cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.13690800
title: BaMBo: An Annotated Bone Marrow Biopsy Dataset for Segmentation Task

description: Bone marrow examination has become increasingly important for the diagnosis and treatment of hematologic and other illnesses. The present methods for analyzing bone marrow biopsy samples involve subjective and inaccurate assessments by visual estimation by pathologists. Thus, there is a need to develop automated tools to assist in the analysis of bone marrow samples. However, there is a lack of publicly available standardized and high-quality datasets that can aid in the research and development of automated tools that can provide consistent and objective measurements. In this paper, we present a comprehensive Bone Marrow Biopsy (BaMBo) dataset consisting 185 semantic-segmented bone marrow biopsy images, specifically designed for the automated calculation of bone marrow cellularity. Our dataset comprises high-resolution, generalized images of bone marrow biopsies, each annotated with precise semantic segmentation of different haematological components. These components are divided into 4 classes: Bony trabeculae, adipocytes, cellular region and BG. The annotations were performed with the help of two experienced hematopathologists that were supported by state-of-the-art DL models and image processing techniques.
DOI: 10.5281/zenodo.13690799
title: BaMBo: An Annotated Bone Marrow Biopsy Dataset for Segmentation Task

description: Bone marrow examination has become increasingly important for the diagnosis and treatment of hematologic and other illnesses. The present methods for analyzing bone marrow biopsy samples involve subjective and inaccurate assessments by visual estimation by pathologists. Thus, there is a need to develop automated tools to assist in the analysis of bone marrow samples. However, there is a lack of publicly available standardized and high-quality datasets that can aid in the research and development of automated tools that can provide consistent and objective measurements. In this paper, we present a comprehensive Bone Marrow Biopsy (BaMBo) dataset consisting 185 semantic-segmented bone marrow biopsy images, specifically designed for the automated calculation of bone marrow cellularity. Our dataset comprises high-resolution, generalized images of bone marrow biopsies, each annotated with precise semantic segmentation of different haematological components. These components are divided into 4 classes: Bony trabeculae, adipocytes, cellular region and BG. The annotations were performed with the help of two experienced hematopathologists that were supported by state-of-the-art DL models and image processing techniques.
DOI: 10.15468/dl.h9pssh
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-41.72747 29.57627,-5.57057 29.57627,-5.57057 49.51848,-41.72747 49.51848,-41.72747 29.57627))",
 "TaxonKey is Melanostomias biseriatus Regan & Trewavas, 1930"
 ]
}

 The dataset includes 5 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037788-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ywb5z5
title: Occurrence Download

description: A dataset containing 10475 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Danaus plexippus (Linnaeus, 1758)",
 "Year 2014-2024"
 ]
}

 The dataset includes 10475 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037789-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13690616
title: BoMBR: An Annotated Bone Marrow Biopsy Dataset for Segmentation of Reticulin Fibers

description: Bone marrow reticulin fibrosis is associated with varied benign as well as malignant hematological conditions. The assessment of reticulin fibrosis is important in the diagnosis, prognostication and management of such disorders. The current methods for quantification of reticulin fibrosis are inefficient and prone to errors. Therefore, there is a need for automated tools for accurate and consistent quantification of reticulin. However, the lack of standardized datasets has hindered the development of such tools. In this study, we present a comprehensive dataset that comprises of 201 Bone Marrow Biopsy images for Reticulin (BoMBR) quantification. These images were meticulously annotated for semantic segmentation, with the focus on performing reticulin fiber quantification. This annotation was done by two trained hematopathologists who were aided by DL models and image processing techniques that generated a rough automated annotation for them to start with. This ensured precise delineation of the reticulin fibers alongside other cellular components such as bony trabeculae, fat, and cells. This is the first publicly available dataset in this domain with the aim to catalyze advancements the development of computational models for improved reticulin quantification.
DOI: 10.5281/zenodo.13690617
title: BoMBR: An Annotated Bone Marrow Biopsy Dataset for Segmentation of Reticulin Fibers

description: Bone marrow reticulin fibrosis is associated with varied benign as well as malignant hematological conditions. The assessment of reticulin fibrosis is important in the diagnosis, prognostication and management of such disorders. The current methods for quantification of reticulin fibrosis are inefficient and prone to errors. Therefore, there is a need for automated tools for accurate and consistent quantification of reticulin. However, the lack of standardized datasets has hindered the development of such tools. In this study, we present a comprehensive dataset that comprises of 201 Bone Marrow Biopsy images for Reticulin (BoMBR) quantification. These images were meticulously annotated for semantic segmentation, with the focus on performing reticulin fiber quantification. This annotation was done by two trained hematopathologists who were aided by DL models and image processing techniques that generated a rough automated annotation for them to start with. This ensured precise delineation of the reticulin fibers alongside other cellular components such as bony trabeculae, fat, and cells. This is the first publicly available dataset in this domain with the aim to catalyze advancements the development of computational models for improved reticulin quantification.
DOI: 10.5281/zenodo.13790322
title: MMDC Europe (full dataset)

description: MMDC-EU is a multi-year, multimodal SITS dataset spanning Europe. This dataset is composed of the following data: the Sentinel 2 L2A product (processed with Sen2cor), the Sentinel 1 ascending and descending orbits, ECMWF AGERA5 weather variables, and a digital elevation model (DEM). Although all modalities are not initially available at a 10m resolution, all products are up-sampled on the Sentinel-2 10m spatial grid. Multi-year multimodal SITS were acquired from January 2017 to December 2020. 




Product name  
Bands      
Average acquisitions/year


S2 L2A 
B2-B8, B8A, B11,B12,SCL, CLM, dataMask, sunAzimuthAngles,sunZenithAngles   
89


S1-GRD-\gamma 0 terrain ASCENDING
VV, VH    
 90


S1-GRD-\gamma 0 terrain DESCENDING
VV, VH
107


ERA 5
Dewpoint-temperature, Precipitation-flux, solar-radiation-flux, temperature-max, temperature-mean, temperature-min, vapour-pressure, wind-speed  
365


DEM 
GLO-30      
-




Specifically, the pre-training dataset gathers data from eighteen S2 tiles. This pre-training dataset is divided into training and validation sets. To build the training dataset, ten smaller non-overlapping ROIs of size (512,512) are randomly selected from each of the twelve training tile. The disjoint validation dataset is composed of the remaining six S2 tiles, from which thirty ROIs of size  (128,128) are randomly drawn. The code utilized to create the multimodal dataset is provided, allowing for potential future expansion : https://src.koda.cnrs.fr/iris.dumeur/openeo_datasets

The training data are available: 



30TXT:  10.5281/zenodo.12750451

31TDL: 10.5281/zenodo.12755396

31TEN: 10.5281/zenodo.12773938

32TPT: 10.5281/zenodo.12795519

32TPQ: 10.5281/zenodo.1278467

32UMB: 10.5281/zenodo.13313224

33TVM: 10.5281/zenodo.13384485

32UQD: 10.5281/zenodo.1332334

33UXR: 10.5281/zenodo.13482459

33TYJ: 10.5281/zenodo.13385645

34UEC: 10.5281/zenodo.13628736

34TFR: 10.5281/zenodo.13618543


The validation data are available at: 



30TYR:  10.5281/zenodo.13629634

31TEK: 10.5281/zenodo.13629668

32TNR: 10.5281/zenodo.13643024

32UPC: 10.5281/zenodo.13644104

33TXK: 10.5281/zenodo.13644596

34UDB: 10.5281/zenodo.13645759


The geojson describing the ROI extent on each S2 tiles are also provided in this repository.
DOI: 10.15468/dl.rkfrcq
title: Occurrence Download

description: A dataset containing 56 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Denmark",
 "Issue is Continent coordinate mismatch",
 "OccurrenceStatus is Present",
 "PublishingOrg is 977178c7-76fe-4c86-94f3-cf039ede5c3c"
 ]
}

 The dataset includes 56 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037792-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12750450
title: MMDC Europe 30TXT (train)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.12750451
title: MMDC Europe 30TXT (train)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.12755395
title: MMDC Europe 31TDL (train)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.12755396
title: MMDC Europe 31TDL (train)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.12773937
title: MMDC Europe 31TEN (train)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.12773938
title: MMDC Europe 31TEN (train)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.12784675
title: MMDC Europe 32TPQ (train)

description: These data are part of the pre-training multimodal dataset named MMDC Europe.  See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.12784676
title: MMDC Europe 32TPQ (train)

description: These data are part of the pre-training multimodal dataset named MMDC Europe.  See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.13385644
title: MMDC Europe 33TYJ (train)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.13385645
title: MMDC Europe 33TYJ (train)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.13482458
title: MMDC Europe 33UXR (train)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.13482459
title: MMDC Europe 33UXR (train)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.13618542
title: MMDC Europe 34TFR (train)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.13618543
title: MMDC Europe 34TFR (train)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.13628735
title: MMDC Europe 34UEC (train)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.13628736
title: MMDC Europe 34UEC (train)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.13629633
title: MMDC Europe 30TYR (val)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.13629634
title: MMDC Europe 30TYR (val)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.57702/5rf5jlkf
title: Demo Hybride KI

description: In diesem Szenario haben wir einen Anrufer, der von einem Autounfall berichtet. Durch ein LLM werden die Anzahl der betroffenen Objekte und die Unfallart erkannt und dem Anwender als Eintrag im entsprechenden Feld vorgeschlagen. Auch die Geolokation wird angelegt. Mit der Anzahl der betroffenen Objekte und der Unfallart, wird durch CBR und RBR die Anzahl an Einsatzfahrzeugen(RTW & NEF) bestimmt und angelegt.
DOI: 10.5281/zenodo.13629667
title: MMDC Europe 31TEK (val)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.13629668
title: MMDC Europe 31TEK (val)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.13643023
title: MMDC Europe 32TNR (val)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.13643024
title: MMDC Europe 32TNR (val)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.13644103
title: MMDC Europe 32UPC (val)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.13644104
title: MMDC Europe 32UPC (val)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.13644595
title: MMDC Europe 33TXK (val)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.13644596
title: MMDC Europe 33TXK (val)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.13645758
title: MMDC Europe 34UDB (val)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.5281/zenodo.13645759
title: MMDC Europe 34UDB (val)

description: These data are part of the pre-training multimodal dataset named MMDC Europe. 

See : https://zenodo.org/uploads/13790323
DOI: 10.15468/dl.vvkcv6
title: Occurrence Download

description: A dataset listing the 25 species recorded in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "IucnRedListCategory is EW"
 ]
}

 The dataset's 25 records were derived from 53 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037750-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57702/mquk2udz
title: Master of Disaster

description: A demonstration of different technical aspects/technologies. Last tab is a Llama 3-based ESG Classification (Classes: environmental event, societal event, governmental event and out-of-scope). The second last one does question answering with SPARQL Structure Prediction and SPARQL Content Population -&gt; Query Generation. The third one is the Universal Event Detector (UED). The second one is an Event Detector: crisis-related LM + supervised contrastive learning on TREC-IS dataset. The first one does showcase KG connection and does visualize it.
DOI: 10.15468/dl.6kzzjz
title: Occurrence Download

description: A dataset containing 56 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Denmark",
 "Issue is Continent coordinate mismatch",
 "OccurrenceStatus is Present",
 "PublishingOrg is 977178c7-76fe-4c86-94f3-cf039ede5c3c"
 ]
}

 The dataset includes 56 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037795-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13843321
title: CropRot T31TFJ

description: Part of the CropRot dataset. The complete dataset is available at : https://zenodo.org/uploads/13880014
DOI: 10.5281/zenodo.13843322
title: CropRot T31TFJ

description: Part of the CropRot dataset. The complete dataset is available at : https://zenodo.org/uploads/13880014
DOI: 10.15468/dl.ayhz7z
title: Occurrence Download

description: A dataset containing 196493 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "Country is one of (United States of America, Canada, Mexico)",
 "Geometry POLYGON((-167.80446 2.94333,-46.98525 2.94333,-46.98525 74.27561,-167.80446 74.27561,-167.80446 2.94333))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Apis mellifera Linnaeus, 1758",
 "Year 2013-2023"
 ]
}

 The dataset includes 196493 records from 82 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0037745-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u48ru2
title: Occurrence Download

description: A dataset containing 180 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Verbesina abscondita Klatt"
 ]
}

 The dataset includes 180 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028130-230810091245214/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a38m5x
title: Occurrence Download

description: A dataset containing 711 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Forestiera phillyreoides (Benth.) Torr."
 ]
}

 The dataset includes 711 records from 51 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0355731-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9hpwra
title: Occurrence Download

description: A dataset containing 2419 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Flora de las sabanas inundables de las cuencas de los ríos Bita, Manacacías y Cravo Sur - SULU II"
 ]
}

 The dataset includes 2419 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004596-200127171203522/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.js838n
title: Occurrence Download

description: A dataset containing 208 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Verbena glabrata Kunth"
 ]
}

 The dataset includes 208 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028126-230810091245214/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cmygw8
title: Occurrence Download

description: A dataset containing 424 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mergus octosetaceus Vieillot, 1817"
 ]
}

 The dataset includes 424 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0364834-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cxugmw
title: Occurrence Download

description: A dataset containing 36 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Puerto Rico",
 "Year 1000-1999",
 "TaxonKey is Antrostomus noctitherus (Wetmore, 1919)"
 ]
}

 The dataset includes 36 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010482-200221144449610/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zz39ww
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Verbesina acapulcensis B.L.Rob. & Greenm."
 ]
}

 The dataset includes 12 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028132-230810091245214/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.82gp8f
title: Occurrence Download

description: A dataset containing 212 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Aegilops caudata L.)",
 "Geometry POLYGON((-9.36035 44.71551,-10.59082 42.81152,-11.82129 36.80928,-7.69043 36.17336,-3.38379 35.88905,3.12012 38.13456,9.18457 38.20366,11.7334 37.16032,12.78809 34.74161,17.09473 33.79741, 23.15918 34.23451,30.10254 32.62087,33.2666 32.99024,35.72754 35.03,33.00293 35.53223,28.69629 35.17381,28.34473 36.31513,25.7959 37.50973,24.91699 39.90974,28.78418 40.6473,30.71777 41.17865,36.87012 45.213,38.18848 46.98025,38.71582 47.7541,39.94629 47.93107,40.20996 49.61071,37.0459 50.34546,35.72754 50.40152,33.79395 52.26816,31.68457 51.94426,31.4209 53.27835,32.56348 53.43572,30.98145 54.77535,30.89355 55.52863,28.43262 56.02295,27.20215 57.65716,27.37793 58.30949,27.90527 59.17593,29.66309 59.88894,27.6416 60.58697,31.50879 62.75473,28.78418 69.83962,30.89355 70.28912,29.22363 71.55274,21.75293 71.30079,14.28223 70.14036,11.38184 67.47492,4.87793 63.66576,-5.53711 71.52491,-10.63477 71.69129,-21.5332 67.74276,-28.56445 65.36684,-24.3457 61.35461,-9.36035 44.71551))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2021"
 ]
}

 The dataset includes 212 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0228682-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bmwu2s
title: Occurrence Download

description: A dataset containing 586 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hakea pandanicarpa R.Br."
 ]
}

 The dataset includes 586 records from 44 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001968-230828120925497/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.