cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.26050/wdcc/ar6.c6cmcsiacc
title: IPCC DDC: CSIRO-ARCCSS ACCESS-CM2 model output prepared for CMIP6 CMIP

description: Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.CSIRO-ARCCSS.ACCESS-CM2' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The Australian Community Climate and Earth System Simulator Climate Model Version 2 climate model, released in 2019, includes the following components: aerosol: UKCA-GLOMAP-mode, atmos: MetUM-HadGEM3-GA7.1 (N96; 192 x 144 longitude/latitude; 85 levels; top level 85 km), land: CABLE2.5, ocean: ACCESS-OM2 (GFDL-MOM5, tripolar primarily 1deg; 360 x 300 longitude/latitude; 50 levels; top grid cell 0-10 m), seaIce: CICE5.1.2 (same grid as ocean). The model was run by the CSIRO (Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia), ARCCSS (Australian Research Council Centre of Excellence for Climate System Science). Mailing address: CSIRO, c/o Simon J. Marsland, 107-121 Station Street, Aspendale, Victoria 3195, Australia (CSIRO-ARCCSS) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, seaIce: 100 km.
DOI: 10.6084/m9.figshare.23749169
title: On the virtues and pitfalls of combined <i>laser ablation</i> Rb-Sr biotite and U-Pb monazite- zircon geochronology: an example from the isotopically disturbed Cape Woolamai Granite, SE Australia

description: Table 1: Zircon U-Pb and TE
DOI: 10.6084/m9.figshare.23749172
title: On the virtues and pitfalls of combined <i>laser ablation</i> Rb-Sr biotite and U-Pb monazite- zircon geochronology: an example from the isotopically disturbed Cape Woolamai Granite, SE Australia

description: Table 3: Mica Rb-Sr
DOI: 10.6084/m9.figshare.23749172.v1
title: On the virtues and pitfalls of combined <i>laser ablation</i> Rb-Sr biotite and U-Pb monazite- zircon geochronology: an example from the isotopically disturbed Cape Woolamai Granite, SE Australia

description: Table 3: Mica Rb-Sr
DOI: 10.5281/zenodo.8184158
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Jean-Frédéric de Chaillet, http://www.wikidata.org/entity/Q21338227. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q21338227
DOI: 10.5281/zenodo.8184157
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Jean-Frédéric de Chaillet, http://www.wikidata.org/entity/Q21338227. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q21338227
DOI: 10.5281/zenodo.8183084
title: Genome-wide CyclomicsSeq of DNA ladders

description: Levels of circulating tumor DNA (ctDNA) in liquid biopsies may serve as a sensitive biomarker for real-time, minimally-invasive tumor diagnostics and monitoring. However, detecting ctDNA is challenging, as much fewer than 5% of the cell-free DNA in the blood typically originates from the tumor. To detect lowly abundant molecules, extremely sensitive sequencing methods are required. We adapted a new technique, CyclomicsSeq, which is based on Oxford Nanopore sequencing of concatenated copies of a single DNA molecule for genome-wide sequencing, and applied this to GeneRuler DNA ladders.
description: GeneRuler 50 bp DNA ladder (https://www.thermofisher.com/order/catalog/product/SM0371) GeneRuler 1 kb DNA ladder (https://www.thermofisher.com/order/catalog/product/SM0311)
DOI: 10.5281/zenodo.8183083
title: Genome-wide CyclomicsSeq of DNA ladders

description: Levels of circulating tumor DNA (ctDNA) in liquid biopsies may serve as a sensitive biomarker for real-time, minimally-invasive tumor diagnostics and monitoring. However, detecting ctDNA is challenging, as much fewer than 5% of the cell-free DNA in the blood typically originates from the tumor. To detect lowly abundant molecules, extremely sensitive sequencing methods are required. We adapted a new technique, CyclomicsSeq, which is based on Oxford Nanopore sequencing of concatenated copies of a single DNA molecule for genome-wide sequencing, and applied this to GeneRuler DNA ladders.
description: GeneRuler 50 bp DNA ladder (https://www.thermofisher.com/order/catalog/product/SM0371) GeneRuler 1 kb DNA ladder (https://www.thermofisher.com/order/catalog/product/SM0311)
DOI: 10.5281/zenodo.8180872
title: Phylogeny of the Braconinae (Hymenoptera: Braconidae): a new tribal order!

description: Supplementary files
DOI: 10.5281/zenodo.8180871
title: Phylogeny of the Braconinae (Hymenoptera: Braconidae): a new tribal order!

description: Supplementary files
DOI: 10.5281/zenodo.8136708
title: Weather-based ML Datasets

description: Included are three datasets and machine learning models from Handler et al. (2020), Flora et al. (2021), and Chase et al. (2022. 2023). Handler et al. (2020) is a 1-hr HRRR-based nowcasting dataset predicting frozen road surfaces. Flora et al. (2021) is a 0-150 min severe weather dataset derived from the convection-allowing ensemble system known as the Warn-on-Forecast System. Lastly, the Chase et al. dataset is a lower resolution of the Storm EVent ImagRy (SEVIR; Veillette et al. 2020) dataset where the goal is to predict lightning.
DOI: 10.5281/zenodo.8136709
title: Weather-based ML Datasets

description: Included are three datasets from Handler et al. (2020), Flora et al. (2021), and Chase et al. (2022. 2023). Handler et al. (2020) is a 1-hr HRRR-based nowcasting dataset predicting frozen road surfaces. Flora et al. (2021) is a 0-150 min severe weather dataset derived from the convection-allowing ensemble system known as the Warn-on-Forecast System. Lastly, the Chase et al. dataset is a lower resolution of the Storm EVent ImagRy (SEVIR; Veillette et al. 2020) dataset where the goal is to predict lightning.
DOI: 10.5281/zenodo.8184201
title: Weather-based ML Datasets

description: Included are three datasets and machine learning models from Handler et al. (2020), Flora et al. (2021), and Chase et al. (2022. 2023). Handler et al. (2020) is a 1-hr HRRR-based nowcasting dataset predicting frozen road surfaces. Flora et al. (2021) is a 0-150 min severe weather dataset derived from the convection-allowing ensemble system known as the Warn-on-Forecast System. Lastly, the Chase et al. dataset is a lower resolution of the Storm EVent ImagRy (SEVIR; Veillette et al. 2020) dataset where the goal is to predict lightning.
DOI: 10.6084/m9.figshare.23749203
title: Test data

description: Test data
DOI: 10.6084/m9.figshare.23749203.v1
title: Test data

description: Test data
DOI: 10.5519/qd.3f3kea6v
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (13 records)
DOI: 10.6073/pasta/7cc54c25287161e7e8ced745ca6c88d0
title: Sawgrass Above and Below Ground Total Phosphorus from the Taylor Slough, Everglades National Park (FCE LTER), Florida, USA, March 2002 - ongoing

description: Once a year during the dry season (Dec-May) three live sawgrass plants are collected from each site. These plants are divided into their live above and live below ground parts. Then both the above and below ground parts are analyzed for TN, TC, and TP.
DOI: 10.21227/cj1s-b323
title: Contextual integrity in the UK

description: Individuals tend to overstate privacy concerns concerning their online behaviors; however, users share more personal data than they realize when accepting terms and conditions. This research explores how contextual integrity -understood as privacy attitudes- often defined as social norms over privacy in a particular context (Nissenbaum 2004)- can be further explored through vignettes in social research. It also focuses on how contextual integrity interacts with trust and the effect of knowledge on data protection, both of which are treated as controls to explain contextual integrity further. Research findings demonstrate when individuals are asked about hypothetical situations around services and products they consume, they tend to accept these contextual integrity vignettes. We focus on millennials because, according to studies, they are the age group that indulges in risky behaviors online that compromise their personal data.
DOI: 10.5517/ccdc.csd.cc24r99j
title: CCDC 1988597: Experimental Crystal Structure Determination

description: Related Article: Xiao-Hui Huang, Yi-Ping Chen, Shao-Ming Ying, Xiao-Jing Hu, Yan-Qiong Sun, Xiao-Xing Huang|2023|J.Mol.Struct.|1292|136161|doi:10.1016/j.molstruc.2023.136161
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.cc23v8nx
title: CCDC 1961669: Experimental Crystal Structure Determination

description: Related Article: Mohammad Chahkandi, Rifat Jawaria, Muhammad Khalid, Muhammad Nawaz Tahir, Muhammad Moazzam Naseer, Mohammad Hassan Zargazi, Zahid Shafiq, Mehdi Baghayeri|2023|Inorg.Chem.Commun.|155|111051|doi:10.1016/j.inoche.2023.111051
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.cc23v8lv
title: CCDC 1961667: Experimental Crystal Structure Determination

description: Related Article: Mohammad Chahkandi, Rifat Jawaria, Muhammad Khalid, Muhammad Nawaz Tahir, Muhammad Moazzam Naseer, Mohammad Hassan Zargazi, Zahid Shafiq, Mehdi Baghayeri|2023|Inorg.Chem.Commun.|155|111051|doi:10.1016/j.inoche.2023.111051
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.cc2bf7tv
title: CCDC 2157687: Experimental Crystal Structure Determination

description: Related Article: Cansu GÖKÇE TOPKAYA, Esin SAKALLI ÇETİN, Tolga GÖKTÜRK, Sultan KINCAL, Tuncer HÖKELEK, Ramazan GÜP|2023|Inorg.Chem.Commun.|155|111040|doi:10.1016/j.inoche.2023.111040
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.cc2cl0ww
title: CCDC 2192068: Experimental Crystal Structure Determination

description: Related Article: Huimin Wen, Dashuai Zhang, Hang Zhao, Yawen Zhang, Xiaojun Yan, Wenhan Lin, Shan He, Lijian Ding|2023|Phytochemistry|213|113779|doi:10.1016/j.phytochem.2023.113779
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.cc2cpddw
title: CCDC 2195308: Experimental Crystal Structure Determination

description: Related Article: Debakanta Tripathy, Soumya Lipsa Rath, Niladri B. Debata, Amlan K. Pal, Dillip K. Chand, Garry S. Hanan|2023|J.Mol.Struct.|1292|136112|doi:10.1016/j.molstruc.2023.136104
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.cc2c0b2t
title: CCDC 2175055: Experimental Crystal Structure Determination

description: Related Article: Harsha Gopal Agrawal, Sajmina Khatun, Aravind Kumar Rengan, Ashutosh Kumar Mishra|2023|Polyhedron|243|116536|doi:10.1016/j.poly.2023.116536
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.cc2cy9d1
title: CCDC 2202903: Experimental Crystal Structure Determination

description: Related Article: Harsha Gopal Agrawal, Sajmina Khatun, Aravind Kumar Rengan, Ashutosh Kumar Mishra|2023|Polyhedron|243|116536|doi:10.1016/j.poly.2023.116536
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.cc2d9tp7
title: CCDC 2213979: Experimental Crystal Structure Determination

description: Related Article: Subham G. Patel, Paras J. Patel, Dipti B. Upadhyay, Adrián Puerta, Apoorva Malik, Nagesh K. Kandukuri, Rakesh K Sharma, José M. Padrón, Hitendra M. Patel|2023|J.Mol.Struct.|1292|136174|doi:10.1016/j.molstruc.2023.136174
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.cc2dy1w9
title: CCDC 2232461: Experimental Crystal Structure Determination

description: Related Article: Haoran Hu, editing, Lei Chen, Tongtong Jing, Chong Zhang, Chengguo Sun, Chao Gao, Yang Du, Bingcheng Hu|2023|Spectrochim.Acta,Part A|303|123118|doi:10.1016/j.saa.2023.123118
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.cc2f1qnw
title: CCDC 2235988: Experimental Crystal Structure Determination

description: Related Article: Si-Hong Chen, Kai Jiang, Yao-Hui Liang, Jin-Ping He, Bing-Jia Xu, Zhao-Hua Chen, Zhao-Yang Wang|2023|Food Chem.|428|136800|doi:10.1016/j.foodchem.2023.136800
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.cc2f1qpx
title: CCDC 2235989: Experimental Crystal Structure Determination

description: Related Article: Si-Hong Chen, Kai Jiang, Yao-Hui Liang, Jin-Ping He, Bing-Jia Xu, Zhao-Hua Chen, Zhao-Yang Wang|2023|Food Chem.|428|136800|doi:10.1016/j.foodchem.2023.136800
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: 10.5281/zenodo.8184267
title: Interview Transcripts on Ocean Modeling and Biogeochemical Modeling

description: This data package contains interview transcripts of interviews that we conducted to understand the domain of ocean modeling with a focus on human interaction, processes and tooling to support our effort to create domain-specific languages to support the work of scientists in this domain. This data package contains the anonymized transcripts of interviews from two phases. The <strong>first phase</strong> was dedicated to collect any theme regarding the domain including processes to develop, maintain and use scientific models (in<br> particular in ocean sciences), as well as, human interaction, technical aspects, and other work environment related themes. The <strong>second phase</strong> focus on the development of biogeochemical models. However, we also included questions regarding the domain.
DOI: 10.5281/zenodo.8184266
title: Interview Transcripts on Ocean Modeling and Biogeochemical Modeling

description: This data package contains interview transcripts of interviews that we conducted to understand the domain of ocean modeling with a focus on human interaction, processes and tooling to support our effort to create domain-specific languages to support the work of scientists in this domain. This data package contains the anonymized transcripts of interviews from two phases. The <strong>first phase</strong> was dedicated to collect any theme regarding the domain including processes to develop, maintain and use scientific models (in<br> particular in ocean sciences), as well as, human interaction, technical aspects, and other work environment related themes. The <strong>second phase</strong> focus on the development of biogeochemical models. However, we also included questions regarding the domain.
DOI: 10.25345/c5862bn7v
title: MassIVE MSV000092522 - Metabolomic Insights in Advanced Cardiomyopathy of Chronic Chagasic and Idiopathic Patients that Underwent Heart Transplant
title: Characterization of plasma metabolomic profile of 15 patients with advanced heart failure referred for heart transplantation (8 patients with chronic chagasic cardiomyopathy and 7 with idiopathic dilated cardiomyopathy) and 12 heart donor individuals using gas chromatography/quadrupole time-of-flight mass spectrometry.
DOI: 10.34740/kaggle/dsv/6116356
title: Harsh driving dataset
DOI: 10.21227/6j2k-z363
title: Scattering results by a 10x10 square array composed of magnetodielectric circular cylinders

description: The uploaded data include input and result files for a 10x10 square array composed of magnetodielectric circular cylinders, which can be used to obtain electromagnetic scattering behaviors excited by a uniform plane wave. We use the input file to fill up the information of positions, radii, relative permittivity, relative permeability, and numbers of computation modes for elements of the square array. The result files computed by a mode-matching technique (MMT) represent the TEz- and TMz-mode echowidths of observation angles, when the element information is set up by the input file. The MMT is combined with an iterative method named as a shooting and bouncing rays for sparse particles (SBR-SP) to accelerate the computation time of multiple scatterers.
DOI: 10.5281/zenodo.8184389
title: The TREASURE semantic social network data on the circular economy aspect of automotive manufacturing

description: The TREASURE project looks at industrial innovation to address the problem of making onboard electronics in the automotive industry easier to recycle, increasing the industry's contribution to the circular economy. As part of it, a team of ethnographers generated and coded the corpus contained in this dataset. interviews conducted between January 2022 and June 2023 with car owners and enthusiasts at car industry events. The interviews focus on experiences with car electronics and perspectives on sustainability and the circular economy. The dataset is pseudonymized. TREASURE is supported by the European Union's Horizon 2020 programme, grant n. 101003587.
DOI: 10.5281/zenodo.8184388
title: The TREASURE semantic social network data on the circular economy aspect of automotive manufacturing

description: The TREASURE project looks at industrial innovation to address the problem of making onboard electronics in the automotive industry easier to recycle, increasing the industry's contribution to the circular economy. As part of it, a team of ethnographers generated and coded the corpus contained in this dataset. interviews conducted between January 2022 and June 2023 with car owners and enthusiasts at car industry events. The interviews focus on experiences with car electronics and perspectives on sustainability and the circular economy. The dataset is pseudonymized. TREASURE is supported by the European Union's Horizon 2020 programme, grant n. 101003587.
DOI: 10.34740/kaggle/dsv/6194144
title:  UCI Dataset with 15k+ rows