cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.gkn8mb
title: Occurrence Download

description: A dataset containing 1322 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Hypericum grandifolium"
 ]
}

 The dataset includes 1322 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080730-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21978/p8290h
title: Geotail Linearly Interpolated 60 s Resolution Tri-axial Fluxgate Magnetometer in GSM Coordinates
title: MGF

description: Geotail 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/p8xk9f
title: Geotail Weimer Propagated using CPI 60 s Resolution Tri-axial Fluxgate Magnetometer in GSM Coordinates
title: MGF

description: Geotail Weimer propagated solar wind data using CPI 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/p8ss5r
title: Geotail Weimer Propagated using CPI 60 s Resolution Tri-axial Fluxgate Magnetometer in GSM Coordinates
title: MGF

description: Geotail Weimer propagated solar wind data using CPI 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/p8j917
title: Geotail Weimer Propagated using LEP 60 s Resolution Tri-axial Fluxgate Magnetometer in GSM Coordinates
title: MGF

description: Geotail Weimer propagated solar wind data using LEP 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/p8p35x
title: Geotail Weimer Propagated using LEP 60 s Resolution Tri-axial Fluxgate Magnetometer in GSE Coordinates
title: MGF

description: Geotail Weimer propagated solar wind data using LEP 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/p8dk9s
title: Geotail Solar Wind Weimer Propagation Details at 1 min Resolution

description: Geotail Weimer propagated solar wind data using CPI and linearly interpolated time delay, cosine angle, and goodness information of propagated data at 1 min Resolution. 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/p88s6g
title: Geotail Solar Wind Weimer Propagation Details at 1 min Resolution

description: Geotail Weimer propagated solar wind data using LEP and linearly interpolated time delay, cosine angle, and goodness information of propagated data at 1 min Resolution. 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: 10.15468/dl.hugwrs
title: Occurrence Download

description: A dataset containing 663 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Colección de Aves Museo Universitario de la Universidad de Antioquia"
 ]
}

 The dataset includes 663 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080731-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22008/fk2/ohi23z/8emhko
title: MB_sector.nc

description: MB by sector. Git hash: 20af941
DOI: 10.15468/dl.7wvjcj
title: Occurrence Download

description: A dataset containing 742 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Accipiter nisus (Linnaeus, 1758)",
 "HasCoordinate is true",
 "Country is Norway",
 "DatasetKey is Norwegian Species Observation Service",
 "Year is 1993",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 742 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0252811-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22008/fk2/ohi23z/ngh2ju
title: MB_SMB_D_BMB.csv

description: MB CSV. Git hash: 20af941
DOI: 10.15468/dl.k5ws97
title: Occurrence Download

description: A dataset containing 2633 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Barbastella barbastellus (Schreber, 1774)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2022",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 2633 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0261392-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4fncs6
title: Occurrence Download

description: A dataset containing 91 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hyloxalus fascianigrus (Grant & Castro-Herrera, 1998)"
 ]
}

 The dataset includes 91 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0106424-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22008/fk2/ohi23z/at38sa
title: MB_region.nc

description: MB region. Git hash: 20af941
DOI: 10.22008/fk2/ohi23z/ce0fmw
title: MB_sector.nc

description: MB by sector. Git hash: 20af941
DOI: 10.15468/dl.zee3n3
title: Occurrence Download

description: A dataset containing 1009718 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "Country is Benin",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1009718 records from 355 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0257624-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zanw9n
title: Occurrence Download

description: A dataset containing 1051 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Picea brachytyla (Franch.) E.Pritz."
 ]
}

 The dataset includes 1051 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0127940-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22008/fk2/ohi23z/gewsd7
title: MB_SMB_D_BMB.csv

description: MB CSV. Git hash: 20af941
DOI: 10.22008/fk2/ohi23z/0nqnl8
title: MB_region.nc

description: MB region. Git hash: 20af941
DOI: 10.15468/dl.7vw3n3
title: Occurrence Download

description: A dataset containing 20082 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is one of (eButterfly Surveys, iNaturalist Research-grade Observations)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "StateProvince is Michigan",
 "TaxonKey is one of (Hesperiidae, Lycaenidae, Nymphalidae, Papilionidae, Pieridae, Riodinidae)",
 "Year 2012-2022"
 ]
}

 The dataset includes 20082 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0257665-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22008/fk2/ohi23z/6arule
title: MB_sector.nc

description: MB by sector. Git hash: 20af941
DOI: 10.15468/dl.n7wgd5
title: Occurrence Download

description: A dataset containing 378 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Herbarium collection of intertidal macroalgae biodiversity along the Northwestern Iberian coast in 2020/2021"
 ]
}

 The dataset includes 378 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0111665-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yrce9m
title: Occurrence Download

description: A dataset containing 382 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Odorrana margaretae (Liu, 1950)"
 ]
}

 The dataset includes 382 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0106445-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22008/fk2/ohi23z/bcr7zw
title: MB_SMB_D_BMB.csv

description: MB CSV. Git hash: 20af941
DOI: 10.15468/dl.4gze2t
title: Occurrence Download

description: A dataset containing 35 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "OccurrenceStatus is Present",
 "TaxonKey is Castor canadensis Kuhl, 1820",
 "Year 2018-2023"
 ]
}

 The dataset includes 35 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0237663-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22008/fk2/ohi23z/lq3dmz
title: MB_region.nc

description: MB region. Git hash: 20af941
DOI: 10.15468/dl.qpeefg
title: Occurrence Download

description: A dataset containing 651 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Larrea cuneifolia Cav."
 ]
}

 The dataset includes 651 records from 60 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0148294-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ghd5zv
title: Occurrence Download

description: A dataset containing 146 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "Month is July",
 "TaxonKey is Trachemys venusta (Gray, 1855)"
 ]
}

 The dataset includes 146 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0106427-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22008/fk2/ohi23z/oisebv
title: MB_sector.nc

description: MB by sector. Git hash: 20af941
DOI: 10.22008/fk2/ohi23z/7qlnr9
title: MB_SMB_D_BMB.csv

description: MB CSV. Git hash: 20af941
DOI: 10.22008/fk2/ohi23z/v1iqjv
title: MB_region.nc

description: MB region. Git hash: 20af941
DOI: 10.15468/dl.363xrc
title: Occurrence Download

description: A dataset containing 229 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Picea chihuahuana Martínez"
 ]
}

 The dataset includes 229 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0237665-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.84cv9p
title: Occurrence Download

description: A dataset containing 44 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Globivenus listeroides (Fischer-Piette & Testud, 1967)"
 ]
}

 The dataset includes 44 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0106452-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vy5v6u
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Paralepas dannevigi (Broch, 1922)"
 ]
}

 The dataset includes 6 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0127942-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22008/fk2/ohi23z/omd578
title: MB_sector.nc

description: MB by sector. Git hash: 20af941
DOI: 10.22008/fk2/ohi23z/9rewsv
title: MB_SMB_D_BMB.csv

description: MB CSV. Git hash: 20af941
DOI: 10.22008/fk2/ohi23z/vyszq7
title: MB_region.nc

description: MB region. Git hash: 20af941