cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/cc140z9f
title: CCDC 1043624: Experimental Crystal Structure Determination

description: Related Article: Jeremiah M. Sears, Wei-Chih Lee, Brian J. Frost|2015|Inorg.Chim.Acta|431|248|doi:10.1016/j.ica.2015.03.033
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/cc140zbg
title: CCDC 1043625: Experimental Crystal Structure Determination

description: Related Article: Jeremiah M. Sears, Wei-Chih Lee, Brian J. Frost|2015|Inorg.Chim.Acta|431|248|doi:10.1016/j.ica.2015.03.033
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/cc140zch
title: CCDC 1043626: Experimental Crystal Structure Determination

description: Related Article: Jeremiah M. Sears, Wei-Chih Lee, Brian J. Frost|2015|Inorg.Chim.Acta|431|248|doi:10.1016/j.ica.2015.03.033
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/cc140zdj
title: CCDC 1043627: Experimental Crystal Structure Determination

description: Related Article: Jeremiah M. Sears, Wei-Chih Lee, Brian J. Frost|2015|Inorg.Chim.Acta|431|248|doi:10.1016/j.ica.2015.03.033
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: 10.15468/dl.mrb6hd
title: Occurrence Download

description: A dataset containing 676816 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "Country is one of (United States of America, Canada, Mexico)",
 "DatasetKey is one of (iNaturalist Research-grade Observations, Monarch Watch, eButterfly Surveys)",
 "TaxonKey is Danaus plexippus"
 ]
}

 The dataset includes 676816 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051487-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hy5pnb
title: Occurrence Download

description: A dataset containing 431 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Glyptorhagada"
 ]
}

 The dataset includes 431 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051499-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26023/j6pk-5pj5-rk0x
title: MAIR-E: GV Navigation Data. Version 1.0

description: This dataset contains location data of the NSF/NCAR HIAPER GV during the MAIR-E project for the PICARRO and Aerodyne datasets.
DOI: 10.15468/dl.zn24rf
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Apterygiformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((150 60,180 60,180 90,150 90,150 60))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058449-250920141307145/datasets/export for details.
DOI: 10.26023/y183-6ans-1x0c
title: ESCAPE: KPR Radar plots. Version 1.0

description: KPR Radar plots collected on board the SPEC Learjet during the Experiment of Sea Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE) field campaign from 2 June through 17 June 2021. These plots are in JPEG format.
DOI: 10.26023/r6gb-28d4-ch01
title: ESCAPE: RaXPol Mobile Radar Data. Version 1.0

description: RaXPol Mobile Radar data collected during the ESCAPE (Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment) field experiment from 2 June to 30 June 2022. The data are in cfRadial format.
DOI: 10.26023/x8fy-9aet-eg14
title: ESCAPE: PX1000 Mobile Radar Data. Version 1.0

description: PX1000 Mobile Radar data collected during the ESCAPE (Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment) field experiment from 31 May to 26 June 2022. The data are in cfRadial format.
DOI: 10.15468/dl.4mf44e
title: Occurrence Download

description: A dataset containing 530229 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Macrhybopsis boschungi, Enneacanthus obesus, Etheostoma raneyi, Notropis rafinesquei, Fundulus olivaceus, Noturus gladiator, Leptolucania ommata, Luxilus zonatus, Noturus albater, Noturus furiosus, Enneacanthus chaetodon, Cottus kanawhae, Umbra pygmaea, Acantharchus pomotis, Enneacanthus gloriosus, Notropis mekistocholas, Lythrurus matutinus, Micropterus salmoides, Notropis scepticus, Cyprinella chloristia, Notropis, Semotilus lumbee, Lucania goodei, Etheostoma brevispinum, Notropis rubellus, Margariscus nachtriebi, Coregonus huntsmani, Noturus trautmani, Macrhybopsis hyostoma, Micropterus punctulatus, Campostoma spadiceum, Macrhybopsis tomellerii, Notropis ariommus, Notropis, Pteronotropis stonei, Macrhybopsis pallida, Fundulus chrysotus, Lepomis punctatus, Elassoma evergladei, Noturus leptacanthus, Ameiurus brunneus, Pteronotropis welaka, Hybopsis winchelli, Fundulus xenicus, Cyprinella callistia, Lepomis solis, Notropis, Notropis, Ictalurus punctatus, Fundulus rathbuni, Elassoma gilberti, Noturus hildebrandi, Percina bimaculata, Micropterus tallapoosae, Notropis, Noturus crypticus, Allohistium maydeni, Noturus fasciatus, Notropis, Notropis, Hybopsis lineapunctata, Phenacobius catostomus, Cyprinodon bovinus, Cyprinodon elegans, Percina freemanorum, Cottus baileyi, Notropis semperasper, Notropis, Luxilus cerasinus, Noturus gilberti, Ambloplites cavifrons, Nocomis raneyi, Thoburnia hamiltoni, Thoburnia rhothoeca, Hybopsis hypsinotus, Notropis, Notropis, Notropis, Noturus flavipinnis, Lythrurus lirus, Lythrurus ardens, Notropis, Nocomis platyrhynchus, Phenacobius teretulus, Percina caprodes, Hemitremia flammea, Lythrurus atrapiculus, Sphoeroides rosenblatti, Gobiesox daedaleus, Halichoeres aestuaricola, Ogilbia galapagosensis, Gobiesox juniperoserrai, Gerres simillimus, Dormitator latifrons, Lutjanus novemfasciatus, Trinectes fimbriatus, Cathorops multiradiatus, Sicydium cocoense)",
 "HasCoordinate is true",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 530229 records from 404 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0058408-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15173145
title: The Spitzer Spectroscopic Data Fusion - Merged Spectroscopic Redshift Catalogs in Spitzer Fields

description: The Spitzer Spectroscopic Data Fusion merges miscellaneous spectroscopic information available within "popular" extragalactic survey fields.

Last Updated on 20 March 2025 - https://zenodo.org/record/6368347 - https://www.mattiavaccari.net/df/specz

Based on the Spitzer Data Fusion Project - https://doi.org/10.5281/zenodo.7850783 - https://mattiavaccari.net/df

Merged Spec-Z ("specz-merged") catalogs merge miscellaneous spec-z information available within a given field. Different spec-z catalogs available within a given field are merged (using a search radius of 1.0 arcsec), and for sources with multiple spec-z measurements the most reliable one is chosen following the (largely arbitrarily) assumed order of decreasing reliability indicated below for each field. If CAT1,...,CATN spec-z catalogs are available in a given field, Z_1 from CAT1 (i.e. NED) is adopted as "best" redshift (i.e. ZBEST), if available, otherwise Z_2 from CAT_2 is adopted if available, and so on up to Z_N and CAT_N. In using ZBEST it's thus important to bear in mind that this is not necessarily actually the "best" redshift for science purposes, and in particular that the choice of NED as CAT1 is often not ideal. However, Z_1,...,Z_N are included to allow users to define the "best" redshift based on their science needs when multiple redshift estimates are available for a given source. ZFLAG specifies which catalog is providing the ZBEST value according to the CATN number below. ZCLASS is meant to provide further info about the class/quality of the spectroscopic redshift measurement, but for the time being is not populated and is simply a copy of ZFLAG. ZWHERE is an additional binary/bit flag indicating in which of the N catalogs each source was given a spec-z estimate in. ZWHERE will e.g. be 2^0=1 if a redshift if available only from CAT_1, whereas it will be 2^0+2^1=3 if a redshift is available *only* from CAT1 and CAT2,so that a source with a redshift available from all catalogues will have ZWHERE=2^0+...+2^n.

See AAAREADME.SPECZ-MERGED within the ZIP archive for further information.
description: MV acknowledges support from the European Commission Research Executive Agency (FP7-SPACE-2013-1 GA 607254) and the South African Department of Science and Technology (DST/CON 0134/2014) as part of the Herschel Extragalactic Legacy Project - HELP. MV acknowledges financial support from the Inter-University Institute for Data Intensive Astronomy (IDIA), a partnership of the University of Cape Town, the University of Pretoria, the University of the Western Cape and the South African Radio Astronomy Observatory, and from the South African Department of Science and Innovation's National Research Foundation under the ISARP RADIOSKY2020 Joint Research Scheme (DSI-NRF Grant Number 113121) and the CSUR HIPPO Project (DSI-NRF Grant Number 121291).
DOI: 10.5281/zenodo.6368348
title: The Spitzer Spectroscopic Data Fusion - Merged Spectroscopic Redshift Catalogs in Spitzer Fields

description: Merged Spec-Z ("specz-merged") catalogs merge miscellaneous spec-z information available within a given field. Different spec-z catalogs available within a given field are merged (using a search radius of 0.5 arcsec), and for sources with multiple spec-z measurements, the most reliable one is chosen following the (assumed) order of decreasing reliability below. ZBEST is thus the most reliable spec-z and ZFLAG specifies which catalog is providing the ZBEST value according to the CATN number below. ZCLASS is meant to provide further info about the class/quality of the spectroscopic redshift measurement, but for the time being, is not populated and is simply a copy of ZFLAG. ZWHERE is an additional binary/bit flag indicating in which of the N catalogs each source was given a spec-z estimate. See AAAREADME.SPECZ-MERGED and http://adsabs.harvard.edu/abs/2015fers.confE..27V See also http://www.mattiavaccari.net/df and http://www.mattiavaccari.net/df/specz
description: MV acknowledges support from the European Commission Research Executive Agency (FP7-SPACE-2013-1 GA 607254) and the South African Department of Science and Technology (DST/CON 0134/2014) as part of the Herschel Extragalactic Legacy Project - HELP. MV acknowledges financial support from the Inter-University Institute for Data Intensive Astronomy (IDIA), a partnership of the University of Cape Town, the University of Pretoria, the University of the Western Cape and the South African Radio Astronomy Observatory, and from the South African Department of Science and Innovation's National Research Foundation under the ISARP RADIOSKY2020 Joint Research Scheme (DSI-NRF Grant Number 113121) and the CSUR HIPPO Project (DSI-NRF Grant Number 121291).
DOI: 10.5281/zenodo.7798708
title: The Spitzer Spectroscopic Data Fusion - Merged Spectroscopic Redshift Catalogs in Spitzer Fields

description: Merged Spec-Z ("specz-merged") catalogs merge miscellaneous spec-z information available within a given field. Different spec-z catalogs available within a given field are merged (using a search radius of 0.5 arcsec), and for sources with multiple spec-z measurements, the most reliable one is chosen following the (assumed) order of decreasing reliability below. ZBEST is thus the most reliable spec-z and ZFLAG specifies which catalog is providing the ZBEST value according to the CATN number below. ZCLASS is meant to provide further info about the class/quality of the spectroscopic redshift measurement, but for the time being, is not populated and is simply a copy of ZFLAG. ZWHERE is an additional binary/bit flag indicating in which of the N catalogs each source was given a spec-z estimate. See AAAREADME.SPECZ-MERGED and https://adsabs.harvard.edu/abs/2015fers.confE..27V See also https://www.mattiavaccari.net/df and https://www.mattiavaccari.net/df/specz
description: MV acknowledges support from the European Commission Research Executive Agency (FP7-SPACE-2013-1 GA 607254) and the South African Department of Science and Technology (DST/CON 0134/2014) as part of the Herschel Extragalactic Legacy Project - HELP. MV acknowledges financial support from the Inter-University Institute for Data Intensive Astronomy (IDIA), a partnership of the University of Cape Town, the University of Pretoria, the University of the Western Cape and the South African Radio Astronomy Observatory, and from the South African Department of Science and Innovation's National Research Foundation under the ISARP RADIOSKY2020 Joint Research Scheme (DSI-NRF Grant Number 113121) and the CSUR HIPPO Project (DSI-NRF Grant Number 121291).
DOI: 10.5281/zenodo.8192299
title: The Spitzer Spectroscopic Data Fusion - Merged Spectroscopic Redshift Catalogs in Spitzer Fields

description: Merged Spec-Z ("specz-merged") catalogs merge miscellaneous spec-z information available<br> within a given field. Different spec-z catalogs available within a given field are merged<br> (using a search radius of 1.0 arcsec), and for sources with multiple spec-z measurements<br> the most reliable one is chosen following the (largely arbitrarily) assumed order of decreasing<br> reliability indicated below for each field. If CAT1,...,CATN spec-z catalogs are available<br> in a given field, Z_1 from CAT1 (i.e. NED) is adopted as "best" redshift (i.e. ZBEST),<br> if available, otherwise Z_2 from CAT_2 is adopted if available, and so on up to Z_N and CAT_N.<br> In using ZBEST it's thus important to bear in mind that this is not necessarily actually the<br> "best" redshift for science purposes, and in particular that the choice of NED as CAT1 is often<br> not ideal. However, Z_1,...,Z_N are included to allow users to define the "best" redshift based<br> on their science needs when multiple redshift estimates are available for a given source.<br> ZFLAG specifies which catalog is providing the ZBEST value according to the CATN number below.<br> ZCLASS is meant to provide further info about the class/quality of the spectroscopic redshift<br> measurement, but for the time being is not populated and is simply a copy of ZFLAG.<br> ZWHERE is an additional binary/bit flag indicating in which of the N catalogs each source<br> was given a spec-z estimate in. ZWHERE will e.g. be 2^0=1 if a redshift if available *only*<br> from CAT_1, whereas it will be 2^0+2^1=3 if a redshift is available *only* from CAT1 and CAT2,<br> so that a source with a redshift available from all catalogues will have ZWHERE=2^0+...+2^n. See AAAREADME.SPECZ-MERGED and https://adsabs.harvard.edu/abs/2015fers.confE..27V See also https://www.mattiavaccari.net/df and https://www.mattiavaccari.net/df/specz
description: MV acknowledges support from the European Commission Research Executive Agency (FP7-SPACE-2013-1 GA 607254) and the South African Department of Science and Technology (DST/CON 0134/2014) as part of the Herschel Extragalactic Legacy Project - HELP. MV acknowledges financial support from the Inter-University Institute for Data Intensive Astronomy (IDIA), a partnership of the University of Cape Town, the University of Pretoria, the University of the Western Cape and the South African Radio Astronomy Observatory, and from the South African Department of Science and Innovation's National Research Foundation under the ISARP RADIOSKY2020 Joint Research Scheme (DSI-NRF Grant Number 113121) and the CSUR HIPPO Project (DSI-NRF Grant Number 121291).
DOI: 10.5281/zenodo.11180080
title: Underwater images collected by an Autonomous Surface Vehicle in Hermitage, Réunion - 2023-11-29

description: This dataset was collected by an Autonomous Surface Vehicle in Hermitage, Réunion - 2023-11-29. 

            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.11180099
title: Underwater images collected by an Autonomous Surface Vehicle in St-Gilles-Canyon, Réunion - 2023-11-29

description: This dataset was collected by an Autonomous Surface Vehicle in St-Gilles-Canyon, Réunion - 2023-11-29. 

            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