cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5257/imf/dots/2025-09
title: Direction of Trade Statistics (DOTS) (September 2025 Edition)

description: The Direction of Trade Statistics (DOTS) presents the value of merchandise exports and imports disaggregated according to a country's primary trading partners. Area and world aggregates are included in the display of trade flows between major areas of the world. Reported data is supplemented by estimates whenever such data is not available or current. Imports are reported on a cost, insurance and freight (CIF) basis and exports are reported on a free on board (FOB) basis, with the exception of a few countries for which imports are also available FOB. Time series data includes estimates derived from reports of partner countries for non-reporting and slow-reporting countries.
DOI: 10.21227/xm6k-fh32
title: "free adult videos & clips on xmilfnut.com"

description: "Title: Stream Free Erotic HD Videos Online | xmilfnutDescription: Watch and stream free erotic HD videos online. xmilfnut.com offers daily updates of adult clips and uncensored movies."
DOI: 10.5281/zenodo.17454612
title: A Realistic, High-Skew Financial Transaction Query Log for Concurrency and Caching Research (v1.0)

description: This dataset provides a realistic, high-skew, and noisy query log simulating a financial Online Transaction Processing (OLTP) system. It was created for the ICCPEAS 2025 paper: "Improving Transactional Concurrency in Financial Systems: A Proactive Caching Strategy using LSTM".

Standard synthetic datasets for database research are often too simplistic, failing to capture the chaotic nature of real-world workloads. This dataset is designed to be an advanced "testbed" for research in database concurrency, lock contention, and proactive caching strategies.

The generator script (generate_dataset.py) models four key real-world phenomena:





Workload Skew (Zipf's Law): Uses a Zipfian distribution (a=1.2) to select "hot" users and merchants, ensuring that a small number of entities are responsible for a large percentage of transactions.




Temporal Rhythm (Time of Day): Simulates a diurnal (day/night) pattern, altering transaction probabilities to reflect high-volume business hours and low-volume overnight activity.




Transactional Integrity (The "Signal"): The log is built from three core transaction patterns: 'Purchase', 'Transfer', and 'Balance Check'.




Stochastic Chaos (The "Noise"): To test model robustness, the dataset injects two forms of chaos:





Transaction Failures (5% Rate): Read/Write transactions randomly abort mid-way to mimic "insufficient funds" or "account frozen" errors.




Stochastic Interruptions (2% Rate): A random read_system_audit_log query is injected into the middle of active transactions, breaking the clean patterns.





The dataset is provided as a .csv file with 9 columns (see the related GitHub repository for the full schema). The code that generated this data is also available at the linked repository.
DOI: 10.5281/zenodo.17454611
title: A Realistic, High-Skew Financial Transaction Query Log for Concurrency and Caching Research (v1.0)

description: This dataset provides a realistic, high-skew, and noisy query log simulating a financial Online Transaction Processing (OLTP) system. It was created for the ICCPEAS 2025 paper: "Improving Transactional Concurrency in Financial Systems: A Proactive Caching Strategy using LSTM".

Standard synthetic datasets for database research are often too simplistic, failing to capture the chaotic nature of real-world workloads. This dataset is designed to be an advanced "testbed" for research in database concurrency, lock contention, and proactive caching strategies.

The generator script (generate_dataset.py) models four key real-world phenomena:





Workload Skew (Zipf's Law): Uses a Zipfian distribution (a=1.2) to select "hot" users and merchants, ensuring that a small number of entities are responsible for a large percentage of transactions.




Temporal Rhythm (Time of Day): Simulates a diurnal (day/night) pattern, altering transaction probabilities to reflect high-volume business hours and low-volume overnight activity.




Transactional Integrity (The "Signal"): The log is built from three core transaction patterns: 'Purchase', 'Transfer', and 'Balance Check'.




Stochastic Chaos (The "Noise"): To test model robustness, the dataset injects two forms of chaos:





Transaction Failures (5% Rate): Read/Write transactions randomly abort mid-way to mimic "insufficient funds" or "account frozen" errors.




Stochastic Interruptions (2% Rate): A random read_system_audit_log query is injected into the middle of active transactions, breaking the clean patterns.





The dataset is provided as a .csv file with 9 columns (see the related GitHub repository for the full schema). The code that generated this data is also available at the linked repository.
DOI: 10.5281/zenodo.17412939
title: Data package: Value of participation by Museum Communities

description: The dataset Value of Participation by Museum Communities  was collected by the Cultural Economics Research Group (GIEC/UVa) at the University of Valladolid as part of the RECHARGE Project. Fieldwork took place between late October 2023 and mid-January 2024 in three European cities — Limerick, Prato, and Tallinn — focusing on the communities surrounding the project’s reference museums (Hunt Museum, Museo del Tessuto, and Estonian Maritime Museum). The research aims to estimate the value assigned by local communities to participatory strategies implemented by museums, as well as to analyze the different dimensions and levels of participation involved. The dataset is openly available under the Creative Commons Attribution 4.0 International license, and related publications include Gómez-Zapata et al. (2024) in Socio-Economic Planning Sciences (https://doi.org/10.1016/j.seps.2024.102111)
DOI: 10.5281/zenodo.17412938
title: Data package: Value of participation by Museum Communities

description: The dataset Value of Participation by Museum Communities  was collected by the Cultural Economics Research Group (GIEC/UVa) at the University of Valladolid as part of the RECHARGE Project. Fieldwork took place between late October 2023 and mid-January 2024 in three European cities — Limerick, Prato, and Tallinn — focusing on the communities surrounding the project’s reference museums (Hunt Museum, Museo del Tessuto, and Estonian Maritime Museum). The research aims to estimate the value assigned by local communities to participatory strategies implemented by museums, as well as to analyze the different dimensions and levels of participation involved. The dataset is openly available under the Creative Commons Attribution 4.0 International license, and related publications include Gómez-Zapata et al. (2024) in Socio-Economic Planning Sciences (https://doi.org/10.1016/j.seps.2024.102111)
DOI: 10.15468/dl.ratsvb
title: Occurrence Download

description: A dataset containing 21 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "Geometry POLYGON((119.77079 30.04498,120.43113 30.04535,120.42989 30.5084,119.77079 30.51195,119.77079 30.04498))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Erinaceus amurensis",
 "Year 2020-2025"
 ]
}

 The dataset includes 21 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002440-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b99tcj
title: Occurrence Download

description: A dataset listing the 35 species recorded in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Geometry POINT(43.92921 25.50337)",
 "Geometry POLYGON((43.5708 25.75057,43.30014 25.48316,43.38818 24.994,43.87408 24.89943,44.46759 25.03314,44.33389 25.79296,43.5708 25.75057))",
 "Geometry POLYGON((42.01611 25.97889,42.03314 25.97889,42.03314 26.02429,42.01611 26.02429,42.01611 25.97889))",
 "Geometry POLYGON((41.90261 23.11874,47.25972 23.11874,47.25972 26.32506,41.90261 26.32506,41.90261 23.11874))"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Mammalia"
 ]
}

 The dataset's 35 records were derived from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002418-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17417733
title: Data for: Diniz et al. (2025) Low resilience to deforestation in nocturnal bees is counteracted by a broad resource range and reliance on pioneers. Apidologie. Doi: 10.1007/s13592-025-01231-7

description: Data and code necessary to reproduce the analyses performed in the manuscript:

Diniz. U.M., Guevara-Andino J.E., Brehm G., Rasmussen C., Leonhardt S.D., Keller A. (2025) Low resilience to deforestation in nocturnal bees is counteracted by a broad resource range and reliance on pioneers. Apidologie. Doi: 10.1007/s13592-025-01231-7

Data refers to Megalopta bee individuals sampled in 62 research plots in Northwestern Ecuador, in the reserves Río Canandé and Tesoro Escondido. Bees were collected in 2022 (March-May, and October-December) using light traps. Furthermore, the data also contains interactions sampled via metabarcoded pollen from the bees' bodies. Bees were collected in a chronosequence setting, with plots belonging to a regeneration gradient of active disturbances, secondary forests, and old-growth forests.

Contact: Ugo Mendes Diniz, ugo.diniz@tum.de
DOI: 10.5281/zenodo.17417732
title: Data for: Diniz et al. (2025) Low resilience to deforestation in nocturnal bees is counteracted by a broad resource range and reliance on pioneers. Apidologie. Doi: 10.1007/s13592-025-01231-7

description: Data and code necessary to reproduce the analyses performed in the manuscript:

Diniz. U.M., Guevara-Andino J.E., Brehm G., Rasmussen C., Leonhardt S.D., Keller A. (2025) Low resilience to deforestation in nocturnal bees is counteracted by a broad resource range and reliance on pioneers. Apidologie. Doi: 10.1007/s13592-025-01231-7

Data refers to Megalopta bee individuals sampled in 62 research plots in Northwestern Ecuador, in the reserves Río Canandé and Tesoro Escondido. Bees were collected in 2022 (March-May, and October-December) using light traps. Furthermore, the data also contains interactions sampled via metabarcoded pollen from the bees' bodies. Bees were collected in a chronosequence setting, with plots belonging to a regeneration gradient of active disturbances, secondary forests, and old-growth forests.

Contact: Ugo Mendes Diniz, ugo.diniz@tum.de
DOI: 10.15468/dl.67dz6g
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Bauhinia racemosa"
 ]
}

 The dataset includes 13 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002441-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9ar8je
title: Occurrence Download

description: A dataset containing 4854511 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is one of (January, February, March, April, May, June, July, August, September, October, November, December)",
 "OccurrenceStatus is Present",
 "Year 2016-2025"
 ]
}

 The dataset includes 4854511 records from 1884 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002402-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13145/bacdive22581.20230509.8.1
title: Nannocystis exedens

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive22581.20251217.10
title: Nannocystis exedens

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0089895.10fu
title: SH0089895.10FU

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/bacdive22582.20230509.8.1
title: Nannocystis exedens

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive22582.20251217.10
title: Nannocystis exedens

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0089896.10fu
title: SH0089896.10FU

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/bacdive22583.20230509.8.1
title: Nannocystis exedens

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive22583.20251217.10
title: Nannocystis exedens

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0089897.10fu
title: SH0089897.10FU

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/bacdive22584.20230509.8.1
title: Nannocystis exedens

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive22584.20251217.10
title: Nannocystis exedens

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0089898.10fu
title: SH0089898.10FU

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/bacdive22585.20230509.8.1
title: Nannocystis exedens

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive22585.20251217.10
title: Nannocystis exedens

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0089899.10fu
title: SH0089899.10FU

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/bacdive22586.20230509.8.1
title: Nannocystis exedens

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive22586.20251217.10
title: Nannocystis exedens

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive22587.20230509.8.1
title: Herpetosiphon sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15156/bio/sh0089900.10fu
title: SH0089900.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0089901.10fu
title: SH0089901.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.x4v6df
title: Occurrence Download

description: A dataset containing 43126 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Bos)",
 "Continent is one of (Europe)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2000"
 ]
}

 The dataset includes 43126 records from 77 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0077175-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13145/bacdive22587.20251217.10
title: Herpetosiphon sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive22588.20230509.8.1
title: Herpetosiphon sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.