cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.23729/1cdd65b5-0487-45af-bd3c-43327b3f73d0
title: Synthetic Datasets by University of Oulu

description: This public dataset, created by the University of Oulu, is part of the deliverable for IDUNN D6.6. It represents the final version of synthetic datasets for cyber intelligence using fair machine learning. The dataset includes comprehensive network traffic data featuring both normal and anomalous behaviors to aid in the development and testing of Network Intrusion Detection Systems (NIDS). 
It addresses limitations in existing datasets by providing dynamically generated, modifiable, and reproducible data that reflects current cyber threat landscapes. This dataset is essential for researchers and developers focused on advancing cybersecurity through fair and effective machine-learning techniques.
DOI: 10.15468/97yemz
title: Lepidoptera (butterfly, macro-moth) records from Akrotiri Peninsula, Cyprus

description: Lepidoptera are a key component of biodiversity and are recognised as important pollinators. This dataset includes 298 occurrence records of butterflies and macro-moths from the Akrotiri peninsula, Cyprus (Sovereign Base Area of Akrotiri and Dekelia). In total, 143 species of Lepidopteran were recorded, including two endemic butterfly species Hipparchia cypriensis (Holik, 1949) and Maniola cypricola (Graves, 1928), as well as five endemic macro-moth species Agrotis sabine Brandstetter, 2010, Ammoconia aholai Fibiger, 1996, Dyscia simplicaria Rebel, 1939, Eumannia arenbergeri Hausmann, 1995, and Selidosema tamsi Rebel, 1939. Euplagia quadripunctaria (Poda, 1761), a priority and Annex II species of the Habitats Directive was sampled within the designated Special Area of Conservation of Akrotiri peninsula. Butterflies were recorded using the line transect method, and moths were sampled using light traps, allowing the creation of an inventory of the Lepidoptera fauna of this ecologically important and biodiversity rich site.
DOI: 10.15468/dl.f4th66
title: Occurrence Download

description: A dataset containing 270 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Thunbergia laevis Wall. ex Nees)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 270 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094624-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.we9z6h
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((121.81388 24.92699,121.88358 24.92699,121.88358 25.01445,121.81388 25.01445,121.81388 24.92699))",
 "OccurrenceStatus is Present",
 "TaxonKey is Squamata"
 ]
}

 The dataset includes 9 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094626-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.evkznv
title: Occurrence Download

description: A dataset containing 12542 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Herbarium of the Université Libre de Bruxelles"
 ]
}

 The dataset includes 12542 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094627-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qxaq35
title: Occurrence Download

description: A dataset containing 102 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Asystasia gangetica var. gangetica)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 102 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094628-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mq7zev
title: Occurrence Download

description: A dataset containing 102 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Asystasia gangetica var. gangetica)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 102 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094629-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11120394
title: CESBIO_AI4QC dataset

description: This dataset was used in the AI4QC project (Artificial Intelligence for Quality Control), in the context of cloud detection through semantic segmentation. It consists of a set of reference cloud masks generated by an active learning method for 30 Sentinel-2 scenes over 10 sites: Alta Floresta (Brazil), Arles (France), Ispra (Italy), Munich (Germany), Orleans (France), Gobabeb (Namibia), Marrakech (Morocco), Railroad Valley (USA), Pretoria (South AFrica) and Mongu (Zambia). The cloud masks are globally distributed and cover the year 2017-2018. The scenes are collected for different seasons and cloud cover types. The dataset is a smaller version of the CESBIO dataset, where the S2 L1C images have been added and the classes modified. The new classes are the following:



0 - clear

1 - thick cloud

2 - thin cloud

3 - cloud shadow


The "classification_maps" folder contains the cloud masks. The folder "S2_images_true_color" contains RGB images combining the bands B04, B03 and B02. These images are of size 1830 x 1830 pixels with a resolution of 60m, matching the size and resolution of the cloud masks. The folders "S2_images_B*" contain the Sentinel-2 scenes for one single band. Their resolution follows the Sentinel-2 specifications: 



B02, B03, B04, B08: 10m

B05, B06, B07, B8A, B11, B12: 20m

B01, B09, B10: 60m


The original CESBIO dataset is available at https://zenodo.org/records/1460961.
DOI: 10.5281/zenodo.11120395
title: CESBIO_AI4QC dataset

description: This dataset was used in the AI4QC project (Artificial Intelligence for Quality Control), in the context of cloud detection through semantic segmentation. It consists of a set of reference cloud masks generated by an active learning method for 30 Sentinel-2 scenes over 10 sites: Alta Floresta (Brazil), Arles (France), Ispra (Italy), Munich (Germany), Orleans (France), Gobabeb (Namibia), Marrakech (Morocco), Railroad Valley (USA), Pretoria (South AFrica) and Mongu (Zambia). The cloud masks are globally distributed and cover the year 2017-2018. The scenes are collected for different seasons and cloud cover types. The dataset is a smaller version of the CESBIO dataset, where the S2 L1C images have been added and the classes modified. The new classes are the following:



0 - clear

1 - thick cloud

2 - thin cloud

3 - cloud shadow


The "classification_maps" folder contains the cloud masks. The folder "S2_images_true_color" contains RGB images combining the bands B04, B03 and B02. These images are of size 1830 x 1830 pixels with a resolution of 60m, matching the size and resolution of the cloud masks. The folders "S2_images_B*" contain the Sentinel-2 scenes for one single band. Their resolution follows the Sentinel-2 specifications: 



B02, B03, B04, B08: 10m

B05, B06, B07, B8A, B11, B12: 20m

B01, B09, B10: 60m


The original CESBIO dataset is available at https://zenodo.org/records/1460961.
DOI: 10.15468/dl.9cja6c
title: Occurrence Download

description: A dataset containing 28 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "Country is South Africa",
 "OccurrenceStatus is Present",
 "TaxonKey is Bazzania nitida (F.Weber) Grolle"
 ]
}

 The dataset includes 28 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094630-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jvj73c
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Lepidagathis hamiltoniana Wall.)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 32 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094631-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.11120855
title: GSFC_AI4QC dataset

description: The dataset was used in the AI4QC project (Artificial Intelligence for Quality Control), in the context of cloud detection through semantic segmentation. It consists of a set of 27 reference cloud masks over NASA GSFC (coordinate reference system EPSG:32618) for various cloud conditions from September 2017 to November 2018. The cloud masks are associated to Sentinel-2 satellite data. The dataset is a smaller version of the GSFC dataset, where S2 L1C images were added, the cloud masks reclassified and rasterized (from Shapefiles to TiFF files).

The new classes are the following:



0 - clear

1 - thick cloud

2 - thin cloud

3 - cloud shadow


The "masks" folder contains the cloud masks. The folder "S2_images_true_color" contains RGB images combining the bands B04, B03 and B02 of Sentinel-2. These images have varying sizes with a resolution of 10m, matching the size and resolution of the corresponding cloud masks. The folder "S2_images_all_bands" contains one folder per Sentinel-2 band, itself containing the 27 scenes for that band. Their resolution follows the Sentinel-2 specifications: 



B02, B03, B04, B08: 10m

B05, B06, B07, B8A, B11, B12: 20m

B01, B09, B10: 60m


The original GSFC dataset is available at https://data.mendeley.com/datasets/r7tnvx7d9g/1.
DOI: 10.5281/zenodo.11120856
title: GSFC_AI4QC dataset

description: The dataset was used in the AI4QC project (Artificial Intelligence for Quality Control), in the context of cloud detection through semantic segmentation. It consists of a set of 27 reference cloud masks over NASA GSFC (coordinate reference system EPSG:32618) for various cloud conditions from September 2017 to November 2018. The cloud masks are associated to Sentinel-2 satellite data. The dataset is a smaller version of the GSFC dataset, where S2 L1C images were added, the cloud masks reclassified and rasterized (from Shapefiles to TiFF files).

The new classes are the following:



0 - clear

1 - thick cloud

2 - thin cloud

3 - cloud shadow


The "masks" folder contains the cloud masks. The folder "S2_images_true_color" contains RGB images combining the bands B04, B03 and B02 of Sentinel-2. These images have varying sizes with a resolution of 10m, matching the size and resolution of the corresponding cloud masks. The folder "S2_images_all_bands" contains one folder per Sentinel-2 band, itself containing the 27 scenes for that band. Their resolution follows the Sentinel-2 specifications: 



B02, B03, B04, B08: 10m

B05, B06, B07, B8A, B11, B12: 20m

B01, B09, B10: 60m


The original GSFC dataset is available at https://data.mendeley.com/datasets/r7tnvx7d9g/1.
DOI: 10.6084/m9.figshare.25376458
title: <b>A Morphological traits dataset of Heteroptera sampled in biodiversity priority areas of southwest China</b>

description: Functional traits reveal the adaptive strategies of species to their environment, and are relevant to the formation of communities, the function of ecosystems, and the mechanisms underlying biodiversity. However, trait databases have not been established for most biological taxa, especially for insects, which encompass a vast number of species. This study measured the morphological traits of 307 species of Heteroptera insects collected in 2019 from the "Xishuangbanna Priority Conservation Area " in southwest China using sweep netting and light trapping methods. This study provides a dataset for 307 Heteroptera species, comprising 34 morphometric measurements and 17 morphological traits. The dataset contains information on species sex, abundance, and the average, maximum, and minimum values of traits. This dataset facilitates an enhanced understanding of the functional traits and ecological associations of Heteroptera insects and offers opportunities for exploring a more diverse range of research topics.See detailed descriptions here: Gao, S., Yu, W., Tian, T., Lu, Z., Zhang, X., Li, Q. & Chen, Y. A morphological traits dataset of Heteroptera sampled in biodiversity priority areas of Southwest China. <i>Scientific Data</i> <b>11,</b> 694 (2024). https://doi.org/10.1038/s41597-024-03556-x
DOI: 10.25934/pr00010274
title: DIGAMS Data Challenge: Visualizing antimicrobial resistance trends on an open access dashboard, to guide prescribing practices.

description: Most antimicrobial stewardship, and surveillance mechanisms in Uganda and other low-income countries are focused on clinical human or veterinary settings, hoping to leverage the informed intermediary practitioners like doctors, to pass on antimicrobial stewardship (AMS) knowledge, collect data and avert AMR. This approach assumes that policies, systems and practices are all well aligned to proper AMS strategies which is not practically true. With most Ugandans especially in rural areas accessing their antibiotics without a prescription, or proper laboratory sensitivity investigations, implementation of most AMS protocols such as AWARE becomes complicated. The economic realities don’t permit people to consult doctors, or veterinarians, do proper laboratory investigations or appropriately adhere to their antibiotics.

We intend to add another line of defense against AMR at the community level by using our internally developed Digital, community based antimicrobial stewardship tool (DIGAMS). Leveraging extensive networks of digitized and AMS trained community health workers, we hope to reach each homestead to assess access, usage and disposal of both human and veterinary antibiotics, identify suspected cases of AMR, collect samples and test them for AMR. This will be in addition to random AMR surveillance at community level. The AMR data will be used to generate and open-0source dashboards to visualize AMR trends to clinicians’ and veterinarians’ prescribing practices. 

Understanding community AMR trends will guide clinicians to prescribe effective antibiotics, improving patient outcomes.

Anchoring AMS strategies, and AMR surveillance in community health systems to target the final consumers of antimicrobials both in knowledge dissemination, AMR surveillance and generation will strengthen stewardship at the community level. 

The AMR data generated will be used to inform public health policies and practices on antimicrobial use. 

Lastly, this program will significantly enhance the pool of human resources available to fight AMR, or advance AMS strengthening health systems in the process.
DOI: 10.5281/zenodo.11121064
title: KappaSet_AI4QC dataset

description: The dataset was used in the AI4QC project (Artificial Intelligence for Quality Control), in the context of semantic segmentation for cloud detection. It consists of 9251 cloud masks, distributed over the full globe and acquired over the four seasons of 2020. To each label file is associated a Sentinel-2 L1C image. The dataset originates from the KappaSet dataset, where the cloud masks were reclassified. The new classes are the following:



0 - clear

1 - thick cloud

2 - thin cloud

3 - cloud shadow


The "masks" folder contains the cloud masks, which have a size of 512 x 512 pixels with 10m resolution. The other 13 folders contain the Sentinel-2 scenes for each Sentinel-2 band. Their resolution follows the Sentinel-2 specifications:



B02, B03, B04, B08: 10m

B05, B06, B07, B8A, B11, B12: 20m

B01, B09, B10: 60m


The original KappaSet data is available at https://zenodo.org/records/7100327#.Y-d7my_P02x.
DOI: 10.5281/zenodo.11121065
title: KappaSet_AI4QC dataset

description: The dataset was used in the AI4QC project (Artificial Intelligence for Quality Control), in the context of semantic segmentation for cloud detection. It consists of 9251 cloud masks, distributed over the full globe and acquired over the four seasons of 2020. To each label file is associated a Sentinel-2 L1C image. The dataset originates from the KappaSet dataset, where the cloud masks were reclassified. The new classes are the following:



0 - clear

1 - thick cloud

2 - thin cloud

3 - cloud shadow


The "masks" folder contains the cloud masks, which have a size of 512 x 512 pixels with 10m resolution. The other 13 folders contain the Sentinel-2 scenes for each Sentinel-2 band. Their resolution follows the Sentinel-2 specifications:



B02, B03, B04, B08: 10m

B05, B06, B07, B8A, B11, B12: 20m

B01, B09, B10: 60m


The original KappaSet data is available at https://zenodo.org/records/7100327#.Y-d7my_P02x.
DOI: 10.15468/dl.gew4uw
title: Occurrence Download

description: A dataset containing 3939 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Aphelandra scabra (Vahl) Sm.)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3939 records from 132 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094632-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12543972
title: twist_panviral_masking

description: Kraken2 database for twist panviral. 1232 viruses (1232 accession numbers corresponding to 516 unique taxons)

Note that there were unmapped accession numbers. We had to add those seqid to taxon mapping in the seqid2tax file of the library before building it.

   NC_027201 taxon:11587   NC_027203 taxon:11587   NC_028101 replaced by NC_012042 taxon is 573977   NC_006947 obsolete according to NCBI taxon is 64287   NC_027202 taxon: 11587   NC_004355 taxon: 172148   NC_001347 taxon: 10359   NC_002617 139270   NC_004148 162145

 

masking option was used and otherise default parameters of the kraken2 build command.
DOI: 10.5281/zenodo.12543973
title: twist_panviral_masking

description: Kraken2 database for twist panviral. 1232 viruses (1232 accession numbers corresponding to 516 unique taxons)

Note that there were unmapped accession numbers. We had to add those seqid to taxon mapping in the seqid2tax file of the library before building it.

   NC_027201 taxon:11587   NC_027203 taxon:11587   NC_028101 replaced by NC_012042 taxon is 573977   NC_006947 obsolete according to NCBI taxon is 64287   NC_027202 taxon: 11587   NC_004355 taxon: 172148   NC_001347 taxon: 10359   NC_002617 139270   NC_004148 162145

 

masking option was used and otherise default parameters of the kraken2 build command.
DOI: 10.15468/dl.4ejq88
title: Occurrence Download

description: A dataset containing 48 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((121.63845 25.02887,121.72896 25.02887,121.72896 25.06949,121.63845 25.06949,121.63845 25.02887))",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "TaxonKey is Squamata"
 ]
}

 The dataset includes 48 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094633-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5519/qd.lp981lu3
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (41 records)
DOI: 10.15468/dl.sn2t4u
title: Occurrence Download

description: A dataset containing 55354 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Montserrat",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 55354 records from 179 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094623-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc257ts1
title: CCDC 2003523: Experimental Crystal Structure Determination

description: Related Article: Ashley L. Sutton, Brendan F. Abrahams, Timothy A. Hudson, Richard Robson|2020|New J.Chem.|44|11437|doi:10.1039/D0NJ02413A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc257tt2
title: CCDC 2003524: Experimental Crystal Structure Determination

description: Related Article: Ashley L. Sutton, Brendan F. Abrahams, Timothy A. Hudson, Richard Robson|2020|New J.Chem.|44|11437|doi:10.1039/D0NJ02413A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc257tv3
title: CCDC 2003525: Experimental Crystal Structure Determination

description: Related Article: Ashley L. Sutton, Brendan F. Abrahams, Timothy A. Hudson, Richard Robson|2020|New J.Chem.|44|11437|doi:10.1039/D0NJ02413A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc257tw4
title: CCDC 2003526: Experimental Crystal Structure Determination

description: Related Article: Ashley L. Sutton, Brendan F. Abrahams, Timothy A. Hudson, Richard Robson|2020|New J.Chem.|44|11437|doi:10.1039/D0NJ02413A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc27f0qf
title: CCDC 2068094: Experimental Crystal Structure Determination

description: Related Article: Daehan Lee, Farzad Molani, Min Su Choe, Hyun Seok Lee, Kyung-Ryang Wee, Seongpil Hwang, Chul Hoon Kim, Art E. Cho, Ho-Jin Son|2024|Inorg.Chem.|63|11506|doi:10.1021/acs.inorgchem.3c03879
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc27xfwh
title: CCDC 2082917: Experimental Crystal Structure Determination

description: Related Article: Jie Wang, Jun Gu, Jia-Yu Zou, Meng-Jie Zhang, Rui Shen, Zhiwen Ye, Ping-Xun Xu, Ying He|2024|Nat.Commun.|15|3254|doi:10.1038/s41467-024-47404-3
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.