cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.13026/cc78-ad74
title: OpenOximetry Repository

description: The OpenOximetry Repository is a structured database designed to store
clinical and laboratory pulse oximetry data and allows for consolidation of
data sets held by collaborating organizations. Matched or independent readings
of oxygen saturations, arterial blood gas samples, high frequency processed
and unprocessed waveforms, and other physiologic metadata are supported (e.g.
skin color readings). Contribution of data to the repository is encouraged; a
data dictionary and standardized data collection protocols are provided to
ensure consistent data archival and interpretation. The goal of this dataset
is to enable researchers to interrogate the effects of physiologic and device
variables on pulse oximeter performance.

A set of controlled desaturation studies is included in the initial release
with ongoing updates planned as more data are available from both controlled
lab desaturation studies and real world prospective clinical trials. Data
captured during these studies may include paired pulse oximeter and arterial
blood gas readings throughout a range of oxygen saturations, patient
demographics and comorbidities, longitudinal quantitative and qualitative skin
color measurement (using multiple methods  at multiple anatomic locations),
finger diameter, continuous ECG, arterial blood pressure, EtCO2/EtO2,
unprocessed photoplethysmography (PPG), pH, PaCO2, hemoglobin, met-Hgb, CO-
Hgb, respiratory rate and multiple other variables depending on the data
source
DOI: 10.13026/e821-1858
title: OpenOximetry Repository

description: The OpenOximetry Repository is a structured database designed to store
clinical and laboratory pulse oximetry data and allows for consolidation of
data sets held by collaborating organizations. Matched or independent readings
of oxygen saturations, arterial blood gas samples, high frequency processed
and unprocessed waveforms, and other physiologic metadata are supported (e.g.
skin color readings). Contribution of data to the repository is encouraged; a
data dictionary and standardized data collection protocols are provided to
ensure consistent data archival and interpretation. The goal of this dataset
is to enable researchers to interrogate the effects of physiologic and device
variables on pulse oximeter performance.

A set of controlled desaturation studies is included in the initial release
with ongoing updates planned as more data are available from both controlled
lab desaturation studies and real world prospective clinical trials. Data
captured during these studies may include paired pulse oximeter and arterial
blood gas readings throughout a range of oxygen saturations, patient
demographics and comorbidities, longitudinal quantitative and qualitative skin
color measurement (using multiple methods  at multiple anatomic locations),
finger diameter, continuous ECG, arterial blood pressure, EtCO2/EtO2,
unprocessed photoplethysmography (PPG), pH, PaCO2, hemoglobin, met-Hgb, CO-
Hgb, respiratory rate and multiple other variables depending on the data
source.
DOI: 10.13026/yq6c-z215
title: OpenOximetry Repository

description: The OpenOximetry Repository is a structured database designed to store
clinical and laboratory pulse oximetry data and allows for consolidation of
data sets held by collaborating organizations. Matched or independent readings
of oxygen saturations, arterial blood gas samples, high frequency processed
and unprocessed waveforms, and other physiologic metadata are supported (e.g.
skin color readings). Contribution of data to the repository is encouraged; a
data dictionary and standardized data collection protocols are provided to
ensure consistent data archival and interpretation. The goal of this dataset
is to enable researchers to interrogate the effects of physiologic and device
variables on pulse oximeter performance.

A set of controlled desaturation studies is included in the initial release
with ongoing updates planned as more data are available from both controlled
lab desaturation studies and real world prospective clinical trials. Data
captured during these studies may include paired pulse oximeter and arterial
blood gas readings throughout a range of oxygen saturations, patient
demographics and comorbidities, longitudinal quantitative and qualitative skin
color measurement (using multiple methods  at multiple anatomic locations),
finger diameter, continuous ECG, arterial blood pressure, EtCO2/EtO2,
unprocessed photoplethysmography (PPG), pH, PaCO2, hemoglobin, met-Hgb, CO-
Hgb, respiratory rate and multiple other variables depending on the data
source.
DOI: 10.15468/dl.upyacx
title: Occurrence Download

description: A dataset containing 124 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Portugal",
 "TaxonKey is Anacamptis collina (Banks & Sol. ex Russell) R.M.Bateman, Pridgeon & M.W.Chase",
 "Year 1975-2025"
 ]
}

 The dataset includes 124 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001201-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8ue2n6
title: Occurrence Download

description: A dataset containing 464 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Heleioporus psammophilus Lee & Main, 1954"
 ]
}

 The dataset includes 464 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001179-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pmukse
title: Occurrence Download

description: A dataset containing 246 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Limnoperna fortunei (Dunker, 1857))",
 "BasisOfRecord is one of (Machine Observation, Human Observation, Observation, Literature Occurrence)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 246 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001202-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ub36am
title: Occurrence Download

description: A dataset containing 87 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Human Observation)",
 "TaxonKey is Espeletia occulta subsp. glossophylla (Mattf.) Mavárez"
 ]
}

 The dataset includes 87 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001182-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gma5pf
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Portugal",
 "OccurrenceStatus is Present",
 "TaxonKey is Alchemilla transiens (Buser) Buser",
 "Year 1975-2025"
 ]
}

 The dataset includes 7 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001180-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kwznkt
title: Occurrence Download

description: A dataset containing 48859 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Veronica polita Fr.)",
 "BasisOfRecord is one of (Machine Observation, Human Observation, Observation, Literature Occurrence)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 48859 records from 464 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001181-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/pcra-ouc11187348
title: Put' = Voie = [The way], no. 43 (April-June 1934)

description: [description english/roman)] Irregular frequency
DOI: 10.15468/dl.5h449a
title: Occurrence Download

description: A dataset containing 343366 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Silene latifolia Poir."
 ]
}

 The dataset includes 343366 records from 2230 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017632-230828120925497/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14264152
title: CR7-DET

description: The CR7-DET dataset consists of surface defect images collected from a steel company in China, representing real-world industrial scenarios. It includes seven types of surface defects: inclusion, dents, oil spots, pits, punching, linear defects, and macular spots. All defects are located on the surface of cold-rolled steel plates. The dataset contains 4,140 images and 11,020 annotations. The defect categories are as follows:



0: Inclusion – Nonmetallic inclusions with spot-like or block-like surfaces, exhibiting discontinuous or continuous distribution, and appearing reddish brown, dark gray, or white in color.

1: Dents – Straight and fine grooves with varying depths on the surface of the steel plate.

2: Oil Spots – Periodic punctate spots appearing yellow or black on the surface.

3: Pits – Shallow surface depressions resembling gravures.

4: Punching – Irregular and spaced holes penetrating the surface.

5: Linear – Scratches caused by rollers or other structures.

6: Macular – Yellow and white discoloration on the surface, giving a blooming appearance.


Dataset Structure:



CR7-DET/: The main folder containing the image and label subfolders.

readme.txt: A file containing the description and instructions for using the dataset.


The dataset is organized into two main subfolders:



image/: Contains the actual steel plate images in .jpg format.

label/: Contains the corresponding annotation files in YOLO format. Each annotation file (e.g., dents1.txt) provides detailed information about the defects in the images, including defect type and location. The annotation format follows the YOLO standard, with each line in the label file corresponding to one defect in the image, with the format as follows:

<class_id> <x_center> <y_center> <width> <height>

Where:



class_id corresponds to the defect category (e.g., 0 for Inclusion, 1 for Dents, etc.)

x_center, y_center represent the coordinates of the center of the defect, normalized by the image width and height.

width, height are the width and height of the defect, normalized by the image width and height.




Each annotation file is linked to its corresponding image file, ensuring a one-to-one correspondence between the image and its annotations.



This dataset can be used for defect detection tasks, and users can access both the images and annotations for training and testing machine learning models.
DOI: 10.5281/zenodo.14264153
title: CR7-DET

description: The CR7-DET dataset consists of surface defect images collected from a steel company in China, representing real-world industrial scenarios. It includes seven types of surface defects: inclusion, dents, oil spots, pits, punching, linear defects, and macular spots. All defects are located on the surface of cold-rolled steel plates. The dataset contains 4,140 images and 11,020 annotations. The defect categories are as follows:



0: Inclusion – Nonmetallic inclusions with spot-like or block-like surfaces, exhibiting discontinuous or continuous distribution, and appearing reddish brown, dark gray, or white in color.

1: Dents – Straight and fine grooves with varying depths on the surface of the steel plate.

2: Oil Spots – Periodic punctate spots appearing yellow or black on the surface.

3: Pits – Shallow surface depressions resembling gravures.

4: Punching – Irregular and spaced holes penetrating the surface.

5: Linear – Scratches caused by rollers or other structures.

6: Macular – Yellow and white discoloration on the surface, giving a blooming appearance.


Dataset Structure:



CR7-DET/: The main folder containing the image and label subfolders.

readme.txt: A file containing the description and instructions for using the dataset.


The dataset is organized into two main subfolders:



image/: Contains the actual steel plate images in .jpg format.

label/: Contains the corresponding annotation files in YOLO format. Each annotation file (e.g., dents1.txt) provides detailed information about the defects in the images, including defect type and location. The annotation format follows the YOLO standard, with each line in the label file corresponding to one defect in the image, with the format as follows:

<class_id> <x_center> <y_center> <width> <height>

Where:



class_id corresponds to the defect category (e.g., 0 for Inclusion, 1 for Dents, etc.)

x_center, y_center represent the coordinates of the center of the defect, normalized by the image width and height.

width, height are the width and height of the defect, normalized by the image width and height.




Each annotation file is linked to its corresponding image file, ensuring a one-to-one correspondence between the image and its annotations.



This dataset can be used for defect detection tasks, and users can access both the images and annotations for training and testing machine learning models.
DOI: 10.15468/dl.mkx9rc
title: Occurrence Download

description: A dataset containing 952 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Mexico, United States of America, Guatemala, El Salvador, Honduras, Belize, Costa Rica, Nicaragua, Panama)",
 "OccurrenceStatus is Present",
 "TaxonKey is Scoliosorus ensiformis (Hook.) T.Moore"
 ]
}

 The dataset includes 952 records from 64 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013905-241126133413365/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.27950523
title: <b>Table </b><b>1</b><b>: Types of Sentiment</b><b> Classification</b><b>Table </b><b>2</b><b>: Types of Sentiment</b><b> </b><b>Analysis Techniques/Algorithms</b><b>Table 3: Literature Review Summary Table</b>

description: In the digital era, sentiment analysis—also referred to as opinion mining or emotion AI—is a key tool for determining client sentiment. This paper offers a thorough overview of the most recent methods, uses, and difficulties in sentiment analysis. It includes a range of strategies, including deep learning models, sentiment lexicons, machine learning techniques, and algorithms. The vast range of applications in marketing, managing brand reputation, analyzing customer feedback, analyzing political sentiment, and improving customer service are all covered in this essay. Also covered are the difficulties with sentiment analysis, including sarcasm recognition, linguistic nuance, linguistic and cultural differences, as well as data imbalance and bias. Researchers and practitioners can enhance sentiment analysis methods and create more precise models in this quickly developing field by tackling these issues.
DOI: 10.5281/zenodo.14263392
title: Quantitative assessment of the reservoir-induced and urbanization-induced impact on multivariate flood risk via a nonstationary vine Copula model

description: Here we show the results of the characteristics of the floods at Huayuankou, Lanzhou and Toudaoguai gauges selected by AMS and POT mentod, respectively. Besides that, the inormation about the reservoirs and the imprevious layer in the control catchment of each station is also uploaded.
DOI: 10.5281/zenodo.14263393
title: Quantitative assessment of the reservoir-induced and urbanization-induced impact on multivariate flood risk via a nonstationary vine Copula model

description: Here we show the results of the characteristics of the floods at Huayuankou, Lanzhou and Toudaoguai gauges selected by AMS and POT mentod, respectively. Besides that, the inormation about the reservoirs and the imprevious layer in the control catchment of each station is also uploaded.
DOI: 10.5281/zenodo.13992558
title: New Challenges in Point Cloud Visual Quality Assessment: A Systematic Review (Dataset)

description: This dataset is a collection of annotated information on the scientific papers screened and analyzed for the systematic review of the literature in Point Cloud Visual Quality Assessment. 

The data is structured as follows:



General information



Document title

Authors

Year of publication

Venue (Conference or Journal title)

Citations (number)

URL/DOI






About the content 



Content Type: Point clouds (PC), Colored Point clouds (CPC), Meshes, Dynamic Point Clouds (DPC)

Content source: Source of the content used in a subjective QA test or the evaluation of one or more QA metrics






About metric benchmarks



Subjective Ground-truth Data: Dataset(s) Source of the subjective scores used as ground-truth in a QA metric benchmark

Assessed Metrics: Types of metrics assessed in a benchmark (JPEG standards, IQM, NR, State-of-the-art, others)

Performance Measures: PLCC, SROCC, KRCC, RMSE, OR, others






About Objective QA metrics



Metric: Name given to the metric introduced in this paper

Base: 3D-based or Projection-based

Categories: Categories that characterize the approach of the proposed metric (Feature-based, Learning-Based, Perceptual-based, IQM, others) 

Reference: Full-Reference (FR), Reduced-Reference (RR) or No-Reference (NR)






About Subjective QA experiments



Display: Type of display (2D, 3D, AR, MR, VR) and interaction approach (passive, interactive, 3DoF, 6DoF) used in the described experiment.

Rendering: Type of rendering used to display the stimuli (Points, Squares, Cubes, Surface)

Lab/Remote: The experiment was run in one or more lab environments, or remotely (Lab, Cross-Lab, Remote)

Rating: Subjective rating methodology used in the experiment (ACR, DSIS, PWC, others)

Dataset: Name of the new subjective dataset if the experiment's results were published.

Observers: Number of observers 

Distortion type: Types of distortions applied to the stimuli and assessed in the experiment
DOI: 10.5281/zenodo.13992559
title: New Challenges in Point Cloud Visual Quality Assessment: A Systematic Review (Dataset)

description: This dataset is a collection of annotated information on the scientific papers screened and analyzed for the systematic review of the literature in Point Cloud Visual Quality Assessment. 

The data is structured as follows:



General information



Document title

Authors

Year of publication

Venue (Conference or Journal title)

Citations (number)

URL/DOI






About the content 



Content Type: Point clouds (PC), Colored Point clouds (CPC), Meshes, Dynamic Point Clouds (DPC)

Content source: Source of the content used in a subjective QA test or the evaluation of one or more QA metrics






About metric benchmarks



Subjective Ground-truth Data: Dataset(s) Source of the subjective scores used as ground-truth in a QA metric benchmark

Assessed Metrics: Types of metrics assessed in a benchmark (JPEG standards, IQM, NR, State-of-the-art, others)

Performance Measures: PLCC, SROCC, KRCC, RMSE, OR, others






About Objective QA metrics



Metric: Name given to the metric introduced in this paper

Base: 3D-based or Projection-based

Categories: Categories that characterize the approach of the proposed metric (Feature-based, Learning-Based, Perceptual-based, IQM, others) 

Reference: Full-Reference (FR), Reduced-Reference (RR) or No-Reference (NR)






About Subjective QA experiments



Display: Type of display (2D, 3D, AR, MR, VR) and interaction approach (passive, interactive, 3DoF, 6DoF) used in the described experiment.

Rendering: Type of rendering used to display the stimuli (Points, Squares, Cubes, Surface)

Lab/Remote: The experiment was run in one or more lab environments, or remotely (Lab, Cross-Lab, Remote)

Rating: Subjective rating methodology used in the experiment (ACR, DSIS, PWC, others)

Dataset: Name of the new subjective dataset if the experiment's results were published.

Observers: Number of observers 

Distortion type: Types of distortions applied to the stimuli and assessed in the experiment
DOI: 10.15468/dl.4huy3f
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Daphnimorpha capitellata (H.Hara) Nakai",
 "HasCoordinate is true",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 5 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013906-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x4g5ew
title: Occurrence Download

description: A dataset containing 310 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is RB - Rio de Janeiro Botanical Garden Herbarium Collection",
 "Geometry POLYGON((-44.67353 -22.39872,-44.65556 -22.39859,-44.65527 -22.3817,-44.67309 -22.38113,-44.67353 -22.39872))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 310 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013908-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ekqy9a
title: Occurrence Download

description: A dataset containing 27 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Daphnimorpha kudoi (Makino) Nakai",
 "HasCoordinate is true",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 27 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013910-241126133413365/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.27950631
title: Data for "<b>A Tri-level </b><b>Planning strategy for Integrated Power and Transport Systems Incorporating EV Elastic Charging Behaviors</b>"

description: The data is used only for the work “<b>A Tri-level </b><b>Planning strategy for Integrated Power and Transport Systems Incorporating EV Elastic Charging Behaviors</b>”
DOI: 10.15468/dl.f6krpe
title: Occurrence Download

description: A dataset containing 492 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pterocarya macroptera Batalin",
 "HasCoordinate is true",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 492 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013912-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rgxr8w
title: Occurrence Download

description: A dataset listing the 6 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Machine Observation, Observation)",
 "Country is Türkiye",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "IucnRedListCategory is one of (CR, EN, VU)",
 "OccurrenceStatus is Present",
 "Year 1000-1955"
 ]
}

 The dataset's 6 records were derived from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013900-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.