cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.jkhxg6
title: Occurrence Download

description: A dataset containing 48732 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Mongolia",
 "TaxonKey is Tracheophyta"
 ]
}

 The dataset includes 48732 records from 120 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004888-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.21227/s0nz-kp96
title: ElecsDataset: a 3D semantic segmentation dataset for substation environments

description: ElecsDataset is a specialized 3D semantic segmentation dataset designed for substation environments. It addresses the shortage of domain-specific annotated data in the field of substation 3D semantic segmentation. This dataset offers high-resolution, meticulously annotated point clouds that capture complex equipment structures and real-world occlusions. It consists of data collected from three substations of varying scales. The dataset is systematically partitioned into 6 distinct spatial regions with heterogeneous dimensions. Following standardized evaluation protocols, Area 5 is designated as the testing subset, while the remaining five areas form the training subset. Moreover, the dataset is divided into 10 categories, including non-equipment entities like busbars, electrical wires, the ground, buildings, overhead structures, walls, and miscellaneous objects, as well as substation equipment categorized into small, medium, and large scales. This comprehensive benchmark dataset is optimized for compatibility with deep neural architectures and maintains computational efficiency during model training.
DOI: 10.21227/78dn-eb90
title: ElecsDataset: a 3D semantic segmentation dataset for substation environments

description: ElecsDataset is a specialized 3D semantic segmentation dataset designed for substation environments. It addresses the shortage of domain-specific annotated data in the field of substation 3D semantic segmentation. This dataset offers high-resolution, meticulously annotated point clouds that capture complex equipment structures and real-world occlusions. It consists of data collected from three substations of varying scales. The dataset is systematically partitioned into 6 distinct spatial regions with heterogeneous dimensions. Following standardized evaluation protocols, Area 5 is designated as the testing subset, while the remaining five areas form the training subset. Moreover, the dataset is divided into 10 categories, including non-equipment entities like busbars, electrical wires, the ground, buildings, overhead structures, walls, and miscellaneous objects, as well as substation equipment categorized into small, medium, and large scales. This comprehensive benchmark dataset is optimized for compatibility with deep neural architectures and maintains computational efficiency during model training.
DOI: 10.21227/jtg9-ns60
title: ElecsDataset: a 3D semantic segmentation dataset for substation environments

description: ElecsDataset is a specialized 3D semantic segmentation dataset designed for substation environments. It addresses the shortage of domain-specific annotated data in the field of substation 3D semantic segmentation. This dataset offers high-resolution, meticulously annotated point clouds that capture complex equipment structures and real-world occlusions. It consists of data collected from three substations of varying scales. The dataset is systematically partitioned into 6 distinct spatial regions with heterogeneous dimensions. Following standardized evaluation protocols, Area 5 is designated as the testing subset, while the remaining five areas form the training subset. Moreover, the dataset is divided into 10 categories, including non-equipment entities like busbars, electrical wires, the ground, buildings, overhead structures, walls, and miscellaneous objects, as well as substation equipment categorized into small, medium, and large scales. This comprehensive benchmark dataset is optimized for compatibility with deep neural architectures and maintains computational efficiency during model training.
DOI: 10.21227/18zd-7a87
title: ElecsDataset: a 3D semantic segmentation dataset for substation environments

description: ElecsDataset is a specialized 3D semantic segmentation dataset designed for substation environments. It addresses the shortage of domain-specific annotated data in the field of substation 3D semantic segmentation. This dataset offers high-resolution, meticulously annotated point clouds that capture complex equipment structures and real-world occlusions. It consists of data collected from three substations of varying scales. The dataset is systematically partitioned into 6 distinct spatial regions with heterogeneous dimensions. Following standardized evaluation protocols, Area 5 is designated as the testing subset, while the remaining five areas form the training subset. Moreover, the dataset is divided into 10 categories, including non-equipment entities like busbars, electrical wires, the ground, buildings, overhead structures, walls, and miscellaneous objects, as well as substation equipment categorized into small, medium, and large scales. This comprehensive benchmark dataset is optimized for compatibility with deep neural architectures and maintains computational efficiency during model training.
DOI: 10.60707/dj9g-ze63
title: TEM analysis of N-rich organic phase from angular lithology
DOI: 10.60707/djqz-j552
title: TEM analysis of N-rich organic phase from angular lithology
DOI: 10.60707/14ms-v290
title: TEM analysis of N-rich organic phase from angular lithology
DOI: 10.60707/80rs-sp67
title: TEM analysis of N-rich organic phase from angular lithology
DOI: 10.60707/29hv-r784
title: TEM analysis of N-rich organic phase from angular lithology
DOI: 10.60707/srt7-9871
title: TEM analysis of N-rich organic phase from angular lithology
DOI: 10.60707/ekhc-ds13
title: TEM analysis of N-rich organic phase from angular lithology
DOI: 10.60707/sxw4-y620
title: TEM analysis of N-rich organic phase from angular lithology
DOI: 10.15468/dl.tqgwnk
title: Occurrence Download

description: A dataset containing 295 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Ormosia formosana Kaneh."
 ]
}

 The dataset includes 295 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004889-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7nc8nu
title: Occurrence Download

description: A dataset containing 650 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Styphnolobium japonicum (L.) Schott",
 "Year 1950-2025"
 ]
}

 The dataset includes 650 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004890-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d2k2m6
title: Occurrence Download

description: A dataset containing 4318 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Registro de Fauna Silvestre en el Inventario Nacional Forestal y de Fauna Silvestre-SERFOR, Perú"
 ]
}

 The dataset includes 4318 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004891-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10006299
title: Dataset for A Novel Hysteretic Model for the Evolution of the Soil-Water Retention Curve with Void Ratio submitted to International Journal of Geomechanics

description: This dataset supports the manuscript “A Novel Hysteretic Model for the Evolution of the Soil-Water Retention Curve (SWRC) with Void Ratio,” which has been submitted to the International Journal of Geomechanics. All data have now been fully uploaded here.
DOI: 10.5281/zenodo.10006300
title: Dataset for A Novel Hysteretic Model for the Evolution of the Soil-Water Retention Curve with Void Ratio submitted to International Journal of Geomechanics

description: This dataset supports the manuscript “A Novel Hysteretic Model for the Evolution of the Soil-Water Retention Curve (SWRC) with Void Ratio”, which has been submitted to International Journal of Geomechanics. 

The complete dataset is available in Version 2.
DOI: 10.5281/zenodo.15098970
title: Dataset for A Novel Hysteretic Model for the Evolution of the Soil-Water Retention Curve with Void Ratio submitted to International Journal of Geomechanics

description: This dataset supports the manuscript “A Novel Hysteretic Model for the Evolution of the Soil-Water Retention Curve (SWRC) with Void Ratio,” which has been submitted to the International Journal of Geomechanics. All data have now been fully uploaded here.
DOI: 10.6084/m9.figshare.28062602
title: Dataset of reinforcement and width estimation in GMAW weld bead process

description: In the search for smarter and more efficient welding methods, the measurement of the quality of parts is fundamental but limited since, traditionally, it is necessary to destroy samples of a prodution batch to estimate this quality. However, for an online estimation and possible corrections in production, this dataset brings the data result of an attempt to estimate the width and reinforcement of the weld bead through acquisition techniques with thermographic sensors and profilometers on a motorized table and controlled in a GMAW process.
DOI: 10.6084/m9.figshare.28682111
title: sequence data.rar

description: A total of 33 subjects were enrolled in this study. Bronchoalveolar lavage (BAL) fluid was collected from all the subjects. Bacterial DNA was then isolation and analyzed by 16S rDNA sequencing.
DOI: 10.6084/m9.figshare.28682162
title: DATA Evaluating the Effectiveness of AI-Driven Business Intelligence Systems in the Malaysian Insurance Industry.doc

description: <b>Evaluating the Effectiveness of AI-Driven Business Intelligence Systems in the Malaysian Insurance Industry</b>
DOI: 10.15468/dl.f2nngn
title: Occurrence Download

description: A dataset containing 1565 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tragopan caboti (Gould, 1857), Lophura nycthemera (Linnaeus, 1758), Taxus mairei (Lemée & Lév.) S.Y.Hu ex T.S.Liu, Anoectochilus roxburghii (Wall.) Lindl.)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Country is one of (China, Chinese Taipei)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1990",
 "Year is less than or equal to 2020"
 ]
}

 The dataset includes 1565 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004894-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7u373m
title: Occurrence Download

description: A dataset listing the 30 species recorded in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
 },
 {
 "and" : [
 "GadmGid is one of (COL.8.10_2, COL.8.12_2, COL.8.18_2)",
 "TaxonKey is one of (Mammalia)",
 "Elevation 1490-2200m"
 ]
 }
 ]
}

 The dataset's 30 records were derived from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004893-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13370415
title: Honey bee nurse behavior - HB2017 OH4

description: Dataset of honey bee nurse behavior collected for:

 Charbonneau, Pekora, Scavetta, Harris, Smithson, Sheahan, Tarpy, Linksvayer, and Vojvodic Kruse, Submitted 2024, Honey bee nurse task allocation shows short, frequent cycles of nursing and resting interrupted by occasional bouts of eating in honey bees
DOI: 10.5281/zenodo.13370416
title: Honey bee nurse behavior - HB2017 OH4

description: Dataset of honey bee nurse behavior collected for:

 Charbonneau, Pekora, Scavetta, Harris, Smithson, Sheahan, Tarpy, Linksvayer, and Vojvodic Kruse, Submitted 2024, Honey bee nurse task allocation shows short, frequent cycles of nursing and resting interrupted by occasional bouts of eating in honey bees
DOI: 10.5281/zenodo.15061020
title: Honey bee nurse behavior - HB2017 OH4

description: Dataset of honey bee nurse behavior collected for:

 Charbonneau, Pekora, Scavetta, Harris, Smithson, Sheahan, Tarpy, Linksvayer, and Vojvodic Kruse, Submitted 2024, Honey bee nurse task allocation shows short, frequent cycles of nursing and resting interrupted by occasional bouts of eating in honey bees
DOI: 10.5281/zenodo.15099282
title: Oarfish Simulated Dataset --- PacBio dataset obtained from UHRR cell line

description: This repository contains PacBio-simulated datasets generated from the UHRR cell line using the TKSM simulator for both RSII and SQ2 HiFi protocols.
DOI: 10.5281/zenodo.15099283
title: Oarfish Simulated Dataset --- PacBio dataset obtained from UHRR cell line

description: This repository contains PacBio-simulated datasets generated from the UHRR cell line using the TKSM simulator for both RSII and SQ2 HiFi protocols.
DOI: 10.15468/dl.5z72dm
title: Occurrence Download

description: A dataset containing 349870778 records in GBIF matching the query:
SELECT catalognumber, scientificname, publishingorgkey, institutioncode, datasetkey, gbifid, decimallatitude, decimallongitude, 
 recordedby, identifiedby, eventdate, kingdomkey, phylumkey, classkey, orderkey, familykey, genuskey, subgenuskey, specieskey
 FROM occurrence WHERE
 classkey = 212 AND orderkey IN (1108, 1448, 1446, 724) 
 AND taxonomicstatus = 'ACCEPTED' //newly added 12Feb2025
 AND hascoordinate = 1
 AND hasgeospatialissues = 0
 AND specieskey IS NOT NULL
 AND occurrencestatus = 'PRESENT'
 -- AND (
 -- basisofrecord = 'HUMAN_OBSERVATION'
 -- OR basisofrecord = 'MACHINE_OBSERVATION'
 -- OR basisofrecord = 'OCCURRENCE'
 -- OR basisofrecord = 'LIVING_SPECIMEN'
 -- OR basisofrecord = 'MATERIAL_SAMPLE'
 -- )
 AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE') AND datasetkey NOT IN ('040c5662-da76-4782-a48e-cdea1892d14c') 

 The dataset's 349870778 records were derived from 11186 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004892-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13145/bacdive149545.20251217.10
title: Staphylococcus aureus

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0137264.10fu
title: SH0137264.10FU

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: 10.13145/bacdive149546.20241212.9.2
title: Staphylococcus aureus

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive149546.20251217.10
title: Staphylococcus aureus

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0137265.10fu
title: SH0137265.10FU

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: 10.13145/bacdive149547.20241212.9.2
title: Haemophilus influenzae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive149547.20251217.10
title: Haemophilus influenzae

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0137266.10fu
title: SH0137266.10FU

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: 10.13145/bacdive149548.20241212.9.2
title: Corynebacterium sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0137267.10fu
title: SH0137267.10FU

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: 10.13145/bacdive149548.20251217.10
title: Corynebacterium sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive149549.20230509.8.1
title: Proteus penneri

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0137268.10fu
title: SH0137268.10FU

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: 10.13145/bacdive149549.20251217.10
title: Proteus penneri

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive149550.20241212.9.2
title: Elizabethkingia meningoseptica

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0137269.10fu
title: SH0137269.10FU

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.