cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.11176065
title: Underwater images collected by an Autonomous Surface Vehicle in Boucan, Réunion - 2023-11-21

description: This dataset was collected by an Autonomous Surface Vehicle in Boucan, Réunion - 2023-11-21. 

            Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation.
            These images can be annotated and shared to train IA models which can in turn predict the objects on the images.
            We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps.

            This dataset is part of larger collection referencing numerous underwater and aerial images Seatizen Altas. 
            Methods, tools and scientific objectives are also described in a dedicated data paper.

            

            
 Generic folder structure 
            
            YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number 
            ├── DCIM :  folder to store videos and photos depending on the media collected. 
            ├── GPS :  folder to store any positioning related file. If any kind of correction is possible on files (e.g. Post-Processed Kinematic thanks to rinex data) then the distinction between device data and base data is made. If, on the other hand, only device position data are present and the files cannot be corrected by post-processing techniques (e.g. gpx files), then the distinction between base and device is not made and the files are placed directly at the root of the GPS folder. 
            │   ├── BASE :  files coming from rtk station or any static positioning instrument. 
            │   └── DEVICE : files coming from the device. 
            ├── METADATA : folder with general information files about the session. 
            ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. 
            │   ├── BATHY :  output folder for bathymetry raw data extracted from mission logs. 
            │   ├── FRAMES :  output folder for georeferenced frames extracted from DCIM videos. 
            │   ├── IA :  destination folder for image recognition predictions. 
            │   └── PHOTOGRAMMETRY :  destination folder for reconstructed models in photogrammetry. 
            └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot,  mission plan etc.).       
            

            
 Software 
            All the raw data was processed using our worflow. All predictions were generated by our inference pipeline. You can find all the necessary scripts to download this data in this repository. Enjoy your data with SeatizenDOI!
description: The Plancha project is co-financed by the Prefecture of Reunion as part of a 2019-2022 convergence and transformation contract, measure 3.3.1.1
DOI: 10.5281/zenodo.11176190
title: Underwater images collected by an Autonomous Surface Vehicle in Boucan, Réunion - 2023-11-21

description: This dataset was collected by an Autonomous Surface Vehicle in Boucan, Réunion - 2023-11-21. 

            Underwater or aerial images collected by scientists or citizens can have a wide variety of use for science, management, or conservation.
            These images can be annotated and shared to train IA models which can in turn predict the objects on the images.
            We provide a set of tools (hardware and software) to collect marine data, predict species or habitat, and provide maps.

            This dataset is part of larger collection referencing numerous underwater and aerial images Seatizen Altas. 
            Methods, tools and scientific objectives are also described in a dedicated data paper.

            

            
 Generic folder structure 
            
            YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number 
            ├── DCIM :  folder to store videos and photos depending on the media collected. 
            ├── GPS :  folder to store any positioning related file. If any kind of correction is possible on files (e.g. Post-Processed Kinematic thanks to rinex data) then the distinction between device data and base data is made. If, on the other hand, only device position data are present and the files cannot be corrected by post-processing techniques (e.g. gpx files), then the distinction between base and device is not made and the files are placed directly at the root of the GPS folder. 
            │   ├── BASE :  files coming from rtk station or any static positioning instrument. 
            │   └── DEVICE : files coming from the device. 
            ├── METADATA : folder with general information files about the session. 
            ├── PROCESSED_DATA : contain all the folders needed to store the results of the data processing of the current session. 
            │   ├── BATHY :  output folder for bathymetry raw data extracted from mission logs. 
            │   ├── FRAMES :  output folder for georeferenced frames extracted from DCIM videos. 
            │   ├── IA :  destination folder for image recognition predictions. 
            │   └── PHOTOGRAMMETRY :  destination folder for reconstructed models in photogrammetry. 
            └── SENSORS : folder to store files coming from other sources (bathymetry data from the echosounder, log file from the autopilot,  mission plan etc.).       
            

            
 Software 
            All the raw data was processed using our worflow. All predictions were generated by our inference pipeline. You can find all the necessary scripts to download this data in this repository. Enjoy your data with SeatizenDOI!
description: The Plancha project is co-financed by the Prefecture of Reunion as part of a 2019-2022 convergence and transformation contract, measure 3.3.1.1
DOI: 10.25549/pcra-c14-151566
title: Suchasnaia sektanctva na Bielarusi = Modern sectarianism in Belarus, 1929

description: [description english/roman)] D. Kajtun, P. Kalajevič. Suchasnaia sektanctva na Bielarusi. (Biblioteka biazbožnika). Miensk, Bielaruś: Bielaruskaje Dziaržaŭnaha Bydaviectva, 1929. = Kaituna D., P. Kalaevich. Modern sectarianism in Belarus. (Ungodly Library). Minsk, Belarus: Belarusian State Publisher, 1929.
DOI: 10.15468/dl.hrzww9
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Arabis rhodantha Greene"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045724-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vvm47p
title: Occurrence Download

description: A dataset containing 19134 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Xeno-canto - Bird sounds from around the world",
 "Geometry POLYGON((-116.62021 16.92489,-83.64190 16.92489,-83.64190 30.11057,-116.62021 30.11057,-116.62021 16.92489))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 19134 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004578-230918134249559/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wb798x
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Raphanus cheiranthiflorus Willd."
 ]
}

 The dataset includes 6 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0045726-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/pcra-c14-152432
title: Kliasavy vorag pad maskai sektanta = The class enemy in the guise of the sectarian, 1930

description: [description english/roman)] M. Galaktsienau. Kliasavy vorag pad maskai sektanta. (Biblioteka Chyrvonaarmeitsa). Mensk, Belarus: Belaruskae Deiarzhaunae Vydavetsiva, 1930. = M. Galaktionov. The class enemy in the guise of the sectarian. (Red Army Library). Minsk, Belarus: Belarusian State Vydabetsiva, 1930. Translated from USSRn into Belarusian by G. Vinagradau (Vinogradov).
DOI: 10.15468/dl.z4cpfx
title: Occurrence Download

description: A dataset containing 26773 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Carex cespitosa L."
 ]
}

 The dataset includes 26773 records from 218 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014547-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/pcra-c14-152424
title: Kliasavy vorag pad maskai sektanta = The class enemy in the guise of the sectarian, 1930

description: [description english/roman)] M. Galaktsienau. Kliasavy vorag pad maskai sektanta. (Biblioteka Chyrvonaarmeitsa). Mensk, Belarus: Belaruskae Deiarzhaunae Vydavetsiva, 1930. = M. Galaktionov. The class enemy in the guise of the sectarian. (Red Army Library). Minsk, Belarus: Belarusian State Vydabetsiva, 1930. Translated from USSRn into Belarusian by G. Vinagradau (Vinogradov).
DOI: 10.25549/pcra-c14-152419
title: Kliasavy vorag pad maskai sektanta = The class enemy in the guise of the sectarian, 1930

description: [description english/roman)] M. Galaktsienau. Kliasavy vorag pad maskai sektanta. (Biblioteka Chyrvonaarmeitsa). Mensk, Belarus: Belaruskae Deiarzhaunae Vydavetsiva, 1930. = M. Galaktionov. The class enemy in the guise of the sectarian. (Red Army Library). Minsk, Belarus: Belarusian State Vydabetsiva, 1930. Translated from USSRn into Belarusian by G. Vinagradau (Vinogradov).
DOI: 10.15468/dl.953c9t
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Enneapterygius paucifasciatus Fricke, 1994"
 ]
}

 The dataset includes 18 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002326-230918134249559/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/pcra-c14-152423
title: Kliasavy vorag pad maskai sektanta = The class enemy in the guise of the sectarian, 1930

description: [description english/roman)] M. Galaktsienau. Kliasavy vorag pad maskai sektanta. (Biblioteka Chyrvonaarmeitsa). Mensk, Belarus: Belaruskae Deiarzhaunae Vydavetsiva, 1930. = M. Galaktionov. The class enemy in the guise of the sectarian. (Red Army Library). Minsk, Belarus: Belarusian State Vydabetsiva, 1930. Translated from USSRn into Belarusian by G. Vinagradau (Vinogradov).
DOI: 10.15468/dl.scuemj
title: Occurrence Download

description: A dataset containing 909 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Human Observation)",
 "Country is one of (Chile, Argentina)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Araucaria araucana (Molina) K.Koch"
 ]
}

 The dataset includes 909 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002347-230918134249559/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ypry2v
title: Occurrence Download

description: A dataset containing 1411 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Rorippa anceps (Wahlenb.) Rchb., Rosa agrestina Crép.)",
 "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 1411 records from 62 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0326437-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/pcra-c14-152426
title: Kliasavy vorag pad maskai sektanta = The class enemy in the guise of the sectarian, 1930

description: [description english/roman)] M. Galaktsienau. Kliasavy vorag pad maskai sektanta. (Biblioteka Chyrvonaarmeitsa). Mensk, Belarus: Belaruskae Deiarzhaunae Vydavetsiva, 1930. = M. Galaktionov. The class enemy in the guise of the sectarian. (Red Army Library). Minsk, Belarus: Belarusian State Vydabetsiva, 1930. Translated from USSRn into Belarusian by G. Vinagradau (Vinogradov).
DOI: 10.25549/pcra-c14-13439
title: Put' = Voie = [The way], no. 45 (October-December 1934)

description: [description english/roman)] Irregular frequency
DOI: 10.5281/zenodo.11075334
title: Universal Rapid Weather Prediction Model (Sonagi Model) Forecast Result

description: Universal Rapid Weather Prediction Model (Sonagi Model) Forecast Result / 15 Days / Created By Jihyeon Yoon(somehowme@gmail.com, flyingtext@nate.com)

Latest prediction can be available on map at https://sonagi-weather.web.app

Prediction is based on the observation data of
 - Korea Meteorological Administration API

 - United States National Weather Service API
 - Canada MSC GeoMet API
DOI: 10.5281/zenodo.11075335
title: Universal Rapid Weather Prediction Model (Sonagi Model) Forecast Result

description: Universal Rapid Weather Prediction Model (Sonagi Model) Forecast Result / 15 Days / Created By Jihyeon Yoon(somehowme@gmail.com, flyingtext@nate.com)

Latest prediction can be available on map at https://sonagi-weather.web.app

Prediction is based on the observation data of
 - Korea Meteorological Administration API

 - United States National Weather Service API
 - Canada MSC GeoMet API
DOI: 10.25549/pcra-c14-13436
title: Put' = Voie = [The way], no. 45 (October-December 1934)

description: [description english/roman)] Irregular frequency
DOI: 10.5517/cc13lmlx
title: CCDC 1030799: Experimental Crystal Structure Determination

description: Related Article: Matthew G. Cowan, Reece G. Miller, Sally Brooker|2015|Dalton Trans.|44|2880|doi:10.1039/C4DT03407D
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.cc13xc0d
title: CCDC 1040143: Experimental Crystal Structure Determination

description: Related Article: Yajing Shi, Na Li, Huihua Song, Haitao Yu|2016|Chin.J.Chem.|34|1335|doi:10.1002/cjoc.201600451
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: 10.5281/zenodo.17404247
title: THED-PV: A High-Resolution Multi-Perspective Thermal Imaging Dataset for Photovoltaic Homography Estimation

description: This dataset, THED-PV, is specifically designed to advance deep learning models for thermal homography in photovoltaic (PV) systems. It includes high-resolution thermal images of PV panels captured under diverse and controlled conditions. The images were taken from various heights, angles, and times of day to reflect the natural variations in temperature and environmental conditions, including panel cleanliness from clean to heavily soiled states. These controlled conditions make the dataset ideal for training and benchmarking homography estimation models in PV inspection tasks.

The dataset consists of 12,460 raw thermal images at a resolution of 640×512, which were preprocessed to mitigate common artifacts like shadows and sun glare. It is further augmented with synthetic homography pairs generated through controlled geometric perturbations, expanding the dataset to 99,680 homography pairs. This rich set of data, including both raw and preprocessed images, is accompanied by environmental metadata such as irradiance, temperature, humidity, and soiling levels.

THED-PV was designed to facilitate advancements in the field of thermal homography estimation, enabling precise fault detection and predictive maintenance in photovoltaic systems. The dataset can be used to train deep learning models or validate classical homography estimation methods, and it includes all necessary tools and documentation for reproducibility and further research.
DOI: 10.5517/cc13xb2f
title: CCDC 1040114: Experimental Crystal Structure Determination

description: Related Article: Chee Leong Kee, Feng Zhou, Haibin Su, Yaw Kai Yan|2015|J.Organomet.Chem.|792|211|doi:10.1016/j.jorganchem.2015.04.046
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/cc13xb3g
title: CCDC 1040115: Experimental Crystal Structure Determination

description: Related Article: Chee Leong Kee, Feng Zhou, Haibin Su, Yaw Kai Yan|2015|J.Organomet.Chem.|792|211|doi:10.1016/j.jorganchem.2015.04.046
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: 10.5281/zenodo.17404246
title: THED-PV: A High-Resolution Multi-Perspective Thermal Imaging Dataset for Photovoltaic Homography Estimation

description: This dataset, THED-PV, is specifically designed to advance deep learning models for thermal homography in photovoltaic (PV) systems. It includes high-resolution thermal images of PV panels captured under diverse and controlled conditions. The images were taken from various heights, angles, and times of day to reflect the natural variations in temperature and environmental conditions, including panel cleanliness from clean to heavily soiled states. These controlled conditions make the dataset ideal for training and benchmarking homography estimation models in PV inspection tasks.

The dataset consists of 12,460 raw thermal images at a resolution of 640×512, which were preprocessed to mitigate common artifacts like shadows and sun glare. It is further augmented with synthetic homography pairs generated through controlled geometric perturbations, expanding the dataset to 99,680 homography pairs. This rich set of data, including both raw and preprocessed images, is accompanied by environmental metadata such as irradiance, temperature, humidity, and soiling levels.

THED-PV was designed to facilitate advancements in the field of thermal homography estimation, enabling precise fault detection and predictive maintenance in photovoltaic systems. The dataset can be used to train deep learning models or validate classical homography estimation methods, and it includes all necessary tools and documentation for reproducibility and further research.
DOI: 10.5517/cc13xb5j
title: CCDC 1040117: Experimental Crystal Structure Determination

description: Related Article: Lanhui Ren, Lianyue Wang, Ying Lv, Sensen Shang, Bo Chen, Shuang Gao|2015|Green Chemistry|17|2369|doi:10.1039/C4GC02471K
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/cc13xb8m
title: CCDC 1040120: Experimental Crystal Structure Determination

description: Related Article: Evgueni G. Mednikov , Sergei A. Ivanov , and Lawrence F. Dahl|2015|Inorg.Chem.|54|6157|doi:10.1021/acs.inorgchem.5b00208
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/cc13xb9n
title: CCDC 1040121: Experimental Crystal Structure Determination

description: Related Article: Evgueni G. Mednikov , Sergei A. Ivanov , and Lawrence F. Dahl|2015|Inorg.Chem.|54|6157|doi:10.1021/acs.inorgchem.5b00208
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/cc13xbbp
title: CCDC 1040122: Experimental Crystal Structure Determination

description: Related Article: Evgueni G. Mednikov , Sergei A. Ivanov , and Lawrence F. Dahl|2015|Inorg.Chem.|54|6157|doi:10.1021/acs.inorgchem.5b00208
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/cc13xbn0
title: CCDC 1040132: Experimental Crystal Structure Determination

description: Related Article: Chelladurai Ganesamoorthy, Georg Bendt, Dieter Bläser, Christoph Wölper, Stephan Schulz|2015|Dalton Trans.|44|5153|doi:10.1039/C5DT00172B
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.