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

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000979-171219132708484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.haogoy
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001229-171219132708484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tfw9ev
title: Occurrence Download

description: A dataset containing 291 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Anolis scypheus Cope, 1864)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 291 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0023187-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3re2tb
title: Occurrence Download

description: A dataset containing 7054 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lycalopex sechurae (Thomas, 1900)"
 ]
}

 The dataset includes 7054 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0234072-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mdgzim
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017250-190415153152247/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.slc7js
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001233-171219132708484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cfp63q
title: Occurrence Download

description: A dataset containing 172526 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Heracleum mantegazzianum Sommier & Levier)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 172526 records from 500 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0075558-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9vc3hh
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Country is Mexico",
 "Geometry POLYGON((-98.91165 18.9864,-98.66218 18.9864,-98.66218 19.30001,-98.91165 19.30001,-98.91165 18.9864))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Mephitis macroura macroura"
 ]
}

 The dataset includes 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0235630-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bzhj37
title: Occurrence Download

description: A dataset containing 673732484 species occurrences available in GBIF matching the query:
{
 "or" : [
 "DatasetKey is Artportalen (Swedish Species Observation System)",
 "DatasetKey is EOD – eBird Observation Dataset",
 "DatasetKey is INPN - Données flore des CBN agrégées par la FCBN",
 "DatasetKey is Norwegian Species Observation Service",
 "DatasetKey is Dutch Vegetation Database",
 "DatasetKey is Ringing and recovery database of birds (TIPU)",
 "DatasetKey is BirdLife Australia, Birdata",
 "DatasetKey is Southern African Bird Atlas Project 2",
 "DatasetKey is NSW BioNet Atlas",
 "DatasetKey is Anillamiento SEO_Bird ringing"
 ]
}

 The dataset includes 673732484 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002869-170925132151566/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xf18vs
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028627-190415153152247/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qwnyny
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "Country is Bosnia and Herzegovina",
 "Geometry POLYGON((13.57794 45.92625,12.98253 45.20765,15.44629 42.70283,18.60811 42.08689,19.7784 43.3393,19.92212 45.57722,16.49339 47.01441,13.57794 45.92625))",
 "TaxonKey is Aquila chrysaetos (Linnaeus, 1758)"
 ]
}

 The dataset includes 19 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0235631-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hr5xua
title: Occurrence Download

description: A dataset containing 9537 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Chlorestes notata (G.C.Reich, 1793)"
 ]
}

 The dataset includes 9537 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0255059-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.srs2c1
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000381-190813142620410/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/8699350
title: Trending Youtube Video Statistics (113 Countries)
DOI: 10.15468/dl.whyuwd
title: Occurrence Download

description: A dataset containing 1891435655 species occurrences available in GBIF matching the query:
{ }

 The dataset includes 1891435655 records from 17878 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002882-170925132151566/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s26x45
title: Occurrence Download

description: A dataset containing 4972 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Euryomyrtus Schauer"
 ]
}

 The dataset includes 4972 records from 44 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000778-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8ud675
title: Occurrence Download

description: A dataset containing 17005 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "TaxonKey is Rana catesbeiana Shaw, 1802"
 ]
}

 The dataset includes 17005 records from 75 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000779-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.43c43a
title: Occurrence Download

description: A dataset containing 295 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Eusideroxylon Teijsm. & Binn."
 ]
}

 The dataset includes 295 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000780-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11169369
title: Estrategia de entrenamiento físico en pacientes isquemicos con disfunción del ventrículo izquierdo.

description: Se efectuará un estudio prospectivo, intervencionista, longitudinal con un método probabilístico no aleatorio, dónde el universo de estudio serán todos los pacientes isquemicos que asistan a consulta de rehabilitación cardiovascular y cumplan los criterios de inclusion. Estos serán sometidos a un programa de entrenamiento físico durante 12 semanas y se les medirá el NTpro-BNP en sangre
DOI: 10.5281/zenodo.7995650
title: Estrategia de entrenamiento físico en pacientes isquemicos con disfunción del ventrículo izquierdo.

description: Se efectuará un estudio prospectivo, intervencionista, longitudinal con un método probabilístico no aleatorio, dónde el universo de estudio serán todos los pacientes isquemicos que asistan a consulta de rehabilitación cardiovascular y cumplan los criterios de inclusion. Estos serán sometidos a un programa de entrenamiento físico durante 12 semanas y se les medirá el NTpro-BNP en sangre
DOI: 10.5281/zenodo.8423483
title: Estrategia de entrenamiento físico en pacientes isquemicos con disfunción del ventrículo izquierdo.

description: Se efectuará un estudio prospectivo, intervencionista, longitudinal con un método probabilístico no aleatorio, dónde el universo de estudio serán todos los pacientes isquemicos que asistan a consulta de rehabilitación cardiovascular y cumplan los criterios de inclusion. Estos serán sometidos a un programa de entrenamiento físico durante 12 semanas y se les medirá el NTpro-BNP en sangre
DOI: 10.15468/dl.2eem4b
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Database of animal species of the laboratory of ecosystem theory"
 ]
}

 The dataset includes 24 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000781-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5066/f7h993bh
title: Fatty Acid Signature Data of Potential Yellow-billed Loon Prey in the Arctic Coastal Plain of Alaska, 2009-2011

description: This dataset contains fatty acid data expressed as mass percent of total fatty acids for several species potentially preyed upon by yellow-billed loons.  These data were utilized in a quantitative fatty acid signature analysis to estimate the diet of yellow-billed loons nesting on the Arctic Coastal Plain of Alaska.
DOI: 10.3886/e155161v69
title: Advance Layoff Notice Data from the WARN Act

description: We collect novel and timely data from advance layoff notices filed under the Worker Adjustment and Retraining Notification (WARN) Act. The act requires larger employers to notify affected workers at least 60 days before a potential mass layoff. We assemble WARN data from across the United States, and for many large states our data begin in the 1990s. We aggregate these data into an unbalanced, monthly panel of the state-level number of workers affected by WARN notices, and we update this panel twice a month. We also aggregate this panel to a national-level indicator of job loss (the "WARN factor") using a dynamic factor model.<br>

<b><br>Data Collection</b><br>We update the data twice a month by collecting WARN
notices from state websites. For many states, we have extended our historical
data by using digital archives of the internet and contacting state
officials.<br> <br><b>Citation</b><br>To learn more about
the data and the dynamic factor model, see:<br>Krolikowski, Pawel M. and Kurt G. Lunsford. 2022. “Advance Layoff Notices and Aggregate Job Loss.” Federal Reserve Bank of Cleveland, Working Paper no. 20-03R. https://doi.org/10.26509/frbc-wp-202003R.<br>Krolikowski, Pawel M., and Kurt G. Lunsford. 2024 “Advance Layoff Notices and Aggregate Job Loss.” Journal of Applied Econometrics. https://doi.org/10.1002/jae.3032.<b><br><br></b><b>File Description</b><br>The file labelled WARNFiles_YYYYMMDD.zip in the
main directory contains our most recent data. All data included in this zip
file were collected as of the date listed in the file name. Previous
vintages of our data appear in the `Archived_Vintages’ folder, with the same
naming convention.<br>
<br>The zip files contain three files:<br>
<br>


1. 
README.txt

<br>2. 
WARNData_NSA_YYYYMMDD.csv


 
 This .csv contains the number of workers affected by
 WARN notices by state and month. These data are not seasonally adjusted.
 These data are the input into the dynamic factor model.
 


3. 
WARNFactors_YYYYMMDD.csv


 
 This .csv contains the output of the dynamic factor
 model. The output is labeled as follows:
 
 WARN Factor: the estimates of the factor from the
 dynamic factor model.
 MSE: the estimated mean squared errors
 of the WARN factor.
 WARN_hat: the number of workers affected by
 WARN notices as implied by the WARN factor.
 WARN_sum: the sum of the number of
 workers affected by WARN notices from several states that form a
 balanced panel beginning in January 2006. These states can change every
 update.<b>Disclaimer</b><br>These data are
updated by the authors and are not an official product of the Federal Reserve
Bank of Cleveland.<br>
description: Smallest Geographic Unit: State
DOI: 10.3886/e155161v71
title: Advance Layoff Notice Data from the WARN Act

description: We collect novel and timely data from advance layoff notices filed under the Worker Adjustment and Retraining Notification (WARN) Act. The act requires larger employers to notify affected workers at least 60 days before a potential mass layoff. We assemble WARN data from across the United States, and for many large states our data begin in the 1990s. We aggregate these data into an unbalanced, monthly panel of the state-level number of workers affected by WARN notices, and we update this panel twice a month. We also aggregate this panel to a national-level indicator of job loss (the "WARN factor") using a dynamic factor model.<br>

<b><br>Data Collection</b><br>We update the data twice a month by collecting WARN
notices from state websites. For many states, we have extended our historical
data by using digital archives of the internet and contacting state
officials.<br> <br><b>Citation</b><br>To learn more about
the data and the dynamic factor model, see:<br>Krolikowski, Pawel M. and Kurt G. Lunsford. 2022. “Advance Layoff Notices and Aggregate Job Loss.” Federal Reserve Bank of Cleveland, Working Paper no. 20-03R. https://doi.org/10.26509/frbc-wp-202003R.<br>Krolikowski, Pawel M., and Kurt G. Lunsford. 2024 “Advance Layoff Notices and Aggregate Job Loss.” Journal of Applied Econometrics. https://doi.org/10.1002/jae.3032.<b><br><br></b><b>File Description</b><br>The file labelled WARNFiles_YYYYMMDD.zip in the
main directory contains our most recent data. All data included in this zip
file were collected as of the date listed in the file name. Previous
vintages of our data appear in the `Archived_Vintages’ folder, with the same
naming convention.<br>
<br>The zip files contain three files:<br>
<br>


1. 
README.txt

<br>2. 
WARNData_NSA_YYYYMMDD.csv


 
 This .csv contains the number of workers affected by
 WARN notices by state and month. These data are not seasonally adjusted.
 These data are the input into the dynamic factor model.
 


3. 
WARNFactors_YYYYMMDD.csv


 
 This .csv contains the output of the dynamic factor
 model. The output is labeled as follows:
 
 WARN Factor: the estimates of the factor from the
 dynamic factor model.
 MSE: the estimated mean squared errors
 of the WARN factor.
 WARN_hat: the number of workers affected by
 WARN notices as implied by the WARN factor.
 WARN_sum: the sum of the number of
 workers affected by WARN notices from several states that form a
 balanced panel beginning in January 2006. These states can change every
 update.<b>Disclaimer</b><br>These data are
updated by the authors and are not an official product of the Federal Reserve
Bank of Cleveland.<br>
description: Smallest Geographic Unit: State
DOI: 10.3886/e155161v72
title: Advance Layoff Notice Data from the WARN Act

description: We collect novel and timely data from advance layoff notices filed under the Worker Adjustment and Retraining Notification (WARN) Act. The act requires larger employers to notify affected workers at least 60 days before a potential mass layoff. We assemble WARN data from across the United States, and for many large states our data begin in the 1990s. We aggregate these data into an unbalanced, monthly panel of the state-level number of workers affected by WARN notices, and we update this panel twice a month. We also aggregate this panel to a national-level indicator of job loss (the "WARN factor") using a dynamic factor model.<br>

<b><br>Data Collection</b><br>We update the data twice a month by collecting WARN
notices from state websites. For many states, we have extended our historical
data by using digital archives of the internet and contacting state
officials.<br> <br><b>Citation</b><br>To learn more about
the data and the dynamic factor model, see:<br>Krolikowski, Pawel M. and Kurt G. Lunsford. 2022. “Advance Layoff Notices and Aggregate Job Loss.” Federal Reserve Bank of Cleveland, Working Paper no. 20-03R. https://doi.org/10.26509/frbc-wp-202003R.<br>Krolikowski, Pawel M., and Kurt G. Lunsford. 2024 “Advance Layoff Notices and Aggregate Job Loss.” Journal of Applied Econometrics. https://doi.org/10.1002/jae.3032.<b><br><br></b><b>File Description</b><br>The file labelled WARNFiles_YYYYMMDD.zip in the
main directory contains our most recent data. All data included in this zip
file were collected as of the date listed in the file name. Previous
vintages of our data appear in the `Archived_Vintages’ folder, with the same
naming convention.<br>
<br>The zip files contain three files:<br>
<br>


1. 
README.txt

<br>2. 
WARNData_NSA_YYYYMMDD.csv


 
 This .csv contains the number of workers affected by
 WARN notices by state and month. These data are not seasonally adjusted.
 These data are the input into the dynamic factor model.
 


3. 
WARNFactors_YYYYMMDD.csv


 
 This .csv contains the output of the dynamic factor
 model. The output is labeled as follows:
 
 WARN Factor: the estimates of the factor from the
 dynamic factor model.
 MSE: the estimated mean squared errors
 of the WARN factor.
 WARN_hat: the number of workers affected by
 WARN notices as implied by the WARN factor.
 WARN_sum: the sum of the number of
 workers affected by WARN notices from several states that form a
 balanced panel beginning in January 2006. These states can change every
 update.<b>Disclaimer</b><br>These data are
updated by the authors and are not an official product of the Federal Reserve
Bank of Cleveland.<br>
description: Smallest Geographic Unit: State
DOI: 10.3886/e155161v74
title: Advance Layoff Notice Data from the WARN Act

description: We collect novel and timely data from advance layoff notices filed under the Worker Adjustment and Retraining Notification (WARN) Act. The act requires larger employers to notify affected workers at least 60 days before a potential mass layoff. We assemble WARN data from across the United States, and for many large states our data begin in the 1990s. We aggregate these data into an unbalanced, monthly panel of the state-level number of workers affected by WARN notices, and we update this panel twice a month. We also aggregate this panel to a national-level indicator of job loss (the "WARN factor") using a dynamic factor model.<br>

<b><br>Data Collection</b><br>We update the data twice a month by collecting WARN
notices from state websites. For many states, we have extended our historical
data by using digital archives of the internet and contacting state
officials.<br> <br><b>Citation</b><br>To learn more about
the data and the dynamic factor model, see:<br>Krolikowski, Pawel M. and Kurt G. Lunsford. 2022. “Advance Layoff Notices and Aggregate Job Loss.” Federal Reserve Bank of Cleveland, Working Paper no. 20-03R. https://doi.org/10.26509/frbc-wp-202003R.<br>Krolikowski, Pawel M., and Kurt G. Lunsford. 2024 “Advance Layoff Notices and Aggregate Job Loss.” Journal of Applied Econometrics. https://doi.org/10.1002/jae.3032.<b><br><br></b><b>File Description</b><br>The file labelled WARNFiles_YYYYMMDD.zip in the
main directory contains our most recent data. All data included in this zip
file were collected as of the date listed in the file name. Previous
vintages of our data appear in the `Archived_Vintages’ folder, with the same
naming convention.<br>
<br>The zip files contain three files:<br>
<br>


1. 
README.txt

<br>2. 
WARNData_NSA_YYYYMMDD.csv


 
 This .csv contains the number of workers affected by
 WARN notices by state and month. These data are not seasonally adjusted.
 These data are the input into the dynamic factor model.
 


3. 
WARNFactors_YYYYMMDD.csv


 
 This .csv contains the output of the dynamic factor
 model. The output is labeled as follows:
 
 WARN Factor: the estimates of the factor from the
 dynamic factor model.
 MSE: the estimated mean squared errors
 of the WARN factor.
 WARN_hat: the number of workers affected by
 WARN notices as implied by the WARN factor.
 WARN_sum: the sum of the number of
 workers affected by WARN notices from several states that form a
 balanced panel beginning in January 2006. These states can change every
 update.<b>Disclaimer</b><br>These data are
updated by the authors and are not an official product of the Federal Reserve
Bank of Cleveland.<br>
description: Smallest Geographic Unit: State