cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/e164581v1
title: Innovative Medicine and Research on COVID-19 (C19): Addressing Potential Ethical, Oversight, and Regulatory Barriers

description: Responses to two separate but related surveys containing open-ended questions to IRB professionals and researchers in the United States who studied COVID-19 during the spring and summer of 2020. These questions focused on ethical, logistical, and practical challenges to overseeing and performing COVID-related research early in the pandemic.
description: This study employed criterion-based convenience sampling to identify US-based researchers conducting COVID-19 research and IRB professional reviewing COVID-19 research. Both researchers and IRB professionals were contacted using publicly available contact information. Researcher contact information was located from ClinicalTrials.gov, Scopus, and Embase Conference Abstracts. Recruitment of IRB professionals was supported by Public Responsibility in Medicine and Research (PRIM&R), who agreed to distribute study recruitment materials in their electronic newsletter, as well as posting recruitment information on their IRB Forum blog page and their COVID-19 webpage.
description: COVID-19 Researchers, IRB professionals reviewing COVID-19 research. Smallest Geographic Unit: United States
description: web-based survey; Please review the provided ReadMe file for additional information about data collection and the contents of this dataset.
DOI: 10.6084/m9.figshare.19338164
title: Supplemental material, tables, for “Association of HLA-DRB1 with viral load and immune response to Epstein Barr virus in adult and pediatric Systemic Lupus Erythematosus patients

description: Table 1 Caption: <sup>a</sup>See reference: 11,15–17, <sup>b</sup>SLE: total SLE patients, <sup>c</sup>HC:<sup> </sup>total healthy controls; Pos: Positive; Neg: Negative; EBV: Epstein-Barr Virus; VCA: viral capsid antigen; EBNA-1: EB nuclear antigen-1; p22: viral capsid antigen; EA-D: viral early antigen diffuse; n: number of samples, SLE: systemic lupus erythematosus; aSLE:adult SLE, pSLE: pediatric SLE, aHC: adult healthy controls, pHC: pediatric healthy controls; Acute infection is described as anti-VCA IgM/IgG positive but anti-EBNA-1 IgG negative; past infection is described as anti-VCA IgG and anti-EBNA-1 IgG positive but anti-VCA IgM negative and viral reactivation is described as positive for anti-EBNA-1 IgG and anti-EA-D IgG.Table 2 Caption: EBV: Epstein Barr Virus; VCA: viral capsid antigen; EBNA-1: EB nuclear antigen; p22: capsid antigen; EA-D: early antigen diffuse; HLA: human leukocyte antigen; aSLE: adult SLE; pSLE: pediatric SLE; n: sample size for calculation of genotype frequency; 2n: sample size for calculation of allele frequency, because each individual contributes two separate alleles
DOI: 10.6084/m9.figshare.19338164.v1
title: Supplemental material, tables, for “Association of HLA-DRB1 with viral load and immune response to Epstein Barr virus in adult and pediatric Systemic Lupus Erythematosus patients

description: Table 1 Caption: <sup>a</sup>See reference: 11,15–17, <sup>b</sup>SLE: total SLE patients, <sup>c</sup>HC:<sup> </sup>total healthy controls; Pos: Positive; Neg: Negative; EBV: Epstein-Barr Virus; VCA: viral capsid antigen; EBNA-1: EB nuclear antigen-1; p22: viral capsid antigen; EA-D: viral early antigen diffuse; n: number of samples, SLE: systemic lupus erythematosus; aSLE:adult SLE, pSLE: pediatric SLE, aHC: adult healthy controls, pHC: pediatric healthy controls; Acute infection is described as anti-VCA IgM/IgG positive but anti-EBNA-1 IgG negative; past infection is described as anti-VCA IgG and anti-EBNA-1 IgG positive but anti-VCA IgM negative and viral reactivation is described as positive for anti-EBNA-1 IgG and anti-EA-D IgG.Table 2 Caption: EBV: Epstein Barr Virus; VCA: viral capsid antigen; EBNA-1: EB nuclear antigen; p22: capsid antigen; EA-D: early antigen diffuse; HLA: human leukocyte antigen; aSLE: adult SLE; pSLE: pediatric SLE; n: sample size for calculation of genotype frequency; 2n: sample size for calculation of allele frequency, because each individual contributes two separate alleles
DOI: 10.18112/openneuro.ds002080.v3.0.0
title: BTC_postop
DOI: 10.15139/s3/ct5h3d
title: Police stops

description: Law enforcement agencies in North Carolina are required to report traffic law enforcement statistics to the Department of Public Safety within 60 days of the close of each month. This dataset includes daily summaries of each agency’s traffic stops, including the reason for the stop, the outcome of the stop, and demographic characteristics of any persons involved. As a result, the data is comprehensive. Daily data is available to the public 60 days after the close of the prior month. Original data is reported by police departments, which vary by geography (for example cities, county sheriffs, universities, state patrols, etc). As a result, county-level summaries may introduce some minor discrepancies.
DOI: 10.3886/e146802v1-111900
title: Hourly U.S. Electricity Generation

description: This deposit combines data from https://doi.org/10.3886/E146782V1 and https://doi.org/10.3886/E146801V1 to produce files containing the hourly generation, costs, and capacities of virtually all power plants in the lower 48 United States between 1999-2012 for their use in "Data and Code for: Imperfect Markets versus Imperfect Regulation in U.S. Electricity Generation" (https://doi.org/10.3886/E115467V1).<br><br><br>
description: Power plants / Generation units in the lower 48 states.
DOI: 10.5281/zenodo.6344804
title: Interview Data on Challenges in big data based communication amid C19

description: <strong>Transcriptions of Interview Data that follows the Semi-Structured Interview Guide</strong> Introduction Prior to beginning the interview, the research participant is given the option to accept or decline the interview being recorded. The interviewers then explained that the interview is entirely confidential and any references to company names, colleague names, or product names will be redacted from the transcripts and kept anonymous. The research participant’s name will not be used or recorded in the transcript or in the final manuscript. Background Can you tell us about your education and professional background? Current role and responsibilities What is your current role/position? What industry is your company part of? What department are you part of? What area of the business do you support? What types of communications are you creating (e.g. communications channels, deliverables, platforms, etc.)? Are you utilizing RPA, AI, or data visualizations tools to communicate data? If so, how? Who are your stakeholders (who is the audience)? Data and communications When communicating data, what are the communication objectives/goals? What communications problems are seeking to solve? What type of data do you use in your role? How do you determine which datasets to use and communicate? How do you assess the datasets for variety, volume, velocity, veracity? How do you use it? (To describe, predict, diagnose, or make recommendations?) What has been the outcome or impact of using data in communications? How do you measure the impact of your communications? What are the challenges in communicating data? Do you use these communications across regions and international markets? What are the challenges in communicating data across regions and international markets? What adjustments are required or what factors are taken into consideration when communicating data across countries? Are these communications shared or utilized across business units, functions, and departments? Conclusion What value do your communications add to achieving business objectives?
DOI: 10.5281/zenodo.6344803
title: Interview Data on Challenges in big data based communication amid C19

description: <strong>Transcriptions of Interview Data that follows the Semi-Structured Interview Guide</strong> Introduction Prior to beginning the interview, the research participant is given the option to accept or decline the interview being recorded. The interviewers then explained that the interview is entirely confidential and any references to company names, colleague names, or product names will be redacted from the transcripts and kept anonymous. The research participant’s name will not be used or recorded in the transcript or in the final manuscript. Background Can you tell us about your education and professional background? Current role and responsibilities What is your current role/position? What industry is your company part of? What department are you part of? What area of the business do you support? What types of communications are you creating (e.g. communications channels, deliverables, platforms, etc.)? Are you utilizing RPA, AI, or data visualizations tools to communicate data? If so, how? Who are your stakeholders (who is the audience)? Data and communications When communicating data, what are the communication objectives/goals? What communications problems are seeking to solve? What type of data do you use in your role? How do you determine which datasets to use and communicate? How do you assess the datasets for variety, volume, velocity, veracity? How do you use it? (To describe, predict, diagnose, or make recommendations?) What has been the outcome or impact of using data in communications? How do you measure the impact of your communications? What are the challenges in communicating data? Do you use these communications across regions and international markets? What are the challenges in communicating data across regions and international markets? What adjustments are required or what factors are taken into consideration when communicating data across countries? Are these communications shared or utilized across business units, functions, and departments? Conclusion What value do your communications add to achieving business objectives?
DOI: 10.5066/f77m062c
title: USGS Minerals Yearbook 2015, v. I, Bromine, Advance Data Release

description: These advance data tables are those to be published with the 2015 USGS Minerals Yearbook volume I Bromine chapter. They contain salient statistics for bromine sold or used from 2011 to 2015, a list of U.S. bromine producing plants in 2015, exports and imports data for bromine and bromine compounds in 2014 and 2015, world production by country from 2011 to 2015, and capacities of major plants outside the United States.
DOI: 10.15468/dl.de7qxh
title: Occurrence Download

description: A dataset containing 4832 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cryptandra parvifolia (Hook.) Hook.fil.)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 4832 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013450-190320150433242/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ghg5xv
title: Occurrence Download

description: A dataset containing 517 species occurrences available in GBIF matching the query:
{
 "SpeciesKey" : [
 "is Suillellus rhodoxanthus (Krombh.) Blanco-Dios"
 ]
}

 The dataset includes 517 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0147166-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.meuoxc
title: Occurrence Download

description: A dataset containing 2222 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Xyleborus dispar Wood & Bright, 1992"
 ]
}

 The dataset includes 2222 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013450-160311141623029/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3nwku2
title: Occurrence Download

description: A dataset containing 4969547 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is South Africa",
 "Year 2018-2020"
 ]
}

 The dataset includes 4969547 records from 57 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0096328-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dsvmzw
title: Occurrence Download

description: A dataset containing 12413 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Limnomedusae"
 ]
}

 The dataset includes 12413 records from 177 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026578-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s9j8vw
title: Occurrence Download

description: A dataset containing 90 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Trimeresurus venustus Vogel, 1991"
 ]
}

 The dataset includes 90 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026567-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t5anfr
title: Occurrence Download

description: A dataset containing 9097 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "TaxonKey is Gossypium hirsutum L.",
 "TaxonKey is Gracilaria arcuata Zanardini",
 "TaxonKey is Gracilaria salicornia (C.Agardh) E.Y.Dawson, 1954",
 "TaxonKey is Gracilaria vermiculophylla (Ohmi) Papenfuss",
 "TaxonKey is Gracilia minuta (Fabricius, 1781)"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 9097 records from 222 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013451-180508205500799/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ufptr4
title: Occurrence Download

description: A dataset containing 43 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((69.44415 2.38639,112.47889 11.6357,104.64799 36.67822,60.38468 34.43731,69.44415 2.38639))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 {
 "or" : [
 "TaxonKey is Kuruna Attigala, Kaththr. & L.G.Clark",
 "TaxonKey is Ravenochloa D.Z.Li & Y.X.Zhang",
 "TaxonKey is Acidosasa C.D.Chu & C.S.Chao ex Keng f."
 ]
 }
 ]
}

 The dataset includes 43 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0074039-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ebekwn
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pinus brutia Ten.",
 "HasCoordinate is true",
 "Country is Iceland",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2000",
 "CoordinateUncertaintyInMeters is less than 10000"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0136077-240321170329656/datasets/export for details.
DOI: 10.15468/dl.856xbg
title: Occurrence Download

description: A dataset containing 12413 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Limnomedusae"
 ]
}

 The dataset includes 12413 records from 177 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026571-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hp9hn8
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Leopoldinia piassaba Wallace",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 32 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013452-180131172636756/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k42gsm
title: Occurrence Download

description: A dataset containing 1382 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "BasisOfRecord is Specimen",
 "BasisOfRecord is Human Observation",
 "BasisOfRecord is Material sample",
 "BasisOfRecord is Unknown evidence"
 ]
 },
 "OccurrenceStatus is Present",
 "TaxonKey is Chrysochloridae",
 "Year 1000-2019"
 ]
}

 The dataset includes 1382 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003331-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8mx4bv
title: Occurrence Download

description: A dataset containing 650 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Chimaera phantasma Jordan & Snyder, 1900"
 ]
}

 The dataset includes 650 records from 59 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026577-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.o7ccih
title: Occurrence Download

description: A dataset containing 404 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Arnebia euchroma (Royle ex Benth.) I.M.Johnst."
 ]
}

 The dataset includes 404 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013456-160118175350007/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uvmrx2
title: Occurrence Download

description: A dataset containing 472 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Austraeolis Burn, 1962"
 ]
}

 The dataset includes 472 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0323480-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9uer9n
title: Occurrence Download

description: A dataset containing 5088917 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Year 2008-2018",
 "TaxonKey is Cardinalis cardinalis (Linnaeus, 1758)"
 ]
}

 The dataset includes 5088917 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013453-181003121212138/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.put4r7
title: Occurrence Download

description: A dataset containing 28 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Pholidoscelis alboguttatus (Boulenger, 1896)"
 ]
}

 The dataset includes 28 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006863-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9ufzhs
title: Occurrence Download

description: A dataset containing 195 species occurrences available in GBIF matching the query:
{
 "SpeciesKey" : [
 "is Squamanita paradoxa (A.H.Sm. & Singer) Bas"
 ]
}

 The dataset includes 195 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0147168-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fzpbxj
title: Occurrence Download

description: A dataset containing 133 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Ecuador",
 "TaxonKey is Atelopus elegans (Boulenger, 1882)"
 ]
}

 The dataset includes 133 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013453-190415153152247/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u939s7
title: Occurrence Download

description: A dataset containing 107 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Combretum meridionalis (H.Perrier) Jongkind"
 ]
}

 The dataset includes 107 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006859-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1025749.10fu
title: SH1025749.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1025750.10fu
title: SH1025750.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.