cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.82z5aj
title: Occurrence Download

description: A dataset containing 4138 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Zalophus wollebaeki Sivertsen, 1953, Diaemus youngii (Jentink, 1893))"
 ]
}

 The dataset includes 4138 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050946-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.stft3n
title: Occurrence Download

description: A dataset containing 77 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-79.38552 -56.22461,-50.93242 -56.22461,-50.93242 -22.65871,-79.38552 -22.65871,-79.38552 -56.22461))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Veniliornis lignarius (Molina, 1782)"
 ]
}

 The dataset includes 77 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0267352-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.oteodq
title: Occurrence Download

description: A dataset containing 8102 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Anopheles Meigen, 1818"
 ]
}

 The dataset includes 8102 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010167-190320150433242/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sf32zr
title: Occurrence Download

description: A dataset containing 24753 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cetonia aurata (Linnaeus, 1758))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Human Observation, Observation, Specimen)",
 "Year is greater than 1945"
 ]
}

 The dataset includes 24753 records from 378 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0278773-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d8b98f
title: Occurrence Download

description: A dataset containing 14388 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Aedes albopictus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 2022",
 "Geometry POLYGON((-25 70, 40 70, 40 35, -25 35, -25 70))"
 ]
}

 The dataset includes 14388 records from 51 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000018-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.y3d83e
title: Occurrence Download

description: A dataset containing 6761 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Platanthera obtusata"
 ]
}

 The dataset includes 6761 records from 158 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000019-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57903/uj/mmi0sz
title: Magnetic interactions controlled by light in the family of Fe(ii)–M(iv) (M = Mo, W, Nb) hybrid organic–inorganic frameworks - replication data

description: The replication data are referenced to the selected Figures in the manuscript "Magnetic interactions controlled by light in the family of Fe(ii)–M(iv) (M = Mo, W, Nb) hybrid organic–inorganic frameworks"
DOI: 10.3886/icpsr38120.v1
title: Survey of Consumer Attitudes and Behavior, August 2018
title: Version 1

description: The Survey of Consumer Attitudes and Behavior series (also known as the Surveys of Consumers) was undertaken to measure changes in consumer attitudes and expectations, to understand why such changes occur, and to evaluate how they relate to consumer decisions to save, borrow, or make discretionary purchases. The data regularly include the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations. Since the 1940s, these surveys have been produced quarterly through 1977 and monthly thereafter.
The surveys conducted in 2018 focused on topics such as evaluations and expectations about personal finances, employment, price changes, and the national business situation. Opinions were collected regarding respondents' appraisals of present market conditions for purchasing houses, automobiles, computers, and other durables.
Also explored in this survey, were respondents' mortgage refinancing, and political affiliation. Demographic information includes ethnic origin, sex, age, marital status, and education.
description: The purpose of this study is to forecast changes in aggregate consumer behavior.
description: This survey is a rotating panel design. For each monthly sample, an independent cross-section sample of households is drawn. The respondents chosen in this drawing are then reinterviewed six months later. The result is a rotating panel design, and the total sample for any one survey is normally made up of 60 percent new respondents with 40 percent being interviewed for the second time.
description: The data are not weighted, however, this collection contains three weight variables; <b>WT</b> (Household head weight), <b>WT_HH</b> (Household weight), and <b>WT_AD</b> (Adult weight) that must be used in any analysis. For more information on weights and sampling, please refer to the documentation and/or visit the Survey of Consumers Website.
description: National sample of telephone numbers from cell (RDD) sampling frame.
description: Datasets: 
DS0: Study-Level Files
DS1: Public-Use Data
DS2: Restricted-Use Data
description: Persons aged 18 years or older living in households with telephones within the coterminous United States. Smallest Geographic Unit: FIPS code
description: computer-assisted telephone interview (CATI)Information on the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations and how they were created can be found in the P.I. Codebook.Additional Information on the Surveys of Consumers can be found by visiting the Surveys of Consumers Website.
DOI: 10.3886/icpsr38120
title: Survey of Consumer Attitudes and Behavior, August 2018
title: Archival Version

description: The Survey of Consumer Attitudes and Behavior series (also known as the Surveys of Consumers) was undertaken to measure changes in consumer attitudes and expectations, to understand why such changes occur, and to evaluate how they relate to consumer decisions to save, borrow, or make discretionary purchases. The data regularly include the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations. Since the 1940s, these surveys have been produced quarterly through 1977 and monthly thereafter.
The surveys conducted in 2018 focused on topics such as evaluations and expectations about personal finances, employment, price changes, and the national business situation. Opinions were collected regarding respondents' appraisals of present market conditions for purchasing houses, automobiles, computers, and other durables.
Also explored in this survey, were respondents' mortgage refinancing, and political affiliation. Demographic information includes ethnic origin, sex, age, marital status, and education.
description: The purpose of this study is to forecast changes in aggregate consumer behavior.
description: This survey is a rotating panel design. For each monthly sample, an independent cross-section sample of households is drawn. The respondents chosen in this drawing are then reinterviewed six months later. The result is a rotating panel design, and the total sample for any one survey is normally made up of 60 percent new respondents with 40 percent being interviewed for the second time.
description: The data are not weighted, however, this collection contains three weight variables; <b>WT</b> (Household head weight), <b>WT_HH</b> (Household weight), and <b>WT_AD</b> (Adult weight) that must be used in any analysis. For more information on weights and sampling, please refer to the documentation and/or visit the Survey of Consumers Website.
description: National sample of telephone numbers from cell (RDD) sampling frame.
description: Datasets: 
DS0: Study-Level Files
DS1: Public-Use Data
DS2: Restricted-Use Data
description: Persons aged 18 years or older living in households with telephones within the coterminous United States. Smallest Geographic Unit: FIPS code
description: computer-assisted telephone interview (CATI)Information on the Index of Consumer Sentiment, the Index of Current Economic Conditions, and the Index of Consumer Expectations and how they were created can be found in the P.I. Codebook.Additional Information on the Surveys of Consumers can be found by visiting the Surveys of Consumers Website.
DOI: 10.21978/p8863g
title: IMP-8 Linearly Interpolated 60 s Resolution Tri-axial Fluxgate Magnetometer in GSM Coordinates
title: IMP-8 MFE data

description: IMP-8 linearly interpolated to have the measurements on the minute at 60 s resolution tri-axial fluxgate magnetometer data in GSM coordinates. This data set consists of processed solar wind data that has been linearly interpolated to 1 min resolution at the position of the spacecraft using the interp1.m function in MATLAB. This data set was originally constructed by Dr. J.M. Weygand for Prof. R.L. McPherron, who was the principle investigator of two National Science Foundation studies: GEM Grant ATM 02-1798 and a Space Weather Grant ATM 02-08501. These data were primarily used in superposed epoch studies and cross correlation studies on solar wind.
DOI: 10.21978/p8cw4p
title: IMP-8 Linearly Interpolated 60 s Resolution Tri-axial Fluxgate Magnetometer in GSE Coordinates
title: IMP-8 MFE data

description: IMP-8 linearly interpolated to have the measurements on the minute at 60 s resolution tri-axial fluxgate magnetometer data in GSE coordinates. This data set consists of processed solar wind data that has been linearly interpolated to 1 min resolution at the position of the spacecraft using the interp1.m function in MATLAB. This data set was originally constructed by Dr. J.M. Weygand for Prof. R.L. McPherron, who was the principle investigator of two National Science Foundation studies: GEM Grant ATM 02-1798 and a Space Weather Grant ATM 02-08501. These data were primarily used in superposed epoch studies and cross correlation studies on solar wind.
DOI: 10.21978/p80p8q
title: IMP-8 Weimer Propagated 60 s Resolution Tri-axial Fluxgate Magnetometer in GSM Coordinates
title: IMP-8 MFE data

description: IMP-8 Weimer propagated solar wind data and linearly interpolated to have the measurements on the minute at 60 s resolution Tri-axial fluxgate magnetometer data in GSM coordinates. This data set consists of propagated solar wind data that has first been propagated to a position just outside of the nominal bow shock (about 17, 0, 0 Re) and then linearly interpolated to 1 min resolution using the interp1.m function in MATLAB. The input data for this data set is a 1 min resolution processed solar wind data constructed by Dr. J.M. Weygand. The method of propagation is similar to the minimum variance technique and is outlined in Dan Weimer et al. [2003; 2004]. The basic method is to find the minimum variance direction of the magnetic field in the plane orthogonal to the mean magnetic field direction. This minimum variance direction is then dotted with the difference between final position vector minus the original position vector and the quantity is divided by the minimum variance dotted with the solar wind velocity vector, which gives the propagation time. This method does not work well for shocks and minimum variance directions with tilts greater than 70 degrees of the sun-earth line. This data set was originally constructed by Dr. J.M. Weygand for Prof. R.L. McPherron, who was the principle investigator of two National Science Foundation studies: GEM Grant ATM 02-1798 and a Space Weather Grant ATM 02-08501. These data were primarily used in superposed epoch studies References: Weimer, D. R. (2004), Correction to ‘‘Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique,’’ J. Geophys. Res., 109, A12104, doi:10.1029/2004JA010691. Weimer, D.R., D.M. Ober, N.C. Maynard, M.R. Collier, D.J. McComas, N.F. Ness, C. W. Smith, and J. Watermann (2003), Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique, J. Geophys. Res., 108, 1026, doi:10.1029/2002JA009405.
DOI: 10.21978/p84c97
title: IMP-8 Weimer Propagated 60 s Resolution Tri-axial Fluxgate Magnetometer in GSE Coordinates
title: IMP-8 MFE data

description: IMP-8 Weimer propagated solar wind data and linearly interpolated to have the measurements on the minute at 60 s resolution tri-axial fluxgate magnetometer data in GSE coordinates. This data set consists of propagated solar wind data that has first been propagated to a position just outside of the nominal bow shock (about 17, 0, 0 Re) and then linearly interpolated to 1 min resolution using the interp1.m function in MATLAB. The input data for this data set is a 1 min resolution processed solar wind data constructed by Dr. J.M. Weygand. The method of propagation is similar to the minimum variance technique and is outlined in Dan Weimer et al. [2003; 2004]. The basic method is to find the minimum variance direction of the magnetic field in the plane orthogonal to the mean magnetic field direction. This minimum variance direction is then dotted with the difference between final position vector minus the original position vector and the quantity is divided by the minimum variance dotted with the solar wind velocity vector, which gives the propagation time. This method does not work well for shocks and minimum variance directions with tilts greater than 70 degrees of the sun-earth line. This data set was originally constructed by Dr. J.M. Weygand for Prof. R.L. McPherron, who was the principle investigator of two National Science Foundation studies: GEM Grant ATM 02-1798 and a Space Weather Grant ATM 02-08501. These data were primarily used in superposed epoch studies. References: Weimer, D. R. (2004), Correction to ‘‘Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique,’’ J. Geophys. Res., 109, A12104, doi:10.1029/2004JA010691. Weimer, D.R., D.M. Ober, N.C. Maynard, M.R. Collier, D.J. McComas, N.F. Ness, C. W. Smith, and J. Watermann (2003), Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique, J. Geophys. Res., 108, 1026, doi:10.1029/2002JA009405.
DOI: 10.21978/p8vw41
title: IMP-8 Linearly Interpolated 60 s Resolution PLS data in GSE Coordinates
title: IMP-8 Plasma Faraday Cup data

description: IMP-8 linearly interpolated to have the measurements on the minute at 60 s resolution PLS data in GSE coordinates. This data set consists of processed solar wind data that has been linearly interpolated to 1 min resolution at the position of the spacecraft using the interp1.m function in MATLAB. This data set was originally constructed by Dr. J.M. Weygand for Prof. R.L. McPherron, who was the principle investigator of two National Science Foundation studies: GEM Grant ATM 02-1798 and a Space Weather Grant ATM 02-08501. These data were primarily used in superposed epoch studies and cross correlation studies on solar wind.
DOI: 10.5281/zenodo.18180570
title: Data on hospitalizations, atmospheric variables, and pollutant concentrations to Fortaleza city, collected by the CAIPORA project.

description: This dataset contains disease-specific environmental and health data primarily focusing on the municipality of Fortaleza and its Metropolitan Region in the state of Ceara, Brazil. The collection includes files in NetCDF format (.nc) for various conditions, such as malignant neoplasms (e.g., lung, stomach, liver, breast, prostate cancer) and infectious diseases (e.g., meningitis, influenza, leptospirosis, dengue, zika, chikungunya). These files are typically used for environmental modeling and geospatial analysis of health outcomes.
DOI: 10.21978/p8md0h
title: IMP-8 PLS Solar Wind Weimer Propagated 60 s Resolution Data in GSE Coordinates
title: IMP-8 Plasma Faraday Cup data

description: IMP-8 PLS propagated solar wind data and linearly interpolated to have the measurements on the minute at 60 s resolution data in GSE coordinates. This data set consists of propagated solar wind data that has first been propagated to a position just outside of the nominal bow shock (about 17, 0, 0 Re) and then linearly interpolated to 1 min resolution using the interp1.m function in MATLAB. The input data for this data set is a 1 min resolution processed solar wind data constructed by Dr. J.M. Weygand. The method of propagation is similar to the minimum variance technique and is outlined in Dan Weimer et al. [2003; 2004]. The basic method is to find the minimum variance direction of the magnetic field in the plane orthogonal to the mean magnetic field direction. This minimum variance direction is then dotted with the difference between final position vector minus the original position vector and the quantity is divided by the minimum variance dotted with the solar wind velocity vector, which gives the propagation time. This method does not work well for shocks and minimum variance directions with tilts greater than 70 degrees of the sun-earth line. This data set was originally constructed by Dr. J.M. Weygand for Prof. R.L. McPherron, who was the principle investigator of two National Science Foundation studies: GEM Grant ATM 02-1798 and a Space Weather Grant ATM 02-08501. These data were primarily used in superposed epoch studies References: Weimer, D. R. (2004), Correction to ‘‘Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique,’’ J. Geophys. Res., 109, A12104, doi:10.1029/2004JA010691. Weimer, D.R., D.M. Ober, N.C. Maynard, M.R. Collier, D.J. McComas, N.F. Ness, C. W. Smith, and J. Watermann (2003), Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique, J. Geophys. Res., 108, 1026, doi:10.1029/2002JA009405.
DOI: 10.21978/p8r646
title: IMP-8 Linearly Interpolated 60 s Resolution PLS data in GSM Coordinates
title: IMP-8 Plasma Faraday Cup data

description: IMP-8 linearly interpolated to have the measurements on the minute at 60 s resolution PLS data in GSM coordinates. This data set consists of processed solar wind data that has been linearly interpolated to 1 min resolution at the position of the spacecraft using the interp1.m function in MATLAB. This data set was originally constructed by Dr. J.M. Weygand for Prof. R.L. McPherron, who was the principle investigator of two National Science Foundation studies: GEM Grant ATM 02-1798 and a Space Weather Grant ATM 02-08501. These data were primarily used in superposed epoch studies and cross correlation studies on solar wind.
DOI: 10.5281/zenodo.18180569
title: Data on hospitalizations, atmospheric variables, and pollutant concentrations to Fortaleza city, collected by the CAIPORA project.

description: This dataset contains disease-specific environmental and health data primarily focusing on the municipality of Fortaleza and its Metropolitan Region in the state of Ceara, Brazil. The collection includes files in NetCDF format (.nc) for various conditions, such as malignant neoplasms (e.g., lung, stomach, liver, breast, prostate cancer) and infectious diseases (e.g., meningitis, influenza, leptospirosis, dengue, zika, chikungunya). These files are typically used for environmental modeling and geospatial analysis of health outcomes.
DOI: 10.21978/p8gp82
title: IMP-8 PLS Solar Wind Weimer Propagated 60 s Resolution Data in GSM Coordinates
title: IMP-8 Plasma Faraday Cup data

description: IMP-8 PLS Weimer propagated solar wind data and linearly interpolated to have the measurements on the minute at 60 s resolution data in GSM coordinates. This data set consists of propagated solar wind data that has first been propagated to a position just outside of the nominal bow shock (about 17, 0, 0 Re) and then linearly interpolated to 1 min resolution using the interp1.m function in MATLAB. The input data for this data set is a 1 min resolution processed solar wind data constructed by Dr. J.M. Weygand. The method of propagation is similar to the minimum variance technique and is outlined in Dan Weimer et al. [2003; 2004]. The basic method is to find the minimum variance direction of the magnetic field in the plane orthogonal to the mean magnetic field direction. This minimum variance direction is then dotted with the difference between final position vector minus the original position vector and the quantity is divided by the minimum variance dotted with the solar wind velocity vector, which gives the propagation time. This method does not work well for shocks and minimum variance directions with tilts greater than 70 degrees of the sun-earth line. This data set was originally constructed by Dr. J.M. Weygand for Prof. R.L. McPherron, who was the principle investigator of two National Science Foundation studies: GEM Grant ATM 02-1798 and a Space Weather Grant ATM 02-08501. These data were primarily used in superposed epoch studies References: Weimer, D. R. (2004), Correction to ‘‘Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique,’’ J. Geophys. Res., 109, A12104, doi:10.1029/2004JA010691. Weimer, D.R., D.M. Ober, N.C. Maynard, M.R. Collier, D.J. McComas, N.F. Ness, C. W. Smith, and J. Watermann (2003), Predicting interplanetary magnetic field (IMF) propagation delay times using the minimum variance technique, J. Geophys. Res., 108, 1026, doi:10.1029/2002JA009405.