cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0187395.10fu
title: SH0187395.10FU

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/sh0187396.10fu
title: SH0187396.10FU

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/sh0187397.10fu
title: SH0187397.10FU

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/sh0187398.10fu
title: SH0187398.10FU

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/sh0187399.10fu
title: SH0187399.10FU

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/sh0187400.10fu
title: SH0187400.10FU

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/sh0187401.10fu
title: SH0187401.10FU

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/sh0187402.10fu
title: SH0187402.10FU

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/sh0187403.10fu
title: SH0187403.10FU

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/sh0187404.10fu
title: SH0187404.10FU

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: 10.7910/dvn/aa4apo
title: Replication Data for Cancel Culture

description: Replication Data for Cancel Culture
DOI: 10.15468/dl.4gp3pw
title: Occurrence Download

description: A dataset containing 270965 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation)",
 "OccurrenceStatus is Present",
 "TaxonKey is Mammalia",
 "Year 2000-2000"
 ]
}

 The dataset includes 270965 records from 630 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069395-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aw4ack
title: Occurrence Download

description: A dataset containing 166008 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Schoenoplectus (Rchb.) Palla"
 ]
}

 The dataset includes 166008 records from 873 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052414-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.72q2aq
title: Occurrence Download

description: A dataset containing 648845 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Argentina",
 "TaxonKey is Tracheophyta"
 ]
}

 The dataset includes 648845 records from 268 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008044-180730143533302/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.avb5jw
title: Occurrence Download

description: A dataset containing 26919 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Lao People’s Democratic Republic",
 "TaxonKey is Aves"
 ]
}

 The dataset includes 26919 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006811-191105090559680/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s59fwz
title: Occurrence Download

description: A dataset containing 3918 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Brosimum alicastrum Sw."
 ]
}

 The dataset includes 3918 records from 199 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052408-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/grzcrfjvjr.1
title: Water and sediment data from the Yellow River, China

description: The dataset includes five parts. Part 1 is grid data of suspended sediment concentration and sediment load at the 17 Yellow River mainstream gauging stations over the period of 1952-2019. Part 2 is monthly rain data at the 17 Yellow River mainstream gauging stations over the period of 1952-2019. Part 3 is data of averaged water discharge and suspended sediment concentration during different time periods for the 17 Yellow River mainstream gauging stations. Part 4 is data of annual sediment infilling in the Xiaolangdi Reservoir. Part 5 is data of monthly and yearly changes in storage of the four reservoirs.
DOI: 10.15468/dl.7ysaqb
title: Occurrence Download

description: A dataset containing 481 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Penelope albipennis Taczanowski, 1878"
 ]
}

 The dataset includes 481 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008044-190320150433242/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cavqhc
title: Occurrence Download

description: A dataset containing 215 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Guatemala",
 "DatasetKey is Orchid Herbarium Collection"
 ]
}

 The dataset includes 215 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017366-181003121212138/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.watddx
title: Occurrence Download

description: A dataset containing 21963 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Isatis tinctoria L."
 ]
}

 The dataset includes 21963 records from 335 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052407-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13140/rg.2.2.32035.99366
title: Revised Cocoa Sample Collection Design Plan.pdf
DOI: 10.5281/zenodo.17055018
title: Black Sea Zooplankton data from the 'MARMOD-FAZ2 DEKOSIM BRIDGE Sep 2021' cruise identified with Zooscan

description: The dataset contains data from samples collected in September 2021 onboard of R/V Bilim-2, at different stations located in Bosphorous sector of Turkish EEZ of Black Sea. The sampling was performed within the BRIDGE-BS project (EU H2020, grant agreement No 101000240). Zooplankton samples were collected by towing a WP-2 net with a 200 µm mesh size and a 57 cm mouth diameter. Lead pieces were attached to the collector to minimize the displacement of the net with the currents. On windy days, the vessel drifted from the point where the net was lowered down. In both cases, the wire angle was calculated and the length of the wire was corrected to collect the whole water column. Hauls were made with a speed of 1 m/s to minimize the spilling out of the water. For the nearshore stations, the net was towed vertically from 4-5 m above the bottom to the surface. For the offshore stations, the net was towed from the start of an anoxic layer (sigma-t, 16.2 kg/m3). The gelatinous organisms were sorted from the sample in the plankton net and analyzed on the board. The rest of the sample were fixed with 5% borax-buffered formaldehyde in 250 ml bottles for the zooplankton analysis. Each sample was filtered with 200 μm and 500 μm mesh to have 2 size fractions. This is because of not missing any rare large organisms while splitting the sample into subsamples. Motoda was used to divide samples into subsamples and at least 1000 organisms were analyzed for each sample. Detritus materials other than zooplankton species were removed from the sample under the stereo microscope. Hydroptic-Zooscan was used to scan the samples. Scanned images were processed with Zooprocess. For each organism, separate images/vignettes were generated from the raw image. These files were then automatically sorted with the Learning Set (Plankton Identifier). Then, the sorting was visually validated using the program XnView. Abundance and biovolume values were expressed in unit volume (m3). The filtration volume was estimated by multiplying the mouth area (πr2) by the wire length. For the biovolume calculation the formula; EBV=4/3π(Major/2) (Minor/2)2 was used (Vandromme et al., 2012). The data file is in OBIS format.
DOI: 10.5281/zenodo.17055019
title: Black Sea Zooplankton data from the 'MARMOD-FAZ2 DEKOSIM BRIDGE Sep 2021' cruise identified with Zooscan

description: The dataset contains data from samples collected in September 2021 onboard of R/V Bilim-2, at different stations located in Bosphorous sector of Turkish EEZ of Black Sea. The sampling was performed within the BRIDGE-BS project (EU H2020, grant agreement No 101000240). Zooplankton samples were collected by towing a WP-2 net with a 200 µm mesh size and a 57 cm mouth diameter. Lead pieces were attached to the collector to minimize the displacement of the net with the currents. On windy days, the vessel drifted from the point where the net was lowered down. In both cases, the wire angle was calculated and the length of the wire was corrected to collect the whole water column. Hauls were made with a speed of 1 m/s to minimize the spilling out of the water. For the nearshore stations, the net was towed vertically from 4-5 m above the bottom to the surface. For the offshore stations, the net was towed from the start of an anoxic layer (sigma-t, 16.2 kg/m3). The gelatinous organisms were sorted from the sample in the plankton net and analyzed on the board. The rest of the sample were fixed with 5% borax-buffered formaldehyde in 250 ml bottles for the zooplankton analysis. Each sample was filtered with 200 μm and 500 μm mesh to have 2 size fractions. This is because of not missing any rare large organisms while splitting the sample into subsamples. Motoda was used to divide samples into subsamples and at least 1000 organisms were analyzed for each sample. Detritus materials other than zooplankton species were removed from the sample under the stereo microscope. Hydroptic-Zooscan was used to scan the samples. Scanned images were processed with Zooprocess. For each organism, separate images/vignettes were generated from the raw image. These files were then automatically sorted with the Learning Set (Plankton Identifier). Then, the sorting was visually validated using the program XnView. Abundance and biovolume values were expressed in unit volume (m3). The filtration volume was estimated by multiplying the mouth area (πr2) by the wire length. For the biovolume calculation the formula; EBV=4/3π(Major/2) (Minor/2)2 was used (Vandromme et al., 2012). The data file is in OBIS format.
DOI: 10.15155/repo-3
title: Hyytiala08_10aerosol

description: The dataset Hyytiala08_10aerosol contains results of routine measurements of atmospheric aerosols carried on in a well equipped boreal research station during 3 years. The particle size range from 3 nm to 15μm is split into 60 fractions and the records of distribution function are presented for 21682 hours of measurements. The dataset provides scientists with a tool for exploring the structure and dynamics of atmospheric aerosol size distribution. Additionally, it can serve as a basis for data analysis exercises for students in field of environmental sciences. The dataset includes three files: Data_Hyytiala08_10aerosol.xls – a spreadsheet, which contains 60 columns of values of the particle size distribution function and 30 columns of complementary variables. Description_Hyytiala08_10aerosol.pdf – detailed description of origin and structure the data. Additionally includes sample diagrams, which illustrate the data and may provoke new ideas for studies on atmospheric aerosol. Package_Hyytiala08_10aerosol.zip – a compressed package, which contains both the data file and the description file. The package is to be downloaded to a personal computer, unzipped and used offline.
DOI: 10.13140/rg.2.2.13082.98249
title: Cross12
DOI: 10.15468/dl.npafuv
title: Occurrence Download

description: A dataset containing 4475 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Padda oryzivora (Linnaeus, 1758)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Country is one of (Brunei Darussalam, Cambodia, Indonesia, Lao People’s Democratic Republic, Malaysia, Myanmar, Philippines, Singapore, Thailand, Viet Nam)"
 ]
}

 The dataset includes 4475 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008420-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.