cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.6205814
title: NumDB-dataset

description: NumDB benchmark: set of tables originally extracted from DBpedia, from which different value samples have been selected and various degrees of errors have been added in order to simulate actual tables on the Web.The dataset has been created for Kacprzak, E., Giménez-García, J. M., Piscopo, A., Koesten, L., Ibáñez, L. D., Tennison, J., & Simperl, E. (2018, November). Making Sense of Numerical Data-Semantic Labelling of Web Tables. In <i>European Knowledge Acquisition Workshop</i> (pp. 163-178). Springer, Cham.A description of the data generation process is in the paper.<br>
DOI: 10.6084/m9.figshare.6205814.v1
title: numdb_0105.zip

description: NumDB benchmark: set of table originally extracted from DBpedia, from which different value samples have been selected and various degrees of errors have been added, in order to simulate actual tables on the Web.The dataset has been created for Kacprzak et al. (2018, under review) <i>Making sense of numerical datasets - semantic labelling of Web tables</i>. Semantics, 2018<br>
DOI: 10.6084/m9.figshare.6205814.v2
title: numdb-dataset.zip

description: NumDB benchmark: set of table originally extracted from DBpedia, from which different value samples have been selected and various degrees of errors have been added, in order to simulate actual tables on the Web.The dataset has been created for Kacprzak et al. (2018, under review) <i>Making sense of numerical datasets - semantic labelling of Web tables</i>. i-Semantics, 2018, where the creation process is also described.<br>
DOI: 10.6084/m9.figshare.6205814.v3
title: numdb-dataset

description: NumDB benchmark: set of table originally extracted from DBpedia, from which different value samples have been selected and various degrees of errors have been added, in order to simulate actual tables on the Web.The dataset has been created for Kacprzak et al. (2018, under review) <i>Making sense of numerical datasets - semantic labelling of Web tables</i>. i-Semantics, 2018, where the creation process is also described.<br>
DOI: 10.6084/m9.figshare.6205769
title: paris-geo

description: Paris listings
DOI: 10.6084/m9.figshare.6205769.v2
title: paris-geo

description: Paris listings
DOI: 10.6084/m9.figshare.6205769.v1
title: paris-listings_detail.csv

description: Paris listings
DOI: 10.6084/m9.figshare.6205754
title: TgPH domain as a PtdIns(3)P probe

description: Image flies associated with TgPH1 PLOS ONE paper<br>
DOI: 10.6084/m9.figshare.6205754.v1
title: TgPH domain as a PtdIns(3)P probe

description: Image flies associated with TgPH1 PLOS ONE paper<br>
DOI: 10.6084/m9.figshare.6205607
title: Early Cenozoic thickening and reworking of the eastern Gangdese arc, south Tibet: constraints from the Oligocene granitoids

description: Table 1: LA–ICP–MS U–Pb zircon data.
DOI: 10.6084/m9.figshare.6205607.v1
title: Early Cenozoic thickening and reworking of the eastern Gangdese arc, south Tibet: constraints from the Oligocene granitoids

description: Table 1: LA–ICP–MS U–Pb zircon data.
DOI: 10.6084/m9.figshare.6205604
title: Early Cenozoic thickening and reworking of the eastern Gangdese arc, south Tibet: constraints from the Oligocene granitoids

description: Table 2 shows LA–MC–ICP–MS zircon Lu–Hf isotope data.
DOI: 10.6084/m9.figshare.6205376
title: Charity Open Access Fund (COAF) open access spend and compliance monitoring: 2016-17

description: This dataset contains details of the 2016-2017 Charity Open Access Fund (COAF) open access spend. During this period the members of COAF were Wellcome Trust, Arthritis Research UK, British Heart Foundation, Bloodwise, Cancer Research UK and Parkinson’s UK. In addition to reporting spend, the data has been analysed through our “compliance monitoring” tool (developed for us by Cottage Labs) to help us determine programmatically whether the paper is in the Europe PMC repository and what licence (if any) is attached to the article. The dataset includes information when an article processing charge (APC) was levied to the COAF fund. If an author has self-archived a paper, this information is not included in this dataset. Equally, data are not included in cases where a researcher (based at an institution not in receipt of a COAF block grant) received a supplement to their grant to cover OA publishing costs. We hope that this data will be of use to help better understand the cost of OA publishing. If through use of this data you identify errors or believe the status of an article to be incorrect please notify Hannah Hope (h.hope[at]welcome.ac.uk). We will endeavour to investigate these issues and correct errors where identified. Corrections to the dataset will be published as a new version of the dataset along with a note explaining the changes.<br>Version 2: 02/05/18 uploaded corrected dataset, see "Summary of change" document for more details
DOI: 10.6084/m9.figshare.6205376.v2
title: Charity Open Access Fund (COAF) open access spend and compliance monitoring: 2016-17

description: This dataset contains details of the 2016-2017 Charity Open Access Fund (COAF) open access spend. During this period the members of COAF were Wellcome Trust, Arthritis Research UK, British Heart Foundation, Bloodwise, Cancer Research UK and Parkinson’s UK. In addition to reporting spend, the data has been analysed through our “compliance monitoring” tool (developed for us by Cottage Labs) to help us determine programmatically whether the paper is in the Europe PMC repository and what licence (if any) is attached to the article. The dataset includes information when an article processing charge (APC) was levied to the COAF fund. If an author has self-archived a paper, this information is not included in this dataset. Equally, data are not included in cases where a researcher (based at an institution not in receipt of a COAF block grant) received a supplement to their grant to cover OA publishing costs. We hope that this data will be of use to help better understand the cost of OA publishing. If through use of this data you identify errors or believe the status of an article to be incorrect please notify Hannah Hope (h.hope[at]welcome.ac.uk). We will endeavour to investigate these issues and correct errors where identified. Corrections to the dataset will be published as a new version of the dataset along with a note explaining the changes.<br>Version 2: 02/05/18 uploaded corrected dataset, see "Summary of change" document for more details
DOI: 10.6084/m9.figshare.6205376.v1
title: Charity Open Access Fund (COAF) open access spend and compliance monitoring: 2016-17

description: This dataset contains details of the 2016-2017 Charity Open Access Fund (COAF) open access spend. During this period the members of COAF were Wellcome Trust, Arthritis Research UK, British Heart Foundation, Bloodwise, Cancer Research UK and Parkinson’s UK. In addition to reporting spend, the data has been analysed through our “compliance monitoring” tool (developed for us by Cottage Labs) to help us determine programmatically whether the paper is in the Europe PMC repository and what licence (if any) is attached to the article. The dataset includes information when an article processing charge (APC) was levied to the COAF fund. If an author has self-archived a paper, this information is not included in this dataset. Equally, data are not included in cases where a researcher (based at an institution not in receipt of a COAF block grant) received a supplement to their grant to cover OA publishing costs. We hope that this data will be of use to help better understand the cost of OA publishing. If through use of this data you identify errors or believe the status of an article to be incorrect please notify Hannah Hope (h.hope[at]welcome.ac.uk). We will endeavour to investigate these issues and correct errors where identified. Corrections to the dataset will be published as a new version of the dataset along with a note explaining the changes.
DOI: 10.6084/m9.figshare.6205256
title: Supplementary_Information.pdf

description: Supplementary figures and tables for Getz et al., Parallel Evolution of Key Genomic Features and Cellular Bioenergetics Across the Marine Radiation of a Bacterial Phylum, bioRxiv 307454; doi: https://doi.org/10.1101/307454 <br>
DOI: 10.6084/m9.figshare.6205256.v1
title: Supplementary_Information.pdf

description: Supplementary figures and tables for Getz et al., Parallel Evolution of Key Genomic Features and Cellular Bioenergetics Across the Marine Radiation of a Bacterial Phylum, bioRxiv 307454; doi: https://doi.org/10.1101/307454 <br>
DOI: 10.6084/m9.figshare.6205235
title: Dataset_S1.xlsx

description: Dataset S1 for Getz et al., Parallel Evolution of Key Genomic Features and Cellular Bioenergetics Across the Marine Radiation of a Bacterial Phylum, bioRxiv 307454; doi: https://doi.org/10.1101/307454.
DOI: 10.6084/m9.figshare.6205124
title: TWOPD-G-KIN.DATA.ZIP

description: Supplementary data associated to the paper:<br>"Chemical Heterogeneities in the Mantle: Progress Towards a Large Scale Quantitative Description"<br>by Max Tirone<br>(Solid Earth, se-2018-67)
DOI: 10.6084/m9.figshare.6205124.v1
title: TWOPD-G-KIN.DATA.ZIP

description: Supplementary data associated to the paper:<br>"Chemical Heterogeneities in the Mantle: Progress Towards a Large Scale Quantitative Description"<br>by Max Tirone<br>(Solid Earth, se-2018-67)
DOI: 10.6084/m9.figshare.6205118
title: Cancer Dependency Map, CRISPR Avana dataset 18Q2 (Avana_public_18Q2)

description: Avana_public_18Q2 contains the results of screening 436 cancer cell lines with the Avana CRISPR-Cas9 genome-scale knockout library generated as part of the Broad Institute's Cancer Dependency Map project.<br>As our screening efforts continue, we will be releasing additional cancer dependency data on a quarterly basis for unrestricted use. For the latest datasets available, further analyses, and to subscribe to our mailing list visit https://depmap.org.<br>Descriptions of the experimental methods and the CERES algorithm are published in http://dx.doi.org/10.1038/ng.3984. Some cell lines were processed using copy number data based on the Sanger Institute whole exome sequencing data (COSMIC: http://cancer.sanger.ac.uk/cell_lines, EGA accession number: EGAD00001001039) reprocessed using CCLE pipelines. <br>Avana_public_18Q2 includes the results of 46 lines not previously made public, while the previously published line HS294T has been dropped for fingerprinting failure. <br>
DOI: 10.6084/m9.figshare.6204995
title: Acoustic televiewer amplitude data for porosity estimation with application to porewater conversion

description: Physical properties determined from core samples and predicted from geophysical logs using linear regression. Each individual geophysical log was regressed against the core derived values. In addition, multiple linear regression was performed between the core derived values and the gamma-gamma, neutron and acoustic televiewer amplitude logs.
DOI: 10.6084/m9.figshare.6204995.v1
title: Acoustic televiewer amplitude data for porosity estimation with application to porewater conversion

description: Physical properties determined from core samples and predicted from geophysical logs using linear regression. Each individual geophysical log was regressed against the core derived values. In addition, multiple linear regression was performed between the core derived values and the gamma-gamma, neutron and acoustic televiewer amplitude logs.
DOI: 10.6084/m9.figshare.6204920
title: MSA teleost PXR sequences, based on LBD

description: Based on their ligand binding domains, sequences identified in the bioinformatic searches of 76 teleost genome assemblies, using zebrafish, medaka, and tetraodon Pxr as query, were aligned with annotated or cloned teleost Pxr (Nr1i1), Vdr (Nr1i2), retinoic acid receptor (RARγ, Nr1b3) and Rev-ERbα(Nr1d1), using Clustal Omega v1.2.2 with default parameters. Due to incomplete sequences in the LBD, <i>Cyttopsis roseus</i>, <i>Neoniphon samara</i>, <i>Lesueurigobius cf.</i>, and <i>Holocentrus rupus</i>was excluded from the alignment. <br>
DOI: 10.6084/m9.figshare.6204920.v2
title: MSA teleost PXR sequences, based on LBD

description: Based on their ligand binding domains, sequences identified in the bioinformatic searches of 76 teleost genome assemblies, using zebrafish, medaka, and tetraodon Pxr as query, were aligned with annotated or cloned teleost Pxr (Nr1i1), Vdr (Nr1i2), retinoic acid receptor (RARγ, Nr1b3) and Rev-ERbα(Nr1d1), using Clustal Omega v1.2.2 with default parameters. Due to incomplete sequences in the LBD, <i>Cyttopsis roseus</i>, <i>Neoniphon samara</i>, <i>Lesueurigobius cf.</i>, and <i>Holocentrus rupus</i>was excluded from the alignment. <br>
DOI: 10.6084/m9.figshare.6204920.v1
title: MSA teleost PXR sequences, based on LBD

description: Searching 76 teleost genomes using zebrafish Pxr as query, the following sequences were extracted and translated to amino acids sequences, and aligned to published or cloned teleost Nr1i and Nr1d sequences.<br>MSA performed in ClustalX 2.1, using default parametres.
DOI: 10.6084/m9.figshare.6204812
title: Data supporting Sheppard et al. (2018) Current Biology

description: These data files support the following publication:<br>Catherine E. Sheppard<sup>†</sup>, Harry H. Marshall<sup>†</sup>, Richard Inger, Faye J. Thompson, Emma I. K. Vitikainen, Sam Barker, Hazel J. Nichols, David A. Wells, Robbie A. McDonald, Michael A. Cant* (2018). Decoupling of genetic and cultural inheritance in a wild mammal. <i>Current Biology.</i><i><br></i><sup>† </sup>These authors contributed equally* Corresponding author<br>Please see read me file for more information
DOI: 10.6084/m9.figshare.6204812.v1
title: Data supporting Sheppard et al. (in press) Current Biology

description: These data files support the following publication:<br>Catherine E. Sheppard<sup>†</sup>, Harry H. Marshall<sup>†</sup>, Richard Inger, Faye J. Thompson, Emma I. K. Vitikainen, Sam Barker, Hazel J. Nichols, David A. Wells, Robbie A. McDonald, Michael A. Cant (in press). Decoupling of genetic and cultural inheritance in a wild mammal. <i>Current Biology.</i><i><br></i><sup>† </sup>These authors contributed equally* Corresponding author<br>Please see read me file for more information
DOI: 10.6084/m9.figshare.6204809
title: Biological market effects predict cleaner fish strategic sophistication

description: Here, we provide evidence that intraspecific variation in the strategic sophistication of “cleaner” fish Labroides dimidiatus in laboratory experiments correlates with small scale / between-years variation in their intra- and interspecific social environment.
DOI: 10.6084/m9.figshare.6204707
title: ResearchGate: Investigating Altmetric Bibliometric Relationships for Environmental Science Researchers at Unisa

description: <b>Abstract</b> The purpose of this paper is to establish the relationships between the altmetrics derived from ResearchGate and bibliometrics derived from Web of Science, Scopus and Google Scholar in order to establish whether the altmetrics indicators influence bibliometric indicators. The investigation forms part of a longitudinal e-visibility study investigating the e-visibility of the Environmental Science researchers at the University of South Africa during December 2014 and December 2016. Using SPSS software, the bibliometric indicator data sourced from Web of Science, Scopus and Google Scholar, and altmetric indicator data sourced from ResearchGate, were analysed to determine the Spearman’s rank correlations between for the Environmental Science researchers. The results indicated a strong positive correlation between the bibliometric indicators and the altmetric indicators. This study finds that ResearchGate altmetric indicators influence the bibliometric indicators positively and the findings recommend ResearchGate to be utilised as an academic social networking tool to influence the Environmental Science researcher’s citations positively at Unisa.<br>
DOI: 10.6084/m9.figshare.6204707.v1
title: ResearchGate: Investigating Altmetric Bibliometric Relationships for Environmental Science Researchers at Unisa

description: <b>Abstract</b> The purpose of this paper is to establish the relationships between the altmetrics derived from ResearchGate and bibliometrics derived from Web of Science, Scopus and Google Scholar in order to establish whether the altmetrics indicators influence bibliometric indicators. The investigation forms part of a longitudinal e-visibility study investigating the e-visibility of the Environmental Science researchers at the University of South Africa during December 2014 and December 2016. Using SPSS software, the bibliometric indicator data sourced from Web of Science, Scopus and Google Scholar, and altmetric indicator data sourced from ResearchGate, were analysed to determine the Spearman’s rank correlations between for the Environmental Science researchers. The results indicated a strong positive correlation between the bibliometric indicators and the altmetric indicators. This study finds that ResearchGate altmetric indicators influence the bibliometric indicators positively and the findings recommend ResearchGate to be utilised as an academic social networking tool to influence the Environmental Science researcher’s citations positively at Unisa.<br>
DOI: 10.6084/m9.figshare.6204137
title: Additional file 2: of Green monomeric photosensitizing fluorescent protein for photo-inducible protein inactivation and cell ablation

description: Numeric data for Fig. 2b, eâ g, Additional file 1: Figures S5, S6 (XLS 71Â kb)
DOI: 10.6084/m9.figshare.6204137.v1
title: Additional file 2: of Green monomeric photosensitizing fluorescent protein for photo-inducible protein inactivation and cell ablation

description: Numeric data for Fig. 2b, eâ g, Additional file 1: Figures S5, S6 (XLS 71Â kb)
DOI: 10.6084/m9.figshare.6204047
title: Additional file 3: of Investigation of the influence of high glucose on molecular and genetic responses: an in vitro study using a human intestine model

description: Table S3. The list of the significantly upregulated genes under high glucose treatment condition (297 genes). (XLSX 85 kb)
DOI: 10.6084/m9.figshare.6204047.v1
title: Additional file 3: of Investigation of the influence of high glucose on molecular and genetic responses: an in vitro study using a human intestine model

description: Table S3. The list of the significantly upregulated genes under high glucose treatment condition (297 genes). (XLSX 85 kb)
DOI: 10.6084/m9.figshare.6204041
title: Additional file 2: of Investigation of the influence of high glucose on molecular and genetic responses: an in vitro study using a human intestine model

description: Table S2. The list of the significantly downregulated genes under high glucose treatment condition (382 genes). (XLSX 89 kb)
DOI: 10.6084/m9.figshare.6204041.v1
title: Additional file 2: of Investigation of the influence of high glucose on molecular and genetic responses: an in vitro study using a human intestine model

description: Table S2. The list of the significantly downregulated genes under high glucose treatment condition (382 genes). (XLSX 89 kb)
DOI: 10.6084/m9.figshare.6203993
title: A continental-scale assessment of fuel loads and consumption by wildfire

description: Samples of litter, grass, shrub and woody fuels were collected from a total of 276 sites across Australia. Most were paired recently burnt and long unburnt sites, allowing estimates of fuel consumption by wildfire across a climatic gradient.<br><br>Subsets of these data have been used in the publications below, which contain more details of the methods and applications.<br>
DOI: 10.6084/m9.figshare.6203993.v1
title: A continental-scale assessment of fuel loads and consumption by wildfire

description: Samples of litter, grass, shrub and woody fuels were collected from a total of 276 sites across Australia. Most were paired recently burnt and long unburnt sites, allowing estimates of fuel consumption by wildfire across a climatic gradient.<br>
DOI: 10.6084/m9.figshare.6203900
title: Figshare_PD study_Fig and Table.docx

description: Fig 1. Schematic illustration of the two-step test. Participants estimated the two-step distance forward with maximum effort and indicated the distance using a laser pointer. After the estimation, the actual distance was measured. <br>Fig 2. Scattergrams of the estimation error distance, and H&Y stage (upper left), and UPDRS part II (upper right) and III (lower)<br><br>Table 1: Demographic clinical details and results of two-step test of control groups (non-overestimation and overestimation) and patients with PD groups (non-overestimation and overestimation) (mean ± <i>SD</i>) <br><br>
DOI: 10.6084/m9.figshare.6203678.v1
title: Distribution, climatic relationships, and status of American pikas (<i>Ochotona princeps</i>) in the Great Basin, USA

description: To advance understanding of the distribution, climatic relationships, and status of American pikas (<i>Ochotona princeps</i>) in the Great Basin, United States, we compiled 2,387 records of extant pika sites surveyed since 2005, 89 records of documented extirpated sites (resurvey of historic sites), and 774 records of sites with old sign only. Extant sites extended across five degrees latitude and ten degrees longitude, encompassed six subregions, traversed forty mountain ranges, spanned 2,378 m in elevation (1,631–4,009 m), and comprised three of five currently described pika subspecies. A climate envelope for extant sites using the PRISM climate model expands the range of temperature and precipitation values that have been previously described. Extirpated and old-sign sites were mostly found within the geographic and climatic space of extant sites, but often in warmer and drier portions. Considerable overlap of extirpated, old, and extant groups within the same climate space suggests that nonclimatic factors have also contributed to population losses. The broad distribution and enlarged climate envelope of extant pika sites indicate that despite some localized extirpations, pika populations are persisting across Great Basin mountains, and appear to be able to tolerate a broader set of habitat conditions than previously understood.
DOI: 10.6084/m9.figshare.6203459
title: Code-switching

description: Dataset for the study How does Code-switching while Giving Instructions in Chinese EFL classrooms
DOI: 10.6084/m9.figshare.6203456
title: Dataset for: Robust versus consistent variance estimators in marginal structural Cox models

description: In survival analyses, inverse-probability-of-treatment (IPT) and inverse-probability-of-censoring (IPC) weighted estimators of parameters in marginal structural Cox models (Cox MSMs) are often used to estimate treatment effects in the presence of time-dependent confounding and censoring. In most applications, a robust variance estimator of the IPT and IPC weighted estimator is calculated leading to conservative confidence intervals. This estimator assumes that the weights are known rather than estimated from the data. Although a consistent estimator of the asymptotic variance of the IPT and IPC weighted estimator is generally available, applications and thus information on the performance of the consistent estimator are lacking. Reasons might be a cumbersome implementation in statistical software, which is further complicated by missing details on the variance formula. In this paper, we therefore provide a detailed derivation of the variance of the asymptotic distribution of the IPT and IPC weighted estimator and explicitly state the necessary terms to calculate a consistent estimator of this variance. We compare the performance of the robust and the consistent variance estimator in an application based on routine health care data and in a simulation study. The simulation reveals no substantial differences between the two estimators in medium and large data sets with no unmeasured confounding, but the consistent variance estimator performs poorly in small samples or under unmeasured confounding, if the number of confounders is large. We thus conclude that the robust estimator is more appropriate for all practical purposes.