cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.s4ya6v
title: Occurrence Download

description: A dataset containing 524727 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Pyrrhopyge araxes (Hewitson, 1867), Rhynchalastor toas (Cresson, 1868), Pilostyles thurberi A.Gray, Chauliognathus opacus LeConte, 1866, Bembix pallidipicta F.Smith, 1873, Epeolus ainsliei Crawford, 1932, Triepeolus obliteratus Graenicher, 1911, Tetraloniella albata (Cresson, 1872), Megachile rugifrons (Smith, 1854), Colletes susannae Swenk, 1925, Perdita perpallida Cockerell, 1901, Colletes wilmattae Cockerell, 1904, Walshia floridensis Hodges, 1978, Colletes howardi Swenk, 1925, Teinopalpus aureus Mell, 1923, Teinopalpus imperialis Hope, 1843, Acrocercops nolckeniella (Zeller, 1877), Scrobipalpula daturae (Zeller, 1877), Cylindroiulus caeruleocinctus (Wood, 1864), Eucarta amethystina (Hübner, 1803), Bicyrtes viduatus (Handlirsch, 1889), Metatrichia bulbosa (Osten Sacken, 1877), Spalangia irregularis Boucek, 1963, Delosperma testaceum (Haw.) Schwantes, Delosperma aereum (L.Bolus) L.Bolus, Sclerotium delphinii Welch, 1924, Neodidymelliopsis xanthina (Sacc.) Qian Chen & L.Cai, Phytomyza aconiti Hendel, 1920, Polychrysia morigera Edwards, 1886, Hypolycaena danis (C.Felder & R.Felder, 1865), Dolichotetranychus vandergooti (Oudemans, 1927), Chliaria kina (Hewitson, 1869), Hypolycaena ithna Hewitson, 1869, Mormyrus rume Valenciennes, 1847, Plutothrix unguttella Heydon, 1997, Cerocephala rufa (Walker, 1833), Luehdorfia japonica Leech, 1889, Cosmocerca podicipinus Baker & Vaucher, 1984, Argyrops spinifer (Forsskål, 1775), Sitobion luteum (Buckton, 1876), Stethopachys formosa, Luehdorfia puziloi (Erschoff, 1872), Luehdorfia longicaudata Lee, 1982, Stenadonta radialis Gaede, 1930, Trifida quadripunctata Thapa & Sohi, 1986, Tetramesa gigantochloae Narendran & Kovac, 1995, Pipistrellus kuhlii (Kuhl, 1817), Pipistrellus pygmaeus (Leach, 1825), Tadarida brasiliensis (I.Geoffroy, 1824), Miniopterus schreibersii (Kuhl, 1817))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 524727 records from 2189 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001508-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1380377.10fu
title: SH1380377.10FU

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/sh1380379.10fu
title: SH1380379.10FU

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/sh1380383.10fu
title: SH1380383.10FU

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/sh1380389.10fu
title: SH1380389.10FU

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/sh1380390.10fu
title: SH1380390.10FU

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: 10.5281/zenodo.18229572
title: MAKTAB DARSLIKLARIDAGI XALQ MAQOLLARINI LINGVOMADANIY JIHATDAN O'RGANISHNING METODIK TAMOYILLARI

description: Xalqimiz asrlar davomida juda katta hayotiy tajriba to’plagan, shu tajriba meros sifatida turli vositalar bilan biz kelajak avlodlarga yetib kelmoqda. Xikmatli so’zlar ana shunday bebaho ma’naviy meros hisoblanadi. Ushbu maqolada o’zbek xalqining asrlar mobaynida sayqal topib, bizgacha yetib kelgan ana shunday so’z durdonalarining ba’zilari bilan tanishibgina qolmay, ularning tarixan qanday shakllanganini hamda mazmunini bilib olamiz.
DOI: 10.5281/zenodo.18229573
title: MAKTAB DARSLIKLARIDAGI XALQ MAQOLLARINI LINGVOMADANIY JIHATDAN O'RGANISHNING METODIK TAMOYILLARI

description: Xalqimiz asrlar davomida juda katta hayotiy tajriba to’plagan, shu tajriba meros sifatida turli vositalar bilan biz kelajak avlodlarga yetib kelmoqda. Xikmatli so’zlar ana shunday bebaho ma’naviy meros hisoblanadi. Ushbu maqolada o’zbek xalqining asrlar mobaynida sayqal topib, bizgacha yetib kelgan ana shunday so’z durdonalarining ba’zilari bilan tanishibgina qolmay, ularning tarixan qanday shakllanganini hamda mazmunini bilib olamiz.
DOI: 10.15156/bio/sh1380392.10fu
title: SH1380392.10FU

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/sh1380394.10fu
title: SH1380394.10FU

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.zy4s4x
title: Occurrence Download

description: A dataset containing 5614572 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is The vascular plants collection (P) at the Herbarium of the Muséum national d'Histoire Naturelle (MNHN - Paris)"
 ]
}

 The dataset includes 5614572 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005750-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wq9weq
title: Occurrence Download

description: A dataset containing 16091 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Anisantha diandra, Anisantha diandra, Anisantha diandra diandra, Anisantha gussonei, Anisantha macranthera, Bromus ambigens, Bromus asperipes, Bromus asperipes, Bromus boraei, Bromus boraei)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Machine Observation)"
 ]
 }
 },
 "Continent is Europe",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 16091 records from 464 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017152-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7gkcc2
title: Occurrence Download

description: A dataset containing 164 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Canthium bibracteatum"
 ]
}

 The dataset includes 164 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017155-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qe86tw
title: Occurrence Download

description: A dataset containing 346 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Erysimum pulchellum"
 ]
}

 The dataset includes 346 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017154-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a2qz2c
title: Occurrence Download

description: A dataset containing 28 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sterigmostemum matthioloides"
 ]
}

 The dataset includes 28 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017153-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ve4px7
title: Occurrence Download

description: A dataset containing 724 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Clutia abyssinica",
 "HasCoordinate is true",
 "Geometry POLYGON ((-17.66889 -35.11691, 51.34702 -35.11691, 51.34702 37.62, -17.66889 37.62, -17.66889 -35.11691))"
 ]
}

 The dataset includes 724 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017156-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qdrztq
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mastacembelus perakensis"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017157-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15242527
title: Time series flood mapping using the Copernicus dataset in Google Earth Engine of Mountainous Region

description: Flood is a major challenge in a mountainous country like Nepal due to complex topography, high snowmelt, and unpredictable monsoon rainfall. This requires an urgent need to develop high-resolution flooded and non-flooded datasets. In this study high-resolution Copernicus optical imageries from 2019 to 2023. The dataset was created using spectral curve normalized difference vegetation index and applying varying threshold values to develop the flooded and non-flooded regions in different topographical regions.

The data was processed using Google Earth Engine in the monsoon composite by cloud masking, and filling was performed. The different thresholds help to delaminate the flooded and non-flooded region better.  This dataset will be applicable in different assessments such as the application of machine learning for early warning for mountainous regions. Identifying the flooded and non-flooded regions will helps in developing risk-sensitive land use planning and developing managed settlement plans. The natural based mitigation strategies can be developed in frequently flooded regions.
DOI: 10.5281/zenodo.15702358
title: Time series flood mapping using the Copernicus dataset in Google Earth Engine of Mountainous Region

description: Flood is a major challenge in a mountainous country like Nepal due to complex topography, high snowmelt, and unpredictable monsoon rainfall. This requires an urgent need to develop high-resolution flooded and non-flooded datasets. In this study high-resolution Copernicus optical imageries from 2019 to 2023. The dataset was created using spectral curve normalized difference vegetation index and applying varying threshold values to develop the flooded and non-flooded regions in different topographical regions.

The data was processed using Google Earth Engine in the monsoon composite by cloud masking, and filling was performed. The different thresholds help to delaminate the flooded and non-flooded region better.  This dataset will be applicable in different assessments such as the application of machine learning for early warning for mountainous regions. Identifying the flooded and non-flooded regions will helps in developing risk-sensitive land use planning and developing managed settlement plans. The natural based mitigation strategies can be developed in frequently flooded regions.
DOI: 10.15468/dl.5nnmch
title: Occurrence Download

description: A dataset containing 250 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is one of (China, Hong Kong, Macao)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ipomoea purpurea",
 "Year 2000-2025"
 ]
}

 The dataset includes 250 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017160-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7uxq3c
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eichhornia crassipes",
 "Country is Myanmar",
 "HasCoordinate is true"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017159-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pttbva
title: Occurrence Download

description: A dataset containing 5953 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Zornia latifolia"
 ]
}

 The dataset includes 5953 records from 268 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017158-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zdkpxk
title: Occurrence Download

description: A dataset containing 24487 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Canis lupus",
 "Country is Australia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 24487 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017161-250711103210423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cydwh9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eichhornia crassipes",
 "Country is Nauru",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017163-250711103210423/datasets/export for details.
DOI: 10.5281/zenodo.14699871
title: Data for "Turbine location-aware multi-decadal wind power predictions for Germany using CMIP6"

description: Supporting data for the paper "Turbine location-aware multi-decadal wind power predictions for Germany using CMIP6" by Effenberger, Ludwig (2024), the corresponding code and documentation can be accessed on GitHub once the paper is published. The paper is currently under review, a pre-print is accessible on arXiv. 

CMIP6 data [1] can be downloaded from the ESGF data node [2]. Power generation for earlier years can be downloaded for the individual German TSOs [3], for later years they are available through the SMARD database [4]. Turbine data is provided by Manske et al. [5]. The reanalysis dataset used is ERA5 [6]. Turbine data is from windpowerlib [7].

[1] Wolfgang A Müller, Johann H Jungclaus, Thorsten Mauritsen, Johanna Baehr, Matthias Bittner, R Budich, Felix Bunzel, Monika Esch, Rohit Ghosh, Helmut Haak, et al. Ahigher-resolution version of the max planck institute earth system model (MPI-ESM1.2-HR). Journal of Advances in Modeling Earth Systems, 10(7):1383–1413, 2018.

[2] ESGF, July 2024. URL https://esgf-metagrid.cloud.dkrz.de/search.

[3] OPSD. Open power system data platform, July 2024. URL https://open-power-system-data.org/data-sources.

[4] Bundesnetzagentur. Smard, July 2024. URL https://www.smard.de/en/downloadcenter/download-market-data/.

[5] David Manske and Julius Schmiedt. Geo-locations and System Data of Renewable Energy Installations in Germany, July 2023. URL https://doi.org/10.5281/zenodo.8188601.

[6] Hans Hersbach, Bill Bell, Paul Berrisford, Shoji Hirahara, Andr.s Hor.nyi, Joaqu.n Mu.oz-Sabater, Julien Nicolas, Carole Peubey, Raluca Radu, Dinand Schepers, et al. The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730):1999–2049, 2020.
DOI: 10.5281/zenodo.14699872
title: Data for "Turbine location-aware multi-decadal wind power predictions for Germany using CMIP6"

description: Supporting data for the paper "Turbine location-aware multi-decadal wind power predictions for Germany using CMIP6" by Effenberger, Ludwig (2024), the corresponding code and documentation can be accessed on GitHub once the paper is published. The paper is currently under review, a pre-print is accessible on arXiv. 

CMIP6 data [1] can be downloaded from the ESGF data node [2]. Power generation for earlier years can be downloaded for the individual German TSOs [3], for later years they are available through the SMARD database [4]. Turbine data is provided by Manske et al. [5]. The reanalysis dataset used is ERA5 [6]. Turbine data is from windpowerlib [7].

[1] Wolfgang A Müller, Johann H Jungclaus, Thorsten Mauritsen, Johanna Baehr, Matthias Bittner, R Budich, Felix Bunzel, Monika Esch, Rohit Ghosh, Helmut Haak, et al. Ahigher-resolution version of the max planck institute earth system model (MPI-ESM1.2-HR). Journal of Advances in Modeling Earth Systems, 10(7):1383–1413, 2018.

[2] ESGF, July 2024. URL https://esgf-metagrid.cloud.dkrz.de/search.

[3] OPSD. Open power system data platform, July 2024. URL https://open-power-system-data.org/data-sources.

[4] Bundesnetzagentur. Smard, July 2024. URL https://www.smard.de/en/downloadcenter/download-market-data/.

[5] David Manske and Julius Schmiedt. Geo-locations and System Data of Renewable Energy Installations in Germany, July 2023. URL https://doi.org/10.5281/zenodo.8188601.

[6] Hans Hersbach, Bill Bell, Paul Berrisford, Shoji Hirahara, Andr.s Hor.nyi, Joaqu.n Mu.oz-Sabater, Julien Nicolas, Carole Peubey, Raluca Radu, Dinand Schepers, et al. The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730):1999–2049, 2020.