cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7652781
title: SuperDARN Grid data in netCDF format (1997-Dec)

description: 1997-Dec SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.7652801
title: SuperDARN Grid data in netCDF format (1997-Oct)

description: 1997-Oct SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.7652802
title: SuperDARN Grid data in netCDF format (1997-Oct)

description: 1997-Oct SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.7652794
title: SuperDARN Grid data in netCDF format (1997-Nov)

description: 1997-Nov SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.7652795
title: SuperDARN Grid data in netCDF format (1997-Nov)

description: 1997-Nov SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.7652817
title: SuperDARN Grid data in netCDF format (1997-Aug)

description: 1997-Aug SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.7652818
title: SuperDARN Grid data in netCDF format (1997-Aug)

description: 1997-Aug SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.7652811
title: SuperDARN Grid data in netCDF format (1997-Sep)

description: 1997-Sep SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.7652812
title: SuperDARN Grid data in netCDF format (1997-Sep)

description: 1997-Sep SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.7652772
title: SuperDARN Grid data in netCDF format (1998-Feb)

description: 1998-Feb SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.7652773
title: SuperDARN Grid data in netCDF format (1998-Feb)

description: 1998-Feb SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.The RST is available here: https://github.com/SuperDARN/rstThe research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (SuperDARN Radar Overview)<strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.7668415
title: SVAD Age Data: Angola

description: <strong>Description</strong> The dental and skeletal age indicators were collected from anonymized radiographic images generated from a clinical context in Angola. All images were generated in the past ~10 years and include individuals between birth and 18 years of age. As part of the SVAD age indicator template, there are 64 age variables (columns) in the dataset, which include diaphyseal lengths and breadths, epiphyseal fusion/appearance of ossification centers, and dental development. However, because this data is collected from two dimensional radiographic images, only epiphyseal fusion/appearance of ossification centers and dental data are included; all diaphyseal dimensions have a 'NA'. The data collection methodology can be found in Stull and Corron (2022) and Corron et al. (2021), and the latter includes the abbreviations and full variable names along with its staging system. <strong>Basic Key Code:</strong> *DL_L/R == diaphyseal lengths *DB_L/R == diapyseal lengths *EF_L/R == epiphyseal fusion *Oss == ossification *man_ and max_ == mandibular and maxillary dental development <strong>References</strong> Stull, K.E. and Corron, L.K. (<em>2022</em>) The Subadult Virtual Anthropology Database (SVAD): An Accessible Repository of Contemporary Subadult Reference Data. Forensic. Sci. 2022, 2, 20–36. https://doi.org/10.3390/forensicsci2010003 Corron, LK, <em>et al. (2021)</em> Standardizing ordinal subadult age indicators: Testing for observer agreement and consistency across modalities. <em>Forensic Science International</em> <strong>320</strong>, 110687.
description: Funded by the National Institute of Justice Award 2017-DN-BX-0144
DOI: 10.5281/zenodo.7668414
title: SVAD Age Data: Angola

description: <strong>Description</strong> The dental and skeletal age indicators were collected from anonymized radiographic images generated from a clinical context in Angola. All images were generated in the past ~10 years and include individuals between birth and 18 years of age. As part of the SVAD age indicator template, there are 64 age variables (columns) in the dataset, which include diaphyseal lengths and breadths, epiphyseal fusion/appearance of ossification centers, and dental development. However, because this data is collected from two dimensional radiographic images, only epiphyseal fusion/appearance of ossification centers and dental data are included; all diaphyseal dimensions have a 'NA'. The data collection methodology can be found in Stull and Corron (2022) and Corron et al. (2021), and the latter includes the abbreviations and full variable names along with its staging system. <strong>Basic Key Code:</strong> *DL_L/R == diaphyseal lengths *DB_L/R == diapyseal lengths *EF_L/R == epiphyseal fusion *Oss == ossification *man_ and max_ == mandibular and maxillary dental development <strong>References</strong> Stull, K.E. and Corron, L.K. (<em>2022</em>) The Subadult Virtual Anthropology Database (SVAD): An Accessible Repository of Contemporary Subadult Reference Data. Forensic. Sci. 2022, 2, 20–36. https://doi.org/10.3390/forensicsci2010003 Corron, LK, <em>et al. (2021)</em> Standardizing ordinal subadult age indicators: Testing for observer agreement and consistency across modalities. <em>Forensic Science International</em> <strong>320</strong>, 110687.
description: Funded by the National Institute of Justice Award 2017-DN-BX-0144
DOI: 10.5517/ccdc.csd.cc2bztz4
title: CCDC 2174587: Experimental Crystal Structure Determination

description: Related Article: Cassandre C. Bories, Geoffrey Gontard, Marion Barbazanges, Etienne Derat, Marc Petit|2023|Org.Lett.|25|843|doi:10.1021/acs.orglett.3c00022
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/ccdc.csd.cc2bzv06
title: CCDC 2174588: Experimental Crystal Structure Determination

description: Related Article: Cassandre C. Bories, Geoffrey Gontard, Marion Barbazanges, Etienne Derat, Marc Petit|2023|Org.Lett.|25|843|doi:10.1021/acs.orglett.3c00022
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/ccdc.csd.cc2bzv17
title: CCDC 2174589: Experimental Crystal Structure Determination

description: Related Article: Cassandre C. Bories, Geoffrey Gontard, Marion Barbazanges, Etienne Derat, Marc Petit|2023|Org.Lett.|25|843|doi:10.1021/acs.orglett.3c00022
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/ccdc.csd.cc2chms9
title: CCDC 2189771: Experimental Crystal Structure Determination

description: Related Article: Asit Ghosh, Yuriy B. Lipisa, Natalia Fridman, Alex M. Szpilman|2023|J.Org.Chem.|88|1977|doi:10.1021/acs.joc.2c02125
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/ccdc.csd.cc2clr4w
title: CCDC 2192758: Experimental Crystal Structure Determination

description: Related Article: Dmitrii O. Tolochenko, Semyon V. Tsybulin, Artyom A. Yakubenko, Elena Yu. Tupikina, Alexander S. Antonov|2023|Org.Lett.|25|977|doi:10.1021/acs.orglett.3c00035
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/ccdc.csd.cc2clr5x
title: CCDC 2192759: Experimental Crystal Structure Determination

description: Related Article: Dmitrii O. Tolochenko, Semyon V. Tsybulin, Artyom A. Yakubenko, Elena Yu. Tupikina, Alexander S. Antonov|2023|Org.Lett.|25|977|doi:10.1021/acs.orglett.3c00035
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/ccdc.csd.cc2cm179
title: CCDC 2193040: Experimental Crystal Structure Determination

description: Related Article: Yuan Wang, Yun-Bao Ma, Xiao-Yan Huang, Tian-Ze Li, Xiao-Feng He, Xue-Mei Zhang, Ji-Jun Chen|2023|Fitoterapia|165|105399|doi:10.1016/j.fitote.2022.105399
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/ccdc.csd.cc2cmf4l
title: CCDC 2193409: Experimental Crystal Structure Determination

description: Related Article: Paz Yepes, Ángel L. Suárez-Sobrino, Miguel A. Rodríguez, Alfredo Ballesteros|2023|Org.Lett.|25|1020|doi:10.1021/acs.orglett.3c00221
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.