cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1401456.10fu
title: SH1401456.10FU

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/sh1401458.10fu
title: SH1401458.10FU

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/sh1401462.10fu
title: SH1401462.10FU

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/sh1401463.10fu
title: SH1401463.10FU

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: 10.17630/5dedf5bf-1cb4-41b0-9f2c-be5341b61b6c
title: The Thermal Dehydrofluorination of GaPO-34 Revealed by NMR Crystallography (dataset)

description: Raw experimental and computational data underpinning The Thermal Dehydrofluorination of GaPO-34 Revealed by NMR Crystallography
DOI: 10.1594/pangaea.973621
title: Morphometric and meristic dataset for the comparison of two species of sciaenid fishes, Atractoscion aequidens and Atractoscion macrolepis

description: Morphometric data were collected and meristic counts taken from up to 33 museum-vouchered specimens of Atractoscion aequidens, sampled from South African coastal waters, and 52 specimens of Atractoscion macrolepis from Angolan coastal waters. The latter included museum-vouchered specimens and specimens collected in the field (but not retained in collections) during May and June 2009. Museum specimens were from the South African National Fish Collection housed at the National Research Foundation - South African Institute for Aquatic Biodiversity. Data were collected to investigate morphometric and meristic differences between the two species to confirm or refute the earlier description of A. macrolepis as a distinct species, and to examine characters that would allow the distinction of the two species, if valid. The earlier description of A. macrolepis was based on a limited number of specimens, and the proposed diagnostic character is unable to discriminate the species when considering a wider sample. The morphometric data set consisted of measurements for 24 variables, taken with rulers and tape measures for the larger measurements and digital calibers for the smaller measurements. Seven meristic counts were taken macroscopically. The full set of morphometric characters included standard length (SL), total length (TL), fork length (FL), body depth (BD), first dorsal fin length (1DFL), second dorsal fin length (2DFL), caudal peduncle length (CPL), upper caudal lobe length (UCLL), medial caudal length (MCL), lower caudal lobe length (LCLL), anal fin base length (AFB), anal fin length (AFL), pectoral fin base length (PFB), pectoral fin length (PFL), pelvic fin base length (PLFB), pelvic fin length (PLFL), pre-pelvic length (PPL), head length (HL), left dentary length (LDL), inter-orbital width (IOW), orbit diameter (OD), snout length (SNL), length of the longest gill filament (GFL) and length of the pectoral skin flap (PSF). The meristic counts included the number of first dorsal fin spines (1DS), the number of second dorsal fin spines (2DS), the number of second dorsal fin rays (2DR), the number of anal fin spines (AFS), the number of anal fin rays (AFR), the number of pectoral fin rays (P) and the number of pored lateral line scales (LL). Counts of the pored lateral line scales, taken using an earlier approach (Henriques et al. 2016), were also included (Original LL). Additional information includes the sampling locality and sex of the individual.
description: The table contains 24 morphometric measures and 8 meristic counts, along with metadata (species identifications, country of sampling, sampling locality and sex) for up to 33 individuals of Atractoscion aequidens and 52 specimens of Atractoscion macrolepis, sampled from South African and Angolan waters, respectively.
DOI: 10.5281/zenodo.18671088
title: Development of Photo-Biocatalytic Redox System for Asymmetric Synthesis of Optically Active Amines Using Blue Light and Transaminases. A Case Study Toward Mavacamten

description: The deposited dataset includes: (i) free induction decay (FID) files, acquisition parameters, and processing details for the recorded 1H, 13C{1H}, and 19F NMR spectra of a set of compounds (e.g., alkenes, amines, amides, and mavacamten), and (ii) raw, unprocessed HPLC analytical data. These data consists of supplementary data for an article entitled: "Development of Photo-Biocatalytic Redox System for Asymmetric Synthesis of Optically Active Amines Using Blue Light and Transaminases. A Case Study Toward Mavacamten" published in Advanced Synthesis & Catalysis 2025, 367, e202500250 (doi: 10.1002/adsc.202500250) on 30 June 2025. This research was funded by the National Science Centre, Poland within the framework of the project "OPUS 24" (Grant No. 2022/47/B/ST4/00139).
DOI: 10.5281/zenodo.18671087
title: Development of Photo-Biocatalytic Redox System for Asymmetric Synthesis of Optically Active Amines Using Blue Light and Transaminases. A Case Study Toward Mavacamten

description: The deposited dataset includes: (i) free induction decay (FID) files, acquisition parameters, and processing details for the recorded 1H, 13C{1H}, and 19F NMR spectra of a set of compounds (e.g., alkenes, amines, amides, and mavacamten), and (ii) raw, unprocessed HPLC analytical data. These data consists of supplementary data for an article entitled: "Development of Photo-Biocatalytic Redox System for Asymmetric Synthesis of Optically Active Amines Using Blue Light and Transaminases. A Case Study Toward Mavacamten" published in Advanced Synthesis & Catalysis 2025, 367, e202500250 (doi: 10.1002/adsc.202500250) on 30 June 2025. This research was funded by the National Science Centre, Poland within the framework of the project "OPUS 24" (Grant No. 2022/47/B/ST4/00139).
DOI: 10.15468/dl.3swfzn
title: Occurrence Download

description: A dataset containing 2469083 records in GBIF matching the query:
SELECT "year", GBIF_EEARGCode( 1000, decimalLatitude, decimalLongitude, COALESCE(coordinateUncertaintyInMeters, 1000) ) AS eeaCellCode, classKey, class, COUNT(*) AS occurrences, MIN(COALESCE(coordinateUncertaintyInMeters, 1000)) AS minCoordinateUncertaintyInMeters, MIN(GBIF_TemporalUncertainty(eventDate, null)) AS minTemporalUncertainty FROM occurrence WHERE occurrenceStatus = 'PRESENT' AND countrycode = 'BE' AND "year" &gt;= 1900 AND hasCoordinate = TRUE 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 (LOWER(identificationVerificationStatus) NOT IN ( 'unverified', 'unvalidated', 'not validated', 'under validation', 'not able to validate', 'control could not be conclusive due to insufficient knowledge', 'uncertain', 'unconfirmed', 'unconfirmed - not reviewed', 'validation requested' ) OR identificationVerificationStatus IS NULL)AND classKey IN (126, 131, 137, 139, 148, 151, 179, 183, 186, 194, 196, 199, 203, 205, 206, 212, 216, 220, 225, 229, 232, 244, 245, 252, 255, 256, 270, 281, 282, 307, 327, 328, 354, 356, 359, 360, 361, 365, 367, 7073593, 7228684, 7742773, 7774442, 7947184, 8179345, 9273948, 10689325, 11133537, 11418114, 11493978, 11545536, 11592253)AND COALESCE(coordinateUncertaintyInMeters, 1000) &lt;= 10000GROUP BY "year", eeaCellCode, classKey, class ORDER BY "year" DESC, eeaCellCode ASC, classKey ASC;

 The dataset's 2469083 records were derived from 673 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003596-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/12510374
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.5w6qxu
title: Occurrence Download

description: A dataset containing 95 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sisymbrium turczaninowii"
 ]
}

 The dataset includes 95 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008141-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25345/c5nk36j21
title: MassIVE MSV000098558 - Soluble Human Plasma Proteoform Analysis via Acetonitrile Precipitation (SPPAP)
title: Advances in Liquid Chromatography-Mass Spectrometry (LC-MS) have significantly improved proteomic analyses of human plasma. However, information at the level of intact proteoforms remains poorly understood due to the high dynamic range of protein abundance and their complexity of post-translational modifications. To address this challenge, we introduce Soluble Plasma Proteoform Analysis via Acetonitrile Precipitation (SPPAP), a streamlined workflow for top-down proteomics (TDP) that isolates small, intact proteoforms from the acetonitrile-soluble plasma fraction. This simple, scalable method uses cold acetonitrile to precipitate abundant proteins, enriching the sample for lower-molecular weight proteoforms. To evaluate its clinical utility, we applied SPPAP to a cohort of 40 individuals, including 30 patients with liver cirrhosis and 10 healthy controls. In total we report a total of 3,746 proteoforms from 255 proteins, including those with phosphorylation, truncation, and disulfide bond modifications. Reproducibility was confirmed with the coefficient of variation &lt;10% for the majority of enriched proteoforms, including those involved in hemostasis, lipoprotein metabolism, and cytoskeletal integrity. SPPAP enabled effective stratification of the three cirrhosis stages, verifying previous results from a different cohort and advancing biomarker candidates reinforced with mechanistic insight. In addition, we identified proteoforms associated with cytoplasmic vesicle lumen, platelet granules, and lipoprotein particles, suggesting their potential as circulating indicators of vesicle trafficking and metabolic activity. Although liver cirrhosis was used as a model system, the SPPAP workflow is broadly applicable to human disease with proteoform-level resolution offering a new path to stronger correlations in smaller cohorts and overcome diagnostic and biomarker discovery challenges.
DOI: 10.15468/dl.2dgtjy
title: Occurrence Download

description: A dataset containing 3400 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "TaxonKey is one of (Hyla gratiosa)"
 ]
}

 The dataset includes 3400 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008142-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gg68hx
title: Occurrence Download

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

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008143-250717081556266/datasets/export for details.
DOI: 10.15468/dl.4mkdqr
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eutrema wuchengyii"
 ]
}

 The dataset includes 10 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008145-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14051742
title: K1702 - Kura Clover (Trifolium ambiguum) USDA Accession Image Dataset

description: Images

This dataset consists of 1135 images of Kura clover (Trifolium ambiguum) USDA accessions grown in Salina, Kansas over the 2017 growing season. Each image contains a single Kura clover plant framed by a PVC sampling quadrat that has an internal area of 0.25 m2. Kura clover plots were hand weeded to remove all other vegetation except Kura clover. Some images may contain dead clover accessions that are either brown and dried up, or missing entirely. The images were acquired with a Canon EOS Rebel T6 DSLR camera under the following settings:



ISO: 200

Exposure: Auto

Focal Length: Variable (33-40mm)

Format: JPEG

Size: 5184x3456

Metering Mode: Multi-segment


Images are separated into three folders: train, val, and test. The train/val split is 80/20 (n=880, n=220), randomly selected. The test set contains 35 images. Images are named in the format "<IMAGE_ID>.jpg".

Annotations

All images are annotated using Labelbox software. Masks were generated by point prompts using Meta's Segment Anything model (SAM). PVC quadrat, quadrat corners, and Kura clover objects were annotated with bounding boxes. 

Segmentation masks are in .mat format with the name "<IMAGE_ID>_mask.mat" with the following keys:



data: A 2d Numpy array with data type np.uint8 corresponding to the class for each pixel.

project: A text field with the name of the project.


The segmentation mapping can be found in the file "segmentation_classes.json". The class mapping is as follows:



0: 'background' class containing all soil and non target materials.

1: 'quadrat' class.

2: 'clover' class for all clover related vegetation whether alive or dead.


Bounding boxes are in the file "bounding_boxes.csv". bbox coordinates are in the format (y1, x1, height, width). Column names are the following:



img_id: The name of the image file.

class: Class of the bbox annotation ∈ ['quadrat', 'quadrat_corner', 'kura_clover'].

y1: The y coordinate of the top of the bbox.

x1: The x coordinate of the left side of the bbox.

height: The height of the bbox (y2 = y1 + height).

width: The width of the bbox (x2 = x1 + width).


No image preprocessing was performed.
DOI: 10.3535/7fz-qnq-23a
title: Isoëtes azorica Durieu ex Milde

description: Digital Specimen for the physical specimen hosted at Natural History Museum Vienna.
DOI: 10.15468/dl.eamsb4
title: Occurrence Download

description: A dataset containing 322 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acacia baileyana",
 "Country is South Africa",
 "HasCoordinate is true"
 ]
}

 The dataset includes 322 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008144-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.26beke
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Brachiaria mutica",
 "Country is India",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008146-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2fd2sf
title: Occurrence Download

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

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008147-250717081556266/datasets/export for details.
DOI: 10.5281/zenodo.10009966
title: Sainfoin Fruit Processing - Object Detection Dataset

description: This dataset consists of 500 images of sainfoin (Onobrychis viciifolia) seed pods, seed, and split seeds. The images were taken as a part of an experiment to determine minimum sample size of seed pods needed to accurately estimate pod threshing trait heritability within sainfoin breeding lines.
The experiment was a complete factorial design with the following factors:

Sainfoin named varieties: AAC Mountainview, Delaney, Eski , Rocky Mountain Remont, and Shoshone
Sample Size: 1, 2, 3, 4, and 5 grams of dried seed pods
Two different threshing types: Belt thresher processed 3X, Haldrup Impact Thresher (35sec @ Speed 9)
This makes for a total factorial combination set of 5 varieties X 5 sample sizes X 2 threshing types = 50.
Each combination was comprised of 10 individual replicates where each replicate in a combination was a unique, random sample of seeds of the same mass (So, 10 random, 2g samples of Eski seed, processed by belt thresher; 10 random, 5g samples of Delaney seed processed by the Haldrup thresher, etc.). This makes for a total of 500 experimental units that comprise the sample set.
Once the seeds were sampled, weighed, and processed through the threshing equipment, they were weighed again and imaged.
The threshed seeds were scattered onto an imaging platform with a blue background, lit by 2 LED panels, and photographed with a Sony ILCE-7RM2 at the following settings:

ISO: 100
Exposure: 1/40s
Focal Length: 55mm
Format: TIFF
Size: 7968x5320
The raw images were converted from TIFF files to JPEG format and annotated in image labeling software. The seed objects were annotated with bounding boxes classified as the following classes

pod: an enclosed seed pod
seed: a seed which was successfully threshed from the legume pod carpel
split: a seed threshed from the pod, but which split in two halves during the threshing process
All image annotations were exported into the convenient COCO format.
No further image processing was performed.
The image set was split into a 80/20 training and validation step using `scikit-learn` in Python 3.11 stratifying the datasets equally over the various experimental factor levels.
The zip file 'train_val_images.zip' contains a 'train' folder with 400 training images, 'val' containing 100 validation images, an image taken with a color correction card named 'color_test.jpg', and a json file with all the annotations.
Another file called 'seed_weights.csv' contains the image_name to global-key mapping in tabular format as well as the before and after threshing seed weights for each experimental sample.
Labeling Metrics:

Pod (48.58%)

36,599 objects
Seed (33.83%)

25,488 object
Split (17.59%)

13,255 objects
TOTAL (100%)

75,342 objects