cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/shdgds
title: Bioecological properties of duckweed (Lemna L.) and Azolla (Azolla L.) in different nutrient media and the use of their biomass in fisheries

description: Data publication of approximately 184 collection specimens for type of plants: 1. Lemna minor L. - 31; 2. Azolla caroliniana Willd. - 26; 3. Alisma plantago-aquatica L. -3; 4. Sisymbrium loeselii L. – 5; 5. Butomus umbellatus L. – 8; 6. Euphorbia helioscopia L. – 1; 7. Imperata cylindrica (L.) Raeusch. – 1; 8. Inula helenium L. – 1; 9. Juncus pallidus R.Br. – 5; 10. Malva neglecta Wallr. – 2; 11. Marrubium anisodon K.Koch. – 1; 12. Myriophyllum spicatum L. – 4; 13. Nasturtium officinale W.T.Aiton. – 8; 14. Papaver pavoninum Schrenk. – 1; 15. Phragmites australis (Cav.) Trin. ex Steud. – 5; 16. Potamogeton natans L. – 1; 17. Ranunculus acris L. – 3; 18. Riccia fluitans L. – 4; 19. Rumex confertus Willd. – 3; 20. Sophora pachycarpa Schrenk ex C.A.Mey. – 1; 21. Sparganium emersum Rehmann. – 2; 22. Typha latifolia L. – 5; 23. Xanthium orientale L. – 1; 24 Convolvulus arvensis L. – 1; 25. Eleocharis palustris (L.) Roem. & Schult. – 1; 26. Elaeagnus orientalis L. – 11; 27. Aeluropus littoralis (Gouan) Parl. – 1; 28. Barbarea vulgaris W.T.Aiton. – 1; 29. Bromus tectorum L. – 1; 30. Calystegia sepium (L.) R.Br. – 3; 31. Carex pachystylis J.Gay. – 1; 32. Chara foetida A.Braun. – 2; 33. Clematis orientalis L. – 2; 34. Convolvulus lineatus L. – 1; 35. Echinochloa crus-galli (L.) P.Beauv. – 2; 36. Elymus abolinii (Drobow) Tzvelev. – 2; 37. Geranium collinum Stephan ex Willd. – 2; 38. Caragana halodendron (Pall.) Dum.Cours. – 1; 39. Juncus bufonius L. – 3; 40. Lotus corniculatus L. – 1; 41. Marchantia polymorpha L. – 5; 42. Medicago minima (L.) Bartal. 1; 43. Phleum paniculatum Huds. – 3; 44. Populus pruinosa Schrenk. – 2; 45. Ranunculus baldschuanicus Regel ex Kom. – 1; 46. Rubus idaeus L. – 2; 47. Salix alba L. – 1; 48. Sisymbrium altissimum L. – 2; 49. Tamarix hispida Willd. – 1; 50. Typha laxmannii Lepech. – 2; 51. Typha angustifolia L. – 2; 52. Typha minima Funck – 1; 53. Veronica anagallis-aquatica L. - 1; 54. Rosa canina L. -1; 55. Urtica dioica L. – 1;
DOI: 10.15156/bio/sh0162805.10fu
title: SH0162805.10FU

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/sh0162806.10fu
title: SH0162806.10FU

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/sh0162807.10fu
title: SH0162807.10FU

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/sh0162808.10fu
title: SH0162808.10FU

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/sh0162809.10fu
title: SH0162809.10FU

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/sh0162810.10fu
title: SH0162810.10FU

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/sh0162811.10fu
title: SH0162811.10FU

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: 10.5517/cc4gv9q
title: CCDC 133433: Experimental Crystal Structure Determination

description: Related Article: L.T.Byrne, J.P.Hos, G.A.Koutsantonis, B.W.Skelton, A.H.White|2000|J.Organomet.Chem.|598|28|doi:10.1016/S0022-328X(99)00666-X
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc4rcdm
title: CCDC 141620: Experimental Crystal Structure Determination

description: Related Article: M.Abdaoui, G.Dewynter, L.Toupet, J.-L.Montero|2000|Tetrahedron|56|2427|doi:10.1016/S0040-4020(00)00114-9
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc4l9ll
title: CCDC 136759: Experimental Crystal Structure Determination

description: Related Article: C.E.Anson, G.Dave, G.R.Stephenson|2000|Tetrahedron|56|2273|doi:10.1016/S0040-4020(99)01110-2
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc4l9mm
title: CCDC 136760: Experimental Crystal Structure Determination

description: Related Article: C.E.Anson, G.Dave, G.R.Stephenson|2000|Tetrahedron|56|2273|doi:10.1016/S0040-4020(99)01110-2
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/cc4rl5m
title: CCDC 141830: Experimental Crystal Structure Determination

description: Related Article: R.C.F.Jones, P.Dimopoulos|2000|Tetrahedron|56|2061|doi:10.1016/S0040-4020(00)00108-3
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15468/dl.exe74j
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dactylogyrus extensus",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008312-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4ajgub
title: Occurrence Download

description: A dataset containing 58 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Lockhartia acuta"
 ]
}

 The dataset includes 58 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001051-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tb977e
title: Occurrence Download

description: A dataset containing 28 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pedicellarum paiei",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 28 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001052-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.39swvf
title: Occurrence Download

description: A dataset containing 2418 records in GBIF matching the query:

 SELECT gbifid, datasetkey, specieskey, kingdom, phylum, class, "order", family, genus, species, scientificname, decimallatitude, decimallongitude, eventdate, institutioncode, "year" AS obs_year, basisofrecord, coordinateuncertaintyinmeters, issue
 FROM occurrence
 WHERE
 decimallatitude IS NOT NULL
 AND decimallongitude IS NOT NULL
 AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID')
 AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH')
 AND "year" &gt;= 2015
 AND "year" &lt;= 2026
 AND coordinateuncertaintyinmeters IS NOT NULL
 AND coordinateuncertaintyinmeters &gt; 0
 AND coordinateuncertaintyinmeters &lt;= 200.0
 AND decimallatitude &gt;= 24.552553756517728
 AND decimallatitude &lt;= 28.773895969281842
 AND decimallongitude &gt;= -10.826001776192014
 AND decimallongitude &lt;= -5.290045945230182
 AND GBIF_Within('POLYGON ((-5.290046 24.552554, -5.290046 28.773896, -10.826002 28.773896, -10.826002 24.552554, -5.290046 24.552554))', decimallatitude, decimallongitude) = TRUE
 

 The dataset's 2418 records were derived from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001045-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5pyknv
title: Occurrence Download

description: A dataset containing 1534 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Malephora crocea"
 ]
}

 The dataset includes 1534 records from 60 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001053-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wytx2q
title: Occurrence Download

description: A dataset containing 393727 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Olea europaea"
 ]
}

 The dataset includes 393727 records from 594 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001032-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zzxtk8
title: Occurrence Download

description: A dataset containing 1430 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Peltandra virginica",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 1430 records from 117 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001054-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18513505
title: TSBench Dataset: A Benchmark for Time Series Stationarity and Structural Analysis

description: Overview

TSBench is a large-scale synthetic benchmark dataset comprising 120,000 unique univariate time series, specifically designed to address the limitations of traditional statistical tests and the evaluation gaps in modern deep learning architectures, including Time Series Foundation Models and Large Language Models (LLMs).

Dataset Structure & Organization

The dataset is provided in two primary compressed formats, organized by complexity and labeling strategy:





Generated_Data.zip: Contains time series characterized by a single primary property. These are ideal for fundamental property testing and baseline evaluations.




Combinations.rar: Contains complex time series where multiple characteristics (e.g., trend + seasonality + volatility) coexist, providing a more challenging environment for advanced models.



Data Labeling and Metadata:





Folder-Based Labeling: The dataset follows a hierarchical directory structure where labels are assigned based on the sub-folder names.




Granular Metadata: In addition to folder-based labels, each leaf directory contains a metadata file that stores precise generation parameters and specific series attributes for high-fidelity research.



Technical Summary





Total Size: 120,000 distinct time series.




Sequence Lengths: Short (50–100), Medium (300–500), and Long (1,000–10,000).




Key Properties: Stationarity/Non-stationarity, Deterministic/Stochastic Trends, Multi-frequency Seasonality, GARCH-based Volatility, Diverse Anomalies, and Structural Breaks.




Primary Tasks: Stationarity Detection, Trend Classification, Anomaly/Break Localization, and LLM Benchmarking.



Code and Resources

The source code for data generation and the underlying framework is available at: https://github.com/ismailguzel/ts-stationary

Funding & Acknowledgments

This work was supported by:





TÜBİTAK (The Scientific and Technological Research Council of Türkiye) under Grant No. 124F095.




METU (Middle East Technical University) Scientific Research Projects Coordination Unit under Grant No. GAP-109-2023-11361.
DOI: 10.5281/zenodo.18513504
title: TSBench Dataset: A Benchmark for Time Series Stationarity and Structural Analysis

description: Overview

TSBench is a large-scale synthetic benchmark dataset comprising 120,000 unique univariate time series, specifically designed to address the limitations of traditional statistical tests and the evaluation gaps in modern deep learning architectures, including Time Series Foundation Models and Large Language Models (LLMs).

Dataset Structure & Organization

The dataset is provided in two primary compressed formats, organized by complexity and labeling strategy:





Generated_Data.zip: Contains time series characterized by a single primary property. These are ideal for fundamental property testing and baseline evaluations.




Combinations.rar: Contains complex time series where multiple characteristics (e.g., trend + seasonality + volatility) coexist, providing a more challenging environment for advanced models.



Data Labeling and Metadata:





Folder-Based Labeling: The dataset follows a hierarchical directory structure where labels are assigned based on the sub-folder names.




Granular Metadata: In addition to folder-based labels, each leaf directory contains a metadata file that stores precise generation parameters and specific series attributes for high-fidelity research.



Technical Summary





Total Size: 120,000 distinct time series.




Sequence Lengths: Short (50–100), Medium (300–500), and Long (1,000–10,000).




Key Properties: Stationarity/Non-stationarity, Deterministic/Stochastic Trends, Multi-frequency Seasonality, GARCH-based Volatility, Diverse Anomalies, and Structural Breaks.




Primary Tasks: Stationarity Detection, Trend Classification, Anomaly/Break Localization, and LLM Benchmarking.



Code and Resources

The source code for data generation and the underlying framework is available at: https://github.com/ismailguzel/ts-stationary

Funding & Acknowledgments

This work was supported by:





TÜBİTAK (The Scientific and Technological Research Council of Türkiye) under Grant No. 124F095.




METU (Middle East Technical University) Scientific Research Projects Coordination Unit under Grant No. GAP-109-2023-11361.
DOI: 10.15468/dl.xs53e4
title: Occurrence Download

description: A dataset containing 201157 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Potamopyrgus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 201157 records from 499 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001036-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.