cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25549/inscriptifact-ouc111149520
title: Pyu Inscription, PYU 31

description: [Text Description:] Pyu Inscription ❧ [Text or Publication Number Note:] PYU31 ❧ [Medium:] Stone ❧ [Script Note:] Pyu ❧ [Physical Object Description:] Funerary tablet; height 63 cm, width 65 cm and depth 13 cm ❧ [Physical Object Note:] Stone
DOI: 10.15468/dl.4tswny
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rhyacionia sonia Miller, 1967",
 {
 "or" : [
 "Country is United States of America",
 "Country is Canada",
 "Continent is North America"
 ]
 }
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0127885-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/inscriptifact-ouc111149521
title: Pyu Inscription, PYU 31

description: [Text Description:] Pyu Inscription ❧ [Text or Publication Number Note:] PYU31 ❧ [Medium:] Stone ❧ [Script Note:] Pyu ❧ [Physical Object Description:] Funerary tablet; height 63 cm, width 65 cm and depth 13 cm ❧ [Physical Object Note:] Stone
DOI: 10.15468/dl.88fdcg
title: Occurrence Download

description: A dataset containing 182620 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen, Occurrence evidence)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Pinus nigra J.F.Arnold"
 ]
}

 The dataset includes 182620 records from 970 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0060938-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/inscriptifact-ouc111149092
title: Pyu Inscription in Pyu and Southern Brahmi Script, PYU 24

description: [Text Description:] Images of four Buddhas in bhumisparsamudra, each with standing attendant ❧ [Text or Publication Number Note:] PYU24 ❧ [Excavation Description:] Khin Ba mound relic chamber ❧ [Medium:] Metal ❧ [Script Note:] Pyu, Southern Brahmi ❧ [Physical Object Description:] Reliquary; height 58 cm, circumference at bottom 127 cm and at top 104 cm ❧ [Physical Object Note:] Silver-gilt
DOI: 10.15468/dl.pzc2y8
title: Occurrence Download

description: A dataset containing 248 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Opuntia pottsii Salm-Dyck"
 ]
}

 The dataset includes 248 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068904-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/inscriptifact-ouc111149856
title: Pyu Inscription, PYU 51

description: [Text Description:] Pyu Inscription ❧ [Text or Publication Number Note:] PYU51 ❧ [Excavation Description:] Subok Gone, Taun Lone Nyo village, Pyay ❧ [Medium:] Stone ❧ [Script Note:] Pyu ❧ [Physical Object Description:] Stela; height 105 cm, width 108 cm and depth 14 cm ❧ [Physical Object Note:] Stone
DOI: 10.15468/dl.ne3vuq
title: Occurrence Download

description: A dataset containing 302 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-80.2582699000000019 25.7180934999999984, -80.2582699000000019 25.7189162499999995, -80.2582699000000019 25.7205617400000008, -80.2582699000000019 25.7219828399999990, -80.2582699000000019 25.7237031300000005, -80.2582699000000019 25.7255730000000007, -80.2574454800000012 25.7255730000000007, -80.2557963099999938 25.7255730000000007, -80.2545219499999973 25.7255730000000007, -80.2531726299999946 25.7255730000000007, -80.2516733799999997 25.7255730000000007, -80.2500991699999986 25.7255730000000007, -80.2477753400000040 25.7255730000000007, -80.2465009799999933 25.7255730000000007, -80.2450019000000054 25.7255730000000007, -80.2450019000000054 25.7240023099999995, -80.2450019000000054 25.7228803799999994, -80.2450019000000054 25.7213844800000011, -80.2450019000000054 25.7201877600000017, -80.2450019000000054 25.7180934999999984, -80.2468757900000043 25.7180934999999984, -80.2480002300000024 25.7180934999999984, -80.2491996199999988 25.7180934999999984, -80.2509237600000063 25.7180934999999984, -80.2520481899999965 25.7180934999999984, -80.2535474400000055 25.7180934999999984, -80.2552715700000050 25.7180934999999984, -80.2568457800000061 25.7180934999999984, -80.2582699000000019 25.7180934999999984))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1932",
 "BasisOfRecord is one of (Human Observation, Living Specimen, Observation, Specimen, Machine Observation)"
 ]
}

 The dataset includes 302 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0093277-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/inscriptifact-ouc111149219
title: Pyu Inscription in Pyu and Southern Brahmi Script, PYU 24

description: [Text Description:] Images of four Buddhas in bhumisparsamudra, each with standing attendant ❧ [Text or Publication Number Note:] PYU24 ❧ [Excavation Description:] Khin Ba mound relic chamber ❧ [Medium:] Metal ❧ [Script Note:] Pyu, Southern Brahmi ❧ [Physical Object Description:] Reliquary; height 58 cm, circumference at bottom 127 cm and at top 104 cm ❧ [Physical Object Note:] Silver-gilt
DOI: 10.25549/inscriptifact-ouc111149246
title: Pyu Inscription, PYU 25

description: [Text Description:] Inscription on bottom of the urn ❧ [Text or Publication Number Note:] PYU25 ❧ [Medium:] Stone ❧ [Script Note:] Pyu ❧ [Physical Object Description:] Urn; height 75 cm, diameter at bottom 78 cm and at top 84 cm ❧ [Physical Object Note:] Stone
DOI: 10.15468/dl.g9y856
title: Occurrence Download

description: A dataset containing 1377 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-96.6569563999999986 40.7659446999999986, -96.6569563999999986 40.7687296000000003, -96.6569563999999986 40.7710689199999976, -96.6569563999999986 40.7724056699999977, -96.6569563999999986 40.7746335900000005, -96.6569563999999986 40.7770842999999985, -96.6540652099999988 40.7770842999999985, -96.6507294700000017 40.7770842999999985, -96.6488392100000056 40.7770842999999985, -96.6467265699999984 40.7770842999999985, -96.6448363100000023 40.7770842999999985, -96.6418341400000003 40.7770842999999985, -96.6396100999999987 40.7770842999999985, -96.6396100999999987 40.7754133600000017, -96.6396100999999987 40.7741880000000023, -96.6396100999999987 40.7722942700000033, -96.6396100999999987 40.7698435599999982, -96.6396100999999987 40.7681726200000014, -96.6396100999999987 40.7659446999999986, -96.6415005599999972 40.7659446999999986, -96.6431684399999966 40.7659446999999986, -96.6451698799999974 40.7659446999999986, -96.6480608699999948 40.7659446999999986, -96.6498399299999988 40.7659446999999986, -96.6522861499999948 40.7659446999999986, -96.6538428300000021 40.7659446999999986, -96.6569563999999986 40.7659446999999986))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1932",
 "BasisOfRecord is one of (Human Observation, Living Specimen, Observation, Specimen, Machine Observation)"
 ]
}

 The dataset includes 1377 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0093283-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/inscriptifact-ouc111149319
title: Pyu Inscription, PYU 25

description: [Text Description:] Inscription on bottom of the urn ❧ [Text or Publication Number Note:] PYU25 ❧ [Medium:] Stone ❧ [Script Note:] Pyu ❧ [Physical Object Description:] Urn; height 75 cm, diameter at bottom 78 cm and at top 84 cm ❧ [Physical Object Note:] Stone
DOI: 10.15468/dl.mmcwa7
title: Occurrence Download

description: A dataset containing 126 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((-85.1175008999999960 41.0613802000000021, -85.1175008999999960 41.0651368600000026, -85.1175008999999960 41.0696448500000031, -85.1175008999999960 41.0722745099999997, -85.1175008999999960 41.0760311700000003, -85.1175008999999960 41.0801634999999976, -85.1158126100000061 41.0801634999999976, -85.1109361299999989 41.0801634999999976, -85.1075601000000006 41.0801634999999976, -85.1032462900000013 41.0801634999999976, -85.0996827000000025 41.0801634999999976, -85.0966817900000052 41.0801634999999976, -85.0929306499999996 41.0801634999999976, -85.0871161000000029 41.0801634999999976, -85.0871161000000029 41.0771581699999970, -85.0871161000000029 41.0728380099999981, -85.0871161000000029 41.0705840199999983, -85.0871161000000029 41.0662638599999994, -85.0871161000000029 41.0632585299999988, -85.0871161000000029 41.0613802000000021, -85.0929306499999996 41.0613802000000021, -85.0961191199999973 41.0613802000000021, -85.1000578099999956 41.0613802000000021, -85.1045591900000034 41.0613802000000021, -85.1075601000000006 41.0613802000000021, -85.1107485699999984 41.0613802000000021, -85.1143121500000035 41.0613802000000021, -85.1175008999999960 41.0613802000000021))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1932",
 "BasisOfRecord is one of (Human Observation, Living Specimen, Observation, Specimen, Machine Observation)"
 ]
}

 The dataset includes 126 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0098296-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/inscriptifact-ouc111149279
title: Pyu Inscription, PYU 25

description: [Text Description:] Inscription on bottom of the urn ❧ [Text or Publication Number Note:] PYU25 ❧ [Medium:] Stone ❧ [Script Note:] Pyu ❧ [Physical Object Description:] Urn; height 75 cm, diameter at bottom 78 cm and at top 84 cm ❧ [Physical Object Note:] Stone
DOI: 10.25549/inscriptifact-ouc111149320
title: Pyu Inscription, PYU 25

description: [Text Description:] Inscription on bottom of the urn ❧ [Text or Publication Number Note:] PYU25 ❧ [Medium:] Stone ❧ [Script Note:] Pyu ❧ [Physical Object Description:] Urn; height 75 cm, diameter at bottom 78 cm and at top 84 cm ❧ [Physical Object Note:] Stone
DOI: 10.5281/zenodo.11204162
title: Underwater images collected by an Autonomous Surface Vehicle in Hermitage, Réunion - 2023-09-27

description: This dataset was collected by an Autonomous Surface Vehicle in Hermitage, Réunion - 2023-09-27. 

            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.11204395
title: Underwater images collected by an Autonomous Surface Vehicle in Hermitage, Réunion - 2023-09-27

description: This dataset was collected by an Autonomous Surface Vehicle in Hermitage, Réunion - 2023-09-27. 

            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.11204735
title: Underwater images collected by an Autonomous Surface Vehicle in Hermitage, Réunion - 2023-09-27

description: This dataset was collected by an Autonomous Surface Vehicle in Hermitage, Réunion - 2023-09-27. 

            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: 10.17882/94031
title: Lagoon hydrodynamics of pearl farming atolls in French Polynesia : the case of Apataki Atoll (Tuamotu Archipelago)

description: Apataki Atoll has been instrumented over a period of 3 months (from April 2022 to late July 2022) separated into 2 Legs. Physical process such as water level, currents ciruclation, water exchanges into passes and "hoa" and water column stratification have been measured to characterized the hydrodynamic functioning of this semi-opened pearl farming atoll. Numerous moorings have been deployed into lagoon, passes, hoa and external reef slope stations with common autonomous oceanographic instruments measuring at high sampling frequency. During the sampling period, one major meteorological event occurred, a distant mega swell hit the South-West Islands of French Polynesia including Apataki on 14th July and has significantly impacted its hydrodynamic. Sampling strategy available on Sextant - Marine Geographic Information System. More informations on ANR MANA project.
DOI: 10.17882/94146
title: Lagoon hydrodynamics of pearl farming atolls in French Polynesia : the case of Takaroa Atoll (Tuamotu Archipelago)

description: Takaroa Atoll has been instrumented for a short period of 3 months (from July 2022 to October 2022) in order to get additionnal data into Takaroa passage (Teauoae Pass). One ADCP has been deployed to measure current direction and speed over the water column to evaluate the water exchanges between the lagoon and the ocean of this semi-open pearl farming atoll. Sampling strategy available on Sextant - Marine Geographic Information System. More informations on ANR MANA project.
DOI: 10.17882/54983
title: Spatial distribution of gas emissions from the Sea of Marmara seafloor from 4 November 2009 to 14 December 2009

description: Acoustic water column data acquired in 2009 during the MARMESONET marine expedition led to establish an accurate spatial distribution of gas emissions on the scale of the Sea of Marmara. The present database is composed of a surface shape file (.shp) dedicated to GIS applications. This seafloor surface represents the insonified area within which gas emissions occurred for more than 1 month of survey, from 4 November 2009 to 14 December 2009; as displayed in Figure 4 of Dupré et al. 2015 (Dupré S, Scalabrin C, Grall C, Augustin AH, Henry P, Şengör AMC, Görür N, Çağatay N, Géli L (2015) Tectonic and sedimentary controls for widespread gas emissions in the Sea of Marmara. Results from systematic, shipborne multibeam echosounder water column imageries. Journal of Geophysical Research 120 (5):2891-2912. doi:10.1002/2014JB011617). This publication Investigated and discussed the relationship between fluid emissions at the seafloor with the fault network (active and inactive faults) and the sedimentary environment (nature, thickness and related-processes). Acoustic detection of gas emissions was performed with water column imagery acquired in 2009 on board the R/V Le Suroît during the MARMESONET expedition, part of the ESONET (European Seas Observatory NETwork) Marmara demonstration mission (Marmara-DM) project. Water column data was acquired with a Kongsberg EM302 shipborne multibeam echo sounder. Water column multibeam acquisition is very efficient for the coverage of wide areas. Thus, more than 4500 km of acoustic tracks, equivalent to ~2900 km2, were recorded over 21 days of acquisition (4 November 2009 to 14 December 2009). Details on water column multibeam data acquisition, processing, vizualisation and identification of gas emissions from the seafloor are presented in Dupré et al 2015.