cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.26024/g8p7-wy42
title: Upgraded Coronal Multi-channel Polarimeter (UCoMP) Data

description: UCoMP images the solar coronal in several emission lines with a narrow passband wavelength tunable filter. UCoMP records full Stokes polarimetry (Intensity, 2 states of linear polarization, circular polarization) over a full field-of-view from 1.04 to 2 solar radii. Level 1 and 2 images are 32-bit 1280x1024, with 3 arcsecond pixels. Level 1 data comprises the images of the 4 Stokes parameters at wavelengths across the emission lines. Level 2 data products include maps of line intensity, enhanced intensity, linear polarization degree, plane-of-sky magnetic field direction, emission line width and doppler velocity. Time series of velocity can be used to infer the plane-of-sky magnetic field through coronal seismology.
DOI: 10.5065/d6bc3x95
title: TC-OBS: The Tropical Cyclone Observations-Based Structure Database
title: A new historical database of tropical cyclone position, intensity, radius of maximum winds, and size parameters based on aircraft and satellite observations

description: A new historical database of tropical cyclone (TC) parameters has been constructed from satellite and aircraft observations. Called the Tropical Cyclone Observations-Based Structure Database (TC-OBS), this database uses objective state estimation algorithms to refine existing historical estimates of the following key parameters: track, intensity, and size (radial extent of winds of a given threshold). Additionally, TC-OBS provides estimates of the radius of maximum winds (RMW), a quantity that has not previously been included as a "best-tracked" quantity in existing historical databases. TC-OBS also provides time-dependent uncertainty bounds on the estimates of these four main quantities. Compared with existing historical databases such as the Hurricane Database (HURDAT2, also known as the "Best Track Dataset"), TC-OBS provides track, intensity, and radius information at higher spatial and temporal precision. Whereas HURDAT2 rounds track points to the nearest tenth of a degree, intensity to the nearest 5-kt increment, and wind radii to 5-nm or even 10-nm increments, TC-OBS does not round any of its estimates to artificial thresholds. While HURDAT generally provides parameters every six hours, TC-OBS provides estimates of all parameters for each hour as well as any of the off-synoptic time points included in HURDAT2. Like HURDAT2, TC-OBS provides estimates of the 34- , 50-, and 64-kt wind radii (size), but TC-OBS also adds estimates for the radial extent of Category 2, 3, 4, and 5 wind speed thresholds (83-kt, 96-kt, 113-kt, and 135-kt). Whenever data coverages are sufficient, TC-OBS also includes estimates of the azimuthal mean wind speed. Finally, TC-OBS is set up to include alternative metrics beyond the traditional metrics for intensity and size. One such metric is related to the spatial and temporal coherence of the location of wind maxima. The database was originally built for wind risk applications, but a wide range of scientific and commercial uses can be envisioned. 

TC-OBS currently includes data for all TCs that occurred in the North Atlantic basin from 1999 to 2013. Somewhat more than half of all Atlantic TCs were sampled by aircraft frequently enough to provide useful input data for TC-OBS. Additionally, since aircraft reconnaissance generally commences when TCs move west of 55 deg in the basin, TC-OBS does not provide observational refinement for TCs in the eastern half of the basin. For the most part however, there is good aircraft coverage during nearly all periods in which TCs were threatening land, so TC-OBS provides observational refinements for nearly all the impactful landfalls in the basin. The current version of TC-OBS (v0.42) provides observational refinements for 253 of the 416 TCs that occurred during 1999 to 2013.
DOI: 10.5065/p8es-mc74
title: METOP-C Data Products

description: METOP-C instrument data and derived products (levels 1-2).
DOI: 10.5065/qan9-we09
title: CHAMP Data Products

description: CHAMP instrument data and derived products (levels 1-2).
DOI: 10.5065/789w-m137
title: METOP-A Data Products

description: METOP-A instrument data and derived products (levels 1-2).
DOI: 10.5065/7m8g-ja33
title: KOMPSAT5 Data Products

description: KOMPSAT5 instrument data and derived products (levels 1-2).
DOI: 10.5065/8r12-hs65
title: CNOFS Data Products

description: CNOFS instrument data and derived products (levels 1-2).
DOI: 10.5065/1k0w-2272
title: METOP-B Data Products

description: METOP-B instrument data and derived products (levels 1-2).
DOI: 10.5065/82ny-4074
title: SACC Data Products

description: SACC instrument data and derived products (levels 1-2).
DOI: 10.5065/chk8-fx07
title: GRACE Data Products

description: GRACE instrument data and derived products (levels 1-2).
DOI: 10.5065/rgpy-g566
title: GPSMET Data Products

description: GPSMET instrument data and derived products (levels 1-2).
DOI: 10.5065/fbxc-0e55
title: UCAR/CU CYGNSS Inundation Maps

description: This dataset provides 3 km maps of inundation fraction for latitudes +/- 38 degrees for the time period Mar 20, 2017 - Jun 30, 2022. Retrievals are derived from the Cyclone Global Navigation Satellite System (CYGNSS) constellation, which uses GNSS-Reflectometry to obtain L-band surface reflectivity observations over the land and ocean surface. To derive the fractional inundation maps, CYGNSS reflectivity observations are first aggregated over a period of 3-days. These observations are then spatially interpolated before they are converted into estimates of inundation fraction. This product was jointly developed by the University Corporation for Atmospheric Research and the University of Colorado Boulder with funding from the NASA Terrestrial Hydrology Program award number 80NSSC19K0046.
DOI: 10.5065/z9nq-8g12
title: The UCAR/CU CYGNSS Soil Moisture Product

description: This dataset provides soil moisture retrievals, which have been gridded to 36 km, for the upper 5 cm of the soil surface at sparsely-sampled 6-hour intervals for +/- 38 degrees latitude for 2017 - present. Retrievals are derived from the Cyclone Global Navigation Satellite System (CYGNSS) constellation, which uses GNSS-Reflectometry to obtain L-band surface reflectivity observations over the land and ocean surface. This product, the UCAR/CU CYGNSS Soil Moisture Product, was jointly developed by the University Corporation for Atmospheric Research and the University of Colorado Boulder. It was developed by calibrating observations of surface reflectivity from CYGNSS to soil moisture retrievals from NASA's Soil Moisture Active Passive (SMAP) mission. Retrievals were validated against observations from over 200 in situ soil moisture probes from 5 networks, with an overall unbiased root mean square error (ubRMSE) of 0.047 cm3 cm-3.
DOI: 10.5065/1qcs-bc46
title: Planet IQ Data Products

description: Planet IQ instrument data and derived products (levels 1-2).
DOI: 10.26024/wt24-5j82
title: NCAR CESM LENS Cloud-Optimized Subset

description: This is a 100 TB subset of the larger (500 TB) National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM) Large Ensemble (LENS) numerical simulation which has been converted to Zarr format and copied to Amazon Web Services (AWS) S3 for broad public access.
DOI: 10.34740/kaggle/dsv/14734970
title: Berita UII
DOI: 10.15468/dl.67pjmr
title: Occurrence Download

description: A dataset containing 1177 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Carex distans, Carex distans, Carex distans, Carex distans, Carex distans, Carex distans, Carex distans)",
 "Year is greater than or equal to 1900",
 "Geometry POLYGON ((8.643 46.99, 14.1 46.92, 14.43 50.75, 8.534 50.83, 8.643 46.99))",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Material sample)"
 ]
}

 The dataset includes 1177 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012541-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g6yf4x
title: Occurrence Download

description: A dataset containing 83224 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dodonaea viscosa"
 ]
}

 The dataset includes 83224 records from 736 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012514-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26024/y48t-q717
title: NCAR CESM2 Large Ensemble Cloud-Optimized Dataset

description: The National Center for Atmospheric Research partnered with the IBS Center for Climate Physics in South Korea to generate the CESM2 Large Ensemble which consists of 100 members at 1 degree spatial resolution covering the period 1850-2100 under CMIP6 historical and SSP370 future radiative forcing scenarios. Data sets from this ensemble were made available via the Climate Data Gateway on June 14th, 2021.
DOI: 10.26024/sprq-2d04
title: CAM6 Data Assimilation Research Testbed (DART) Reanalysis: Cloud-Optimized Dataset

description: This is a cloud-hosted subset of the CAM6+DART (Community Atmosphere Model version 6 Data Assimilation Research Testbed) Reanalysis dataset. These data products are designed to facilitate a broad variety of research using the NCAR CESM 2.1 (National Center for Atmospheric Research’s Community Earth System Model version 2.1), including model evaluation, ensemble hindcasting, data assimilation experiments, and sensitivity studies. They come from an 80 member ensemble reanalysis of the global troposphere and stratosphere using DART and CAM6. The data products represent states of the atmosphere consistent with observations from 2011 through 2019 at 1 degree horizontal resolution and weekly frequency. Each ensemble member is an equally likely description of the atmosphere, and is also consistent with dynamics and physics of CAM6. The dataset also contains corresponding land surface values at 6-hourly frequency. This dataset is a reformatting, with no change to numerical values, of data from the “CAM6 Data Assimilation Research Testbed (DART) Reanalysis”, DOI:10.5065/JG1E-8525.
This dataset is a reformatting, with no change to numerical values, of data  from the "CAM6 Data Assimilation Research Testbed (DART) Reanalysis", DOI:10.5065/JG1E-8525
DOI: 10.5517/ccdc.csd.cc1jdsf4
title: CCDC 1412466: Experimental Crystal Structure Determination

description: Related Article: Yukihiro Yoshida, Hiromi Hayama, Manabu Ishikawa, Akihiro Otsuka, Hideki Yamochi, Yuto Nakamura, Hideo Kishida, Hiroshi Ito, Mitsuhiko Maesato, Gunzi Saito|2015|J.Phys.Soc.Jpn.|84|123801|doi:10.7566/JPSJ.84.123801
description: Related Article: Yukihiro Yoshida, Hiromi Hayama, Manabu Ishikawa, Akihiro Otsuka, Hideki Yamochi, Yuto Nakamura, Hideo Kishida, Hiroshi Ito, Mitsuhiko Maesato, Gunzi Saito|2025|CSD Communication|||
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: 10.25934/pr00012603.0
title: Available datapackage for study 'Safety, Testing/Transmission, and Outcomes in Pregnancies with COVID-19 (STOP COVID-19)'

description: Vivli is an independent, non-profit organization that has developed a global data-sharing and analytics platform to serve all elements of the international research community. Our mission is to promote, coordinate, and facilitate scientific sharing and reuse of clinical research data through the creation and implementation of a sustainable global data-sharing enterprise. The Vivli platform includes an independent data repository, in-depth search engine and a cloud-based, secure analytics platform.
DOI: 10.15468/dl.p87vay
title: Occurrence Download

description: A dataset containing 27934483 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "Geometry POLYGON((-10.57477 35.54504,4.72837 35.54504,4.72837 44.50437,-10.57477 44.50437,-10.57477 35.54504))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is one of (Geodetic datum assumed WGS84, Coordinate rounded)",
 "TaxonKey is Animalia",
 "Year 1976-2026"
 ]
}

 The dataset includes 27934483 records from 725 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012508-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15156/bio/sh1219168.10fu
title: SH1219168.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1219171.10fu
title: SH1219171.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1219172.10fu
title: SH1219172.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1219173.10fu
title: SH1219173.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1219174.10fu
title: SH1219174.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1219176.10fu
title: SH1219176.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1219183.10fu
title: SH1219183.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1219184.10fu
title: SH1219184.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1219186.10fu
title: SH1219186.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.