cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10821435
title: ROCOv2: Radiology Objects in COntext Version 2, An Updated Multimodal Image Dataset

description: Recent advances in deep learning techniques have enabled the development of systems for automatic analysis of medical images. These systems often require large amounts of training data with high quality labels, which is difficult and time consuming to generate.

Here, we introduce Radiology Object in COntext Version 2 (ROCOv2), a multimodal dataset consisting of radiological images and associated medical concepts and captions extracted from the PubMed Open Access subset. Concepts for clinical modality, anatomy (X-ray), and directionality (X-ray) were manually curated and additionally evaluated by a radiologist. Unlike MIMIC-CXR, ROCOv2 includes seven different clinical modalities.

It is an updated version of the ROCO dataset published in 2018, and includes 35,705 new images added to PubMed since 2018, as well as manually curated medical concepts for modality, body region (X-ray) and directionality (X-ray). The dataset consists of 79,789 images and has been used, with minor modifications, in the concept detection and caption prediction tasks of ImageCLEFmedical 2023. The participants had access to the training and validation sets after signing a user agreement.

The dataset is suitable for training image annotation models based on image-caption pairs, or for multi-label image classification using the UMLS concepts provided with each image, e.g., to build systems to support structured medical reporting.

Additional possible use cases for the ROCOv2 dataset include the pre-training of models for the medical domain, and the evaluation evaluation of deep learning models for multi-task learning.
DOI: 10.5281/zenodo.8333644
title: ROCOv2: Radiology Objects in COntext Version 2, An Updated Multimodal Image Dataset

description: Recent advances in deep learning techniques have enabled the development of systems for automatic analysis of medical images. These systems often require large amounts of training data with high quality labels, which is difficult and time consuming to generate.

Here, we introduce Radiology Object in COntext Version 2 (ROCOv2), a multimodal dataset consisting of radiological images and associated medical concepts and captions extracted from the PubMed Open Access subset. Concepts for clinical modality, anatomy (X-ray), and directionality (X-ray) were manually curated and additionally evaluated by a radiologist. Unlike MIMIC-CXR, ROCOv2 includes seven different clinical modalities.

It is an updated version of the ROCO dataset published in 2018, and includes 35,705 new images added to PubMed since 2018, as well as manually curated medical concepts for modality, body region (X-ray) and directionality (X-ray). The dataset consists of 79,789 images and has been used, with minor modifications, in the concept detection and caption prediction tasks of ImageCLEFmedical 2023. The participants had access to the training and validation sets after signing a user agreement.

The dataset is suitable for training image annotation models based on image-caption pairs, or for multi-label image classification using the UMLS concepts provided with each image, e.g., to build systems to support structured medical reporting.

Additional possible use cases for the ROCOv2 dataset include the pre-training of models for the medical domain, and the evaluation evaluation of deep learning models for multi-task learning.
DOI: 10.5281/zenodo.8333645
title: ROCOv2: Radiology Objects in COntext Version 2, An Updated Multimodal Image Dataset

description: Recent advances in deep learning techniques have enabled the development of systems for automatic analysis of medical images. These systems often require large amounts of training data with high quality labels, which is difficult and time consuming to generate.

Here, we introduce Radiology Object in COntext Version 2 (ROCOv2), a multimodal dataset consisting of radiological images and associated medical concepts and captions extracted from the PubMed Open Access subset. Concepts for clinical modality, anatomy (X-ray), and directionality (X-ray) were manually curated and additionally evaluated by a radiologist. Unlike MIMIC-CXR, ROCOv2 includes seven different clinical modalities.

It is an updated version of the ROCO dataset published in 2018, and includes 35,852 new images added to PubMed since 2018, as well as manually curated medical concepts for modality, body region (X-ray) and directionality (X-ray). The dataset consists of 80,080 images and has been used, with minor modifications, in the concept detection and caption prediction tasks of ImageCLEFmedical 2023. The participants had access to the training and validation sets after signing a user agreement.

The dataset is suitable for training image annotation models based on image-caption pairs, or for multi-label image classification using the UMLS concepts provided with each image, e.g., to build systems to support structured medical reporting.

Additional possible use cases for the ROCOv2 dataset include the pre-training of models for the medical domain, and the evaluation evaluation of deep learning models for multi-task learning.

Please do not use this version of the dataset, use the most recent version instead!
DOI: 10.15468/dl.32k6x5
title: Occurrence Download

description: A dataset listing the 6 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry MULTIPOLYGON(((-98.73093 55.74482,-98.73383 55.6418,-98.671 55.51518,-98.54746 55.40398,-98.37386 55.31732,-98.36939 55.31567,-98.1298 55.25582,-97.86949 55.24296,-97.86926 55.24297,-97.69459 55.2619,-97.69379 55.26204,-97.43709 55.33805,-97.43684 55.33817,-97.25366 55.45184,-97.24964 55.45538,-97.23657 55.46729,-97.23532 55.46847,-97.19811 55.50774,-97.19787 55.50803,-97.17027 55.54496,-97.16949 55.54615,-97.16138 55.55907,-97.16108 55.55957,-97.11849 55.70955,-97.11852 55.71161,-97.12406 55.76116,-97.1242 55.76185,-97.20506 55.91287,-97.3738 56.0391,-97.37538 56.03993,-97.59895 56.12266,-97.85915 56.15971,-97.86039 56.15977,-98.15169 56.14334,-98.4129 56.06989,-98.41433 56.06928,-98.51453 56.01882,-98.51735 56.01714,-98.64272 55.89935,-98.65587 55.90295,-98.6595 55.89874,-98.67791 55.86614,-98.69443 55.85052,-98.69562 55.84852,-98.71053 55.80821,-98.73013 55.77333,-98.73069 55.75362,-98.73369 55.74546,-98.73377 55.74496,-98.73093 55.74482)))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "IucnRedListCategory is one of (VU, NT)",
 "License is one of (CC0 1.0, CC-BY 4.0)",
 "OccurrenceStatus is Present",
 "Year 2014-2024"
 ]
}

 The dataset's 6 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004137-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qrqtej
title: Occurrence Download

description: A dataset containing 82 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Anthophora atroalba Lepeletier, 1841",
 "PhylumKey is Arthropoda",
 "Year is greater than or equal to 1992",
 "Year is less than or equal to 2012",
 "Geometry POLYGON((-26 30, 46 30, 46 68, -26 68, -26 30))"
 ]
}

 The dataset includes 82 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004192-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10158807
title: Mapping and modelling global mobility infrastructure stocks, material flows and their embodied greenhouse gas emissions - Data

description: Dynamics of societal material stocks such as buildings and infrastructures and their spatial patterns drive surging resource use and emissions. Building up and maintaining stocks requires large amounts of resources; currently stock-building materials amount to almost 60% of all materials used by humanity. Buildings, infrastructures and machinery shape social practices of production and consumption, thereby creating path dependencies for future resource use. They constitute the physical basis of the spatial organization of most socio-economic activities, for example as mobility networks, urbanization and settlement patterns and various other infrastructures. 
The data in this repository show the material stocks contained in global mobility infrastructure networks at the country-level and mapped at 5arcmins, as well as country-level estimates of material flows for maintenance, replacement and expansion of those infrastructures, and the associated GHG emissions from materials production. This repository contains all data as shown in figures of the article, including the GeoTIFF files for figure 3, and the supplementary data file containing full country-level results.
DataThis dataset includes the following data:

Global maps of material stocks in mobility infrastructure networks at 5 arcmins, separate for all roads, all rail-based infrastructure, as well as in total and per capita
Global country-level material stock estimates for mobility infrastructures
Global country-level estimates of material flows and associated GHG emissions for materials production
Material intensity in mass per area of road (kg/m²) per road type
Material intensity in mass per area of railway track (kg/m²) per railway type
Material intensity in mass per area (kg/m²) per bridges and tunnels
Material intensity factors are available for iron and steel, concrete, asphalt, aggregate (sand & gravel), timber, and other.
Further informationThis dataset complements the following scientific article:
Wiedenhofer, Dominik, André Baumgart, Sarah Matej, Doris Virág, Gerald Kalt, Maud Lanau, Danielle Densley Tingley, u. a. "Mapping and Modelling Global Mobility Infrastructure Stocks, Material Flows and Their Embodied Greenhouse Gas Emissions". Journal of Cleaner Production, November 2023, 139742. https://doi.org/10.1016/j.jclepro.2023.139742.
For further information please see the publication. You can also contact Dominik Wiedenhofer dominik.wiedenhofer(a)boku.ac.at and visit our website to learn more about our project: MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society.
FundingThis research was funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950).
DOI: 10.15468/dl.rmabhb
title: Occurrence Download

description: A dataset containing 67385 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ceratonia siliqua L."
 ]
}

 The dataset includes 67385 records from 331 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004187-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k829up
title: Occurrence Download

description: A dataset containing 42726 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "TaxonKey is Pistacia lentiscus L.",
 "Year 1901-2024"
 ]
}

 The dataset includes 42726 records from 88 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004191-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xyvkpr
title: Occurrence Download

description: A dataset containing 2756 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Chenopodium album L."
 ]
}

 The dataset includes 2756 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004193-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.932ccz
title: Occurrence Download

description: A dataset containing 6646 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "TaxonKey is Pistacia terebinthus L.",
 "Year 1901-2024"
 ]
}

 The dataset includes 6646 records from 65 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004195-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4sqchf
title: Occurrence Download

description: A dataset containing 82 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Anthophora dispar Lepeletier, 1841",
 "PhylumKey is Arthropoda",
 "Year is greater than or equal to 1992",
 "Year is less than or equal to 2012",
 "Geometry POLYGON((-26 30, 46 30, 46 68, -26 68, -26 30))"
 ]
}

 The dataset includes 82 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004196-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.unr4rn
title: Occurrence Download

description: A dataset containing 29327 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "TaxonKey is Cistus albidus L.",
 "Year 1901-2024"
 ]
}

 The dataset includes 29327 records from 101 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004197-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dnj4gv
title: Occurrence Download

description: A dataset containing 5798 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Swiss National Databank of Vascular Plants",
 "TaxonKey is Potentilla crantzii (Crantz) Beck ex Fritsch"
 ]
}

 The dataset includes 5798 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004199-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fyucz3
title: Occurrence Download

description: A dataset containing 5322 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Anthophora plumipes (Pallas, 1772)",
 "PhylumKey is Arthropoda",
 "Year is greater than or equal to 1992",
 "Year is less than or equal to 2012",
 "Geometry POLYGON((-26 30, 46 30, 46 68, -26 68, -26 30))"
 ]
}

 The dataset includes 5322 records from 100 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004198-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u86u5m
title: Occurrence Download

description: A dataset containing 192 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bassaricyon neblina Helgen, Pinto, Kays, Helgen, Tsuchiya, Quinn, Wilson & Maldonado, 2013",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 192 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004200-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7hy7ga
title: Occurrence Download

description: A dataset containing 1498 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "TaxonKey is Cytisus oromediterraneus Rivas Mart. et al.",
 "Year 1901-2024"
 ]
}

 The dataset includes 1498 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004201-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.97x494
title: Occurrence Download

description: A dataset containing 503 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Anthophora retusa (Linnaeus, 1758)",
 "PhylumKey is Arthropoda",
 "Year is greater than or equal to 1992",
 "Year is less than or equal to 2012",
 "Geometry POLYGON((-26 30, 46 30, 46 68, -26 68, -26 30))"
 ]
}

 The dataset includes 503 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004202-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13907802
title: QCA-2024-SCC-UZ14090 R&D data

description: Project Code: QCA-2024-SCC-UZ14090.This project is classified as CONFIDENTIAL. All information, data, and results associated with this project are strictly restricted to authorized personnel only. Any dissemination, distribution, or copying of the project details is strictly prohibited without prior approval from the project lead and the university's Office of Research Compliance.
DOI: 10.5281/zenodo.13907803
title: QCA-2024-SCC-UZ14090 R&D data

description: Project Code: QCA-2024-SCC-UZ14090.This project is classified as CONFIDENTIAL. All information, data, and results associated with this project are strictly restricted to authorized personnel only. Any dissemination, distribution, or copying of the project details is strictly prohibited without prior approval from the project lead and the university's Office of Research Compliance.
DOI: 10.5281/zenodo.13908000
title: MACHINE LEARNING APPROACHES FOR DEMAND FORECASTING: THE IMPACT OF CUSTOMER SATISFACTION ON PREDICTION ACCURACY

description: This study investigates the effectiveness of various machine learning models in predicting product demand based on customer satisfaction data. Four models—Linear Regression, Random Forest, Gradient Boosting, and Support Vector Machine (SVM)—were evaluated using performance metrics, including Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R² score. The results indicate that Gradient Boosting achieved the highest accuracy, with an MAE of 2.56, MSE of 12.75, RMSE of 3.57, and R² score of 0.82, effectively capturing the complex, non-linear relationships inherent in customer satisfaction factors. Random Forest also demonstrated strong performance, while Linear Regression and SVM showed limitations in handling intricate datasets. These findings underscore the importance of utilizing advanced machine learning techniques for accurate demand forecasting, highlighting the critical role of customer satisfaction data in enhancing predictive capabilities. The insights gained from this research can guide organizations in optimizing inventory management and improving customer satisfaction in a rapidly evolving market.
DOI: 10.5281/zenodo.13908001
title: MACHINE LEARNING APPROACHES FOR DEMAND FORECASTING: THE IMPACT OF CUSTOMER SATISFACTION ON PREDICTION ACCURACY

description: This study investigates the effectiveness of various machine learning models in predicting product demand based on customer satisfaction data. Four models—Linear Regression, Random Forest, Gradient Boosting, and Support Vector Machine (SVM)—were evaluated using performance metrics, including Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R² score. The results indicate that Gradient Boosting achieved the highest accuracy, with an MAE of 2.56, MSE of 12.75, RMSE of 3.57, and R² score of 0.82, effectively capturing the complex, non-linear relationships inherent in customer satisfaction factors. Random Forest also demonstrated strong performance, while Linear Regression and SVM showed limitations in handling intricate datasets. These findings underscore the importance of utilizing advanced machine learning techniques for accurate demand forecasting, highlighting the critical role of customer satisfaction data in enhancing predictive capabilities. The insights gained from this research can guide organizations in optimizing inventory management and improving customer satisfaction in a rapidly evolving market.
DOI: 10.5281/zenodo.13906982
title: Data used in "Land use change influence on atmospheric organic gases, aerosols, and radiative effects" (Vella et al., 2024)

description: Model outputs used in the study: "Land use change influence on atmospheric organic gases, aerosols, and radiative effects"
DOI: 10.5281/zenodo.13906983
title: Data used in "Land use change influence on atmospheric organic gases, aerosols, and radiative effects" (Vella et al., 2024)

description: Model outputs used in the study: "Land use change influence on atmospheric organic gases, aerosols, and radiative effects"
DOI: 10.15468/dl.k8yrt2
title: Occurrence Download

description: A dataset containing 886290 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Spain, Portugal, Gibraltar, Andorra)",
 "TaxonKey is Sturnus unicolor Temminck, 1820"
 ]
}

 The dataset includes 886290 records from 94 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004171-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sbt5fx
title: Occurrence Download

description: A dataset containing 1304 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "TaxonKey is Althaea officinalis L.",
 "Year 1901-2024"
 ]
}

 The dataset includes 1304 records from 51 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004204-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5291/ill-data.9-11-2103
title: Investigation of the Mesoscopic Structure of Three Mucin-Mimicking Hydrogels
DOI: 10.5291/ill-data.dir-360
title: characterization of recycled perfluorosulfonic acid membrrane for a circular hydrogen economy
DOI: 10.5291/ill-data.dir-361
title: Clarfying the molecular mechanism of the glass transitions of the amorphous ices
DOI: 10.15468/dl.r9uxbp
title: Occurrence Download

description: A dataset containing 428 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Bombus ruderatus (Fabricius, 1775)",
 "PhylumKey is Arthropoda",
 "Year is greater than or equal to 1992",
 "Year is less than or equal to 2012",
 "Geometry POLYGON((-26 30, 46 30, 46 68, -26 68, -26 30))"
 ]
}

 The dataset includes 428 records from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004205-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.