cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.1594/pangaea.962567
title: First- and second-year sea-ice salinity, temperature, and density during GoNorth 2022 leg 1

description: First- and second-year sea-ice thickness, draft, salinity, temperature, and density were measured during two ice stations on 24 October 2022 and 30 October 2022 during leg 1 of the GoNorth 2022 expedition. The ice cores were extracted with 7.25-cm (Mark III) internal diameter ice corers (Kovacs Enterprise, US). During each ice station, ice temperature was measured in situ from a separate temperature core, using Ebro TFX 410 Thermometer thermometers in drill holes with a length of half-core-diameter at 5 cm vertical resolution. Ice bulk practical salinity was measured from melted core sections at 5 cm resolution using a Mettler Toledo SevenGo conductivity meter. Sea ice density was measured using the hydrostatic weighing method (Pustogvar and Kulyakhtin, 2016) from several density cores in the freezer laboratory onboard RV Kronprins Haakon at the temperature from –10°C to –14°C. Relative volumes of brine and gas were estimated from ice salinity, temperature, and density using Cox and Weeks (1983) for cold ice and Leppäranta and Manninen (1988) for ice warmer than –2°C.This sea ice physics data was collected during leg 1 of the GoNorth 2022 scientific expedition on 14 October – 3 November 2022 (cruise number 2022713) on the RV Kronprins Haakon. The ice cores were collected at two ice stations (Station 6 and Super Station 14) located at 82°13.56' N and 26°41.43' E for the first and 82°31.05' N and 17°30.04' E for the second sea ice station in the area north of Svalbard. The data contains the event label (1), station (2), time (3), global coordinates (4,5) of each coring measurement, ice type (11), and sample ID (12). Each core has its manually measured ice thickness (6), ice draft (7), snow height (8), and local coordinates for each ice station (7,8). Each core section has the total length of its top (13) and bottom (14) measured in situ. Each core section has the value of its practical salinity (15), each core section of a temperature core has the value of its in situ temperature (16), and each core section of density cores has the value of its ice density (18). Each core section also has laboratory temperature (17), an estimate of brine volume fraction (19), and gas volume fraction (20).
DOI: 10.1594/pangaea.969554
title: Borehole indentation strength of first- and second-year sea-ice during GoNorth 2022 leg 1

description: Borehole indentation strength measurements were carried out on first- and second-year sea ice during two ice stations on 24 October 2022 and 30 October 2022, during leg 1 of the GoNorth 2022 expedition. The first station was termed station 6, located at 82°13.56' N, 26°41.43' E, while the second station was termed super station 14, located at 82°31.05' N, 17°30.04' E. The measurements were carried out using the NTNU borehole jack (Kallelid et al., 2019; Rødtang et al., 2023). At each station, a 77 mm borehole was augered and the borehole jack was inserted. The indentation was carried out at mainly 0.50 m and 0.16 m from the top of the ice on the second-year ice and first-year ice respectively, in the approximate middle of each ice sheet. Two indentations were carried out per borehole, in positive and negative y-direction. The indentation resistance was measured with two load cells and converted to pressure via a calibration factor. The borehole strength was recorded as the maximum measured pressure during indentation.
DOI: 10.15468/dl.2spuun
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Racotis inconclusa (Walker, 1860)"
 ]
}

 The dataset includes 13 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050302-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u329zy
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((149.148794 -36.654217, 149.144302 -36.654217, 149.144302 -36.651972, 149.142057 -36.651972, 149.142057 -36.660955, 149.160023 -36.660955, 149.160023 -36.658709, 149.164515 -36.658709, 149.164515 -36.656463, 149.162269 -36.656463, 149.162269 -36.654217, 149.157777 -36.654217, 149.157777 -36.651972, 149.155531 -36.651972, 149.155531 -36.64748, 149.15104 -36.64748, 149.15104 -36.651972, 149.148794 -36.651972, 149.148794 -36.654217), (149.148794 -36.654217, 149.15104 -36.654217, 149.15104 -36.656463, 149.148794 -36.656463, 149.148794 -36.654217))"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050303-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.t2c85c
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((148.266195 -33.786332, 148.266195 -33.788578, 148.261703 -33.788578, 148.261703 -33.795315, 148.254966 -33.795315, 148.254966 -33.802053, 148.25272 -33.802053, 148.25272 -33.806544, 148.250474 -33.806544, 148.250474 -33.811036, 148.25272 -33.811036, 148.25272 -33.817773, 148.250474 -33.817773, 148.250474 -33.833494, 148.259458 -33.833494, 148.259458 -33.826756, 148.261703 -33.826756, 148.261703 -33.824511, 148.272932 -33.824511, 148.272932 -33.822265, 148.275178 -33.822265, 148.275178 -33.817773, 148.281916 -33.817773, 148.281916 -33.815527, 148.284161 -33.815527, 148.284161 -33.811036, 148.288653 -33.811036, 148.288653 -33.806544, 148.290899 -33.806544, 148.290899 -33.799807, 148.288653 -33.799807, 148.288653 -33.802053, 148.284161 -33.802053, 148.284161 -33.806544, 148.281916 -33.806544, 148.281916 -33.80879, 148.275178 -33.80879, 148.275178 -33.806544, 148.277424 -33.806544, 148.277424 -33.795315, 148.281916 -33.795315, 148.281916 -33.786332, 148.266195 -33.786332)), ((148.290899 -33.799807, 148.293145 -33.799807, 148.293145 -33.795315, 148.290899 -33.795315, 148.290899 -33.799807)))"
 ]
}

 The dataset includes 4 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050304-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26499886
title: The genome sequences of 82 bacterial isolates.

description: The 82 genome sequences of bacteria isolated from chicken fecal samples.
DOI: 10.6084/m9.figshare.26499886.v1
title: The genome sequences of 82 bacterial isolates.

description: The 82 genome sequences of bacteria isolated from chicken fecal samples.
DOI: 10.15468/dl.6x8c3h
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((146.161881 -36.654217, 146.161881 -36.656463, 146.159636 -36.656463, 146.159636 -36.667692, 146.161881 -36.667692, 146.161881 -36.663201, 146.166373 -36.663201, 146.166373 -36.660955, 146.168619 -36.660955, 146.168619 -36.654217, 146.161881 -36.654217))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050306-240626123714530/datasets/export for details.
DOI: 10.15468/dl.mhvauz
title: Occurrence Download

description: A dataset containing 464 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Year is 1980",
 "TaxonKey is Ardeotis australis (J.E.Gray, 1829)"
 ]
}

 The dataset includes 464 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050308-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.s9zjvg
title: Occurrence Download

description: A dataset containing 377 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((148.964639 -33.795315, 148.964639 -33.799807, 148.966884 -33.799807, 148.966884 -33.802053, 148.971376 -33.802053, 148.971376 -33.811036, 148.980359 -33.811036, 148.980359 -33.795315, 148.964639 -33.795315)), ((148.971376 -33.811036, 148.966884 -33.811036, 148.966884 -33.815527, 148.964639 -33.815527, 148.964639 -33.822265, 148.966884 -33.822265, 148.966884 -33.824511, 148.982605 -33.824511, 148.982605 -33.822265, 148.987097 -33.822265, 148.987097 -33.820019, 148.971376 -33.820019, 148.971376 -33.811036)), ((148.982605 -33.824511, 148.982605 -33.826756, 148.989342 -33.826756, 148.989342 -33.824511, 148.982605 -33.824511)))"
 ]
}

 The dataset includes 377 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050307-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k57phv
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((148.939935 -33.817773, 148.939935 -33.822265, 148.942181 -33.822265, 148.942181 -33.826756, 148.948918 -33.826756, 148.948918 -33.824511, 148.951164 -33.824511, 148.951164 -33.817773, 148.939935 -33.817773))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050313-240626123714530/datasets/export for details.
DOI: 10.15468/dl.skutaq
title: Occurrence Download

description: A dataset containing 102 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Material citation)",
 "DatasetKey is one of (Digitalización y Sistematización de las Colecciones Biológicas Nacionales del Instituto de Biología, UNAM (vertebrados), Actualización de la base de datos de la colección nacional de anfibios y reptiles (CNAR), University of Michigan Museum of Zoology, Division of Reptiles & Amphibians, Computarización de las colecciones de vertebrados terrestres de la Escuela Nacional de Ciencias Biológicas, IPN Fase 4 (Anfibios y reptiles), KUBI Herpetology Collection, CAS Herpetology (HERP), MVZ Herp Collection (Arctos), LACM Vertebrate Collection, Formación de una base de datos y elaboración de un atlas de la herpetofauna de México (Anfibiosreptiles), UCM Amphibian and Reptile Collection (Arctos))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "PublishingOrg is one of (ff90b050-c256-11db-b71b-b8a03c50a862, 6ea87510-0561-11d8-b851-b8a03c50a862, b554c320-0560-11d8-b851-b8a03c50a862, 66522820-055c-11d8-b84e-b8a03c50a862, 493fe050-055d-11d8-b84f-b8a03c50a862, 8edbbde0-055e-11d8-b850-b8a03c50a862, 4cadac10-3e7b-11d9-8439-b8a03c50a862)",
 "TaxonKey is Salvadora mexicana (Duméril, Bibron & Duméril, 1854)",
 "Year 1950-2024"
 ]
}

 The dataset includes 102 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050310-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zeuxmw
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((148.935443 -36.654217, 148.935443 -36.656463, 148.948918 -36.656463, 148.948918 -36.654217, 148.935443 -36.654217)), ((148.948918 -36.656463, 148.948918 -36.660955, 148.951164 -36.660955, 148.951164 -36.667692, 148.957901 -36.667692, 148.957901 -36.669938, 148.964639 -36.669938, 148.964639 -36.667692, 148.960147 -36.667692, 148.960147 -36.660955, 148.957901 -36.660955, 148.957901 -36.656463, 148.948918 -36.656463)))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050312-240626123714530/datasets/export for details.
DOI: 10.25582/data.2024-04.3083032/2548026
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3083037/2548027
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3083039/2548028
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3083041/2548029
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3083042/2548030
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3083043/2548031
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3083045/2548032
title: Data for EMSL Project 51287 from April 2024
DOI: 10.5281/zenodo.6595475
title: COKI Open Access Dataset

description: The COKI Open Access Dataset measures open access performance for 142 countries and 5117 institutions and is available in JSON Lines format. The data is visualised at the COKI Open Access Dashboard: https://open.coki.ac/. The COKI Open Access Dataset is created with the COKI Academic Observatory data collection pipeline, which fetches data about research publications from multiple sources, synthesises the datasets and creates the open access calculations for each country and institution. Each week a number of specialised research publication datasets are collected. The datasets that are used for the COKI Open Access Dataset release include Crossref Metadata, Microsoft Academic Graph, Unpaywall and the Research Organization Registry. After fetching the datasets, they are synthesised to produce aggregate time series statistics for each country and institution in the dataset. The aggregate timeseries statistics include publication count, open access status and citation count. See https://open.coki.ac/data/ for the dataset schema. A new version of the dataset is deposited every week. <strong>Code</strong> The COKI Academic Observatory data collection pipeline is used to create the dataset. The COKI OA Website Github project contains the code for the web app that visualises the dataset at open.coki.ac. It can be found on Zenodo here. <strong>License</strong><br> COKI Open Access Dataset © 2022 by Curtin University is licenced under CC BY 4.0. <strong>Attributions</strong><br> This work contains information from: Microsoft Academic Graph which is made available under the ODC Attribution Licence. Crossref Metadata via the Metadata Plus program. Bibliographic metadata is made available without copyright restriction and Crossref generated data under a CC0 licence. See metadata licence information for more details. Unpaywall. The Unpaywall Data Feed is used under license. Data is freely available from Unpaywall via the API, data dumps and as a data feed. Research Organization Registry which is made available under a CC0 licence.
description: The Curtin Open Knowledge Initiative (COKI) is a strategic initiative of the Research Office at Curtin, the Faculty of Humanities, School of Media, Creative Arts and Social Inquiry and the Curtin Institute for Computation, with additional support from the Andrew W. Mellon Foundation and the Arcadia Fund, a charitable fund of Lisbet Rausing and Peter Baldwin.
DOI: 10.5281/zenodo.6665697
title: COKI Open Access Dataset

description: The COKI Open Access Dataset measures open access performance for 142 countries and 5117 institutions and is available in JSON Lines format. The data is visualised at the COKI Open Access Dashboard: https://open.coki.ac/. The COKI Open Access Dataset is created with the COKI Academic Observatory data collection pipeline, which fetches data about research publications from multiple sources, synthesises the datasets and creates the open access calculations for each country and institution. Each week a number of specialised research publication datasets are collected. The datasets that are used for the COKI Open Access Dataset release include Crossref Metadata, Microsoft Academic Graph, Unpaywall and the Research Organization Registry. After fetching the datasets, they are synthesised to produce aggregate time series statistics for each country and institution in the dataset. The aggregate timeseries statistics include publication count, open access status and citation count. See https://open.coki.ac/data/ for the dataset schema. A new version of the dataset is deposited every week. <strong>Code</strong> The COKI Academic Observatory data collection pipeline is used to create the dataset. The COKI OA Website Github project contains the code for the web app that visualises the dataset at open.coki.ac. It can be found on Zenodo here. <strong>License</strong><br> COKI Open Access Dataset © 2022 by Curtin University is licenced under CC BY 4.0. <strong>Attributions</strong><br> This work contains information from: Microsoft Academic Graph which is made available under the ODC Attribution Licence. Crossref Metadata via the Metadata Plus program. Bibliographic metadata is made available without copyright restriction and Crossref generated data under a CC0 licence. See metadata licence information for more details. Unpaywall. The Unpaywall Data Feed is used under license. Data is freely available from Unpaywall via the API, data dumps and as a data feed. Research Organization Registry which is made available under a CC0 licence.
description: The Curtin Open Knowledge Initiative (COKI) is a strategic initiative of the Research Office at Curtin, the Faculty of Humanities, School of Media, Creative Arts and Social Inquiry and the Curtin Institute for Computation, with additional support from the Andrew W. Mellon Foundation and the Arcadia Fund, a charitable fund of Lisbet Rausing and Peter Baldwin.
DOI: 10.5281/zenodo.7030235
title: COKI Open Access Dataset

description: The COKI Open Access Dataset measures open access performance for 142 countries and 5117 institutions and is available in JSON Lines format. The data is visualised at the COKI Open Access Dashboard: https://open.coki.ac/. The COKI Open Access Dataset is created with the COKI Academic Observatory data collection pipeline, which fetches data about research publications from multiple sources, synthesises the datasets and creates the open access calculations for each country and institution. Each week a number of specialised research publication datasets are collected. The datasets that are used for the COKI Open Access Dataset release include Crossref Metadata, Microsoft Academic Graph, Unpaywall and the Research Organization Registry. After fetching the datasets, they are synthesised to produce aggregate time series statistics for each country and institution in the dataset. The aggregate timeseries statistics include publication count, open access status and citation count. See https://open.coki.ac/data/ for the dataset schema. A new version of the dataset is deposited every week. <strong>Code</strong> The COKI Academic Observatory data collection pipeline is used to create the dataset. The COKI OA Website Github project contains the code for the web app that visualises the dataset at open.coki.ac. It can be found on Zenodo here. <strong>License</strong><br> COKI Open Access Dataset © 2022 by Curtin University is licenced under CC BY 4.0. <strong>Attributions</strong><br> This work contains information from: Microsoft Academic Graph which is made available under the ODC Attribution Licence. Crossref Metadata via the Metadata Plus program. Bibliographic metadata is made available without copyright restriction and Crossref generated data under a CC0 licence. See metadata licence information for more details. Unpaywall. The Unpaywall Data Feed is used under license. Data is freely available from Unpaywall via the API, data dumps and as a data feed. Research Organization Registry which is made available under a CC0 licence.
description: The Curtin Open Knowledge Initiative (COKI) is a strategic initiative of the Research Office at Curtin, the Faculty of Humanities, School of Media, Creative Arts and Social Inquiry and the Curtin Institute for Computation, with additional support from the Andrew W. Mellon Foundation and the Arcadia Fund, a charitable fund of Lisbet Rausing and Peter Baldwin.
DOI: 10.5281/zenodo.8127223
title: COKI Open Access Dataset

description: The COKI Open Access Dataset measures open access performance for 221 countries and 14,477 institutions and is available in JSON Lines format. The data is visualised at the COKI Open Access Dashboard: https://open.coki.ac/. The COKI Open Access Dataset is created with the COKI Academic Observatory data collection pipeline, which fetches data about research publications from multiple sources, synthesises the datasets and creates the open access calculations for each country and institution. Each week a number of specialised research publication datasets are collected. The datasets that are used for the COKI Open Access Dataset release include Crossref Metadata, OpenAlex, Unpaywall and the Research Organization Registry. After fetching the datasets, they are synthesised to produce aggregate time series statistics for each country and institution in the dataset. The aggregate timeseries statistics include publication count, open access status and citation count. See https://open.coki.ac/data/ for the dataset schema. A new version of the dataset is deposited every week. <strong>Code</strong> The COKI Academic Observatory data collection pipeline is used to create the dataset. The COKI OA Website Github project contains the code for the web app that visualises the dataset at open.coki.ac. It can be found on Zenodo here. <strong>License</strong><br> COKI Open Access Dataset © 2022 by Curtin University is licenced under CC BY 4.0. <strong>Attributions</strong><br> This work contains information from: OpenAlex which is made available under the CC0 license. Crossref Metadata via the Metadata Plus program. Bibliographic metadata is made available without copyright restriction and Crossref generated data under a CC0 licence. See metadata licence information for more details. Unpaywall. The Unpaywall Data Feed is used under license. Data is freely available from Unpaywall via the API, data dumps and as a data feed. Research Organization Registry which is made available under a CC0 licence.
description: The Curtin Open Knowledge Initiative (COKI) is a strategic initiative of the Research Office at Curtin, the Faculty of Humanities, School of Media, Creative Arts and Social Inquiry and the Curtin Institute for Computation, with additional support from the Mellon Foundation and the Arcadia Fund, a charitable fund of Lisbet Rausing and Peter Baldwin.
DOI: 10.25582/data.2024-04.3083047/2548033
title: Data for EMSL Project 51287 from April 2024