cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.22033/esgf/cmip6.12340
title: IPSL 4AOP-v1-5 model output prepared for CMIP6 RFMIP

description: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets: These data include all datasets published for 'CMIP6.RFMIP.IPSL.4AOP-v1-5' 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 Line-By-Line Radiative Transfer Model v1.5, Laboratoire Meteorologie Dynamique, GEISA spectroscopic database climate model, released in 2019, was run by the Institut Pierre Simon Laplace, Paris 75252, France (IPSL). 

Project: 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. - Project website: https://pcmdi.llnl.gov/CMIP6.
DOI: 10.22033/esgf/cmip6.12369
title: IPSL 4AOP-v1-5 model output prepared for CMIP6 RFMIP rad-irf

description: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets: These data include all datasets published for 'CMIP6.RFMIP.IPSL.4AOP-v1-5.rad-irf' 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 Line-By-Line Radiative Transfer Model v1.5, Laboratoire Meteorologie Dynamique, GEISA spectroscopic database climate model, released in 2019, was run by the Institut Pierre Simon Laplace, Paris 75252, France (IPSL). 

Project: 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. - Project website: https://pcmdi.llnl.gov/CMIP6.
DOI: 10.22033/esgf/cmip6.8570
title: NOAA-GFDL GFDL-ESM4 model output prepared for CMIP6 DAMIP hist-GHG

description: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets: These data include all datasets published for 'CMIP6.DAMIP.NOAA-GFDL.GFDL-ESM4.hist-GHG' 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 GFDL-ESM4 climate model, released in 2018, includes the following components:
 aerosol: interactive, atmos: GFDL-AM4.1 (Cubed-sphere (c96) - 1 degree nominal horizontal resolution; 360 x 180 longitude/latitude; 49 levels; top level 1 Pa), atmosChem: GFDL-ATMCHEM4.1 (full atmospheric chemistry), land: GFDL-LM4.1, landIce: GFDL-LM4.1, ocean: GFDL-OM4p5 (GFDL-MOM6, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 75 levels; top grid cell 0-2 m), ocnBgchem: GFDL-COBALTv2, seaIce: GFDL-SIM4p5 (GFDL-SIS2.0, tripolar - nominal 0.5 deg; 720 x 576 longitude/latitude; 5 layers; 5 thickness categories). 
The model was run by the National Oceanic and Atmospheric Administration, Geophysical Fluid Dynamics Laboratory, Princeton, NJ 08540, USA (NOAA-GFDL) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, landIce: 100 km, ocean: 50 km, ocnBgchem: 50 km, seaIce: 50 km. 

Project: 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. - Project website: https://pcmdi.llnl.gov/CMIP6.
DOI: 10.22033/esgf/cmip6.8709
title: NUIST NESMv3 model output prepared for CMIP6 CMIP 1pctCO2

description: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets: These data include all datasets published for 'CMIP6.CMIP.NUIST.NESM3.1pctCO2' 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 NUIST ESM v3 climate model, released in 2016, includes the following components:
 atmos: ECHAM v6.3 (T63; 192 x 96 longitude/latitude; 47 levels; top level 1 Pa), land: JSBACH v3.1, ocean: NEMO v3.4 (NEMO v3.4, tripolar primarily 1deg; 384 x 362 longitude/latitude; 46 levels; top grid cell 0-6 m), seaIce: CICE4.1. 
The model was run by the Nanjing University of Information Science and Technology, Nanjing, 210044, China (NUIST) in native nominal resolutions: atmos: 250 km, land: 2.5 km, ocean: 100 km, seaIce: 100 km. 

Project: 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. - Project website: https://pcmdi.llnl.gov/CMIP6.
DOI: 10.22033/esgf/cmip6.7782
title: SNU SAM0-UNICON model output prepared for CMIP6 CMIP 1pctCO2

description: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets: These data include all datasets published for 'CMIP6.CMIP.SNU.SAM0-UNICON.1pctCO2' 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 SAM0-UNICON (SNU Atmosphere Model version 0 with Unified Convection Scheme) climate model, released in 2017, includes the following components:
 aerosol: MAM3, atmos: CAM5.3 with UNICON (1deg; 288 x 192 longitude/latitude; 30 levels; top level ~2 hPa), land: CLM4.0, ocean: POP2 (Displaced Pole; 320 x 384 longitude/latitude; 60 levels; top grid cell 0-10 m), seaIce: CICE4.0. 
The model was run by the Seoul National University, Seoul 08826, Republic of Korea (SNU) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km. 

Project: 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. - Project website: https://pcmdi.llnl.gov/CMIP6.
DOI: 10.22033/esgf/input4mips.9861
title: UoM-AIM-ssp370-1-2-1 GHG concentrations

description: CMIP6 Forcing Datasets (input4MIPs): These data include all datasets published for 'input4MIPs.CMIP6.ScenarioMIP.UoM.UoM-AIM-ssp370-1-2-1' with the full Data Reference Syntax following the template 'activity_id.mip_era.target_mip.institution_id.source_id.realm.frequency.variable_id.grid_label'.
 
 The model UoM-AIM-ssp370-1-2-1 (UoM-AIM-ssp370-1-2-1) was run by the UoM (UoM) in native nominal resolutions: unknown. 

Project: The forcing datasets (and boundary conditions) needed for CMIP6 experiments are being prepared by a number of different experts. Initially many of these datasets may only be available from those experts, but over time as part of the 'input4MIPs' activity most of them will be archived by PCMDI and served by the Earth System Grid Federation (https://esgf-node.llnl.gov/search/input4mips/ ). More information is available in the living document: http://goo.gl/r8up31 .
DOI: 10.5683/sp3/zwshgv
title: Monica Lecce MASc thesis videos

description: Supplemental videos for Monica Lecce's Master's thesis.
DOI: 10.5683/sp3/4mwfoi
title: Deecker_Shayna_R_202211_PhD_datatables

description: Much of the data used to conduct the bioinformatic analyses in Chapter 3 of my PhD thesis consists of large tables that are unsuitable for the thesis format. They are available here under the filename:

Deecker_Shayna_R_202211_PhD_datatables.xlsx.

The contents of the tables are as follows:

Table S1: The Legionella pneumophila isolates used in this study.

Table S2: The hits for each L. pneumophila spacer from metagenomic sequences.

Table S3: The hits for each L. pneumophila spacer in complete and/or draft genomes.

Table S4: The accession numbers and Microviridae subfamily classifications for the major 
capsid phylogeny tree. 

Table S5: The mobile elements predicted by both PhiSpy and VirSorter.

Table S6: Orthologous groups for LME-1 and their predicted function by BLASTp against the viral database (taxid:10239) and by HHpred against the Uniprot SwissProt viral database (Uniprot-SwissProt-versio-70_23_aug_2020) with a probability cutoff of &gt;70%.

Table S7: List of CRISPR-Cas spacers from all examined L. pneumophila isolates.
description: This data was also published as a peer review publication prior to its inclusion in my thesis. The citation for this publication is as follows:

Deecker S.R., Urbanus M.L., Nicholson B. and Ensminger A.W. Legionella pneumophila CRISPR-Cas Suggests Recurrent Encounters with One or More Phages in the Family Microviridae. Appl Environ Microbiol. 2021 Aug 11;87(17):e0046721. doi: 10.1128/AEM.00467-21.
DOI: 10.5683/sp3/cfvpho
title: The Entrepreneurs: Dairy farmer perspectives on finding an industry solution for the surplus calf issue – a participatory case study

description: The main objective of this case study was to pilot a novel methodology to deepen our understanding of how dairy producers envision the future of surplus calves in Atlantic Canada, including identifying who they felt were important to speak to as they discussed this topic. A second objective was to understand the perspectives of a key group the producers requested to speak to, representing a variety of dairy industry partners, including veterinarians, genetics companies and animal welfare scientists amongst others (referred to as the allied industry) on the future of surplus calves. To reach these objectives, we used an inclusive participatory approach that, to our knowledge, has not yet been applied to the surplus calf issue. This approach included a series of five participatory group discussions with volunteer dairy farmers from Atlantic Canada; the allied industry group was invited to two group discussions. Key themes from the discussions included: 1) challenges with surplus calf production on the dairy farm, such as a lack of knowledge about what type of calf would be desired by the marketplace, 2) the role of leadership and partnership in the creation of a dairy beef system, including the need to overcome communication barriers between different stakeholders, 3) post-farm gate aspects of surplus calf production, including the desire to cater to a local market, and 4) ensuring that the proposed system is economically and socially sustainable.
DOI: 10.5683/sp3/oe3sat
title: Reproducible archive for article Genest-Grégoire, A., Godbout, L., & Guay, J.-H. (2022). Lists: A Novel Experimental Method to Measure Tax Evasion. National Tax Journal, 75(3), 517–537. https://doi.org/10.1086/719469

description: Code, data and documentation to reproduce results presented in Genest-Grégoire, A., Godbout, L., & Guay, J.-H. (2022). Lists: A Novel Experimental Method to Measure Tax Evasion. National Tax Journal, 75(3), 517–537. https://doi.org/10.1086/719469
DOI: 10.5683/sp3/6pbahk
title: Replication Data for: Exceptional Wildfire Enhancements of PAN, C2H4, CH3OH, and HCOOH Over the Canadian High Arctic During August 2017

description: This dataset contains the measurements used in 'Exceptional Wildfire Enhancements of PAN, C2H4, CH3OH, and HCOOH Over the Canadian High Arctic During August 2017' by Wizenberg et al. (2023). It includes: (1) the 2006-2020 data for CO, PAN, C2H4, CH3OH and HCOOH retrieved from mid-IR spectra from the Bruker IFS 125HR FTIR located at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut (80.05°N, 86.42°W), (2) the limited IASI dataset at the original sampling in the vicinity of Eureka for the same species, (3) the IASI data re-gridded to the 2°x2.5° GEOS-Chem model grid, and (4) the GFAS files with modified mean altitude of maximum injection (mami) values used to investigate the influence of injection height on the simulated wildfire plume transport.
DOI: 10.5683/sp3/lod4e3
title: P-TarPMir: A Web server for accurate plant-specific miRNA target prediction

description: microRNAs (miRNAs) are small non-coding ribonucleic acids that post-transcriptionally regulate gene expression through the targeting of messenger RNA (mRNAs). Most miRNA target predictors have focused on animal species and prediction performance drops substantially when applied to plant species. Several rule-based miRNA target predictors have been developed in plant species, but they often fail to discover new miRNA targets with non-canonical miRNA-mRNA binding. Here, the recently published TarDB database of plant miRNA-mRNA data is leveraged to retrain the TarPMir miRNA target predictor for application on plant species. Rigorous experiment design across four plant test species demonstrates that animal-trained predictors fail to sustain performance on plant species, and that the use of plant-specific training data improves accuracy depending on the quantity of plant training data used. Surprisingly, our results indicate that the complete exclusion of animal training data leads to the most accurate plant-specific miRNA target predictor indicating that animal-based data may detract from miRNA target prediction in plants. Our final plant-specific miRNA prediction method, dubbed P-TarPMir, is freely available for use at ptarpmir.cu-bic.ca. The final P-TarPMir method is used to predict targets for all miRNA within the soybean genome. Those ranked predictions, together with GO term enrichment, are available here.
DOI: 10.5683/sp3/pd11yo
title: Having time to oneself in times of extended togetherness: Solitude experiences during the COVID‐19 pandemic

description: The dataset, R code and study materials were used for all analyses reported in: Choi, Y., Pauly, T., Zambrano Garza, E., Broen, T., Gerstorf, T., & Hoppmann, C. A. (2022). Having time to oneself in times of extended togetherness: Solitude experiences during the COVID‐ 19 pandemic
DOI: 10.5683/sp3/6gqpml
title: Extending Aerial Surveys with Landsat-based Canopy Cover: A Case Study in Montreal

description: GIS files created to allow for the comparison between aerial and satellite urban canopy data in Montreal
DOI: 10.5683/sp3/qc057t
title: PREVENT VCI Study: ASL Baseline Data

description: Excel File containing the baseline ASL data from the PREVENT VCI Study, used to provide public access to the data in an upcoming publication.
DOI: 10.5683/sp3/bdfe7s
title: The State of Social Media in Canada 2022

description: The report provides a snapshot of the social media usage trends amongst online Canadian adults based on an online survey of 1500 participants. Canada continues to be one of the most connected countries in the world. An overwhelming majority of online Canadian adults (94%) have an account on at least one social media platform. However, the 2022 survey results show that the COVID-19 pandemic has ushered in some changes in how and where Canadians are spending their time on social media. Dominant platforms such as Facebook, messaging apps and YouTube are still on top but are losing ground to newer platforms such as TikTok and more niche platforms such as Reddit and Twitch.
DOI: 10.5683/sp3/lkmeoo
title: Search Strategy replication data for "The national and global impact of systemic and structural violence on the effective prevention, treatment and management of COVID-19 in the African/Black population: Protocol for a Scoping Review"

description: The files in this dataset contains the full MEDLINE (Ovid), Embase (Ovid), CAB Abstracts (Ovid), PsychInfo (Ovid), CINAHL (EBSCO), Cochrane Library, Scopus, Web of Science, and Global Index Medicus search strategies for Covid-19, African/Black individuals and communities, and racism. Original search date: (2021-08)
DOI: 10.5683/sp3/6bprbl
title: Replication Code for: Optimal income taxation with tax avoidance and endogenous labor supply

description: The programs replicate tables and figures from "Optimal income taxation with tax avoidance and endogenous labor supply", by Casamatta. Please see the ReadMe file for additional details.
DOI: 10.5683/sp3/fvgdy6
title: Cross-sector comparison of methane emissions from anthropogenic sources: A case study in Canada

description: Methane emission estimates for the oil and gas industry, farms and a landfill in Grande Prairie, Alberta, Canada, from mobile measurements.
DOI: 10.5683/sp3/x2mjxv
title: ACE-FTS 2022 study of 2019 Raikoke eruption: JGR figure data

description: This data set contains measured and fitted sulfate aerosol spectra from figures in a 2022 Journal of Geophysical Research article regarding a study of the 2019 Raikoke volcanic eruption using the Atmospheric Chemistry Experiment satellite mission.
description: To view the figures associated with these data, see the article (when published).
DOI: 10.5683/sp3/8mvu6l
title: Pan-Canadian Survey on the Impact of the COVID-19 Pandemic on Cervical Cancer Screening and Management

description: This dataset contains the survey instrument, data, data dictionary and code for the Pan-Canadian Survey on the Impact of the COVID-19 Pandemic on Cervical Cancer Screening and Management
DOI: 10.5683/sp3/viwcau
title: Data for the paper entitled "Fluoride removal from drinking water (Metlaoui, Tunisia) using untreated and treated natural clays".

description: This data set includes X-ray diffraction results for clays tested with and without treatments, and the removal efficiencies as a function of clay dosage, contact time and agitation speed.
DOI: 10.5683/sp3/mhhokh
title: Old Mill Smiths Falls

description: This is a dataset of information compiled for Courses CIVE3207 (ARCN4100), CIVE4601 (ARCN4200), or any other for students of the Architectural Conservation and Sustainability Program (Engineers and architects) at Carleton University. This material can not be used for commercial purposes or use in any form without the permission of Dr. Mario Santana, the authors, and site custodians.
DOI: 10.5683/sp3/pneni2
title: Données et code de réplication pour: Le rôle des universités et la mobilité sociale intergénérationnelle au Québec

description: Code de reproduction pour le mémoire de maîtrise « Le rôle des universités et la mobilité sociale intergénérationnelle au Québec ». Voir le fichier ReadMe pour plus de détails.
DOI: 10.5683/sp3/nzu9lj
title: Python Script for calculating energy loss for different household behaviours in IWS systems

description: The files for calculating energy loss versus supply continuity under three household assumptions. The Cautious and Patient Household can be implemented by the same Python file. The Hasty Household would require running the corresponding Python file