cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17514693
title: COCO-Formatted Bounding Box Annotations for the NIH Thin Blood Smear Malaria Dataset

description: This repository provides bounding box annotations in COCO format for the publicly available NIH-NLM Thin Blood Smear Dataset for Plasmodium falciparum detection. The annotations were generated through a combination of automated instance segmentation using Cellpose and targeted manual correction. A detailed description of the database curation can be obtained from this manuscript:



Wilm, Frauke, et al. "A COCO-Formatted Instance-Level Dataset for Plasmodium Falciparum Detection in Giemsa-Stained Blood Smears." arXiv preprint arXiv:2507.18483 (2025), doi: 10.48550/arXiv.2507.18483. 


Dataset Structure

The repository contains the following files:



nih_polys_coco.json: COCO annotations for the polygon-labeled subset

nih_points_coco.json: COCO annotations for the point-labeled subset (converted to boxes)

categories.json: Class label definitions


All annotation files follow the COCO format. The annotations include bounding boxes for three classes: non-infected red blood cells, infected red blood cells, and white blood cells. Each file corresponds to one of the original NIH subsets:



nih_polys_coco.json: derived from the 165 polygon-labeled images.

nih_points_coco.json: derived from the 800 point-annotated images.


Modalities and Tasks

Modality: Brightfield microscopy images of Giemsa-stained thin-blood smears.

Task: Object detection of individual red and white blood cells, with classification into:



Non-infected red blood cells

Infected red blood cells

White blood cells


Patient Information Fields

The annotation files do not include identifiable patient information. However, each image in the original NIH dataset is associated with one of 193 patients. The original dataset includes:



148 infected patients

45 uninfected patients

5 images per patient


Please refer to the original dataset publication for additional metadata:  



Kassim, Yasmin M., et al. "Clustering-based dual deep learning architecture for detecting red blood cells in malaria diagnostic smears." IEEE Journal of Biomedical and Health Informatics 25.5 (2020): 1735-1746.


Link to dataset

Licensing and Usage

The original NIH dataset is provided under the following license terms:



The data may be used, modified, and redistributed for commercial and non-commercial purposes.

Attribution must be provided: “Courtesy of the U.S. National Library of Medicine.”

Please cite the original dataset publication.


The annotation files in this repository are released under the same terms as the original dataset. If used, please cite the accompanying publication describing the annotation process and evaluation.

Contact

For questions or feedback, please contact: Frauke Wilm
DOI: 10.5281/zenodo.17514694
title: COCO-Formatted Bounding Box Annotations for the NIH Thin Blood Smear Malaria Dataset

description: This repository provides bounding box annotations in COCO format for the publicly available NIH-NLM Thin Blood Smear Dataset for Plasmodium falciparum detection. The annotations were generated through a combination of automated instance segmentation using Cellpose and targeted manual correction. A detailed description of the database curation can be obtained from this manuscript:



Wilm, Frauke, et al. "A COCO-Formatted Instance-Level Dataset for Plasmodium Falciparum Detection in Giemsa-Stained Blood Smears." arXiv preprint arXiv:2507.18483 (2025), doi: 10.48550/arXiv.2507.18483. 


Dataset Structure

The repository contains the following files:



nih_polys_coco.json: COCO annotations for the polygon-labeled subset

nih_points_coco.json: COCO annotations for the point-labeled subset (converted to boxes)

categories.json: Class label definitions


All annotation files follow the COCO format. The annotations include bounding boxes for three classes: non-infected red blood cells, infected red blood cells, and white blood cells. Each file corresponds to one of the original NIH subsets:



nih_polys_coco.json: derived from the 165 polygon-labeled images.

nih_points_coco.json: derived from the 800 point-annotated images.


Modalities and Tasks

Modality: Brightfield microscopy images of Giemsa-stained thin-blood smears.

Task: Object detection of individual red and white blood cells, with classification into:



Non-infected red blood cells

Infected red blood cells

White blood cells


Patient Information Fields

The annotation files do not include identifiable patient information. However, each image in the original NIH dataset is associated with one of 193 patients. The original dataset includes:



148 infected patients

45 uninfected patients

5 images per patient


Please refer to the original dataset publication for additional metadata:  



Kassim, Yasmin M., et al. "Clustering-based dual deep learning architecture for detecting red blood cells in malaria diagnostic smears." IEEE Journal of Biomedical and Health Informatics 25.5 (2020): 1735-1746.


Link to dataset

Licensing and Usage

The original NIH dataset is provided under the following license terms:



The data may be used, modified, and redistributed for commercial and non-commercial purposes.

Attribution must be provided: “Courtesy of the U.S. National Library of Medicine.”

Please cite the original dataset publication.


The annotation files in this repository are released under the same terms as the original dataset. If used, please cite the accompanying publication describing the annotation process and evaluation.

Contact

For questions or feedback, please contact: Frauke Wilm
DOI: 10.48717/wf8v-7e93
title: EVN Experiment EM041
DOI: 10.48717/s6p9-2e24
title: EVN Observation EM043A
DOI: 10.48717/85t3-5f61
title: EVN Observation EM043B
DOI: 10.48717/xpsa-7q29
title: EVN Experiment EM043
DOI: 10.1285/i9788883052378n1p81
title: bIAs: su computazione algoritmica e razzismo sistemico
DOI: 10.48717/076e-hj28
title: EVN Observation F01L2
DOI: 10.48717/x1ab-7k29
title: EVN Experiment F01L2
DOI: 10.48717/90r2-gw86
title: EVN Observation GG047
DOI: 10.48717/p205-y384
title: EVN Experiment GG047
DOI: 10.48717/gmhm-1v51
title: EVN Observation GS017
DOI: 10.48717/jrx5-dp89
title: EVN Experiment GS017
DOI: 10.48717/741t-mt23
title: EVN Observation S01C2
DOI: 10.48717/wyt5-j532
title: EVN Experiment S01C2
DOI: 10.48717/j4n8-p673
title: EVN Observation N01C2
DOI: 10.48717/sfxz-z433
title: EVN Experiment N01C2
DOI: 10.15468/dl.cwk4q9
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Oxalis pes-caprae",
 "Country is Czechia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053972-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.11582/2021.00025
title: Temperature, salinity, light and fluorescence (CTD) measurements from the Rijpfjorden (Svalbard) marine observatory (mooring) September 2012-September 2013

description: As part of the "KROP - Kongsfjorden Rijpfjorden Observatory Programme" UiT The Arctic University of Norway and The Scottish Association for Marine Science maintain marine observatories (moorings) in two high-Arctic fjords in Svalbard: Kongsfjorden and Rijpfjorden. The observatories consists of an array of CTDs, temperature loggers, ADCPs and a sediment trap, in addition to various other instruments or installations that change from year to year. 
This dataset contains the CTD, PAR and fluorescence data from Rijpfjorden 2012-2013. 
Fluorescence data is given as raw voltage only, due to calibration and fouling issues. It is meant as an indication of the timing of the phytoplankton bloom, not as absolute chlorophyll a concentration. 
No post-recovery processing of light data (to correct for fouling) has been performed. 
The observatory layout is available in the mooring diagram provided. 
For this deployment the SBE16p was attached above the subsurface sphere, together with a bag of blue mussels (survival experiment). A second SBE16p was deployed at the regular depth (38m). An additional sediment trap was mounted at 50m depth. Last deployment using Vemco temperature loggers. Vemco logger s/n 1596, 1599 and 1600 failed (not data).
DOI: 10.15468/dl.chc2mv
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Parthenocissus quinquefolia",
 "Country is Slovenia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 7 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053971-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.11582/2021.00026
title: Temperature, salinity, light and fluorescence (CTD) measurements from the Rijpfjorden (Svalbard) marine observatory (mooring) September 2010-September 2011

description: As part of the "KROP - Kongsfjorden Rijpfjorden Observatory Programme" UiT The Arctic University of Norway and The Scottish Association for Marine Science maintain marine observatories (moorings) in two high-Arctic fjords in Svalbard: Kongsfjorden and Rijpfjorden. The observatories consists of an array of CTDs, temperature loggers, ADCPs and a sediment trap, in addition to various other instruments or installations that change from year to year. 
This dataset contains the CTD, PAR and fluorescence data from Rijpfjorden 2010-2011. 
Fluorescence data is given as raw voltage only, due to calibration and fouling issues. It is meant as an indication of the timing of the phytoplankton bloom, not as absolute chlorophyll a concentration. 
No post-recovery processing of light data (to correct for fouling) has been performed. 
The observatory layout is available in the mooring diagram provided. 
We missed the target depth by 15m, the entire mooring about 15m deeper than usual, thus light and fluorescence data are not directly comparable between years.
DOI: 10.11582/2021.00027
title: Temperature, salinity, light and fluorescence (CTD) measurements from the Rijpfjorden (Svalbard) marine observatory (mooring) September 2011-September 2012

description: As part of the "KROP - Kongsfjorden Rijpfjorden Observatory Programme" UiT The Arctic University of Norway and The Scottish Association for Marine Science maintain marine observatories (moorings) in two high-Arctic fjords in Svalbard: Kongsfjorden and Rijpfjorden. The observatories consists of an array of CTDs, temperature loggers, ADCPs and a sediment trap, in addition to various other instruments or installations that change from year to year. 
This dataset contains the CTD, PAR and fluorescence data from Rijpfjorden 2011-2012. 
Fluorescence data is given as raw voltage only, due to calibration and fouling issues. It is meant as an indication of the timing of the phytoplankton bloom, not as absolute chlorophyll a concentration. 
No post-recovery processing of light data (to correct for fouling) has been performed. 
The observatory layout is available in the mooring diagram provided. 
This deployment is lacking the typcial top SBE37.
DOI: 10.11582/2021.00028
title: Pictures from an all-sky camera with hourly resolution from the light observatory at Ny-Ålesund, Svalbard, Norway (complete year 2017)

description: UiT The Arctic University of Norway (UiT) and the Norwegian University of Science and Technology (NTNU) established a light observatory at Kings Bay, Ny-Ålesund (Svalbard, Norway) in January 2017. The observatory consists of a range of light sensors including an all sky camera. It is located outside the settlement of Ny-Ålesund, approximately 1 km N-NW of the airport towards Brandalspynten. The array of sensors, including the camera, is mounted on a tripod under a transparent dome. This dataset contains the pictures taken during 2017 at hourly intervals by the all-sky-camera. The camera (Canon EOS 5D Mark III) is equipped with a fish-eye lens with a focal length set to 8 mm with aperture manually set to open (f/4) to ensure maximum sensitivity (Canon EF 8-15mm f/4L), providing a 180° image of the atmosphere (only possible with a full-size sensor). Both shutter speed (exposure time, ranging from 0.000125 to 30 seconds) and ISO (sensitivity, ranging from 100 at Midnight Sun period and up to 6400 during Polar Night) are set to auto. White balance manually set to “day light”. It is remotely controlled by a PC, pictures were stored in a cloud storage. Short gaps in the time series are due to power failures. In this dataset there is one larger gap: 2017-01-19 to 2017-01-21 caused by a crash of the controlling PC which was not monitored at that time. The pictures were primarily intended as a visual quality control of the data from the light sensors (obstructions on the dome, light pollution), but have also been used as a highly sensitive light sensor of its own by extracting data from each picture. Light data from the sensor array is also available on NIRD.
DOI: 10.15468/dl.kmskun
title: Occurrence Download

description: A dataset containing 10 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Nyctereutes procyonoides",
 "Country is Latvia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 10 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053974-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.11582/2021.00029
title: Pictures from an all-sky camera with hourly resolution from the light observatory at Ny-Ålesund, Svalbard, Norway (complete year 2018)

description: UiT The Arctic University of Norway (UiT) and the Norwegian University of Science and Technology (NTNU) established a light observatory at Kings Bay, Ny-Ålesund (Svalbard, Norway) in January 2017. The observatory consists of a range of light sensors including an all sky camera. It is located outside the settlement of Ny-Ålesund, approximately 1 km N-NW of the airport towards Brandalspynten. The array of sensors, including the camera, is mounted on a tripod under a transparent dome. This dataset contains the pictures taken during 2018 at hourly intervals by the all-sky-camera. The camera (Canon EOS 5D Mark III) is equipped with a fish-eye lens with a focal length set to 8 mm with aperture manually set to open (f/4) to ensure maximum sensitivity (Canon EF 8-15mm f/4L), providing a 180° image of the atmosphere (only possible with a full-size sensor). Both shutter speed (exposure time, ranging from 0.000125 to 30 seconds) and ISO (sensitivity, ranging from 100 at Midnight Sun period and up to 6400 during Polar Night) are set to auto. White balance manually set to “day light”. It is remotely controlled by a PC, pictures were stored in a cloud storage. Short gaps in the time series are due to power failures. In this dataset there are two large gaps: 2018-05-16 to 2018-05-18 and 2018-08-20 to 2018-08-22 caused by a crash of the controlling PC. The pictures were primarily intended as a visual quality control of the data from the light sensors (obstructions on the dome, light pollution), but have also been used as a highly sensitive light sensor of its own by extracting data from each picture. Light data from the sensor array is also available on NIRD.
DOI: 10.15468/dl.ve5af2
title: Occurrence Download

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

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053975-250717081556266/datasets/export for details.
DOI: 10.15468/dl.y78mws
title: Occurrence Download

description: A dataset containing 39 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Nyctereutes procyonoides",
 "Country is Lithuania",
 "HasCoordinate is true"
 ]
}

 The dataset includes 39 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053977-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.11582/2021.00031
title: Temperature, salinity, light and fluorescence (CTD) measurements from the Rijpfjorden (Svalbard) marine observatory (mooring) August 2018-September 2020

description: As part of the "KROP - Kongsfjorden Rijpfjorden Observatory Programme" UiT The Arctic University of Norway and The Scottish Association for Marine Science maintain marine observatories (moorings) in two high-Arctic fjords in Svalbard: Kongsfjorden and Rijpfjorden. The observatories consists of an array of CTDs, temperature loggers, ADCPs and a sediment trap, in addition to various other instruments or installations that change from year to year. 
This dataset contains the CTD, PAR and fluorescence data from Rijpfjorden 2018-2020. 
Fluorescence data is given as raw voltage only, due to calibration and fouling issues. It is meant as an indication of the timing of the phytoplankton bloom, not as absolute chlorophyll a concentration. 
No post-recovery processing of light data (to correct for fouling) has been performed. 
The observatory layout is available in the mooring diagram provided. 
The mooring was deployed for 2 years due to heavy ice cover on Rijpfjorden in 2019 which made recovery impossible. It was equipped with 6 SBE37 to get a good picture of the water mass exchange throughout the water column. All sensor still logging after 2 years, the sediment trap only collected the 2018-19 samples.
DOI: 10.15468/dl.sdr4hv
title: Occurrence Download

description: A dataset containing 259 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Nyctereutes procyonoides",
 "Country is Netherlands",
 "HasCoordinate is true"
 ]
}

 The dataset includes 259 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053978-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g6v9q4
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Stethobaris laevimargo",
 "HasCoordinate is true"
 ]
}

 The dataset includes 20 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053976-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.22nup2
title: Occurrence Download

description: A dataset containing 2504 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Emberiza cineracea)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "License is one of (CC-BY 4.0, CC0 1.0)"
 ]
}

 The dataset includes 2504 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053979-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tuwge5
title: Occurrence Download

description: A dataset containing 553 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Parthenocissus quinquefolia",
 "Country is Sweden",
 "HasCoordinate is true"
 ]
}

 The dataset includes 553 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053980-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.11582/2021.00037
title: Photosynthetic active radiation (PAR) time series measured under the dome of a light observatory in the Arctic (Ny-Ålesund, Svalbard, Norway)

description: Two LiCor PAR (Photosynthetically Active Radiation, 400-700 nm) sensors were installed under a plexiglass dome in a light observatory in Ny-Ålesund, Svalbard, Norway in January 2020. One sensor is controlled by a Sutron Xlite 9210 data logger with a 16bit A/D converter, the second sensor by a Campbell Scientific CR6 data logger with a 24bit A/D converter. This dataset contains the 2020 data (start: 2020-01-11) from the Sutron logger. There are two variables recorded: one for data collected with standard A/D configuration and the second one with ‘Volts x128’ option applied by the data logger in order to achieve better A/D resolutions. The data logger is set to store data in 10 minute intervals, no averaging. The sensor is accompanied by other light sensors to cover the entire range of bright midnight sun to dark polar night: an USSIMO sensor, an all-sky SLR camera and a self-designed underwater light sensor.  Together with the light sensor several temperature sensors were also deployed in the observatory. The light sensor data in this archive is not temperature corrected but corresponding temperature files are available. The setup is part of the Arctic ABC Development project funded by the Norwegian Research Council (grant number: 245923).
DOI: 10.15468/dl.2qq8a8
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Oxalis pes-caprae",
 "Country is Denmark",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0053981-250717081556266/datasets/export for details.
DOI: 10.11582/2021.00038
title: Code and software used in the article "Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification"

description: This upload contains all the code and software used in the manuscript "Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification". The README file provides guidance on how to execute the code to reproduce the findings. Note that the software wrapped inside this upload have their own license statements, but included in this upload just for the sake of freezing the versions used in this study.