cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14218086
title: Annotated Cows in Aerial Images - Test Set for Livestock Detection Models

description: This dataset contains a test set of aerial images from fields in Juchowo, Poland and Wageningen, the Netherlands, with annotated cows. The annotations are provided in a CSV format containing image file paths, bounding box coordinates (xmin, ymin, xmax, ymax), and labels for the objects (cows). The dataset is intended for evaluating livestock detection models in deep learning, particularly DeepForest.

The images and their corresponding bounding box annotations are included in this archive. The test set consists of 10% of the total images, split from the original dataset created by G.J. Franke and Sander Mucher, which is available in [Harvard Dataverse](https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/N7GJYU). This dataset is part of the GenTORE project (https://www.gentore.eu), focusing on precision livestock farming using automated detection and deep learning techniques.

Contributions

Notebook





Alejandro Coca-Castro (author), The Alan Turing Institute, @acocac



Dataset reference and documentation





Franke, G.J., & Mucher, S. (2021). Annotated cows in aerial images for use in deep learning models. Harvard Dataverse. https://doi.org/10.7910/DVN/N7GJYU
DOI: 10.5281/zenodo.14218941
title: Annotated Cows in Aerial Images - Test Set for Livestock Detection Models

description: This dataset contains a test set of aerial images from fields in Juchowo, Poland and Wageningen, the Netherlands, with annotated cows. The annotations are provided in a CSV format containing image file paths, bounding box coordinates (xmin, ymin, xmax, ymax), and labels for the objects (cows). The dataset is intended for evaluating livestock detection models in deep learning, particularly DeepForest.

The images and their corresponding bounding box annotations are included in this archive. The test set consists of 10% of the total images, split from the original dataset created by G.J. Franke and Sander Mucher, which is available in [Harvard Dataverse](https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/N7GJYU). This dataset is part of the GenTORE project (https://www.gentore.eu), focusing on precision livestock farming using automated detection and deep learning techniques.

Contributions

Notebook





Alejandro Coca-Castro (author), The Alan Turing Institute, @acocac



Dataset reference and documentation





Franke, G.J., & Mucher, S. (2021). Annotated cows in aerial images for use in deep learning models. Harvard Dataverse. https://doi.org/10.7910/DVN/N7GJYU
DOI: 10.5281/zenodo.13851269
title: Annotated Cows in Aerial Images - Test Set for Livestock Detection Models

description: This dataset contains a test set of aerial images from fields in Juchowo, Poland and Wageningen, the Netherlands, with annotated cows. The annotations are provided in a CSV format containing image file paths, bounding box coordinates (xmin, ymin, xmax, ymax), and labels for the objects (cows). The dataset is intended for evaluating livestock detection models in deep learning, particularly DeepForest.

The images and their corresponding bounding box annotations are included in this archive. The test set consists of 10% of the total images, split from the original dataset created by G.J. Franke and Sander Mucher, which is available in [Harvard Dataverse](https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/N7GJYU). This dataset is part of the GenTORE project (https://www.gentore.eu), focusing on precision livestock farming using automated detection and deep learning techniques.

Contributions

Notebook





Alejandro Coca-Castro (author), The Alan Turing Institute, @acocac



Dataset reference and documentation





Franke, G.J., & Mucher, S. (2021). Annotated cows in aerial images for use in deep learning models. Harvard Dataverse. https://doi.org/10.7910/DVN/N7GJYU
DOI: 10.5281/zenodo.14219057
title: Annotated Cows in Aerial Images - Test Set for Livestock Detection Models

description: This dataset contains a test set of aerial images from fields in Juchowo, Poland and Wageningen, the Netherlands, with annotated cows. The annotations are provided in a CSV format containing image file paths, bounding box coordinates (xmin, ymin, xmax, ymax), and labels for the objects (cows). The dataset is intended for evaluating livestock detection models in deep learning, particularly DeepForest.

The images and their corresponding bounding box annotations are included in this archive. The test set consists of 10% of the total images, split from the original dataset created by G.J. Franke and Sander Mucher, which is available in [Harvard Dataverse](https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/N7GJYU). This dataset is part of the GenTORE project (https://www.gentore.eu), focusing on precision livestock farming using automated detection and deep learning techniques.

Contributions

Notebook





Alejandro Coca-Castro (author), The Alan Turing Institute, @acocac



Dataset reference and documentation





Franke, G.J., & Mucher, S. (2021). Annotated cows in aerial images for use in deep learning models. Harvard Dataverse. https://doi.org/10.7910/DVN/N7GJYU
DOI: 10.15468/dl.8jsjwz
title: Occurrence Download

description: A dataset containing 120 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Country is Mexico",
 "Geometry POLYGON((-86.81863 21.14863,-86.81961 21.14309,-86.81299 21.1426,-86.81314 21.14828,-86.81863 21.14863))",
 "HasGeospatialIssue is false",
 "Month is one of (January, February, March, April, May, June, July, August, September, October, November)",
 "OccurrenceStatus is Present",
 "Year 2024-2024"
 ]
}

 The dataset includes 120 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000750-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14060739
title: Single-molecule two- and three-colour FRET studies reveal a hidden transition state in SNARE disassembly by NSF

description: Raw Data for the NC manuscript
DOI: 10.5281/zenodo.14060740
title: Single-molecule two- and three-colour FRET studies reveal a hidden transition state in SNARE disassembly by NSF

description: Raw Data for the NC manuscript
DOI: 10.15468/dl.3z22t5
title: Occurrence Download

description: A dataset containing 675 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Aspidistra elatior Blume"
 ]
}

 The dataset includes 675 records from 131 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000751-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.m3jzr3
title: Occurrence Download

description: A dataset containing 13499 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pogona barbata (Cuvier, 1829)"
 ]
}

 The dataset includes 13499 records from 81 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000753-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3cnkhd
title: Occurrence Download

description: A dataset containing 1636 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia acuminata Benth."
 ]
}

 The dataset includes 1636 records from 62 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000752-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3xeh4n
title: Occurrence Download

description: A dataset containing 984 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-87.94 41.644,-87.524 41.644,-87.524 42.023,-87.94 42.023,-87.94 41.644))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Quercus L."
 ]
}

 The dataset includes 984 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000755-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9rnvte
title: Occurrence Download

description: A dataset containing 984 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-87.94 41.644,-87.524 41.644,-87.524 42.023,-87.94 42.023,-87.94 41.644))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Quercus L."
 ]
}

 The dataset includes 984 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000754-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25574/00361
title: Chandra X-ray Observatory ObsId 00361

description: ACIS IMAGING OF THE STARBURST GALAXY M82
DOI: 10.25574/01302
title: Chandra X-ray Observatory ObsId 01302

description: ACIS IMAGING OF THE STARBURST GALAXY M82
DOI: 10.15468/dl.8w29td
title: Occurrence Download

description: A dataset containing 21246 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Achillea millefolium L.",
 "Geometry POLYGON((-106 36, -80 36, -80 54, -106 54, -106 36))"
 ]
}

 The dataset includes 21246 records from 124 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000756-241125135418005/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.27904938
title: Supplementary Data

description: Supplementary Data for "Environmental DNA vs. Community Science: Strengths and Limitations for Urban Odonata Surveys." Data includes the passed reads from the Nanopore run, and the BOLDigger results for the forward and reverse compliment of each clustered OTU.
DOI: 10.6084/m9.figshare.27904938.v1
title: Supplementary Data

description: Supplementary Data for "Environmental DNA vs. Community Science: Strengths and Limitations for Urban Odonata Surveys." Data includes the passed reads from the Nanopore run, and the BOLDigger results for the forward and reverse compliment of each clustered OTU.
DOI: 10.6084/m9.figshare.27904980
title: Exploring patterns and trends of snake roadkill in the new world: research gaps and mitigation strategies

description: This README file was generated on 2024-01-12 by Daniel Faustino Gomes# General information## Dataset TitleExploring patterns and trends of snake roadkill in the new world: research gaps and mitigation strategies## Date of Data Collection2024## Contributors*Daniel Faustino Gomes:Departamento de Vertebrados, Museu Nacional, Universidade Federal do Rio de Janeiro, Quinta da Boa Vista, São Cristóvão, 20940-040, Rio de Janeiro, Brasil.*Cecília Bueno:Universidade Veiga de Almeida, Campus Tijuca, 20271-901 Rio de Janeiro, RJ, Brasil.*Paulo Passos:Departamento de Vertebrados, Museu Nacional, Universidade Federal do Rio de Janeiro, Quinta da Boa Vista, São Cristóvão, 20940-040, Rio de Janeiro, Brasil.## OverviewThis supplemental dataset, an integral part of our research paper, contains data crucial to understanding the patterns and trends in roadkills of New World snakes discovered in our study. It includes two Excel documents - General data (data, species and landscape use) and Studies used for data collection (Authors, Title and DOI).## Data Formats* **Excel Files:*** **.xlsx/.xls**: Utilized for organizing and presenting data summaries and metadata.# Supplementary File 1.## File FormatExcel File (.xlsx)## Content OverviewThis file presents information such as:first tab - Authors, year of publication, country of publication, size of the highway, type of pavement, lanes roads, traffic volume, maximum speed, mitigation measure for section, sampling time (in months), sampling time, monitoring means, sampling speed, sampling, sampling period in datails; sampling period (morning; afternoon; evening), sampled group, total number (carcass), snakes, N species, Hotspots-hotmoments, near the conservation unit and landscape categories.second tab - list of species present in the 91 studies surveyed, in addition to conservation status (IUCN).third tab - classification of land use according to the authors.# Supplementary File 2.Excel File (.xlsx)## Content OverviewThis file presents survey of studies (N=91), description of: authors + title + DOI## Purpose and Utility* These files contain a broad survey of studies on roadkill snakes in Latin America, with the aim of understanding and filling knowledge gaps.<br><br>
DOI: 10.5281/zenodo.14218954
title: Growth mechanism of oleylammonium-based tin and lead bromide perovskite nanostructures
DOI: 10.5281/zenodo.14218955
title: Growth mechanism of oleylammonium-based tin and lead bromide perovskite nanostructures
DOI: 10.15468/dl.wssuct
title: Occurrence Download

description: A dataset containing 1696 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Puma concolor (Linnaeus, 1771)"
 ]
}

 The dataset includes 1696 records from 80 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000757-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8c4akn
title: Occurrence Download

description: A dataset containing 227 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rangifer tarandus (Linnaeus, 1758)",
 "Country is French Southern Territories",
 "Year is greater than or equal to 1500"
 ]
}

 The dataset includes 227 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000758-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fw39q9
title: Occurrence Download

description: A dataset containing 129 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Agropyron repens (L.) P.Beauv.",
 "Geometry POLYGON((-106 36, -80 36, -80 54, -106 54, -106 36))"
 ]
}

 The dataset includes 129 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000759-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2kpqww
title: CCDC 2374379: Experimental Crystal Structure Determination

description: Related Article: Guo-Yang Ma, Ya-Fei Li, Qing Xu, Yue-Yao Ma, Ya-Wen Li, Guo-Qiang Gong, Ning Zhang, Tan Dang, Kai-Kai Wang|2024|Tetrahedron|168|134328|doi:10.1016/j.tet.2024.134328
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2krc8z
title: CCDC 2375941: Experimental Crystal Structure Determination

description: Related Article: Paulina Kalle, Stanislav I. Bezzubov, Lyudmila G. Kuzmina, Andrei V. Churakov|2024|Cryst.Growth Des.|24|9173|doi:10.1021/acs.cgd.4c01197
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15468/dl.gt3upn
title: Occurrence Download

description: A dataset containing 8440 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Amorpha canescens Pursh",
 "Geometry POLYGON((-106 36, -80 36, -80 54, -106 54, -106 36))"
 ]
}

 The dataset includes 8440 records from 84 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000760-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uca3vs
title: Occurrence Download

description: A dataset containing 9437 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Andropogon gerardi Vitman",
 "Geometry POLYGON((-106 36, -80 36, -80 54, -106 54, -106 36))"
 ]
}

 The dataset includes 9437 records from 110 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000763-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qddpbe
title: Occurrence Download

description: A dataset containing 552 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rattus rattus (Linnaeus, 1758)",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "Year is greater than or equal to 1500"
 ]
}

 The dataset includes 552 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000764-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9u9m4k
title: Occurrence Download

description: A dataset containing 67 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "Geometry POLYGON((-149.46214 59.9818,-149.29424 59.9818,-149.29424 60.13958,-149.46214 60.13958,-149.46214 59.9818))",
 "TaxonKey is Eumetopias jubatus (Schreber, 1776)"
 ]
}

 The dataset includes 67 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000765-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gz8ecr
title: Occurrence Download

description: A dataset containing 48878 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lavandula angustifolia Mill."
 ]
}

 The dataset includes 48878 records from 634 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000762-241125135418005/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh0210383.10fu
title: SH0210383.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0210384.10fu
title: SH0210384.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0210385.10fu
title: SH0210385.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0210386.10fu
title: SH0210386.10FU

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