for being analyzed in R. In particular, each file corresponds to a community smell, e.g., Black Cloud. Each file contains the 40 metrics computed and the variability of the community smells, used for building the models.<br>3) Script R. The folder contains the script used to build and run the statistical model through R Studio. Each community smell has its own script.<br>4) Results. Results obtained for each community smell
DOI: 10.6084/m9.figshare.3761562.v1650
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.3761562.v1649
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.12971054.v1
title: ERA-20C Surge Reconstruction

description: A daily maximum storm surge reconstruction for 867tide gauge locations around the globe. The surge reconstruction is based on the ERA-20C atmospheric reanalysis product
DOI: 10.6084/m9.figshare.13118081.v1
title: Preventable Deaths: PFD reports

description: This data was collected using a web scrape of the UK's Courts and Judiciary Website (https://www.judiciary.uk/subject/prevention-of-future-deaths/) as discussed in our publication here (https://www.nature.com/articles/d41586-020-02558-0), and the scrape is available here: https://github.com/georgiarichards/georgiarichards.github.io <br>We have a number of active research projects that are systematically analysing this data, including an assessment of suicides, and deaths from opioids and cardiovascular disease. <br><br>If using this data, please reach out to us at georgia.richards@kellogg.ox.ac.uk
DOI: 10.6084/m9.figshare.13125809.v2
title: Dataset with meta-data for Canada Geese field experiment

description: The purpose of the field experiment would be concentrating on looking for 'guard' or 'observer' in the Canada Geese (Branta canadensis) colonies group. my experiment design is as follows. Because that Canadian geese prefer to forage collectively in the open grassland, York University and highland garden are chose as experimental sites. Also, due to the high dynamic moving characters of Canadian geese, the requirement of observing groups of the same number of individuals seems a bit impractical. Hence, for exploring whether there is an observer role played in different sizes of groups, the comparison groups will be divided into large size group-a group containing more than 10 individuals, and a small size group- a group less than 10 individuals.Here is my dataset together with meta-data. The duration of each replicate is 20 min maximum. During the experiment, the number of individuals who were observed to have upright upper body behavior and the time ranges they maintained this behavior are noted.<br>
DOI: 10.6084/m9.figshare.13125809.v1
title: Dataset with meta-data for Canada Geese field experiment

description: The purpose of the field experiment would be concentrating on looking for 'guard' or 'observer' in the Canada Geese colonies group. my experiment design is as follows. Because that Canadian geese prefer to forage collectively in the open grassland, York University and highland garden are chose as experimental sites. Also, due to the high dynamic moving characters of Canadian geese, the requirement of observing groups of the same number of individuals seems a bit impractical. Hence, for exploring whether there is an observer role played in different sizes of groups, the comparison groups will be divided into large size group-a group containing more than 10 individuals, and a small size group- a group less than 10 individuals.Here is my dataset together with meta-data. The duration of each replicate is 20 min maximum. During the experiment, the number of individuals who were observed to have upright upper body behavior and the time ranges they maintained this behavior are noted.<br>
DOI: 10.6084/m9.figshare.13114175.v2
title: Supporting Information for the article - Distribution of microplastics in soil and freshwater environments: Global analysis and framework for transport modeling

description: File 1: Concentration of Microplastics in Soil and Water Environments.File 2: Biodegradation of Microplastics by various bacteria.
DOI: 10.6084/m9.figshare.13114175.v1
title: Supporting Information for the article - Distribution of microplastics in soil and freshwater environments: Global analysis and framework for transport modeling

description: File 1: Concentration of Microplastics in Soil and Water Environments.File 2: Biodegradation of Microplastics by various bacteria.
DOI: 10.6084/m9.figshare.13125086.v2
title: MDA-MB-231 Morphology Training and Test Sets

description: Text file format contains measurements from binary images of training and test set examples of five cancer cell migration modes observed in MDA-MB-231 cells in 3D migration. Class 0 = actin-enriched leading edge. Class 1 = Filopodia. Class 2 = Hemi-spherical blebbing. Class 3 = Lamellipodia. Class 4 = Small-bleb. Please note, classes 2 and 4 are both bleb-based migration mechanisms and do not display significant separation in shape-space. Therefore, these classes can be combined during training to describe migration dominated by contractility.Line 1 contains geometric measure titles, with the last column being the class each example is part of. Each other line is a training example. Each measure units are in micron scale, if appropriate. Binary images of training and test examples are available upon request.
DOI: 10.6084/m9.figshare.3761562.v1656
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.3761562.v1655
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.6084/m9.figshare.12400979.v2
title: Cyano_MAGs_2020

description: Several cyanobacterial species are dominant primary producers in hot spring microbial mats around the world. The present study released 58 medium and high-quality cyanobacterial MAGs which were recovered from 18 hot spring metagenomes available in the NCBI database and 4 new metagenomes from a temperature range from 32 to 75 celcius degrees and a pH range from 5.8 to 9.2. These metagenomes were distributed in 8 countries and 4 continents. The MAGs revealed a high degree of taxonomic novelty in the phylum, as also some common genomic features that distinguish thermophilic cyanobacteria from other mesophilic relatives.
DOI: 10.6084/m9.figshare.12400979.v1
title: Cyano_MAGs_2020_Prokka

description: Several cyanobacterial species are dominant primary producers in hot spring microbial mats around the world. The present study released 58 medium and high-quality cyanobacterial MAGs which were recovered from 18 hot spring metagenomes available in the NCBI database and 4 new metagenomes from a temperature range from 32 to 75 celcius degrees and a pH range from 5.8 to 9.2. These metagenomes were distributed in 8 countries and 4 continents. The MAGs revealed a high degree of taxonomic novelty in the phylum, as also some common genomic features that distinguish thermophilic cyanobacteria from other mesophilic relatives.
DOI: 10.6084/m9.figshare.13139948.v2
title: R0312_20191113a_videos

description: Rat 0312, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.13139948.v1
title: R0312_20191113a_videos

description: Rat 0312, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.13148171.v2
title: Arctic COSMO-CLM Reanalysis 2006

description: COSMO-CLM Russian Arctic climate dataset
DOI: 10.6084/m9.figshare.13148171.v1
title: Arctic COSMO-CLM Reanalysis 2006

description: COSMO-CLM Russian Arctic climate dataset
DOI: 10.6084/m9.figshare.13154480.v1
title: Type 2 Diabetes MendelVar example

description: MendelVar annotation results for Xue et al. (2018) type 2 diabetes GWAS.Detailed description of the output files in the "Results" section of MendelVar tutorial at:https://www.notion.so/mendelvar/MendelVar-tutorial-ab91d2a6acb846f2b9f2978fcd942dd5<br>
DOI: 10.6084/m9.figshare.3761562.v1660
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.