cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.16499409.v1
title: The influence of connectivity on the functional role of a natural and re-constructed side-arm in the lower Waikato River

description: A comparison of a natural and a reconstructed side-arm during different phases of hydrological connectivity in the lower Waikato River. This data set investigates the physico-chemical variables in order to compare each side arm with the river, and any occurring patterns within the side-arm longitudinally.<br><br><b>Quality control:</b> Accuracy; Calibration; Model; Sensor height (m)<br><br><b>Type of waterbody:</b> River<br><br><b>Variables:</b> Conductivity; Dissolved Oxygen Concentration; Water Temperature<br><br><b>Start date:</b> 2009-11-01<br><br><b>End date:</b> 2010-10-01<br><br><b>Region:</b> Waikato<br><br><b>River:</b> Waikato River<br><br>This dataset was originally hosted in the LERNZdb freshwater data repository that was developed as part of the Lake Ecosystem Restoration New Zealand (LERNZ) project run by the Environmental Research Institute at the University of Waikato, New Zealand. <br><br>In retrieving LERNZdb material you agree that you rely on the data at your own risk; the University of Waikato offers no warranty or representation that the data is fit for any particular purpose, or free from defects, and will not be liable for any losses or damages whatsoever including any indirect, special, incidental or consequential damages incurred by you arising out of the use of the database or in reliance on the data retrieved. You agree that data is not of a kind ordinarily supplied for personal or domestic purposes, and that the Consumer Guarantees Act 1993 does not apply.
DOI: 10.25505/fiz.icsd.cc2483g0
title: CSD 1974001: Experimental Crystal Structure Determination

description: Related Article: Zhuang Li, Youquan Liu, Shengzi Zhang, Wenhao Xing, Wenlong Yin, Zheshuai Lin, Jiyong Yao, Yicheng Wu|2020|Inorg.Chem.|59|7614|doi:10.1021/acs.inorgchem.0c00490
DOI: 10.6084/m9.figshare.16458696.v1
title: Mangatawhiri Stream (2004)

description: Mangatawhiri stream electro-fishing survey (2004).<br><br><b>Type of waterbody:</b> River<br><br><b>Variables:</b> Area Fished; Distance fished; EF % range; EF Range; EF current; EF pulse rate; Fish Species Counts; Specific Conductance; Time fished; Water Temperature<br><br><b>Start date:</b> 2004-12-09<br><br><b>End date:</b> 2004-12-09<br><br><b>Region:</b> Waikato<br><br><b>River:</b> Mangatawhiri River<br><br>This dataset was originally hosted in the LERNZdb freshwater data repository that was developed as part of the Lake Ecosystem Restoration New Zealand (LERNZ) project run by the Environmental Research Institute at the University of Waikato, New Zealand. <br><br>In retrieving LERNZdb material you agree that you rely on the data at your own risk; the University of Waikato offers no warranty or representation that the data is fit for any particular purpose, or free from defects, and will not be liable for any losses or damages whatsoever including any indirect, special, incidental or consequential damages incurred by you arising out of the use of the database or in reliance on the data retrieved. You agree that data is not of a kind ordinarily supplied for personal or domestic purposes, and that the Consumer Guarantees Act 1993 does not apply.
DOI: 10.5517/ccdc.csd.cc248jcb
title: CCDC 1974401: Experimental Crystal Structure Determination

description: Related Article: J.C. González Espiet, J.A. Cintrón Cruz, D.M. Piñero Cruz|2020|Acta Crystallogr.,Sect.E:Cryst.Commun.|76|231|doi:10.1107/S2056989020000365
description: Related Article: E. Bernhardt, R. Herbst-Irmer|2020|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|76|231|doi:10.1107/S205322961901725X
DOI: 10.5517/ccdc.csd.cc245tqw
title: CCDC 1971808: Experimental Crystal Structure Determination

description: Related Article: J.C. González Espiet, J.A. Cintrón Cruz, D.M. Piñero Cruz|2020|Acta Crystallogr.,Sect.E:Cryst.Commun.|76|231|doi:10.1107/S2056989020000365
description: Related Article: E. Bernhardt, R. Herbst-Irmer|2020|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|76|231|doi:10.1107/S205322961901725X
DOI: 10.25505/fiz.icsd.cc245w4c
title: CSD 1971852: Experimental Crystal Structure Determination

description: Related Article: María Alejandra Gómez Torres, Gilles H. Gauthier, Anna M. Kaczmarek, Marielle Huvé, Pascal Roussel, Valérie Dupray, Lina Yuan, Anastasiya Zadoya, Marie Colmont|2020|Inorg.Chem.|59|5929|doi:10.1021/acs.inorgchem.9b03689
DOI: 10.5517/ccdc.csd.cc245trx
title: CCDC 1971809: Experimental Crystal Structure Determination

description: Related Article: J.C. González Espiet, J.A. Cintrón Cruz, D.M. Piñero Cruz|2020|Acta Crystallogr.,Sect.E:Cryst.Commun.|76|231|doi:10.1107/S2056989020000365
description: Related Article: E. Bernhardt, R. Herbst-Irmer|2020|Acta Crystallogr.,Sect.C:Cryst.Struct.Chem.|76|231|doi:10.1107/S205322961901725X
DOI: 10.6084/m9.figshare.16464531.v1
title: 2006-12-19 11-39 Lake Okareka

description: A CTD cast on Lake Okareka<br><br><b>Quality control:</b> Calibration; Model; Sensor height (m)<br><br><b>Type of waterbody:</b> Lake<br><br><b>Variables:</b> Beam Transmission; Chlorophyll Fluorescence; Conductivity; Dissolved Oxygen Concentration; Dissolved Oxygen Saturation; Photosynthetically Active Radiation; Salinity; Specific Conductance; Water Temperature<br><br><b>Start date:</b> 2006-12-19<br><br><b>End date:</b> 2006-12-19<br><br><b>Lake:</b> Lake Okareka<br><br><b>Region:</b> Bay of Plenty<br><br>This dataset was originally hosted in the LERNZdb freshwater data repository that was developed as part of the Lake Ecosystem Restoration New Zealand (LERNZ) project run by the Environmental Research Institute at the University of Waikato, New Zealand. <br><br>In retrieving LERNZdb material you agree that you rely on the data at your own risk; the University of Waikato offers no warranty or representation that the data is fit for any particular purpose, or free from defects, and will not be liable for any losses or damages whatsoever including any indirect, special, incidental or consequential damages incurred by you arising out of the use of the database or in reliance on the data retrieved. You agree that data is not of a kind ordinarily supplied for personal or domestic purposes, and that the Consumer Guarantees Act 1993 does not apply.
DOI: 10.25505/fiz.icsd.cc248lnp
title: CSD 1974472: Experimental Crystal Structure Determination

description: Related Article: Bei Zhu, Jianhua Jiang, Tianyu Zhu, Haoming Yang, Yong Jin, Minfeng Lü|2020|Dalton Trans.|49|9751|doi:10.1039/D0DT00037J
DOI: 10.25505/fiz.icsd.cc248mxz
title: CSD 1974511: Experimental Crystal Structure Determination

description: Related Article: Mengsi Zhang, Yujie Song, Zhiying Zhao, Jinyang Li, Wanwan Zhang, Yaxin Xie, Xing Huang, Xiaoying Huang, Zhangzhen He|2020|Inorg.Chem.|59|8054|doi:10.1021/acs.inorgchem.0c00316
DOI: 10.6084/m9.figshare.16469505.v1
title: 2007-04-16 11-23 Lake Ngaroto

description: A CTD cast on Lake Ngaroto<br><br><b>Quality control:</b> Calibration; Model; Sensor height (m)<br><br><b>Type of waterbody:</b> Lake<br><br><b>Variables:</b> Beam Transmission; Chlorophyll Fluorescence; Conductivity; Dissolved Oxygen Concentration; Dissolved Oxygen Saturation; Photosynthetically Active Radiation; Salinity; Specific Conductance; Water Temperature<br><br><b>Start date:</b> 2007-04-16<br><br><b>End date:</b> 2007-04-16<br><br><b>Lake:</b> Lake Ngaroto<br><br><b>Region:</b> Waikato<br><br>This dataset was originally hosted in the LERNZdb freshwater data repository that was developed as part of the Lake Ecosystem Restoration New Zealand (LERNZ) project run by the Environmental Research Institute at the University of Waikato, New Zealand. <br><br>In retrieving LERNZdb material you agree that you rely on the data at your own risk; the University of Waikato offers no warranty or representation that the data is fit for any particular purpose, or free from defects, and will not be liable for any losses or damages whatsoever including any indirect, special, incidental or consequential damages incurred by you arising out of the use of the database or in reliance on the data retrieved. You agree that data is not of a kind ordinarily supplied for personal or domestic purposes, and that the Consumer Guarantees Act 1993 does not apply.
DOI: 10.6084/m9.figshare.13485897.v2
title: Agrarian capital accumulation in Uruguay, 1955-2019

description: Base de datos con variables centrales de la acumulación de capital en el agro uruguayo, 1955-2019<br>
DOI: 10.6084/m9.figshare.13485897.v1
title: Acumulación de capital agro uruguayo, 1955-2019

description: Base de datos con variables centrales de la acumulación de capital en el agro uruguayo, 1955-2019<br>
DOI: 10.6084/m9.figshare.14995314.v19
title: Effect of behavioural sampling methods on local and global social network metrics: A case-study of three macaque species

description: Data set and R-codes
DOI: 10.6084/m9.figshare.14995314.v18
title: Effect of behavioural sampling methods on local and global social network metrics: A case-study of three macaque species

description: Data set and R-codes
DOI: 10.5517/ccdc.csd.cc248ntx
title: CCDC 1974539: Experimental Crystal Structure Determination

description: Related Article: Le Zhou, Ming Bai, Qing-Jun He, Zi-Lin Hou, Li-Wei Lu, Jie Wang, Xiao-Xiao Huang, Bin Lin, Shao-Jiang Song|2022|New J.Chem.|46|2423|doi:10.1039/D1NJ03800A
description: Related Article: Le Zhou, Qingjun He, Zilin Hou, Liwei Lu, Jie Wang, Xiaoxiao Huang, Bin Lin, Shaojiang Song|2021|CSD Communication|||
DOI: 10.6084/m9.figshare.14995314.v21
title: Effect of behavioural sampling methods on local and global social network metrics: A case-study of three macaque species

description: Data set and R-codes
DOI: 10.6084/m9.figshare.14995314.v20
title: Effect of behavioural sampling methods on local and global social network metrics: A case-study of three macaque species

description: Data set and R-codes
DOI: 10.6084/m9.figshare.3761562.v1965
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.v1964
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.15167709.v3
title: Data for IOBM/IOD experiments using WACCM4

description: For more detailed information, please see readme.txt
DOI: 10.6084/m9.figshare.16530771.v3
title: Amaranthus dubius plastome matrix and tree

description: Amaranthus plastomes matrix and ML phylogenetic tree
DOI: 10.6084/m9.figshare.16530771.v2
title: Amaranthus dubius plastome matrix and tree

description: Amaranthus plastomes matrix and ML phylogenetic tree
DOI: 10.6084/m9.figshare.13049780.v3
title: Single-cell DNA and RNA sequencing reveals the dynamics of intra-tumor heterogeneity in a colorectal cancer model

description: Single Cell Transcripts T1<br>Data List:https://figshare.com/articles/dataset/Single_Cell/14518056<br>
DOI: 10.6084/m9.figshare.13049780.v2
title: Single-cell DNA and RNA sequencing reveals the dynamics of intra-tumor heterogeneity in a colorectal cancer model

description: Single Cell Transcripts T1<br>Data List:https://figshare.com/articles/dataset/Single_Cell/14518056<br>
DOI: 10.6084/m9.figshare.13060247.v2
title: Single-cell DNA and RNA sequencing reveals the dynamics of intra-tumor heterogeneity in a colorectal cancer model

description: Single Cell Transcripts T2<br>Data List:https://figshare.com/articles/dataset/Single_Cell/14518056<br>
DOI: 10.6084/m9.figshare.3761562.v1968
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.v1967
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.16543968.v1
title: Estimated decline in global earthworm population size caused by pesticide residue in soil

description: This package includes the calculated LC<sub>50,mix</sub> in [mg/kg-soil] resulting from the soil residue of up to 20 active ingredients of pesticides used in 9 cropping systems and the percent decline in earthworm population size in these cropping systesm. The 9 cropping systems under consideration are: corn, soybean, wheat, cotton, vegetables and fruits, rice, orchards and grapes, alfalfa, and other.
DOI: 10.6084/m9.figshare.16548078.v1
title: Methodology for Designing Humanitarian Supply Chains: Distribution of COVID-19 Vaccines in Mexico

description: A sentiment analysis of more than 900 newspaper articles is conducted to determine the population perception of the government strategy for vaccine distribution in Mexico
DOI: 10.6084/m9.figshare.16550109.v1
title: Readiness Index_Dataset.xlsx

description: As global changes continue, the repercussions in Africa remain profound. This is reflected notably in food and water crises across Africa. This work examines the readiness of Africa to climate change adaptation through a newly developed readiness Index (<i>ClimAdaptCap</i> Index). Readiness for climate change adaptation is driven by the intensity of climate forcing and adaptive capacity. The historical climate score data of precipitation and temperature for the period 1991-2016 were used in this investigation. The latter were culled from the World Bank Climate Portal. The historical adaptive capacity score data included proxies such as poverty and literacy rates for the period 1991-2016. These were collected from the World Bank and Macrotrends. These climate data were normalized using the normalization function to enhance interpretation, comparison/fusion into the Index. Missing poverty and literacy rate data were estimated by linear interpolation od the poverty and literacy rate data. The <i>ClimAdaptCap</i> Index was developed to compute readiness. The results show that North and Southern Africa are the readiest for climate change adaptation. West Africa is the least ready while Middle and East Africa are in the middle. Consistent is that readiness has a positive correlation with literacy rates and an inverse one with poverty rates. The developed readiness Index adequately simulates readiness to climate change adaptation in Africa and is complementary to previous frameworks of adaptation readiness.
DOI: 10.6084/m9.figshare.3761562.v1970
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.v1969
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.14811255.v2
title: SvelocityModel.xyz

description: Shear-wave velocity model in central Japan island estimated by adjoint waveform tomography.
DOI: 10.6084/m9.figshare.14811255.v1
title: SvelocityModel.xyz

description: Shear-wave velocity model in central Japan island estimated by adjoint waveform tomography.
DOI: 10.6084/m9.figshare.12130980.v110
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, c/o Dept Zoology, University of 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.v109
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, c/o Dept Zoology, University of Oxford) on behalf of the MOOD H2020 project. Data will be periodically updated. Additional maps can be obtained on request to the authors.
DOI: 10.48370/ofd/byoqer/pogkgo
title: Golovinomyces montagnei U. Braun F-0433.tif

description: :unav
DOI: 10.6084/m9.figshare.14699736.v2
title: NETosis good example

description: This is an example of a successful NETosis assay. In this experiment we were comparing male and female, 5-months-old C57BL/6 mice.
DOI: 10.48370/ofd/byoqer
title: Golovinomyces montagnei U. Braun, 433

description: Fungarium Mikromycetes
DOI: 10.6084/m9.figshare.14699736.v1
title: NETosis good example

description: This is an example of a successful NETosis assay. In this experiment we were comparing VCD injected mice with vehicle injected mice, 100 days after injection. A sample sheet is included to distinguish the groups.
DOI: 10.6084/m9.figshare.6741425.v11
title: COCI N-Triples dataset of all the citation data

description: This dataset contains all the citation data (in N-Triples format) included in COCI, released on 3 September 2021. In particular, any citation in the dataset, defined as an individual of the class <i>cito:Citation</i>, includes the following information:<b>[citation IRI]</b> the Open Citation Identifier (OCI) for the citation, defined in the final part of the URL identifying the citation (https://w3id.org/oc/index/coci/ci/[OCI]);<b>[property "cito:hasCitingEntity"]</b> the citing entity identified by its DOI URL (http://dx.doi.org/[DOI]);<b>[property "cito:hasCitedEntity"]</b> the cited entity identified by its DOI URL (http://dx.doi.org/[DOI]);<b>[property "cito:hasCitationCreationDate"]</b> the creation date of the citation (i.e. the publication date of the citing entity);<b>[property "cito:hasCitationTimeSpan"]</b> the time span of the citation (i.e. the interval between the publication date of the cited entity and the publication date of the citing entity);<b>[type "cito:JournalSelfCitation"]</b> it records whether the citation is a journal self-citations (i.e. the citing and the cited entities are published in the same journal);<b>[type "cito:AuthorSelfCitation"]</b> it records whether the citation is an author self-citation (i.e. the citing and the cited entities have at least one author in common).This version of the dataset contains:<br>1,186,958,898 citations;69,074,291 bibliographic resources.The size of the zipped archive is 57.9 GB, while the size of the unzipped N-Triples file is 1.28 TB.<br>Additional information about COCI can be retrieved in the official webpage.<br>