cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17055228
title: Black Sea Zooplankton data from the 'BRIDGE-BS-DEKOSIM Jun 2023' cruise identified with Zooscan

description: The dataset contains data from samples collected in June 2023 onboard of R/V Bilim-2, at different stations located in 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.17055169
title: Black Sea Zooplankton data from the 'BRIDGE-BS Dec 2022' cruise identified with Zooscan

description: The dataset contains data from samples collected in December 2022 onboard of R/V Bilim-2, at different stations located in 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.17055170
title: Black Sea Zooplankton data from the 'BRIDGE-BS Dec 2022' cruise identified with Zooscan

description: The dataset contains data from samples collected in December 2022 onboard of R/V Bilim-2, at different stations located in 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: 10.15468/dl.wvd2y9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Zosterops poliogastrus",
 "Country is one of (Brunei Darussalam, Indonesia, Philippines, Timor-Leste, Singapore)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029344-250920141307145/datasets/export for details.
DOI: 10.18150/crdudu
title: The role of phoenixin in brown adipogenesis

description: The results were collected within the project entitled “The effects of phoenixin on white and brown adipocytes as well as metabolism and adipose tissue in obesity”, funded by the National Science Centre, Poland (2022/45/B/NZ5/03453 The dataset consists of 13 files, including 12 in .csv format and one in .xlsx format, presenting comprehensive experimental results on the effects of phoenixin (PNX) in rat brown preadipocytes and brown adipose tissue. The files are organized according to specific data types and experimental outcomes. These include mRNA expression data for Smim20 and Gpr173 in rat brown preadipocytes (Fig 1_D_G) and in brown adipose tissue from young and adult rats (Fig 1_J_M). Protein expression data for PNX and GPR173 are provided both for rat brown preadipocytes (Fig 1_F_I) and for brown adipose tissue from young and adult rats (Fig 1_L_O). Functional data on the effects of PNX on cell proliferation in brown preadipocytes assessed by the BrdU assay are included (Fig 2_A_B), as well as changes in intracellular cAMP levels following PNX treatment (Fig 2_C). Signaling pathway analyses are provided, showing phosphorylation of ERK1/2 and AKT after PNX treatment (Fig 2_E_G), alongside the impact of inhibitors H-89, ESI-09, and U0126 on PNX-induced proliferation after 24 hours of incubation (Fig 2_H). The dataset also contains mRNA expression levels of key differentiation markers-Ucp1, Pparγ, Prdm16, Pgc1α, Cebpα, Cebpβ, and Fgf-21-in brown preadipocytes differentiated with PNX (Fig 3_A_D_E_F_G_H_K), complemented by protein expression data of UCP1, PPARγ, and FGF-21 in these differentiated cells (Fig 3_C_J_M). Additionally, intracellular lipid accumulation after seven days of differentiation with or without PNX treatment is quantified (Fig 4_D), and mitochondrial content under the same conditions is assessed (Fig 4_H). Finally, a comprehensive .xlsx file named “Raw_data_The role of phoenixin in brown adipogenesis” compiles all experimental results into an integrated resource.
DOI: 10.5281/zenodo.17225264
title: 12S_Raw_data_LaReunion_Mayotte_Islands_Fish

description: Data from NGS sequencing targeting the 12S rNRA marker. The data were used in environmental DNA metabarcoding of water samples collected from various rivers on La Réunion and Mayotte islands to study fish communities (JANNEL et al. 2025).
DOI: 10.5281/zenodo.17225265
title: 12S_Raw_data_LaReunion_Mayotte_Islands_Fish

description: Data from NGS sequencing targeting the 12S rNRA marker. The data were used in environmental DNA metabarcoding of water samples collected from various rivers on La Réunion and Mayotte islands to study fish communities (JANNEL et al. 2025).
DOI: 10.15468/dl.qfnh4q
title: Occurrence Download

description: A dataset containing 4216 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Verbascum nigrum",
 "Country is Russian Federation",
 "HasCoordinate is true"
 ]
}

 The dataset includes 4216 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029348-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vqva8v
title: Occurrence Download

description: A dataset containing 102 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Verbascum nigrum",
 "Country is Canada",
 "HasCoordinate is true"
 ]
}

 The dataset includes 102 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029345-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jsqsqs
title: Occurrence Download

description: A dataset containing 68 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Mesoplodon mirus)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 68 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029346-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sha6dd
title: Occurrence Download

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

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029347-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17225072
title: British Chamber of Commerce for Switzerland: Trade index 1921

description: Dataset containing data about the Trade index of the British Chamber of Commerce for Switzerland for the year 1921. The original focument is on e-manuscripta (https://doi.org/10.7891/e-manuscripta-174832)

This dataset contains



Mid-resolution imagery used for processing (=images of the pages)

Page.XML (=Transkribus export data)

Parsed JSON data (=data of project-specific parser, built to extract named entities)

Resulting JSON data (=proper data files with authentication data)

List of consolidated companies


 

The resulting data contains:



Information about companies and people (actors) listed in the trade index

The parser recognizes company and person's names, locations, traded goods,section

Found company (see list of consolidated companies)

Found locations and their geo-info (geonames id, label, lat, lng, country, region)

Found goods and their info (WZ 2008 and ISIC Rev04)

Section where the actor is listed (WZ 2008 and ISIC Rev04)

Source metadata and IIIF Snippet data


 

This data has been created and published as part of the dissertation project 'Lessons to learn? Unfolding a Global Market in Difficult Times'; The British Chamber of Commerce for Switzerland 1920 – 1950 (https://data.snf.ch/grants/grant/211961)
DOI: 10.5281/zenodo.17225073
title: British Chamber of Commerce for Switzerland: Trade index 1921

description: Dataset containing data about the Trade index of the British Chamber of Commerce for Switzerland for the year 1921. The original focument is on e-manuscripta (https://doi.org/10.7891/e-manuscripta-174832)

This dataset contains



Mid-resolution imagery used for processing (=images of the pages)

Page.XML (=Transkribus export data)

Parsed JSON data (=data of project-specific parser, built to extract named entities)

Resulting JSON data (=proper data files with authentication data)

List of consolidated companies


 

The resulting data contains:



Information about companies and people (actors) listed in the trade index

The parser recognizes company and person's names, locations, traded goods,section

Found company (see list of consolidated companies)

Found locations and their geo-info (geonames id, label, lat, lng, country, region)

Found goods and their info (WZ 2008 and ISIC Rev04)

Section where the actor is listed (WZ 2008 and ISIC Rev04)

Source metadata and IIIF Snippet data


 

This data has been created and published as part of the dissertation project 'Lessons to learn? Unfolding a Global Market in Difficult Times'; The British Chamber of Commerce for Switzerland 1920 – 1950 (https://data.snf.ch/grants/grant/211961)
DOI: 10.15468/dl.bhyzz5
title: Occurrence Download

description: A dataset containing 45 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Nitzschia longissima",
 "Geometry POLYGON((119.300000 20.500000, 122.100000 20.500000, 122.100000 25.400000, 119.300000 25.400000, 119.300000 20.500000))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 45 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029349-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5zsyfh
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Zosterops kaffensis",
 "Country is one of (Brunei Darussalam, Indonesia, Philippines, Timor-Leste, Singapore)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029351-250920141307145/datasets/export for details.
DOI: 10.6084/m9.figshare.30233314
title: Characterization of fucoxanthin-deficient strains in the Haptophyte <i>Tisochrysis lutea </i>induced by heavy-Ion beam irradiation

description: Pigment ectracts were obtained from wild-type (WT) strain and heavy-ion beam mutants (GR1 and GR2) of the haptophyte <i>Tisochrysis lutea </i>and subjected to a Nexera X2 UHPLC system (Shimadzu). All data of mass spectrum were obtained using an LCMS-8040 mass spectrometer (DUIS mode).<br>Kubo WT: LC–MS data used for Fig. 3B (Peak 4).Kubo GR1: LC–MS data used for Fig. 3B (Peak 10).Kubo GR2: LC–MS data used for Fig. 3B (Peak 11).
DOI: 10.6084/m9.figshare.30233314.v1
title: Characterization of fucoxanthin-deficient strains in the Haptophyte <i>Tisochrysis lutea </i>induced by heavy-Ion beam irradiation

description: Pigment ectracts were obtained from wild-type (WT) strain and heavy-ion beam mutants (GR1 and GR2) of the haptophyte <i>Tisochrysis lutea </i>and subjected to a Nexera X2 UHPLC system (Shimadzu). All data of mass spectrum were obtained using an LCMS-8040 mass spectrometer (DUIS mode).<br>Kubo WT: LC–MS data used for Fig. 3B (Peak 4).Kubo GR1: LC–MS data used for Fig. 3B (Peak 10).Kubo GR2: LC–MS data used for Fig. 3B (Peak 11).
DOI: 10.15468/dl.gbcc23
title: Occurrence Download

description: A dataset containing 12016158 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Portugal",
 "DatasetKey is EOD – eBird Observation Dataset"
 ]
}

 The dataset includes 12016158 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029308-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t8nb9u
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Micromeria glomerata)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029352-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xwbm7a
title: Occurrence Download

description: A dataset containing 112 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Verbascum nigrum",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 112 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029353-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kkq8t9
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Nitzschia lorenziana",
 "Geometry POLYGON((119.300000 20.500000, 122.100000 20.500000, 122.100000 25.400000, 119.300000 25.400000, 119.300000 20.500000))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029354-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30230740
title: Data of paper "Sediment Shape as a Proxy for Fluvial Processes A Factorial Analysis in the Yarlung Tsangpo Grand Canyon"

description: This study addresses the current lack of research linking particle shape characteristics with fluvial dynamics and sediment supply processes. Field investigations were conducted in the remote Yarlung Tsangpo Grand Canyon, spanning from the confluence of the Parlung Tsangpo and Layuequ to the vicinity of Dexing Township, with ten sampling sites established along the transect. Using digital image analysis, two-dimensional shape parameters were extracted from over 36,000 individual particles. Multivariate statistical techniques, including Principal Component Analysis (PCA) and Factor Analysis (FA), were applied to identify three physically meaningful composite factors. The spatial and sediment size dependent patterns of these factors revealed that: (a) coarser particles, relative to finer ones, exhibit reduced mobility and longer residence times within the channel. Prolonged exposure to hydraulic abrasion and inter-particle collisions leads to lower saturation but higher smoothness, while lithologically homogeneous coarse sediments display greater strength and a more equant morphology compared to finer fractions; (b) abundant sediment supply largely preserves source-derived particle shapes, whereas variations in fluvial conditions along the transect dominate shape modification. For example, confluences reduce flow velocity, promoting particle deposition and prolonged in-channel exposure, thereby enhancing smoothness. Higher smoothness observed in the mainstem relative to tributaries indicates more intense flow and faster abrasion in the main channel.This study established relationships between particle shape, fluvial processes, and sediment supply through field investigations, providing a reference for future research in sediment dynamics.
DOI: 10.6084/m9.figshare.30230740.v2
title: Data of paper "Sediment Shape as a Proxy for Fluvial Processes A Factorial Analysis in the Yarlung Tsangpo Grand Canyon"

description: This study addresses the current lack of research linking particle shape characteristics with fluvial dynamics and sediment supply processes. Field investigations were conducted in the remote Yarlung Tsangpo Grand Canyon, spanning from the confluence of the Parlung Tsangpo and Layuequ to the vicinity of Dexing Township, with ten sampling sites established along the transect. Using digital image analysis, two-dimensional shape parameters were extracted from over 36,000 individual particles. Multivariate statistical techniques, including Principal Component Analysis (PCA) and Factor Analysis (FA), were applied to identify three physically meaningful composite factors. The spatial and sediment size dependent patterns of these factors revealed that: (a) coarser particles, relative to finer ones, exhibit reduced mobility and longer residence times within the channel. Prolonged exposure to hydraulic abrasion and inter-particle collisions leads to lower saturation but higher smoothness, while lithologically homogeneous coarse sediments display greater strength and a more equant morphology compared to finer fractions; (b) abundant sediment supply largely preserves source-derived particle shapes, whereas variations in fluvial conditions along the transect dominate shape modification. For example, confluences reduce flow velocity, promoting particle deposition and prolonged in-channel exposure, thereby enhancing smoothness. Higher smoothness observed in the mainstem relative to tributaries indicates more intense flow and faster abrasion in the main channel.This study established relationships between particle shape, fluvial processes, and sediment supply through field investigations, providing a reference for future research in sediment dynamics.