cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0193228.10fu
title: SH0193228.10FU

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/sh0193229.10fu
title: SH0193229.10FU

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/sh0193230.10fu
title: SH0193230.10FU

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: 10.5281/zenodo.15190071
title: Enhancing Scalability and Privacy in 5G-Enabled IoT  Networks through Block chain Integration and AI  Solutions

description: The proliferation of Internet of Things (IoT) devices in the digital landscape has ushered in a new era of connectivity, empowering billions of devices to communicate over the internet. However, the reliance on centralized protocols for data transfer poses significant security challenges. The emergence of 5G technology promises high-speed data transfer, yet it also underscores the need for robust security measures. Integrating Artificial Intelligence (AI) with 5G networks offers solutions to various challenges, including security concerns and the demand for autonomous systems like self-driving vehicles and virtual reality applications. Blockchain technology, known for its decentralized ledger system, presents an opportunity to address security and trust issues in IoT environments. However, integrating blockchain with IoT networks presents its own set of challenges, particularly in terms of throughput limitations.
DOI: 10.5281/zenodo.15190072
title: Enhancing Scalability and Privacy in 5G-Enabled IoT  Networks through Block chain Integration and AI  Solutions

description: The proliferation of Internet of Things (IoT) devices in the digital landscape has ushered in a new era of connectivity, empowering billions of devices to communicate over the internet. However, the reliance on centralized protocols for data transfer poses significant security challenges. The emergence of 5G technology promises high-speed data transfer, yet it also underscores the need for robust security measures. Integrating Artificial Intelligence (AI) with 5G networks offers solutions to various challenges, including security concerns and the demand for autonomous systems like self-driving vehicles and virtual reality applications. Blockchain technology, known for its decentralized ledger system, presents an opportunity to address security and trust issues in IoT environments. However, integrating blockchain with IoT networks presents its own set of challenges, particularly in terms of throughput limitations.
DOI: 10.5281/zenodo.14853744
title: Systematic review on virtual collaboration: Determining factors in higher education
DOI: 10.5281/zenodo.14853745
title: Systematic review on virtual collaboration: Determining factors in higher education
DOI: 10.15468/dl.5xufcd
title: Occurrence Download

description: A dataset listing the 2346 species recorded in GBIF matching the query:
{
 "and" : [
 "Country is Chile",
 "OccurrenceStatus is Present",
 "TaxonKey is Lecanoromycetes"
 ]
}

 The dataset's 2346 records were derived from 130 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024030-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hwuwjv
title: Occurrence Download

description: A dataset containing 858 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Astragalus angustifolius Lam."
 ]
}

 The dataset includes 858 records from 76 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024110-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.aragtr
title: Occurrence Download

description: A dataset containing 492 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Plantago asiatica L.",
 "Year 1970-2000"
 ]
}

 The dataset includes 492 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024114-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pdw3dh
title: Occurrence Download

description: A dataset containing 141 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is North America",
 "DatasetKey is one of (iNaturalist Research-grade Observations, Ecología poblacional y conservación de Tapirus bairdii en la Sierra Mixe, Oaxaca, Fortalecimiento de la Colección de fotocolectas biológicas (CFB): una propuesta del uso de la imagen digital al servicio del conocimiento de la biodiversidad)",
 "OccurrenceStatus is Present",
 "PublishingOrg is ff90b050-c256-11db-b71b-b8a03c50a862",
 "TaxonKey is Puma concolor (Linnaeus, 1771)",
 "Year 2008-2025"
 ]
}

 The dataset includes 141 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024118-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.689361
title: Radiosonde M3_R050 during METEOR cruise M3 on 1966-03-14 10:26h

description: Height of tropause 11400 m; Data processing by Wolfgang Gloeden, Maritime Klimaüberwachung (KU24), Deutscher Wetterdienst, http://www.dwd.de
DOI: 10.1594/pangaea.323263
title: Water temperature and salinity real-time profiles from cruise 6459700 (DCQC)

description: For definition of quality flags see hdl:10013/epic.31518.d001
DOI: 10.1594/pangaea.665779
title: Oceanography at CTD/bottle station IFREMER_2605
DOI: 10.1594/pangaea.663681
title: Oceanography at CTD/bottle station IFREMER_0521
DOI: 10.1594/pangaea.843436
title: Chlorophyll a measurements from water samples during Maria S. Merain cruise MSM17/4
DOI: 10.1594/pangaea.663280
title: Oceanography at CTD/bottle station IFREMER_0120
DOI: 10.1594/pangaea.665446
title: Oceanography at CTD/bottle station IFREMER_2286
DOI: 10.15468/dl.vkfuwd
title: Occurrence Download

description: A dataset containing 386 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae, Coccidae Stephens 1829, Coccidae Stephens, 1829, Coccidae Fallen 1814, Coccidae Fallen, 1814, Coccidae Fallén, 1814, Coccidae Fallén, 1814, Coccidae Stephens, 1829, Coccidae Fallen 1814, Coccidae Lin & Cook in Lin, Ding, Gullan & Cook, 2017, Aclerdidae Cockerell 1905, Micrococcidae Silvestri 1939, Aclerdidae, Pseudococcidae Heymons 1915, Micrococcidae, Kerriidae Lindinger 1937, Conchaspididae Green, 1896, Stictococcidae Lindinger, Kerriidae, Hyliidae Bates, 1930, Kermesidae Signoret 1875, Pseudococcidae, Riodinidae Grote, 1895, Riodinidae Grote, 1895, Kermesidae, Pseudococcidae, Lecaniidae, Lecaniidae)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "Country is one of (China, Chinese Taipei)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 386 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069646-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.943418
title: Physical oceanography from glider mission IFM12_depl08

description: One Slocum glider owned by GEOMAR (ifm12) was used during the cruise M156 to intensify the survey of the 18°W, 18.5°N cyclonic eddy. The glider was deployed on 24-Jul-2019 at 18°05'W, 18°35'N. It conducted an eastward transect along 18°42'N from the core to the periphery of the cyclonic eddy and was recovered on 28-Jul-2019 at 17°W, 18°42'N. The glider was equipped with temperature, conductivity, pressure, chlorophyll (chl-a), turbidity and optode oxygen sensors. An optical nitrate sensor (SUNA, Satlantic) was mounted to the glider's top as a self-contained sensor package.
DOI: 10.1594/pangaea.943409
title: ADCP current measurements (38 and 75 kHz) during METEOR cruise M160

description: A Teledyne RDI Ocean Surveyor system with 38 and 75 kHz transmission frequency was used. Data was processed with a software package developed at GEOMAR following the GO-SHIP standards (Firing and Hummon, 2010). The data was subsequently averaged over one minute intervals, converted to a NetCDF based format.
DOI: 10.1594/pangaea.943657
title: Underway CTD data collected during METEOR cruise M160

description: The UCTD is a CTD system that can be deployed from a moving ship, allowing for the sampling of water masses at high horizontal resolution (ranging from less than 1 km for the Rapidcast system to 10 km for deep UCTD casts) with good accuracy of the pressure, temperature, and conductivity sensors. Processing of the data involved mostly the fall-rate dependent correction of the thermal lag of the conductivity sensor and followed the approach described by Ullman and David (2014). Subsequently the corrected data was calibrated against the calibrated coincident Thermosalinograph and the calibrated nearby CTD data.The typical accuracies of the final pressure, temperature, and salinity data are 1 dbar, 0.01 °C, and 0.01 g/kg, respectively.
description: Version = PO-GLOBAL-SVN = 748Matlab = 9.4.0.813654 (R2018a)Release = 1
DOI: 10.15468/dl.p9gyee
title: Occurrence Download

description: A dataset containing 54902 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((16.99676 -22.62101, 17.11715 -22.62101, 17.11715 -22.48761, 16.99676 -22.48761, 16.99676 -22.62101))",
 "Year is greater than or equal to 2000",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 54902 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069643-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.1594/pangaea.943431
title: Physical oceanography (CTD) during METEOR cruise M156

description: Seabird 911plus systems equipped with dual temperature-conductivity-oxygen sensors were employed. All systems had a 24-bottle water sampling rosette with 10 l Niskin bottles. Water sampling, processing, and calibration followed GO-SHIP recommendations (Swift, 2010; McTaggart et al., 2010; Uchida et al., 2010) and included the recommended steps Data Conversion, Sensor Time-Alignment, Creation of Bottle Files, Outlier Removal, Pressure Sensor Filtering, Conductivity Cell Thermal Mass Correction, Ship Roll Correction and Deck Offset Correction by Loop Editing, as well as Derivation of Calculated Properties. After these steps, conductivity and oxygen readings were calibrated against values determined with salinometry and Winkler titration , respectively. Finally, the downcast data was averaged over 1 dbar wide intervals. An independent upcast calibration was used to obtain calibrated CTDO values coincident with the discrete water samples.
description: PO-GLOBAL-SVN = 687 used on 14-May-2020 12:17:44Matlab = 9.4.0.813654 (R2018a)Release = 2nc_uncertainty_p = 2.000000nc_uncertainty_t = 0.002000nc_uncertainty_s = 0.006000nc_uncertainty_o = 2.000000
DOI: 10.1594/pangaea.943432
title: Physical oceanography (CTD) during METEOR cruise M160

description: Seabird 911plus systems equipped with dual temperature-conductivity-oxygen sensors were employed. All systems had a 24-bottle water sampling rosette with 10 l Niskin bottles. Water sampling, processing, and calibration followed GO-SHIP recommendations (Swift, 2010; McTaggart et al., 2010; Uchida et al., 2010) and included the recommended steps Data Conversion, Sensor Time-Alignment, Creation of Bottle Files, Outlier Removal, Pressure Sensor Filtering, Conductivity Cell Thermal Mass Correction, Ship Roll Correction and Deck Offset Correction by Loop Editing, as well as Derivation of Calculated Properties. After these steps, conductivity and oxygen readings were calibrated against values determined with salinometry and Winkler titration , respectively. Finally, the downcast data was averaged over 1 dbar wide intervals. An independent upcast calibration was used to obtain calibrated CTDO values coincident with the discrete water samples.
description: PO-GLOBAL-SVN = 901 used on 31-Mar-2022 14:17:43Matlab = 9.4.0.813654 (R2018a)Release = 3Release_History = 1: initial release 2: new time-position info in header 3: with OPUS nitrate datanc_uncertainty_p = 2.000000nc_uncertainty_t = 0.002000nc_uncertainty_s = 0.003000nc_uncertainty_o = 1.000000Comment = par is UNCALIBRATEDComment = spar is UNCALIBRATEDComment = Fluorescence and Turbidity data still contain deck offsets. Use with caution
DOI: 10.1594/pangaea.659082
title: Frequency distributions of Siphonodictyon insidiosum spicule dimensions (Johnson, 1899); from drawing of spicules of holotype

description: See also doi:10.1594/PANGAEA.658976 for primary data
DOI: 10.1594/pangaea.401319
title: Water temperature and current velocity from surface drifter SVP_1445
DOI: 10.1594/pangaea.406910
title: Water temperature and current velocity from surface drifter SVP_9812729
DOI: 10.1594/pangaea.846656
title: (Table 2) Abundance of lithic grains in the carbonate-free coarse fraction in sediment core SU90-09
DOI: 10.1594/pangaea.663658
title: Oceanography at CTD/bottle station IFREMER_0498
DOI: 10.1594/pangaea.476356
title: Hydrochemistry measured on water bottle samples at station NAtl_1981_AN_26N/209

description: This data sets is part of a compilation by James Swift for the Java OceanAtlas software. Data are from various pre-WOCE sources, mainly with contributions and quality control from Joseph Reid (SIO) and NODC.
DOI: 10.1594/pangaea.846215
title: Isotopic carbon record for ODP Hole 207-1260B
DOI: 10.1594/pangaea.829686
title: (Table S3) Mineral composition of sediment core HU91-045-091
DOI: 10.1594/pangaea.847645
title: (Table 1) Temperature, salinity and dissolved organic carbon during POLARSTERN cruise ARK-XIII/3
DOI: 10.15468/dl.3hzj4c
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.704126 -33.777349, 148.704126 -33.784086, 148.710863 -33.784086, 148.710863 -33.779595, 148.706372 -33.779595, 148.706372 -33.777349, 148.704126 -33.777349))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069647-240626123714530/datasets/export for details.
DOI: 10.1594/pangaea.817828
title: (Table 1) Bulk and clay mineralogy at DSDP Leg 66 Holes

description: During Leg 66 eight sites on an active margin transect off southern Mexico were drilled in order to determine the nature of ocean-continent transition across a subduction zone. Present outcrops of Mesozoic to Precambrian basement at the coast intruded by Mesozoic magmas within only 65 km of the Middle America Trench axis indicate truncation of the continental margin, tectonic removal of an accretionary zone, and consumption of ocean sediments and crust by subduction.
description: Sediment depth is given in mbsf. Empty cells mean no data. ?0 = possibly present, &lt;1 = traces.
description: Supplement to: Schumann, Dieter; Nagel, Ulrich (1982): Appendix I. X-ray mineralogical analysis. In: Watkins, JS; Casey Moore, J; et al. (eds.), Initial Reports of the Deep Sea Drilling Project (U.S. Govt. Printing Office), 66, 853-857
DOI: 10.1594/pangaea.232387
title: Diatom abundance of Hole 85-572D

description: Relative abundance: D = dominant, A = abundant, C = common, F = few, R = rare, T = trace, P = present (numerical values are abundance in percent)
DOI: 10.1594/pangaea.689154
title: Radiosonde M2_R185 during METEOR cruise M2 on 1965-10-05 03:02h

description: Height of tropause 16220 m; Data processing by Wolfgang Gloeden, Maritime Klimaüberwachung (KU24), Deutscher Wetterdienst, http://www.dwd.de
DOI: 10.1594/pangaea.689287
title: Radiosonde M2_R327 during METEOR cruise M2 on 1965-12-01 23:04h

description: Height of tropause 16120 m; Data processing by Wolfgang Gloeden, Maritime Klimaüberwachung (KU24), Deutscher Wetterdienst, http://www.dwd.de
DOI: 10.1594/pangaea.843577
title: Basic measurements of radiation at station Chesapeake Light (2015-02)
DOI: 10.1594/pangaea.952520
title: Physical oceanography (CTD) during METEOR cruise M181

description: Seabird 911plus systems equipped with dual temperature-conductivity-oxygen sensors were employed. All systems had a 24-bottle water sampling rosette with 10 l Niskin bottles. Water sampling, processing, and calibration followed GO-SHIP recommendations (Swift, 2010; McTaggart et al., 2010; Uchida et al., 2010) and included the recommended steps Data Conversion, Sensor Time-Alignment, Creation of Bottle Files, Outlier Removal, Pressure Sensor Filtering, Conductivity Cell Thermal Mass Correction, Ship Roll Correction and Deck Offset Correction by Loop Editing, as well as Derivation of Calculated Properties. After these steps, conductivity and oxygen readings were calibrated against values determined with salinometry and Winkler titration , respectively. Finally, the downcast data was averaged over 1 dbar wide intervals. An independent upcast calibration was used to obtain calibrated CTDO values coincident with the discrete water samples.
description: PO-GLOBAL-SVN = 975 used on 16-Dec-2022 12:30:42Matlab = 9.4.0.813654 (R2018a)Release = 3nc_uncertainty_p = 2.000000nc_uncertainty_t = 0.002000nc_uncertainty_s = 0.003000nc_uncertainty_o = 1.000000
DOI: 10.1594/pangaea.885401
title: (Table S3) Age model of ODP Site 162-982

description: Ages &lt; 4 Ma derived from Lawrence et al. 2009 partially based on orbital tuning of Lisiecki and Raymo, 2005 of isotopic data from Venz and Hodell, 2002 and Venz et al., 1999.Ages &gt;4 Ma and &lt; 8.9 Ma derived from orbital tuning of isotopic data by Hodell, retuned in the 5.2-6.4 Ma interval by van der Laan et al. 2006.Ages &gt; 8.9 Ma estimated from biostratigraphic datums reported by the scientific party and high resolution sampling by Lirer and Iaccarino, 2005; Spiegler, 1999; Drury et al. 2016, 2017Age estimates with uncertainties were made using the Bacon program (Blaauw and Christen, 2011. Bacon program age modeling parameters: cc=0, acc.shape=1.5, acc.mean=20, mem.strength=70, mem.mean=0.38
DOI: 10.1594/pangaea.476449
title: Hydrochemistry measured on water bottle samples at station NAtl_1981_AN_37N/67

description: This data sets is part of a compilation by James Swift for the Java OceanAtlas software. Data are from various pre-WOCE sources, mainly with contributions and quality control from Joseph Reid (SIO) and NODC.