cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.3761562.v1659
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.12471461.v11
title: Knight et al. The Clostridioides difficile species problem: global phylogenomic analysis uncovers three ancient, toxigenic, genomospecies. bioRxiv 2020.09.21.307223; doi: https://doi.org/10.1101/2020.09.21.307223

description: <b>1. </b>Global MLST phylogeny (manuscript Fig. 2)<b><br></b><b><br></b><b>2. </b>BEAST tree file<b> </b>(manuscript Fig. 4)<br><b></b><b><br></b><b>3. </b>BactDating tree file (manuscript Fig. 4)<b><br></b><b>4. </b>Supplementary Data<b> </b>(Tables S1-15, Figures S1-5 and pangenome stats)<b><br></b>
DOI: 10.6084/m9.figshare.12471461.v10
title: Knight et al, (unpublished). Supplementary Data: The Clostridioides difficile species problem: global phylogenomic analysis uncovers three ancient, toxigenic, genomospecies.

description: <b>1. </b>Global MLST phylogeny (manuscript Fig. 2)<b><br></b><b><br></b><b>2. </b>BEAST tree file<b> </b>(manuscript Fig. 4)<br><b></b><b><br></b><b>3. </b>BactDating tree file (manuscript Fig. 4)<b><br></b><b>4. </b>Supplementary Data<b> </b>(Tables S1-15 and Figures S1-5)<b><br></b>
DOI: 10.6084/m9.figshare.13161980.v1
title: Phase2-Step1- EE survey responses

description: Responses of EE survey (UES-ptBR)
DOI: 10.6084/m9.figshare.13166471.v1
title: Yost Index - raw ACS files

description: These are the raw American Community Survey files compiled in support of a paper to be published in Spatial and Spatiotemporal Epidemiology. More information to be added soon.
DOI: 10.6084/m9.figshare.1228760.v5
title: galvani test data

description: Data for the unit tests of https://github.com/cechemdata/galvani<br>
DOI: 10.6084/m9.figshare.1228760.v4
title: galvani test data

description: Data for the unit tests of galvani
DOI: 10.6084/m9.figshare.3761562.v1664
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.v1663
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.12765995.v2
title: Data --- Ion Pressure Evolution (Dynamic Magnetic, SC Ei)

description: Ion Pressure Evolution (Dynamic Magnetic, with Self-Consistent Ei)
DOI: 10.6084/m9.figshare.12765995.v1
title: Data --- Ion Pressure Evolution (Dynamic Magnetic, SC Ei)

description: Ion Pressure Evolution (Dynamic Magnetic, with Self-Consistent Ei)
DOI: 10.6084/m9.figshare.3761562.v1667
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.v1666
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.11375736.v8
title: typhoon

description: The data set is a compressed file. For the windows user, the rar file can be opened using WinRAR, which can be downloaded at https://www.win-rar.com/start.html?&L=0. For the Mac user, the rar file can be opened using the Unarchiver, which can be downloaded at https://www.theunarchiver.com/. When you extract the file, you will get 15 folders to represent 15 figures in the manuscript. There are two types of data in these folders, one is mat file and the other one is txt file , both can be opened using Matlab (https://www.mathworks.com/products/matlab.html). I also have added a readme.txt file in each of the folders to help using the data.
DOI: 10.6084/m9.figshare.12174864.v4
title: Atopic dermatitis MendelVar example

description: MendelVar annotation results for sub-significant loci Paternoster et al. (2015) atopic dermatitis GWAS. Detailed description of the output files in the "Results" section of MendelVar tutorial at:https://www.notion.so/mendelvar/MendelVar-tutorial-ab91d2a6acb846f2b9f2978fcd942dd5<br><br>
DOI: 10.6084/m9.figshare.12174864.v3
title: Atopic dermatitis MendelVar example

description: MendelVar annotation results for sub-significant loci Paternoster et al. (2015) atopic dermatitis GWAS. Detailed description of the output files in the "Results" section of MendelVar tutorial at:https://www.notion.so/mendelvar/MendelVar-tutorial-ab91d2a6acb846f2b9f2978fcd942dd5<br><br>
DOI: 10.6084/m9.figshare.3761562.v1669
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.v1668
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.v1673
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.v1672
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.v53
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.v52
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.3761562.v1675
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.v1674
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.12436808.v1
title: Supplementary Tables.

description: 1. VSG and Sham pair-fed EVs protein enrichment analysis. Pathways and their representative genes in each respective group.<br>2. Ingenuity pathway analysis of the proteins that were obtained from the intestinal extracellular viscles of Sham pair-fed and Vertical Sleeve Gastrectomy mice.
DOI: 10.6084/m9.figshare.12465476.v2
title: 143 Metagenome Assembled Geneomes (MAGs) from Arctic & Atlantic surface oceans

description: 143 Metagenome Assembled Genomes (MAGs) retrieved from 12 samples taken from across the Arctic and Atlantic Oceans. 122 prokaryotic MAGs retrieved the IMG pipeline, as well as 21 eukaryotic MAGs. For Eukaryotic MAGs predicted proteins are also included.<br>
DOI: 10.6084/m9.figshare.12465476.v1
title: 140 Metagenome Assembled Geneomes (MAGs) from Arctic & Atlantic surface oceans

description: 140 Metagenome Assembled Genomes (MAGs) retrieved from 12 samples taken from across the Arctic and Atlantic Oceans. 122 prokaryotic MAGs retrieved the IMG pipeline, as well as 18 eukaryotic MAGs. For Eukaryotic MAGs predicted proteins are also included.<br>
DOI: 10.6084/m9.figshare.3761562.v1677
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.v1676
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.7392272.v1
title: Stakeholder - Digital Cultures

description: Concepts maps and content analysis generated using Leximancer for the stakeholder group, Digital Cultures, a component of thesis, the Socioethical Implications of Body Worn Computers: An Ethnographic Study. This research was conducted in the Faculty of Engineering and Information Systems, School of Computing and Information Technology (SCIT) at the University of Wollongong with research strength Innovation in Business & Social Research under Principal Supervisor Professor Katina Michael (University of Wollongong) and Associate Supervisor Dr Teemu Leinonen (Aalto University Finland). The full thesis can be accessed at https://ro.uow.edu.au/theses1/853
DOI: 10.6084/m9.figshare.12365984.v2
title: Permeability testing of drill core from basement rocks in the fault-hosted Gryphon U deposit (eastern Athabasca Basin, Canada): Insights into fluid-rock interactions related to deposit formation and redistribution

description: Dataset for Natural Resources Research manuscript by Scibek and Annesley, updated Nov 15, 2020.<br><br>The summary of permeability values at test spots in drill core, depth along drill holes, test quality notes, and lithologic units are in file:<i>Permeability data - Gryphon U - Scibek and Annesley.xlsx</i><br><br>The sorted log(m2) permeability values and their summary statistics are in file:<i>Permeability summary statistics Gryphon U deposit - Scibek and Annesley.xlsx</i><br><br>The porosity and density values of selected samples are in file:<i>Porosity and density of selected drill core samples - Gryphon U deposit - Annesley and Scibek.xlsx</i><br><br>Two examples of results and P-decay curves are given from two batches of tests on two drill holes:<i>example 1 - WR-507-D2 Aug12 test 14 to 21<br></i><i>example 2 - WR-668-D2 Aug8HS tests 46 to 57</i><br><br>Calibration tests on the same drill core samples and the same epoxy ring test spots at McGill and Kyoto universities, using two different methods and devices are in this file:<i>Calibration check of apparatus.xlsx</i><br><br>
DOI: 10.6084/m9.figshare.12365984.v1
title: Matrix permeability testing in the fault-hosted Gryphon U deposit (eastern Athabasca Basin, Canada): Insights into fluid-rock interactions related to deposit formation and redistribution

description: As a demonstration of the utility of testing permeability of rocks, in this study the matrix permeability was tested across a wide fault zone in Precambrian metasedimentary rocks at the basement-hosted Gryphon uranium deposit. It is part of the Wheeler River project by Denison Mines in Athabasca Basin, Saskatchewan, Canada.The permeability tests were done on unconfined dry uncut drill core pieces (4.7 to 6.1 cm diameter), sampled from inclined exploration drill holes. A portable nitrogen gas probe permeameter device was constructed and adapted for testing spots on whole drill core pieces. The device features a stiff aluminum metal frame and can hold a variety of drill core sizes. A pressure-decay method was used, with initial gas pressure charged to about 50 psi (pounds per square inch), equivalent to approximately 0.345 MPa, charged from an external tank, and an intermediate container.793 tests had good quality results of 900 attempted tests. In the failed (rejected) tests, a small leak occurred in about 5% of the samples, and a large leak in another 5%. In basement lithologies 666 tests were successful.<br><br>
DOI: 10.6084/m9.figshare.12152754.v2
title: Excess pressures of the terrestrial and Elysium Fossae dike systems

description: All excess pressures calculated for the terrestrial and Martian dike data sets presented in the work 'Subsurface Geometry and Emplacement Conditions of a Giant Dike System in Elysium Fossae, Mars', as described in Section 3.3.
DOI: 10.6084/m9.figshare.12152754.v1
title: Excess pressures of the terrestrial and Elysium Fossae dike systems

description: All excess pressures calculated for the terrestrial and Martian dike data sets presented in the work 'Subsurface Geometry and Emplacement Conditions of a Giant Dike System in Elysium Fossae, Mars', as described in Section 3.3.
DOI: 10.6084/m9.figshare.3761562.v1683
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.v1682
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.v55
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.v54
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.12380021.v1
title: Image Library: Physalis hunickenii Deanna, Wilf & Gandolfo

description: Full-resolution image library of <i>Physalis hunickenii</i> Deanna, Wilf & Gandolfo published in this primary article:<br>Deanna R, P Wilf, MA Gandolfo. 2020. New physaloid fruit-fossil species from early Eocene South America. American Journal of Botany XX doi XX.<br><br>Filenames are composed as:Field_number repository_number (time stamp).tif<br>Please always cite specimens by the repository number as given in the filename, which here is either:<b>MPEF-Pb 6443a</b> or <b>MPEF-Pb 6443b</b>.<br>Please refer to the primary paper for all details and cite both the primary paper and this Figshare archive if you use these images.<br>
DOI: 10.6084/m9.figshare.11521389.v1
title: datasets for geospatial data matching

description: Run main.m in Matlab to produce matching resultsdata_BJ and data_HK are two datasets for testing the geospatial data matching methods.The objects are represented by their centroids and corresponding vertices.<br><br>