cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.z6tfnc
title: Occurrence Download

description: A dataset containing 450 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Geometry POLYGON((-122.97156 57.59091,-122.96524 57.59722,-122.94631 57.61301,-122.9421 57.63825,-122.95122 57.65053,-122.95988 57.65941,-122.97467 57.66647,-122.97612 57.68244,-122.98383 57.69997,-122.9954 57.71049,-123.021 57.714,-123.03678 57.69647,-123.0473 57.67613,-123.04695 57.65509,-123.04309 57.64983,-123.03398 57.63966,-123.03783 57.62668,-123.03012 57.61195,-123.01714 57.60073,-122.9961 57.59267,-122.97156 57.59091))",
 "Geometry POLYGON((-122.69488 58.13364,-122.72005 58.14442,-122.73946 58.14094,-122.75906 58.12784,-122.76771 58.10018,-122.7649 58.08034,-122.75806 58.0601,-122.74466 58.04933,-122.72889 58.04433,-122.71366 58.04014,-122.70327 58.04074,-122.69269 58.04101,-122.6843 58.04336,-122.66551 58.06112,-122.66087 58.08391,-122.66304 58.10138,-122.66633 58.11237,-122.67503 58.12177,-122.68516 58.12811,-122.69028 58.13078,-122.69488 58.13364))"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 450 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008106-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/frwz8m2gnj
title: Physiological buffering and cognitive flexibility drive female-biased stress resilience in a wolf Spider

description: Experiment data in different conditions:
1. Sun heating; 
2. Hot water escape; 
3. Starving tolerance; 
4. Hot tolerance; 
5. Dry tolerance; 
6. Learning and training 1; 
7. Learning and training 2.
DOI: 10.17632/frwz8m2gnj.1
title: Physiological buffering and cognitive flexibility drive female-biased stress resilience in a wolf Spider

description: Experiment data in different conditions:
1. Sun heating; 
2. Hot water escape; 
3. Starving tolerance; 
4. Hot tolerance; 
5. Dry tolerance; 
6. Learning and training 1; 
7. Learning and training 2.
DOI: 10.17632/jx5r674vks.1
title: Dataset of posts from foreign news agency sites by tag "Russia" in 2022-2024

description: The dataset consisted in .XLSX tables divided by countries, and includes columns: data, source, title, fulltext and link (for verifying). 
The data was collected by students of Department of Politology, History and Regional Studies of History Faculty, Irkutsk State University (Russia). Advisor investigator is Prof. Arseniy N. Fartyshev, Candidate of Sci. (in Geography).

Country Number Date coverage Advisor Sources
Turkey 802 2007-2024 Bogdanova Milena Evgenevna YeniSafak, AA, Sabah, Haber7, Dailysabah, Cumhuriyet, Aksam
Israel 310 2021-2024 Bukina Maria Vasilievna Yated
Croatia 488 2021-2024 Vdovkin Aleksei Igorevich Net.hr, tportal
GB 526 2022-2024 Dashinimaeva Selmeg Chingisovna The Economist, The Guardian, BBC
Syria 1595 2013-2024 Demchenkov Mihail Andreevich Sana
Japan 1426 2024 Korytov Andrei japannews.yomiuri
Serbia 9733 2021-2024 Litovchenko Ivan Aleskandrovich Telegraf.rs
USA 823 2023-2024 Mineev Mihail Aleskandrovich New York Times
Germany 2322 2023 Monastyrskiy Daniil Sergeevich N-TV
Armenia 1119 2021-2024 Perendya Daria Aleskeevna Aravot
Sweizerland 2795 2021-2024 Ryzhov Andrei Dmitrievich Watson.ch
Greece 2863 2012-2024 Sadykova Maria Alekseevna Enikos
South Korea 389 2021-2024 Sannikova Elizaveta Sergeevna choson
China 873 2023-2022 Fomina Sofia Ivanovna Xinhua
Finland 1233 2021-2024 Tsyrendorzhieva Valeria Timurovna Yle
Italy 869 2022-2024 Segreeva Elizaveta Antonovna rainews.it
Canada 2146 2024 Fedorova Anastasia Andreevna nationalpost
Venezuela 407 2022-2024 Topuchkanov Dmitriy Sergeevich El Aragueno, Lapatilla, Noticia al Dia
TOTAL 30719
DOI: 10.15468/dl.nub3wp
title: Occurrence Download

description: A dataset containing 962 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Flemingia macrophylla (Willd.) Kuntze ex Merr.)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1945"
 ]
}

 The dataset includes 962 records from 57 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008007-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/fxbshhpwh7
title: Lipidomics analyses of WAT and BAT from wildtype and adipose-tissue specific deletion of ACBP

description: Lipid composition of white and brown adipose tissues from Adipoq-Acbp-/- and Ucp1-Acbp-/- mice housed at room temperature or 4C using liquid chromatography – mass spectrometry (LC-MS) based lipidomics.
DOI: 10.17632/fxbshhpwh7.1
title: Lipidomics analyses of WAT and BAT from wildtype and adipose-tissue specific deletion of ACBP

description: Lipid composition of white and brown adipose tissues from Adipoq-Acbp-/- and Ucp1-Acbp-/- mice housed at room temperature or 4C using liquid chromatography – mass spectrometry (LC-MS) based lipidomics.
DOI: 10.15468/dl.2c59dj
title: Occurrence Download

description: A dataset containing 314265 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Camponotus Mayr, 1861"
 ]
}

 The dataset includes 314265 records from 816 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008095-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/jxynk5xbb8.1
title: Inoculation Powder Segmentation Dataset

description: This dataset, Inoculation Powder Segmentation Dataset (IPSD), contains a collection of images captured during the casting and inoculant powder spraying process in an industrial production line. The main objective of this dataset is to offer valuable resources for training artificial intelligence models aimed at real-time monitoring of the inoculation process in the casting industry.
The IPSD consists of 4,286 images, each with a resolution of 512 × 512 pixels. These images are meticulously annotated with two distinct classes: powder and background. The segmentation of these classes was performed by human experts to ensure the accuracy and reliability of the dataset. This careful annotation process is crucial for the successful training of machine learning models designed to distinguish between inoculant powder and background objects in the images.
Additionally, the dataset provides a wide range of images captured under various conditions, which can help improve the robustness of models when applied to real-world scenarios. The dataset has been carefully curated to include high-quality images that reflect the complexity and variability of the casting process, ensuring that the models trained on this data can generalize well to different operational environments.
DOI: 10.17632/jxynk5xbb8.2
title: Inoculation Powder Segmentation Dataset

description: This dataset, Inoculation Powder Segmentation Dataset (IPSD), contains a collection of images captured during the casting and inoculant powder spraying process in an industrial production line. The main objective of this dataset is to offer valuable resources for training artificial intelligence models aimed at real-time monitoring of the inoculation process in the casting industry.
The IPSD consists of 4,286 images, each with a resolution of 512 × 512 pixels. These images are meticulously annotated with two distinct classes: powder and background. The segmentation of these classes was performed by human experts to ensure the accuracy and reliability of the dataset. This careful annotation process is crucial for the successful training of machine learning models designed to distinguish between inoculant powder and background objects in the images.
Additionally, the dataset provides a wide range of images captured under various conditions, which can help improve the robustness of models when applied to real-world scenarios. The dataset has been carefully curated to include high-quality images that reflect the complexity and variability of the casting process, ensuring that the models trained on this data can generalize well to different operational environments.
DOI: 10.17632/jxynk5xbb8.3
title: Inoculation Powder Segmentation Dataset

description: This dataset, Inoculation Powder Segmentation Dataset (IPSD), contains a collection of images captured during the casting and inoculant powder spraying process in an industrial production line. The main objective of this dataset is to offer valuable resources for training artificial intelligence models aimed at real-time monitoring of the inoculation process in the casting industry.
The IPSD consists of 4,286 images, each with a resolution of 512 × 512 pixels. These images are meticulously annotated with two distinct classes: powder and background. The segmentation of these classes was performed by human experts to ensure the accuracy and reliability of the dataset. This careful annotation process is crucial for the successful training of machine learning models designed to distinguish between inoculant powder and background objects in the images.
Additionally, the dataset provides a wide range of images captured under various conditions, which can help improve the robustness of models when applied to real-world scenarios. The dataset has been carefully curated to include high-quality images that reflect the complexity and variability of the casting process, ensuring that the models trained on this data can generalize well to different operational environments.
DOI: 10.15468/dl.s2ys2r
title: Occurrence Download

description: A dataset containing 45112 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is one of (Brazil, Paraguay, Argentina)",
 "TaxonKey is Eupsittula aurea (J.F.Gmelin, 1788)",
 "Year 1000-2024"
 ]
}

 The dataset includes 45112 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008009-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mq53sm
title: Occurrence Download

description: A dataset containing 1602 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Brazil",
 "TaxonKey is Pyrrhura cruentata (Wied-Neuwied, 1820)",
 "Year 1000-2024"
 ]
}

 The dataset includes 1602 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008010-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x4xpx5
title: Occurrence Download

description: A dataset containing 1050 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Acanthoscurria Ausserer, 1871"
 ]
}

 The dataset includes 1050 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008011-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sfra5p
title: Occurrence Download

description: A dataset containing 1510 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Flemingia strobilifera (L.) W.T.Aiton)",
 "BasisOfRecord is one of (Specimen, Human Observation, Observation, Living Specimen, Machine Observation, Literature Occurrence)",
 "Geometry POLYGON((-180 -90,180 -90,180 90,-180 90,-180 -90))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1945"
 ]
}

 The dataset includes 1510 records from 77 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008012-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ykb4vt
title: Occurrence Download

description: A dataset containing 3732 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Corvus imparatus J.L.Peters, 1929"
 ]
}

 The dataset includes 3732 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008107-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6073/pasta/f42ee1b37eb935d065482f5c20ad835c
title: ASD02 Stream discharge measured at the flumes on watershed N04D at Konza Prairie

description: Stream discharge is measured on a catchment (N04D), with 4-year fire return interval and grazed by bison since 1992. Measurements are taken at 5 minute intervals at a triangular throated flume. The prairie streams are 3rd-order and are intermittent. Daily and stormflow discharge records are available.
DOI: 10.5281/zenodo.12625360
title: AGENT Guidelines for dataflow

description: The AGENT project aims at integrating data from different sources (genebanks, research institutes, international archives) and types (passport, phenotypic, genomic data).

These guidelines have been developed to explain the data flow within the AGENT project and should be useful for other projects.
DOI: 10.5281/zenodo.12625359
title: AGENT Guidelines for dataflow

description: The AGENT project aims at integrating data from different sources (genebanks, research institutes, international archives) and types (passport, phenotypic, genomic data).

These guidelines have been developed to explain the data flow within the AGENT project and should be useful for other projects.

The phenotypic data templates are included.
DOI: 10.5281/zenodo.14989870
title: AGENT Guidelines for dataflow

description: The AGENT project aims at integrating data from different sources (genebanks, research institutes, international archives) and types (passport, phenotypic, genomic data).

These guidelines have been developed to explain the data flow within the AGENT project and should be useful for other projects.

The phenotypic data templates are included.
DOI: 10.5281/zenodo.14989734
title: Additional data from the Col du Lac Blanc site, for the preprint entitled 'On the proper use of temperature screen-level measurements in weather forecasting models over mountains'

description: Details of the dataset are available in the ‘readme_meteo.txt’ file.
DOI: 10.5281/zenodo.14989735
title: Additional data from the Col du Lac Blanc site, for the preprint entitled 'On the proper use of temperature screen-level measurements in weather forecasting models over mountains'

description: Details of the dataset are available in the ‘readme_meteo.txt’ file.
DOI: 10.15468/dl.h8r3jg
title: Occurrence Download

description: A dataset containing 1197 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rhynchopsitta pachyrhyncha (Swainson, 1827)"
 ]
}

 The dataset includes 1197 records from 74 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008108-250227182430271/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4fjxdp
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lobelia villaregalis T.J.Ayers"
 ]
}

 The dataset includes 12 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008013-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6vr3yc
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lobelia villaregalis T.J.Ayers"
 ]
}

 The dataset includes 12 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008110-250227182430271/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.28551230
title: DeepNanoHi-C

description: Single-cell long-read concatemer sequencing (scNanoHi-C) technology provides unique insights into the higher-order chromatin structure across the genome in individual cells, crucial for understanding 3D genome organization. However, the lack of specialized analytical tools for scNanoHi-C data impedes progress, as existing methods, which primarily focus on scHi-C technologies, do not fully address the specific challenges of scNanoHi-C, such as sparsity, cell-specific variability, and complex chromatin interaction networks. Here, we introduce DeepNanoHi-C, a novel deep learning framework specifically designed for scNanoHi-C data, which leverages a multi-step autoencoder and a Sparse Gated Mixture of Experts (MoE) to accurately predict chromatin interactions by imputing sparse contact maps, thereby capturing cell-specific structural features. DeepNanoHi-C effectively captures complex global chromatin contact patterns through the multi-step autoencoder and dynamically selects the most appropriate expert from a pool of experts based on distinct chromatin contact patterns. Furthermore, DeepNanoHi-C integrates multi-scale predictions through a dual-channel prediction net, refining complex interaction information and facilitating comprehensive downstream analyses of chromatin architecture. Experimental validation shows that DeepNanoHi-C outperforms existing methods in distinguishing cell types and demonstrates robust performance in data imputation tasks. Additionally, the framework identifies single-cell 3D genome features, such as cell-specific topologically associating domain (TAD) boundaries, further confirming its ability to accurately model chromatin interactions. Beyond single-cell analysis, DeepNanoHi-C also uncovers conserved genomic structures across species, providing insights into the evolutionary conservation of chromatin organization.
DOI: 10.6084/m9.figshare.28551230.v2
title: DeepNanoHi-C

description: Single-cell long-read concatemer sequencing (scNanoHi-C) technology provides unique insights into the higher-order chromatin structure across the genome in individual cells, crucial for understanding 3D genome organization. However, the lack of specialized analytical tools for scNanoHi-C data impedes progress, as existing methods, which primarily focus on scHi-C technologies, do not fully address the specific challenges of scNanoHi-C, such as sparsity, cell-specific variability, and complex chromatin interaction networks. Here, we introduce DeepNanoHi-C, a novel deep learning framework specifically designed for scNanoHi-C data, which leverages a multi-step autoencoder and a Sparse Gated Mixture of Experts (MoE) to accurately predict chromatin interactions by imputing sparse contact maps, thereby capturing cell-specific structural features. DeepNanoHi-C effectively captures complex global chromatin contact patterns through the multi-step autoencoder and dynamically selects the most appropriate expert from a pool of experts based on distinct chromatin contact patterns. Furthermore, DeepNanoHi-C integrates multi-scale predictions through a dual-channel prediction net, refining complex interaction information and facilitating comprehensive downstream analyses of chromatin architecture. Experimental validation shows that DeepNanoHi-C outperforms existing methods in distinguishing cell types and demonstrates robust performance in data imputation tasks. Additionally, the framework identifies single-cell 3D genome features, such as cell-specific topologically associating domain (TAD) boundaries, further confirming its ability to accurately model chromatin interactions. Beyond single-cell analysis, DeepNanoHi-C also uncovers conserved genomic structures across species, providing insights into the evolutionary conservation of chromatin organization.
DOI: 10.15468/dl.km69xr
title: Occurrence Download

description: A dataset containing 217 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Biofokus",
 "Geometry POLYGON((5.48561 58.72888,5.54817 58.72888,5.54817 58.7712,5.48561 58.7712,5.48561 58.72888))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 217 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008014-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6073/pasta/bcced91893195e7bba9076d91ca42096
title: ASD04 Stream discharge measured at the flumes on watershed N20B at Konza Prairie

description: Stream discharge is measured on a catchment (N20B), with 20-year fire return interval and grazed by bison since 1992. Measurements are taken at 5 minute intervals at a triangular throated flume. The prairie streams are 3rd-order and are intermittent. Daily and stormflow discharge records are available.
DOI: 10.5066/p9atq1q3
title: Juvenile carp survival rates relative to season, habitat and predator species combinations in experimental pond exposures

description: Prey survival rates relative to season, habitat and species of predator from eighteen two-week experiments, from April-October in 2015 and 2016, that were conducted in experimental ponds with differing habitats of artificial structure, vegetation, or no habitat combinations.
DOI: 10.48329/mrh9-5e82
title: CPRD Gold Ethnicity Record March 2025

description: The CPRD Ethnicity Record is comprised of a single derived ethnicity category for each patient in CPRD GOLD and CPRD Aurum. The Ethnicity Records draw ethnicity data from the primary care databases and, for linkage eligible patients, Hospital Episode Statistics (HES) datasets. Access is subject to fees and an approved study protocol. Further information is available at https://cprd.com/cprd-algorithm-derived-data
Data Sources
The CPRD GOLD Ethnicity Record March 2025 is based on the CPRD GOLD March 2025 dataset.
For linkage eligible patients, the following linked data releases were used: CPRD GOLD Source file November 2024, CPRD GOLD HES APC November 2024, CPRD GOLD HES OP November 2024, CPRD GOLD HES A August 2021, CPRD GOLD HES DID August 2021
Contact
Please contact enquiries@cprd.com for further information or if you have any questions.
DOI: 10.15468/dl.dq8xhq
title: Occurrence Download

description: A dataset containing 41 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Lichen herbarium, Oslo (O) UiO",
 "Geometry POLYGON((5.47489 58.71188,5.59393 58.71188,5.59393 58.79616,5.47489 58.79616,5.47489 58.71188))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 41 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008015-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rjths4
title: Occurrence Download

description: A dataset containing 144727 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is one of (Brazil, Argentina, Paraguay)",
 "TaxonKey is Psittacara leucophthalmus (Müller & Pls, 1776)",
 "Year 1000-2024"
 ]
}

 The dataset includes 144727 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008008-250227182400228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.