cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.5shyd7
title: Occurrence Download

description: A dataset containing 2017 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Myrmotherula surinamensis)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "License is one of (CC-BY 4.0, CC0 1.0)"
 ]
}

 The dataset includes 2017 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015248-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rubpu4
title: Occurrence Download

description: A dataset containing 147 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-69.83747 43.26794,-59.56342 43.26794,-59.56342 47.37580,-69.83747 47.37580,-69.83747 43.26794))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Leptodea ochracea"
 ]
}

 The dataset includes 147 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015247-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8rghvr
title: Occurrence Download

description: A dataset containing 6095 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Myrmotherula unicolor)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "License is one of (CC-BY 4.0, CC0 1.0)"
 ]
}

 The dataset includes 6095 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015249-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16746157
title: MOVES 4.0 Updates for the Fuel and Emissions Calculator (FEC): Emission Rate Substitution Spreadsheet

description: This project employs the outputs from MOVES-Matrix 4.0 to generate a data set that can be employed by users of the 2018 Fuel and Emissions Calculator (Version 3.0) to update energy use and emission rates to reflect the latest outputs from the U.S. Environmental Protection Agency’s (USEPA’s) MOVES 4.0 energy use and emission rate model for the Atlanta, GA summer scenario.  The data employed in this project were generated as part of the NCST Project entitled MOVES-Matrix 4.0 for High-Performance On-road Energy Use and Emission Rate Modeling Applications (Lu, et al., 2025).  As described in this report, the team queried more than 90 billion cells within full MOVES-Matrix 4.0 data set to generate MOVES 4.0 data that can be substituted for the older MOVES 2014 data in FEC Version 3.0 for Georgia.  The query output data are contained in an Excel spreadsheet, allowing users to update their personal copies of the FEC.  Should technology transfer funds become available in 2025 from another source, the research team will update and release the next full version of the FEC model, which will be accompanied by an updated user manual.

The data employed in this project were generated as part of another NCST Project, entitled MOVES-Matrix 4.0 for High-Performance On-road Energy Use and Emission Rate Modeling Applications.  The team generated a data set to update the older MOVES energy use and emission rate data in the FEC tables by querying more than 90 billion cells within MOVES-Matrix4.0.  The output data are contained in an Excel spreadsheet so that users can update their current versions of the FEC.  This spreadsheet is entitled “moves4 updated data for fec substitution 2025.xlw” and is provided for download in the NCST archive as an accompanying project output.

User-integration of the replacement Georgia data into a copy of FEC 3.0 also allows user to run scenarios in a teaching setting that allows users to compare MOVES 4.0 case study modeling result to those generated using the older MOVES 2014 energy use and emission rates.  Should technology transfer funds become available in 2025 from another source, the research team will update and release the next full version of the FEC model along with an updated user manual.
DOI: 10.5281/zenodo.16746158
title: MOVES 4.0 Updates for the Fuel and Emissions Calculator (FEC): Emission Rate Substitution Spreadsheet

description: This project employs the outputs from MOVES-Matrix 4.0 to generate a data set that can be employed by users of the 2018 Fuel and Emissions Calculator (Version 3.0) to update energy use and emission rates to reflect the latest outputs from the U.S. Environmental Protection Agency’s (USEPA’s) MOVES 4.0 energy use and emission rate model for the Atlanta, GA summer scenario.  The data employed in this project were generated as part of the NCST Project entitled MOVES-Matrix 4.0 for High-Performance On-road Energy Use and Emission Rate Modeling Applications (Lu, et al., 2025).  As described in this report, the team queried more than 90 billion cells within full MOVES-Matrix 4.0 data set to generate MOVES 4.0 data that can be substituted for the older MOVES 2014 data in FEC Version 3.0 for Georgia.  The query output data are contained in an Excel spreadsheet, allowing users to update their personal copies of the FEC.  Should technology transfer funds become available in 2025 from another source, the research team will update and release the next full version of the FEC model, which will be accompanied by an updated user manual.

The data employed in this project were generated as part of another NCST Project, entitled MOVES-Matrix 4.0 for High-Performance On-road Energy Use and Emission Rate Modeling Applications.  The team generated a data set to update the older MOVES energy use and emission rate data in the FEC tables by querying more than 90 billion cells within MOVES-Matrix4.0.  The output data are contained in an Excel spreadsheet so that users can update their current versions of the FEC.  This spreadsheet is entitled “moves4 updated data for fec substitution 2025.xlw” and is provided for download in the NCST archive as an accompanying project output.

User-integration of the replacement Georgia data into a copy of FEC 3.0 also allows user to run scenarios in a teaching setting that allows users to compare MOVES 4.0 case study modeling result to those generated using the older MOVES 2014 energy use and emission rates.  Should technology transfer funds become available in 2025 from another source, the research team will update and release the next full version of the FEC model along with an updated user manual.
DOI: 10.7929/issda/kkykhm
title: CUPID COVID-19 Survey: parents’ experience of seeking healthcare for their children during COVID-19, March to May 2020.

description: The CUPID COVID-19 National Parents Survey, with a sample of 1,044 parents living throughout Ireland, was conducted from 5th June to 10th June 2020 to assess parents’ experience of seeking healthcare for their children during the restrictive public health measures or “lockdown” introduced in response to the COVID-19 pandemic. The survey asked if parents needed to access healthcare for their child since the schools closed on 12th March and the lockdown was announced, and if they decided not to access the healthcare needed. They we also asked their level of hesitancy on accessing such healthcare during lockdown and as the country entered Phase One of reopening, the public health stage at the time of the survey. Respondents were asked if they had one or more of the following concerns on accessing healthcare for their child: contracting Covid-19, services would be too busy, the Government advice was to stay away, the service was needed by others, worried about being judged for using a service if it wasn’t an emergency, not having a car and didn’t want to use public transport, or some other reason. Those who did access healthcare for their child indicated the type of healthcare accessed including face-to-face consultation with a GP, video or telephone consultation, attendance at the emergency department, or accessing another service. Further questions included where respondents sought information about healthcare during the public health restrictions, the health status of members of their household, their experience of contracting and isolating due to COVID-19, and usual accessibility of healthcare. The stress scale from the Depression Anxiety Stress Scale (DASS-21) (Lovibond & Lovibond, 1995) was also included in the survey. Demographic information was captured on gender, age, marital status, medical card/GP card ownership, county of resident, level of education, age and number of children, and if the respondent was a healthcare worker.
DOI: 10.15468/dl.s265pa
title: Occurrence Download

description: A dataset containing 555 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Hong Kong, Thailand, China, Chinese Taipei, Nepal, Viet Nam, Myanmar, Lao People’s Democratic Republic, India, Bangladesh, Bhutan)",
 "TaxonKey is Python bivittatus",
 "Year 1996-2025"
 ]
}

 The dataset includes 555 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015250-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29218022
title: A Bayesian Criterion for Rerandomization

description: Rerandomization is a powerful tool for experiment-based causal inference because it can better balance covariates than classic randomized designs, thereby leading to more accurate causal effect estimation. However, basic rerandomization and some of its extensions do not prioritize covariates that believed to be strongly associated with potential outcomes. To address this limitation, and thereby create more efficient rerandomization procedures, the quantification of covariate heterogeneity is appealing. We propose a Bayesian criterion for rerandomization that addresses this issue. Both theoretical analyses and numerical studies suggest that rerandomization procedures using Bayesian criterion can outperform existing procedures for balancing covariates. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.6084/m9.figshare.29218022.v1
title: A Bayesian Criterion for Rerandomization

description: Rerandomization is a powerful tool for experiment-based causal inference because it can better balance covariates than classic randomized designs, thereby leading to more accurate causal effect estimation. However, basic rerandomization and some of its extensions do not prioritize covariates that believed to be strongly associated with potential outcomes. To address this limitation, and thereby create more efficient rerandomization procedures, the quantification of covariate heterogeneity is appealing. We propose a Bayesian criterion for rerandomization that addresses this issue. Both theoretical analyses and numerical studies suggest that rerandomization procedures using Bayesian criterion can outperform existing procedures for balancing covariates. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.
DOI: 10.15468/dl.ytkcq7
title: Occurrence Download

description: A dataset containing 216 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "OccurrenceStatus is Present",
 "TaxonKey is Gardenia sokotensis"
 ]
}

 The dataset includes 216 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015251-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9gv7uz
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Caracterización preliminar de la herpetofauna, en el municipio de Medina Cundinamarca, bajo la jurisdicción del Parque Nacional Natural Chingaza"
 ]
}

 The dataset includes 25 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015252-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m2hvrc
title: Occurrence Download

description: A dataset containing 738 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Plantas del municipio de Medina, Cundinamarca y San Juanito, Meta - Proyecto Colombia Bio"
 ]
}

 The dataset includes 738 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015253-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kre2pp
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pomatomus telescopium"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015254-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rxeaqs
title: Occurrence Download

description: A dataset containing 2856 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "OccurrenceStatus is Present",
 "TaxonKey is Crossopteryx febrifuga"
 ]
}

 The dataset includes 2856 records from 72 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015255-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6mm28z
title: Occurrence Download

description: A dataset containing 190 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Myrmotherula sunensis)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "License is one of (CC-BY 4.0, CC0 1.0)"
 ]
}

 The dataset includes 190 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015256-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vrpyyv
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Clusia portlandiana"
 ]
}

 The dataset includes 3 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015258-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p46k5u
title: Occurrence Download

description: A dataset containing 16958 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "Geometry POLYGON((-115.1647 37.65684,-115.378 37.67373,-115.4271 37.50599,-115.4504 37.61634,-115.6779 37.54731,-115.5296 37.24377,-115.7473 37.02409,-116.0185 37.27166,-115.928 36.99763,-115.9906 36.93546,-116.6995 36.9972,-116.8065 37.28315,-116.9092 37.19524,-117.0246 37.43963,-117.1808 37.52838,-117.879 37.40723,-117.9617 37.28309,-117.8731 37.28723,-117.7944 37.07732,-117.9544 37.00084,-117.9515 36.88746,-117.8227 36.66252,-117.5905 36.53221,-117.702 36.54888,-117.7001 36.33985,-117.8002 36.52408,-117.9937 36.60588,-118.0845 36.84138,-118.2462 36.70385,-118.0401 36.46577,-117.8747 35.6612,-118.1077 35.52994,-118.0064 35.30001,-118.067 35.21965,-118.7917 34.78093,-118.4387 34.71956,-117.4643 34.26589,-117.1769 34.41801,-116.4889 34.32896,-116.5167 34.16457,-116.3997 34.13626,-116.4803 34.10575,-116.3148 34.09686,-115.9023 33.67817,-115.4918 33.71225,-115.3721 33.95609,-115.2841 33.87187,-115.5649 34.39096,-115.3579 34.50802,-115.2336 34.50913,-115.1734 34.281,-115.0287 34.49015,-114.9045 34.48742,-114.8483 34.31828,-114.0637 34.52534,-113.7549 34.46349,-113.6928 34.6298,-113.9285 34.76649,-114.0439 35.11463,-113.8177 35.22367,-113.8187 35.40141,-113.7145 35.4153,-113.8815 35.71407,-114.0844 35.81357,-113.816 36.22755,-113.7161 36.52703,-113.7669 36.72443,-113.3502 36.84576,-113.2794 37.29557,-113.8386 37.20913,-113.9632 37.38364,-114.3332 37.26329,-114.575 37.38097,-114.8029 37.22457,-114.8184 37.32927,-114.9423 37.28012,-115.1626 37.47778,-115.1647 37.65684))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Spizella passerina"
 ]
}

 The dataset includes 16958 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015259-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qap4bk
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sus scrofa",
 "Country is Antigua and Barbuda",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015260-250802193616735/datasets/export for details.
DOI: 10.7910/dvn/io3bz1
title: Replication Data for: The World Is More Uncertain than You Think: Assessing and Combating Overconfidence Among 2,000 National Security Officials

description: This file contains the article's online appendix, as well as replication materials.
DOI: 10.17026/pt/iznjnm
title: Data for submission of "Imaging scattering resonances in low-energy inelastic ND3-H2 collisions"

description: Data for submission of &lt;i&gt;"Imaging scattering resonances in low-energy inelastic ND3-H2 collisions"&lt;/i&gt; &lt;br&gt;&lt;br&gt;
Authors: Stach E.J. Kuijpers, David H. Parker, Jérôme Loreau, Ad van der Avoird, Sebastiaan Y.T. van de Meerakker &lt;br&gt;&lt;br&gt;
Available at: &lt;br&gt;
Nature Communications &lt;a href="https://doi.org/10.1038/s41467-025-62511-5"&gt; https://doi.org/10.1038/s41467-025-62511-5&lt;/a&gt; &lt;br&gt;
arXiv &lt;a href="https://doi.org/10.48550/arXiv.2506.11577"&gt; https://doi.org/10.48550/arXiv.2506.11577&lt;/a&gt;
DOI: 10.15468/dl.zu3yhm
title: Occurrence Download

description: A dataset containing 91 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sus scrofa",
 "Country is Armenia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 91 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015261-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29828942
title: school

description: This document contains image data obtained from the indoor parking lot of a certain school, which has undergone structured processing and was finally converted into CSV table data. Since the original images contain a large amount of personal sensitive information such as license plate numbers, the image data has not been uploaded, and only the structured table data is included.
DOI: 10.6084/m9.figshare.29828942.v1
title: school

description: This document contains image data obtained from the indoor parking lot of a certain school, which has undergone structured processing and was finally converted into CSV table data. Since the original images contain a large amount of personal sensitive information such as license plate numbers, the image data has not been uploaded, and only the structured table data is included.
DOI: 10.15468/dl.r9p59r
title: Occurrence Download

description: A dataset containing 284 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "OccurrenceStatus is Present",
 "TaxonKey is Bombax costatum"
 ]
}

 The dataset includes 284 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015262-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4tuatk
title: Occurrence Download

description: A dataset containing 165 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Anfibios y reptiles en el municipio Medina, Cundinamarca - Proyecto Colombia BIO"
 ]
}

 The dataset includes 165 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015264-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f4qd4k
title: Occurrence Download

description: A dataset containing 743 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Myrmotherula urosticta)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "License is one of (CC-BY 4.0, CC0 1.0)"
 ]
}

 The dataset includes 743 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015263-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wq9sgn
title: Occurrence Download

description: A dataset containing 539 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "OccurrenceStatus is Present",
 "TaxonKey is Sophora davidii"
 ]
}

 The dataset includes 539 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015265-250802193616735/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16745909
title: Mobile and Manual Dataset for Greenhouse Tomato Crop

description: Mobile and Manual Dataset for Greenhouse Tomato Crop

SummaryThis dataset contains weekly measurements from 135 tomato plants grown in a greenhouse under 27 different treatment combinations. Data were collected between November 9, 2023, and April 1, 2024, using a mobile station with IoT sensors, manual observations, and yield variables.

LocationThe study was conducted at the Technological Development and Innovation Campus of the University of Antioquia (UdeA), located in Carmen de Viboral, Antioquia, Colombia (2,150 meters above sea level, average temperature: 17°C).

Data Collection- Frequency: Once per week- Number of sessions: 20- Sensor types: Mobile IoT-based station and manual instruments- Treatment groups: 27 combinations- Number of plants: 135

File Information- Format: CSV- Rows: 2,666- Columns: 40- Missing or anomalous values were processed using the method described in Section 4 of the associated documentation.

ContentsThe dataset includes:- Sensor-based environmental measurements- Manually collected variables- Yield-related variables- Treatment identifiers

A detailed explanation of sensors, variables, and structure is available in Section 2 of the documentation.

LicenseCreative Commons Attribution 4.0 International (CC BY 4.0)

ProjectThis dataset was developed as part of the project:"Development of an intelligent and energy-autonomous agriculture platform for continuous monitoring of relevant variables aimed at improving productivity and mitigating environmental impact in Antioquia and Quindío horticultural crops"  (BPIN Code: 2022000100012)  Executed by the University of Antioquia.

Suggested UseThe dataset supports analysis of treatment effects, yield prediction modeling, and development of decision support systems for smart agriculture.

ContactFor more information about dataset usage:Paulina Arregocés-Guerra  PAI Project  University of Antioquia  paulina.arregocesg@udea.edu.co