cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5066/p9jltt76
title: Bathymetric Data Collection for Larimore Dam in North Dakota, August 2020

description: Data were collected in August, 2020 to support development of a bathymetric map for Larimore Dam in Grand Forks County, North Dakota. Global Navigation Satellite System (GNSS) surveying equipment was used in static and real-time kinematic (RTK) mode to establish a local reference mark and check-in/check-out point, to collect water surface elevations, and to collect topographic points along established data collection transects. Topographic points were collected on land, in water too shallow for boating, and in areas of the lake where thick aquatic vegetation prohibited use of an echosounder and transducer. In areas of the lake deep enough for boating and where aquatic vegetation was not present, depth data was collected using an echosounder with a dual frequency (200/24 kilohertz with a 4/20 degree beam) transducer. Data were collected on a set of transects roughly perpendicular to the axis of the waterbody, plus on a set of oblique transects that intersected the regular transects. Data collected on the oblique transects is intended to be used in map accuracy and quality-assurance/quality-control measures. Bar checks were completed twice daily (before and after echosounder data were collected) on August 4 and August 7. GNSS RTK was used to navigate the survey vessel on data collection transects. This data release includes a polyline shapefile and metadata describing the data collection transects, a point shapefile and metadata describing the data collected with GNSS RTK, a point shapefile and metadata describing the edited data collected with echosounder and transducer, and a comma spaced variable file containing raw echosounder data with associated metadata.
DOI: 10.7277/bqj2-yd98
title: Development of a Performance-Based Seismic Design Philosophy for Mid-Rise Woodframe Construction (NEES-2006-0138)

description: &lt;p&gt;&lt;strong&gt;Title&lt;/strong&gt;: Development of a Performance-Based Seismic Design Philosophy for Mid-Rise Woodframe Construction (NEES-2011-0138)&lt;/p&gt; &lt;p&gt;&lt;b&gt;Year Of Curation: &lt;/b&gt;2011&lt;/p&gt; &lt;p&gt;&lt;b&gt;Description: &lt;/b&gt;This project dealt with the shake table testing program of a full-scale two-story woodframe townhouse building conducted within the NEESWood Project. The test building represents the worlda??s largest woodframe structure tested on a shake table. The size and weight of the test structure required the simultaneous use of the two tri-axial shake tables at the University at Buffalo UB-NEES site. The testing program is focusing on the various construction elements that may have significant influence on the seismic response of woodframe buildings and that should be considered in performance-based seismic design.&lt;/p&gt; &lt;p&gt;&lt;b&gt;Award: &lt;/b&gt;http://www.nsf.gov/awardsearch/showAward?AWD_ID=0529903&lt;/p&gt; &lt;p&gt;&lt;b&gt;PIs &amp; CoPIs: &lt;/b&gt;John Van de Lindt, Rachel Davidson, Andre Filiatrault, David Rosowsky, Michael Symans&lt;/p&gt; &lt;p&gt;&lt;b&gt;Dates: &lt;/b&gt;October 01, 2005 - September 30, 2009&lt;/p&gt; &lt;p&gt;&lt;b&gt;Organizations: &lt;/b&gt;State University of New York at Buffalo, NY, United States&lt;/p&gt; &lt;p&gt;&lt;b&gt;Facilities: &lt;/b&gt;State University of New York at Buffalo, NY, United States&lt;/p&gt; &lt;p&gt;&lt;b&gt;Sponsor: &lt;/b&gt;NSF - 0529903 &lt;/p&gt; &lt;p&gt;&lt;b&gt;Keywords: &lt;/b&gt;Wood,Wood-Frame House,Shake Table&lt;/p&gt; &lt;p&gt;&lt;b&gt;Publications &lt;/b&gt;&quot;NW-01: Seismic Testing of a Full-Scale Two-Story Light-Frame Wood Building: NEESWood Benchmark Test&quot; &lt;/p&gt; &lt;nb:citations&gt;&lt;/nb:citations&gt;
DOI: 10.6084/m9.figshare.12711767
title: Data describing the role of interleukin 6 as a predictive factor for a severe course of Covid-19

description: This dataset consists of a single <b>.xlsx </b>spreadsheet of data describing the role of interleukin 6 as a predictive factor for a severe course of Covid-19. <br>The data underlie the manuscript: "Role of interleukin 6 as a predictive factor for a severe course of Covid-19: retrospective data analysis of patients from a Long-term Care Facility during Covid-19 Outbreak". The related study aimed to find an effective screening tool to identify the elderly patients in long-term care facilities who were at risk of severe illness and death due to Covid-19, and explored the role of interleukin 6 (IL-6) as a predictive factor. <br>The spreadsheet contains demographic, clinical and biochemical variables of SARS-CoV-2 positive patients obtained during the first day of intervention in the outbreak of Covid-19 in one long-term care facility in Slovakia in April 2020. All data were obtained during initial screening on the first day of intervention.
DOI: 10.6084/m9.figshare.12711767.v1
title: Data describing the role of interleukin 6 as a predictive factor for a severe course of Covid-19

description: This dataset consists of a single <b>.xlsx </b>spreadsheet of data describing the role of interleukin 6 as a predictive factor for a severe course of Covid-19. <br>The data underlie the manuscript: "Role of interleukin 6 as a predictive factor for a severe course of Covid-19: retrospective data analysis of patients from a Long-term Care Facility during Covid-19 Outbreak". The related study aimed to find an effective screening tool to identify the elderly patients in long-term care facilities who were at risk of severe illness and death due to Covid-19, and explored the role of interleukin 6 (IL-6) as a predictive factor. <br>The spreadsheet contains demographic, clinical and biochemical variables of SARS-CoV-2 positive patients obtained during the first day of intervention in the outbreak of Covid-19 in one long-term care facility in Slovakia in April 2020. All data were obtained during initial screening on the first day of intervention.
DOI: 10.5519/qd.9hj4kpnm
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (363 records)
DOI: 10.5281/zenodo.3900656
title: Microseismic Catalog for ToC2ME dataset

description: Microseismic catalog for the Tony Creek dual Microseismic Experiment (ToC2ME) dataset, a passive microseismic dataset collected near Fox Creek, Alberta, Canada, in 2016. Number of events: 18040 Location/detection method: Absolute locations based on P- and S-waveforms from 3C sensor. Method involves stacking waveforms along ray-tracing travel times within a volume. Includes all events that exceeded quality control criteria from a larger catalog of detected events from multi-channel 3D cross-correlation. High resolution in x and y, but with a large uncertainty in depth. Method developed by James Verdon at the University of Bristol. Magnitudes obtained from 3C geophones using the standard Brune formula. See https://github.com/ToC2ME for more information.
DOI: 10.6084/m9.figshare.13944143.v1
title: Abyssal Current

description: Abyssal current data
DOI: 10.6084/m9.figshare.13681456.v1
title: Metadata record for the manuscript: Immune microenvironment characterization and dynamics during anti-HER2-based neoadjuvant treatment in HER2-positive breast cancer

description: <b>Summary</b> This metadata record provides details of the data supporting the claims of the related manuscript: “Immune microenvironment characterization and dynamics during anti-HER2-based neoadjuvant treatment in HER2-positive breast cancer”. The related study investigated changes in tumour immune contexture as assessed by stromal tumour-infiltrating lymphocytes (sTILs) and by multiplexed spatial cellular phenotyping during treatment with lapatinib-trastuzumab in HER2+ breast cancer (BC) patients (PAMELA trial), and evaluated the relationship of tumour immune contexture with hormone receptor (HR) status, intrinsic subtype and immune-related gene expression. Type of data: Excel, txt & Visiopharm APP folder Subject of data: <i>Homo sapiens</i> Population characteristics: Detailed in the previous manuscript reporting clinical data from the PAMELA trial (Llombart-Cussac A. et al. Lancet Oncol 2018 https://doi.org/10.1016/S1470-2045(17)30021-9) Trial registration number: clinicaltrials.gov, NCT01973660 <b>Data access</b> The data files underlying the related study are available from the corresponding authors upon reasonable request. However, several files are not publicly available in order to protect patient privacy. A comprehensive list of data files underlying the related manuscript along with details of their availability is contained in the spreadsheet ‘Griguolo_et_al_2021_underlying_datafile_list.xlsx’, available as part of this data record. The custom-developed algorithms (T-cell APP) created using the Author® module of VISIOPHARM® (VIS) Image Analysis Software (Visiopharm Integrator System version 2019.02.1.6005, Visiopharm, Denmark) are described in Supplementary Table S19 of the related manuscript and are available as part of this data record. Download all files into a folder and put the folder into C:\ProgramData\Visiopharm\APPs to use the APP. <b>Corresponding author(s) for this study</b> Aleix Prat, MD PhD Department of Medical Oncology Hospital Clínic of Barcelona Translational Genomics and Targeted Therapeutics in Solid Tumors, IDIBAPS Villarroel 170, Barcelona, 08035, Spain. Phone: (+34) 93 227 54 00 Email: alprat@clinic.cat Paolo Nuciforo, MD PhD Molecular Oncology Group Vall d´Hebron Institute of Oncology (VHIO) Natzaret 115-117, Barcelona, 08035, Spain. Phone: (+34) 93 227 54 00 Email: pnuciforo@vhio.net <br> <b>Study approval </b> The study protocol was approved by independent ethics committees at each centre.
DOI: 10.6084/m9.figshare.13664540
title: Metadata record for the manuscript: Inflation of Tumor Mutation Burden by Tumor-Only Sequencing in Under-Represented Groups

description: <b>Summary</b><br> This metadata record provides details of the data supporting the claims of the related manuscript: “Inflation of Tumor Mutation Burden by Tumor-Only Sequencing in Under-Represented Groups ”. The related study investigated the impact of minority group representation in public germline variant databases and hypothesised that tumour mutational burden (TMB) would be more greatly inflated in underrepresented groups. Type of data: exome sequencing data of tumor (CD138+ bone marrows) and patient-paired germline samples, clinical characteristics of patients Subject of data: <i>Homo sapiens</i> Sample size: 701 patients Population characteristics: 575 self-reported White patients and 126 self-reported Black patients <b>Data access</b> The exome sequencing data of tumour (CD138+ bone marrows) and patient-paired germline samples can be obtained by controlled access from <i>dbGAP</i> under accession https://identifiers.org/dbgap:phs000748. The self-reported race and other clinical characters of the patients can be accessed from the Multiple Myeloma Research Foundation Researcher Gateway (https://research.themmrf.org/). Additionally, the data underlying the figures, table and supplementary file of the related article, as well as Supplementary File 1 (Excel spreadsheet) are shared as part of this <i>figshare </i>record in the files ‘Supporting_Data.xlsx’ and ‘Supplemental File 1.xlsx’. <b>Corresponding author(s) for this study</b> Aaron S. Mansfield, MD, Division of Medical Oncology, Department of Oncology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905 (Mansfield.Aaron@mayo.edu) 507-266-9160.
DOI: 10.6084/m9.figshare.13664540.v1
title: Metadata record for the manuscript: Inflation of Tumor Mutation Burden by Tumor-Only Sequencing in Under-Represented Groups

description: <b>Summary</b><br> This metadata record provides details of the data supporting the claims of the related manuscript: “Inflation of Tumor Mutation Burden by Tumor-Only Sequencing in Under-Represented Groups ”. The related study investigated the impact of minority group representation in public germline variant databases and hypothesised that tumour mutational burden (TMB) would be more greatly inflated in underrepresented groups. Type of data: exome sequencing data of tumor (CD138+ bone marrows) and patient-paired germline samples, clinical characteristics of patients Subject of data: <i>Homo sapiens</i> Sample size: 701 patients Population characteristics: 575 self-reported White patients and 126 self-reported Black patients <b>Data access</b> The exome sequencing data of tumour (CD138+ bone marrows) and patient-paired germline samples can be obtained by controlled access from <i>dbGAP</i> under accession https://identifiers.org/dbgap:phs000748. The self-reported race and other clinical characters of the patients can be accessed from the Multiple Myeloma Research Foundation Researcher Gateway (https://research.themmrf.org/). Additionally, the data underlying the figures, table and supplementary file of the related article, as well as Supplementary File 1 (Excel spreadsheet) are shared as part of this <i>figshare </i>record in the files ‘Supporting_Data.xlsx’ and ‘Supplemental File 1.xlsx’. <b>Corresponding author(s) for this study</b> Aaron S. Mansfield, MD, Division of Medical Oncology, Department of Oncology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905 (Mansfield.Aaron@mayo.edu) 507-266-9160.
DOI: 10.6084/m9.figshare.13681456
title: Metadata record for the manuscript: Immune microenvironment characterization and dynamics during anti-HER2-based neoadjuvant treatment in HER2-positive breast cancer

description: <b>Summary</b> This metadata record provides details of the data supporting the claims of the related manuscript: “Immune microenvironment characterization and dynamics during anti-HER2-based neoadjuvant treatment in HER2-positive breast cancer”. The related study investigated changes in tumour immune contexture as assessed by stromal tumour-infiltrating lymphocytes (sTILs) and by multiplexed spatial cellular phenotyping during treatment with lapatinib-trastuzumab in HER2+ breast cancer (BC) patients (PAMELA trial), and evaluated the relationship of tumour immune contexture with hormone receptor (HR) status, intrinsic subtype and immune-related gene expression. Type of data: Excel, txt & Visiopharm APP folder Subject of data: <i>Homo sapiens</i> Population characteristics: Detailed in the previous manuscript reporting clinical data from the PAMELA trial (Llombart-Cussac A. et al. Lancet Oncol 2018 https://doi.org/10.1016/S1470-2045(17)30021-9) Trial registration number: clinicaltrials.gov, NCT01973660 <b>Data access</b> The data files underlying the related study are available from the corresponding authors upon reasonable request. However, several files are not publicly available in order to protect patient privacy. A comprehensive list of data files underlying the related manuscript along with details of their availability is contained in the spreadsheet ‘Griguolo_et_al_2021_underlying_datafile_list.xlsx’, available as part of this data record. The custom-developed algorithms (T-cell APP) created using the Author® module of VISIOPHARM® (VIS) Image Analysis Software (Visiopharm Integrator System version 2019.02.1.6005, Visiopharm, Denmark) are described in Supplementary Table S19 of the related manuscript and are available as part of this data record. Download all files into a folder and put the folder into C:\ProgramData\Visiopharm\APPs to use the APP. <b>Corresponding author(s) for this study</b> Aleix Prat, MD PhD Department of Medical Oncology Hospital Clínic of Barcelona Translational Genomics and Targeted Therapeutics in Solid Tumors, IDIBAPS Villarroel 170, Barcelona, 08035, Spain. Phone: (+34) 93 227 54 00 Email: alprat@clinic.cat Paolo Nuciforo, MD PhD Molecular Oncology Group Vall d´Hebron Institute of Oncology (VHIO) Natzaret 115-117, Barcelona, 08035, Spain. Phone: (+34) 93 227 54 00 Email: pnuciforo@vhio.net <br> <b>Study approval </b> The study protocol was approved by independent ethics committees at each centre.
DOI: 10.6084/m9.figshare.13944143
title: Data

description: Data
DOI: 10.6084/m9.figshare.13944143.v3
title: Data

description: Data
DOI: 10.6084/m9.figshare.13944143.v2
title: Data

description: Data
DOI: 10.6084/m9.figshare.14141366
title: Test a

description: This dataset was uploaded to see how figshare works.<br>
DOI: 10.6084/m9.figshare.14141366.v2
title: Test a

description: This dataset was uploaded to see how figshare works.<br>
DOI: 10.6084/m9.figshare.14141366.v1
title: Test.xlsx

description: Test for test.<br>
DOI: 10.15468/tuuven
title: A new species of large green treefrog (Litoria, Pelodryadidae) from Papua Indonesia

description: This dataset contains the digitized treatments in Plazi based on the original journal article Oliver, Paul, Günther, Rainer, Tjaturadi, Burhan, Richards, Stephen J. (2021): A new species of large green treefrog (Litoria, Pelodryadidae) from Papua Indonesia. Zootaxa 4903 (1): 117-126, DOI: https://doi.org/10.11646/zootaxa.4903.1.7
DOI: 10.6084/m9.figshare.14139287
title: Supplementary Figure 4

description: L-DOPA does not react with Glyphosate to form new compounds
DOI: 10.6084/m9.figshare.14139287.v2
title: Supplementary Figure 4

description: L-DOPA does not react with Glyphosate to form new compounds
DOI: 10.6084/m9.figshare.14139287.v1
title: Supplementary Figure 4

description: L-DOPA does not react with Glyphosate to form new compounds
DOI: 10.5281/zenodo.4574053
title: GRAY2017

description: GRAY2017 PharmacoSet (PSet) generated by ORCESTRA. Metadata can be found on ORCESTRA at: http://orcestra.ca/10.5281/zenodo.4574053
DOI: 10.5281/zenodo.4574052
title: GRAY2017

description: GRAY2017 PharmacoSet (PSet) generated by ORCESTRA. Metadata can be found on ORCESTRA at: http://orcestra.ca/10.5281/zenodo.4574053
DOI: 10.15468/jgcccb
title: Pilargidae (Annelida: Phyllodocida) from coastal and deep waters of the Southwestern Atlantic, with descriptions of two new species

description: This dataset contains the digitized treatments in Plazi based on the original journal article Ribeiro, Rannyele Passos, Barbosa, Aline Da Cruz, Freitas, Roberta, Zanol, Joana, Glasby, Christopher J., Ruta, Christine (2020): Pilargidae (Annelida: Phyllodocida) from coastal and deep waters of the Southwestern Atlantic, with descriptions of two new species. Zootaxa 4878 (1): 56-76, DOI: https://doi.org/10.11646/zootaxa.4878.1.2
DOI: 10.34740/kaggle/dsv/1988972
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.6084/m9.figshare.12816488.v2
title: Data assimilation

description: Upon acceptance of publication, bathymetry and ship location data used in the study "data assimilation for tsunami forecasting" will be stored here in a tar file. Bathymetry data is formatted as .grd file and ship location data is formatted as HDF5. <br>
DOI: 10.15468/wzugkz
title: Two new species of Cantharis Linnaeus, 1758 from Baltic amber

description: This dataset contains the digitized treatments in Plazi based on the original journal article Fanti, Fabrizio, Pankowski, Maximilian G. (2020): Two new species of Cantharis Linnaeus, 1758 from Baltic amber. Zootaxa 4878 (3): 401-411, DOI: https://doi.org/10.11646/zootaxa.4878.3.1
DOI: 10.6084/m9.figshare.12816488.v3
title: Data assimilation

description: Ship location data used in the study "data assimilation for tsunami forecasting" <br>
DOI: 10.17632/f7wwg384rp.1
title: SCELTSE: the Small Corpus of English Language Teachers’ Self-Evaluations

description: SCELTSE (the Small Corpus of English Language Teachers’ Self-Evaluations) can be classified as a small specialized monolingual corpus. It is made up of 44 post-teaching self-evaluations written by L1-English English as a Second Language (ESL) teachers. The corpus comprises 25,423 tokens, 2,456 word types, and 2,128 lemmas in total. The corpus is balanced for gender. The texts in the corpus were written by 22 female and 22 male ESL teachers between the ages of 24 and 39. The data presented here includes: 1. The corpus of 44 unannotated plain texts (.txt) 2. The corpus of 44 (POS) annotated plain texts (.txt) 3. The corpus metadata (.xls) 4. Statistical data and categorisation of top 100 key nouns (.xls) 5. Statistical data and categorisation of top 100 key ngrams (.xls)
DOI: 10.17632/94zngr7kb9.1
title: Complementary data: Spermatic profile of captive giant anteaters (Myrmecophaga tridactyla): knowing more to preserve better
DOI: 10.17632/mpvwnhv4vb.1
title: Extended Federated Ensemble Regression using Classification

description: Datasets used for the evaluation of the Extended Federated Ensemble Regression using Classification algorithm.
DOI: 10.17632/wh6txd9rx2.1
title: Emad Abraik

description: This file is used to generate the numerical results
DOI: 10.15468/kc86y7
title: Six new species of the spider genus Centroctenus Mello-Leitão from the Neotropical region (Ctenidae, Cteninae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Brescovit, Antonio D., Torres, Richard A., Rego, Felipe N. A. A., Polotow, Daniele (2020): Six new species of the spider genus Centroctenus Mello-Leitão from the Neotropical region (Ctenidae, Cteninae). Zootaxa 4877 (2): 311-328, DOI: https://doi.org/10.11646/zootaxa.4877.2.5
DOI: 10.25390/caryinstitute.8120816.v1
title: Cary Environmental Monitoring Program Precipitation Chemistry Event-Based Data: 1984-2018

description: The Cary Institute of Ecosystem Studies Environmental Monitoring Program is a long-term data collection program designed to understand how the environment changes over time. The program includes monitoring of climate including temperature and precipitation, as well as variables related to air pollution, such as acid deposition and ozone, water pollution and streamwater hydrology. The Cary Institute of Ecosystem Studies, Environmental Monitoring Program furnishes data under the following conditions: The data have received quality assurance scrutiny by our program, and, although we are confident of the accuracy of these data, the Cary Institute will not be held liable for errors in these data. Data are subject to change resulting from updates in data screening or models used. Data citation: The following is a standard citation for referencing data from the Cary Institute of Ecosystem Studies, Environmental Monitoring Program:<br>Cary Institute of Ecosystem Studies, Environmental Monitoring Program. 2019 (or current year). Cary Institute of Ecosystem Studies, Box AB, Millbrook, NY 12545, www.caryinstitute.org.<br>Those wishing to publish data from the Cary Institute of Ecosystem Studies, Environmental Monitoring Program are encouraged to contact Data Manager Vicky Kelly, kellyv@caryinstitute.org.