cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1056117.10fu
title: SH1056117.10FU

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/sh1056120.10fu
title: SH1056120.10FU

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/sh1056121.10fu
title: SH1056121.10FU

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/sh1056123.10fu
title: SH1056123.10FU

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: 10.5281/zenodo.17523561
title: Dataset for "Model-based deep learning enables time-resolved computational microscopy"

description: Introduction

This repository contains the experimental dataset for the paper "Model-based deep learning enables time-resolved computational microscopy" PhotoniX 7, 3 (2026) https://doi.org/10.1186/s43074-025-00222-2.

The dataset includes experimentally collected raw images from a lensless coded ptychographic microscope, along with the corresponding calibration metadata and visualizations. The associated data processing and reconstruction code is available on GitHub at https://github.com/THUHoloLab/STRIVER-deep

For further information, please contact the authors: Yunhui Gao (gyh21@mails.tsinghua.edu.cn), Liangcai Cao (clc@tsinghua.edu.cn)

 

Dataset structure

The tables below summarize the dataset underlying the results presented in this work. As an example, “E13/G96 (20–109)” indicates that the corresponding data can be found in the folder E13/G96 (contained within E13.zip), and the reported results were obtained using raw images indexed from 20 to 109.

 

Results presented in the main text




Figure
Dataset
Description


Fig. 2a-c
E10/G5
Section of a xylophyta dicotyledonous stem


Fig. 2d-f
E11/G1
Quantitative phase target (QPT)


Fig. 3a
E13/G96 (20-109)
Paramecium specimen


Fig. 3b
E19/G25 (85-174)
Paramecium specimen


Fig. 3c, d, g
E13/G97 (70-129)
Paramecium specimen


Fig. 3e, f, h
E13/G97 (190-279)
Paramecium specimen


Fig. 3i-m
E19/G32 (50-139)
Paramecium specimen


Fig. 4a, b
E19/G27 (210-314)
Paramecium specimen


Fig. 4c, d
E19/G28 (20-94)
Paramecium specimen


Fig. 5a-d
E30/G15 (260-369)
Paramecia and rotifers


Fig. 5e-h
E30/G12 (15-124)
Paramecia and rotifers


Fig. 5i-m
E30/G6 (180-289)
Dense rotifer colonies




 

Results presented in the supplementary document




Figure
Dataset
Description


Supplementary Note Fig. 7
E10/G3
Section of a Parascaris equorum uterus


Supplementary Note Fig. 8
E10/G4
Thin tissue slice


Supplementary Note Fig. 9
E10/G2
Thin tissue slice


Supplementary Note Fig. 23
E30/G2 (5-64)
Paramecia and rotifers
DOI: 10.15156/bio/sh1056124.10fu
title: SH1056124.10FU

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: 10.5281/zenodo.17523560
title: Dataset for "Model-based deep learning enables time-resolved computational microscopy"

description: Introduction

This repository contains the experimental dataset for the paper "Model-based deep learning enables time-resolved computational microscopy" PhotoniX 7, 3 (2026) https://doi.org/10.1186/s43074-025-00222-2.

The dataset includes experimentally collected raw images from a lensless coded ptychographic microscope, along with the corresponding calibration metadata and visualizations. The associated data processing and reconstruction code is available on GitHub at https://github.com/THUHoloLab/STRIVER-deep

For further information, please contact the authors: Yunhui Gao (gyh21@mails.tsinghua.edu.cn), Liangcai Cao (clc@tsinghua.edu.cn)

 

Dataset structure

The tables below summarize the dataset underlying the results presented in this work. As an example, “E13/G96 (20–109)” indicates that the corresponding data can be found in the folder E13/G96 (contained within E13.zip), and the reported results were obtained using raw images indexed from 20 to 109.

 

Results presented in the main text




Figure
Dataset
Description


Fig. 2a-c
E10/G5
Section of a xylophyta dicotyledonous stem


Fig. 2d-f
E11/G1
Quantitative phase target (QPT)


Fig. 3a
E13/G96 (20-109)
Paramecium specimen


Fig. 3b
E19/G25 (85-174)
Paramecium specimen


Fig. 3c, d, g
E13/G97 (70-129)
Paramecium specimen


Fig. 3e, f, h
E13/G97 (190-279)
Paramecium specimen


Fig. 3i-m
E19/G32 (50-139)
Paramecium specimen


Fig. 4a, b
E19/G27 (210-314)
Paramecium specimen


Fig. 4c, d
E19/G28 (20-94)
Paramecium specimen


Fig. 5a-d
E30/G15 (260-369)
Paramecia and rotifers


Fig. 5e-h
E30/G12 (15-124)
Paramecia and rotifers


Fig. 5i-m
E30/G6 (180-289)
Dense rotifer colonies




 

Results presented in the supplementary document




Figure
Dataset
Description


Supplementary Note Fig. 7
E10/G3
Section of a Parascaris equorum uterus


Supplementary Note Fig. 8
E10/G4
Thin tissue slice


Supplementary Note Fig. 9
E10/G2
Thin tissue slice


Supplementary Note Fig. 23
E30/G2 (5-64)
Paramecia and rotifers
DOI: 10.15156/bio/sh1056125.10fu
title: SH1056125.10FU

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/sh1056126.10fu
title: SH1056126.10FU

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/sh1056130.10fu
title: SH1056130.10FU

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/sh1056132.10fu
title: SH1056132.10FU

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/sh1056135.10fu
title: SH1056135.10FU

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: 10.15468/dl.yant85
title: Occurrence Download

description: A dataset containing 178448 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Arabidopsis thaliana, Arabidopsis lyrata)",
 "Year 1990-2025"
 ]
}

 The dataset includes 178448 records from 1526 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002388-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bf5xez
title: Occurrence Download

description: A dataset containing 38805 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Pinus uncinata Ramond ex DC."
 ]
}

 The dataset includes 38805 records from 320 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008040-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14630529
title: Raw data to "Measurement force, speed and post-mortem time affect the ratio of CNS grey to white matter elasticity" by Becker et al., 2025

description: This dataset contains the rawdata used in "Measurement force, speed and post-mortem time affect the ratio of CNS grey to white matter elasticity" by Becker et al., 2025.

The dataset contains force-distance curves obtained with a JPK Atomic Force Microscope (AFM) in force spectroscopy mode in the '.jpk-force' file format and the same curves converted to the '.txt' format. It also contains summary tables of the data as we analysed them. The summary tables include information about cantilever bead size, sensitivity and spring constant.

Data are sorted by experiment type. Within experiments, data are sorted by date and animal ID. All data files contained in this dataset contributed to our published results.

For information about the analysis conducted on these data and the AFM data analysis pipeline used for analysis, please consult the referenced publication. Custom-written software for AFM and AFM data analysis is available from https://github.com/FranzeLab/AFM-data-analysis-and-processing/tree/Batchforce_1.1/Batchforce and https://github.com/FranzeLab/AFM-data-analysis-and-processing/tree/master/JuliaBeckerThesis.
DOI: 10.5281/zenodo.14630530
title: Raw data to "Measurement force, speed and post-mortem time affect the ratio of CNS grey to white matter elasticity" by Becker et al., 2025

description: This dataset contains the rawdata used in "Measurement force, speed and post-mortem time affect the ratio of CNS grey to white matter elasticity" by Becker et al., 2025.

The dataset contains force-distance curves obtained with a JPK Atomic Force Microscope (AFM) in force spectroscopy mode in the '.jpk-force' file format and the same curves converted to the '.txt' format. It also contains summary tables of the data as we analysed them. The summary tables include information about cantilever bead size, sensitivity and spring constant.

Data are sorted by experiment type. Within experiments, data are sorted by date and animal ID. All data files contained in this dataset contributed to our published results.

For information about the analysis conducted on these data and the AFM data analysis pipeline used for analysis, please consult the referenced publication. Custom-written software for AFM and AFM data analysis is available from https://github.com/FranzeLab/AFM-data-analysis-and-processing/tree/Batchforce_1.1/Batchforce and https://github.com/FranzeLab/AFM-data-analysis-and-processing/tree/master/JuliaBeckerThesis.
DOI: 10.5281/zenodo.14987825
title: Curvature-based pebble segmentation for reconstructed surface meshes

description: Photos, resulting models, as well as used Python software with a tutorial.



sandbox.ply is the model reconstructed from photos in sandbox_jpegs.tar.bz2.

sandbox_segments.ply is a instance segmentation from that model, computed with the code in python_software.tar.bz2

This software also includes a tutorial.ipynb file.

??_mm.ply are the globally matched ground truth models for the ten pebbles reconstructed from photos in ground_truth_pebbles.tar.bz2.

table_tennis_balls.ply is the accuracy assessment model of stacked table tennis balls with a fixed radius of 20 mm.
DOI: 10.15468/dl.94qgnk
title: Occurrence Download

description: A dataset containing 1331 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((13.13892 55.53667,13.57629 55.60921,13.56463 55.87511,13.24972 56.07091,12.82984 56.06114,13.13892 55.53667))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Formicidae",
 "Year 1851-2025"
 ]
}

 The dataset includes 1331 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007948-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21942/uva.28554332
title: Small maze recorded with a RAE robot

description: This is is a rosbag [1], which is synchronized format of measurements recorded with a small RAE robot [2]. The measurements collected are the robots odometry and imu-data, together with video-frames from the RAE camera [3].
DOI: 10.21942/uva.28554332.v2
title: Small maze recorded with a RAE robot

description: This is is a rosbag [1], which is synchronized format of measurements recorded with a small RAE robot [2]. The measurements collected are the robots odometry and imu-data, together with video-frames from the RAE camera [3].
DOI: 10.21942/uva.28554332.v1
title: Small maze recorded with a RAE robot - Robotics Accessible for Everyone

description: This is is a rosbag [1], which is synchronized format of measurements recorded with a small RAE robot [2]. The measurements collected are the robots odometry and imu-data, together with video-frames from the RAE camera [3].
DOI: 10.6084/m9.figshare.28498778
title: Hydrogen molecule interacting with palladium cluster anchored to graphene vacancy (H<sub>2</sub>Pd<sub>6</sub>C<sub>vac </sub>)

description: The dataset contains 100 ab-initio molecular dynamics simulations generated by DFT. It captures hydrogen molecule interacting with palladium cluster anchored to the graphene vacancy. Different processes such as H<sub>2</sub> scattering after one or multiple bouncing events, as well as H<sub>2</sub> adsorption and H<sub>2</sub> dissociation on the Pd<sub>6</sub> cluster that often involve Pd<sub>6</sub> isomerization are observed.Dataset was originally generated forAlducin, Maite, et al. "Dynamics of cluster isomerization induced by hydrogen adsorption." <i>The Journal of Physical Chemistry C</i> 123.24 (2019): 15236-15243.Each of the 100 AIMD simulations is encoded in the ASE Trajectory object, and corresponding velocities are assumed to be in the basis of lattice vectors multiplied by the integration time of the underlying simulation.
DOI: 10.21227/sefe-ye78
title: ICA_SVD_GLCM_data

description: Volcanic deformation monitoring is crucial for understanding magmatic activity and assessing potential hazards. This project applies Independent Component Analysis (ICA) to multi-temporal InSAR (MT-InSAR) data to separate volcanic deformation signals from atmospheric noise and other error sources over Hawaii’s active volcanoes. By integrating ICA with Singular Value Decomposition (SVD) and Grey-Level Co-occurrence Matrix (GLCM), the study aims to enhance the accuracy of deformation signal extraction. The proposed method will be tested on SAR datasets from Sentinel-1 and other relevant missions, providing insights into long-term surface deformation patterns and improving early warning systems for volcanic activity in Hawaii.
DOI: 10.15468/dl.naf622
title: Occurrence Download

description: A dataset containing 59 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Melanochlamys diomedea (Bergh, 1894)"
 ]
}

 The dataset includes 59 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007949-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.