cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5683/sp3/6aguaw
title: Convolutional Neural Network Battery SOH Estimation Example Code

description: The provided code files are utilized to construct a convolutional neural network (CNN)-based state of health (SOH) estimator using data from Samsung 30T cylindrical 21700 cells. These files encompass essential functions: 1) Preprocessing of original data, including normalization and data splitting, 2) Training the CNN-based SOH estimator, and 3) Evaluating performance and generating result plots for the CNN-based SOH estimator. The comprehensive functionality of these files, as well as detailed discussion of results, are extensively covered in the IEEE Xplore publication titled "A Convolutional Neural Network for Estimation of Lithium-Ion Battery State-of-Health during Constant Current Operation," and supplemented by the accompanying user guide "CNN based SOH estimation code - Users Guide.pdf".

The battery aging data used is also open source:
“Fifteen minute fast charge aging dataset - Samsung 30T cells”, Borealis Data, 2023. https://doi.org/10.5683/SP3/UYPYDJ
DOI: 10.5683/sp3/drzba6
title: Census of Population, 2021 [Canada]: Data Tables, Type of Dwelling [B2020 & CSV]

description: The Data Tables are a series of cross-tabulations presents a portrait of Canada based on the various census topics. They range in complexity and are available for various levels of geography. The topic of this dataset is Type of Dwelling.
description: Census of Population
DOI: 10.5683/sp3/uypydj
title: Battery Aging Dataset for 15 Minute Fast Charging of Samsung 30T Cells

description: This aging dataset was designed to be used for training/parameterization and testing of machine learning and conventional filter based state of charge and state of health estimation models. A number of characterization tests (HPPC, C/20 charge discharge, etc) are applied to each cell and are followed by repeating series of drive cycle discharges and a fifteen minute fast charge. 

The characterization and drive cycle tests are repeated until the battery cells reach 70% SOH (around 1500 to 2000 cycles). The rate of aging for each cell is different because each cell is fast charged using a different method (standard CC/CV - same profile on two cells, boost charge - higher current at low SOC, and three pulsed charge methods). The six cells tested are brand new 3Ah Samsung INR21700-30T lithium ion battery cells. The testing was performed in a thermal chamber at 25 degrees Celsius using an Arbin battery cycler.
DOI: 10.5683/sp3/c541on
title: Replication Data and Code for: An experimental investigation of persuasion through selective disclosure of evidence

description: The data and programs replicate tables and figures from "An experimental investigation of persuasion through selective disclosure of evidence", by Degan, Li, and Xie. Please see the ReadMe file for additional details.
DOI: 10.5683/sp3/otadbz
title: Replication Data for "A longer wood growing season does not lead to higher carbon sequestration"

description: Wood phenology and anatomy for 27 balsam firs [Abies balsamea (L.) Mill.]. Wood microcores collected weekly from April to October 2018 in Quebec (Canada).
DOI: 10.5683/sp3/vbvcrh
title: Données et code de réplication pour : Inégalités de réussite, que nous disent les données PISA 2000 à 2018.

description: Code de reproduction pour le mémoire de maîtrise « Inégalités de réussite, que nous disent les données PISA 2000 à 2018 ». Voir le fichier ReadMe pour plus de détails.
DOI: 10.5683/sp3/mnap00
title: Replication data for "Post-conflict movements of polar bears in western Hudson Bay, Canada"

description: Replication data for "Post-conflict movements of polar bears in western Hudson Bay, Canada" published in Arctic Science.
description: In press.
DOI: 10.5683/sp3/opqzwq
title: Machine Learning for Descriptive Epidemiology

description: The dataset is an imputed, de-identified cross-sectional data of LGBTQI2S+ young adults who was living in Ontario and Quebec in Canada during the pandemic and responded to a range of questions regarding their mental health and substance use status and related factors. This data is used as an illustrative example on how to use machine learning for descriptive epidemiology. Codes can be found on the project github page
DOI: 10.5683/sp3/sxsypd
title: Lessons from 20 years of medical cannabis use in Canada
title: Health Canada administrative data and Licensed Producer catalog data 2006 to 2022

description: These are the source data used to create Figures 2 - 7 of the forthcoming publication: Shim MS, Nguyen HV, Grootendorst P. Lessons from 20 years of medical cannabis use in Canada. PLOS One, forthcoming. Figures 8 and 9 of the paper rely on public use versions of the Statistics Canada and Health Canada survey data which were obtained from ODESI. Licensing restrictions prevent reposting the source data.
DOI: 10.5683/sp3/uticpy
title: Characteristics of Natural Organic Matter in Forested Canadian Water Sources by LC-OCD

description: This dataset consists of a subset of liquid chromatography-organic carbon detector (LC-OCD) and pH data collected as part of a forWater NSERC Strategic Network project. LC-OCD is a size exclusion chromatography/dissolved organic carbon detection technique employed for characterizing the fractional composition of carbon in water samples. Natural water samples were collected from streams in six different forested watersheds across Canada from April 2019 to September 2022 by collaborating researchers. Sample analysis was conducted by the WaterSTP Group in the Department of Civil and Environmental Engineering at the University of Waterloo. Data from select samples collected from July 2019 to June 2021 are included in this dataset.
DOI: 10.5683/sp3/rhi4pl
title: Supplementary material for: A randomized controlled trial investigating the effect of transport duration and age at transport on surplus dairy calves: Part I. Impact on health and growth

description: The primary objective of this study was to investigate the effects of transport duration on diarrhea, respiratory disease, and growth in young surplus dairy calves following 6, 12, and 16 h of continuous road transport from source dairy farms to a single commercial veal facility. The secondary objective was to explore how variables such as breed, sex, transfer of passive immunity status, weight before transport, and age at transport influence calf health following transport. This dataset contains supplementary material for the following publication: H. M. Goetz, K. C. Creutzinger, D. F. Kelton, J. H. C. Costa, C. B. Winder, and D. L. Renaud. 2023. A randomized controlled trial investigating the effect of transport duration and age at transport on surplus dairy calves: Part I. Impact on health and growth. Journal of Dairy Science. 106(4): 2784-2799. https://doi.org/10.3168/jds.2022-22366.
DOI: 10.5683/sp3/bnnae7
title: Open Data Training Workshop: Case Studies in Open Data for Qualitative and Quantitative Clinical Research

description: &lt;strong&gt;Objective(s):&lt;/strong&gt; Momentum for open access to research is growing. Funding agencies and publishers are increasingly requiring researchers make their data and research outputs open and publicly available. However, clinical researchers struggle to find real-world examples of Open Data sharing. &lt;br /&gt;

&lt;br /&gt;The aim of this 1 hr virtual workshop is to provide real-world examples of Open Data sharing for both qualitative and quantitative data. &lt;br /&gt;

&lt;br /&gt;Specifically, participants will learn:&lt;br /&gt;
1. Primary challenges and successes when sharing quantitative and qualitative clinical research data. &lt;br /&gt;

&lt;br /&gt;2. Platforms available for open data sharing.&lt;br /&gt;

&lt;br /&gt;3. Ways to troubleshoot data sharing and publish from open data.&lt;br /&gt;

&lt;br /&gt;Workshop Agenda:&lt;br /&gt;

&lt;br /&gt;1. “Data sharing during the COVID-19 pandemic” - Speaker: Srinivas Murthy, Clinical Associate Professor, Department of Pediatrics, Faculty of Medicine, University of British Columbia. Investigator, BC Children's Hospital &lt;br /&gt;

&lt;br /&gt;2. “Our experience with Open Data for the 'Integrating a neonatal healthcare package for Malawi' project.” - Speaker: Maggie Woo Kinshella, Global Health Research Coordinator, Department of Obstetrics and Gynaecology, BC Children’s and Women’s Hospital and University of British Columbia &lt;br /&gt;

&lt;br /&gt;This workshop draws on work supported by the Digital Research Alliance of Canada.&lt;br /&gt;

&lt;br /&gt;&lt;strong&gt;Data Description:&lt;/strong&gt; Presentation slides, Workshop Video, and Workshop Communication&lt;br /&gt;
&lt;br /&gt;Srinivas Murthy: Data sharing during the COVID-19 pandemic presentation and accompanying PowerPoint slides.&lt;br /&gt;
&lt;br /&gt;Maggie Woo Kinshella: Our experience with Open Data for the 'Integrating a neonatal healthcare package for Malawi' project presentation and accompanying Powerpoint slides.&lt;br /&gt;

&lt;br /&gt;This workshop was developed as part of Dr. Ansermino's Data Champions Pilot Project supported by the &lt;a href = "https://alliancecan.ca/en"&gt;Digital Research Alliance of Canada&lt;/a&gt;.&lt;br /&gt;
description: &lt;br /&gt;&lt;strong&gt;NOTE for restricted files:&lt;/strong&gt; If you are not yet a CoLab member, please complete our &lt;a href = "https://rc.bcchr.ca/redcap/surveys/?s=EDCYL7AC79"&gt;membership application survey&lt;/a&gt; to gain access to restricted files within 2 business days.
&lt;br /&gt;Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator on &lt;a href = "https://www.bcchr.ca/pediatric-sepsis-data-colab"&gt;this page&lt;/a&gt; under "collaborate with the pediatric sepsis colab."
DOI: 10.5683/sp3/7xyzvc
title: Open Data Training Video: A proposed data de-identification framework for clinical research

description: &lt;strong&gt;Objective(s):&lt;/strong&gt; Data sharing has enormous potential to accelerate and improve the accuracy of research, strengthen collaborations, and restore trust in the clinical research enterprise. Nevertheless, there remains reluctancy to openly share raw data sets, in part due to concerns regarding research participant confidentiality and privacy. We provide an instructional video to describe a standardized de-identification framework that can be adapted and refined based on specific context and risks.&lt;br /&gt;

&lt;br /&gt;&lt;strong&gt;Data Description:&lt;/strong&gt; Training video, presentation slides.&lt;br /&gt;

&lt;br /&gt;&lt;strong&gt;Related Resources:&lt;/strong&gt; The data de-identification algorithm, dataset, and data dictionary that correspond with this training video are available through the &lt;a href = "https://borealisdata.ca/dataset.xhtml?persistentId=doi:10.5683/SP3/MSTH98 "&gt;Smart Triage sub-Dataverse.&lt;/a&gt;
description: &lt;br /&gt;&lt;strong&gt;NOTE for restricted files:&lt;/strong&gt; If you are not yet a CoLab member, please complete our &lt;a href = "https://rc.bcchr.ca/redcap/surveys/?s=EDCYL7AC79"&gt;membership application survey&lt;/a&gt; to gain access to restricted files within 2 business days.
&lt;br /&gt;Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator on &lt;a href = "https://www.bcchr.ca/pediatric-sepsis-data-colab"&gt;this page&lt;/a&gt; under "collaborate with the pediatric sepsis colab."
DOI: 10.5683/sp3/ivskz6
title: Open Data Training Workshop: Synthetic Data & The 2023 Pediatric Sepsis Data Challenge

description: &lt;strong&gt;Objective(s):&lt;/strong&gt; Momentum for open access to research is growing. Funding agencies and publishers are increasingly requiring researchers make their data and research outputs open and publicly available. However, this introduces many challenges, especially when managing confidential clinical data.&lt;br /&gt;

&lt;br /&gt;The aim of this 1 hr virtual workshop is to provide participants with knowledge about what synthetic data is, methods to create synthetic data, and the 2023 Pediatric Sepsis Data Challenge.&lt;br /&gt;

&lt;br /&gt;Workshop Agenda:&lt;br /&gt;

&lt;br /&gt;1. Introduction - Speaker: Mark Ansermino, Director, Centre for International Child Health &lt;br /&gt;

&lt;br /&gt;2. "Leveraging Synthetic Data for an International Data Challenge" - Speaker: Charly Huxford, Research Assistant, Centre for International Child Health &lt;br /&gt;

&lt;br /&gt;3. "Methods in Synthetic Data Generation." - Speaker: Vuong Nguyen, Biostatistician, Centre for International Child Health and The HIPpy Lab &lt;br /&gt;

&lt;br /&gt;This workshop draws on work supported by the Digital Research Alliance of Canada.&lt;br /&gt;

&lt;br /&gt;&lt;strong&gt;Data Description:&lt;/strong&gt; Presentation slides, Workshop Video, and Workshop Communication&lt;br /&gt;
&lt;br /&gt;Charly Huxford: Leveraging Synthetic Data for an International Data Challenge presentation and accompanying PowerPoint slides.&lt;br /&gt;
&lt;br /&gt;Vuong Nguyen: Methods in Synthetic Data Generation presentation and accompanying Powerpoint slides.&lt;br /&gt;

&lt;br /&gt;This workshop was developed as part of Dr. Ansermino's Data Champions Pilot Project supported by the &lt;a href = "https://alliancecan.ca/en"&gt;Digital Research Alliance of Canada&lt;/a&gt;.&lt;br /&gt;
description: &lt;br /&gt;&lt;strong&gt;NOTE for restricted files:&lt;/strong&gt; If you are not yet a CoLab member, please complete our &lt;a href = "https://rc.bcchr.ca/redcap/surveys/?s=EDCYL7AC79"&gt;membership application survey&lt;/a&gt; to gain access to restricted files within 2 business days.
&lt;br /&gt;Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator on &lt;a href = "https://www.bcchr.ca/pediatric-sepsis-data-colab"&gt;this page&lt;/a&gt; under "collaborate with the pediatric sepsis colab."
DOI: 10.5683/sp3/5iedao
title: Replication Data for: Synthetic Indoor Ecosystem

description: The proof of concept project tested whether it is possible to construct a stable and productive modular synthetic ecosystem for indoor or limited outdoor spaces. The design relied on four modules: green waste digester, algal culture, zooplankton culture, and fish. We measured several biotic and abiotic variables to assess the stability and productivity of the components. We include the following temporal series data: Chlorophyll a, Daphnia population, dissolved oxygen, duckweed density, ecosystem productivity, pH, and vegetable waste additions.
description: MS Excel, 365
DOI: 10.5683/sp3/uevzed
title: Disability and Deafhood Database
title: Base de données sur le handicap et la sourditude

description: &lt;p&gt;This database, open source and free of charge, identifies and collects French and English Canadian sources of iconic productions (comic books, graphic novels) and audiovisual productions (documentary and fiction films and fictional television series) featuring at least one character with a disability.&lt;/p&gt;

 &lt;p&gt;Through the development of an analytical sheet for each media production, for each member of the production (creation; illustration/drawing; direction; scripting) and for each character, it is possible to determine the characteristics of the (self)representations and the themes addressed (e.g., the type of role of the characters: main, secondary, tertiary; disabling situations encountered; whether they are subjected to ableism, intimidation or abuse, etc.).&lt;/p&gt;

&lt;p&gt;As of March 15, 2023, 137 entries media productions from a corpus of 215 have been analyzed.&lt;/p&gt;

&lt;p&gt;The analysis grids used to characterize each media production can be found in the "Questionnaires" folder. Video clips explaining how to query the database are available in the "Tutorials" folder.&lt;/p&gt;
description: Acknowledgment
<b>Research assistance</b> : Amélie Barrette, Emmanuel Bernier, Jason Burnham, Danick-André Dubuc, Guillaume Massie-Hamel, Judith McMurray, Matthieu Meignan, Yoann Thomas, Jérôme Vaillancourt
<b>Implementation of the database structure</b> / Bureau des initiatives numériques (BIN) : Pierre Léveillé, Philippe Nazair, Louis Renaud-Desjardins
<b>Coordination</b> : Rachel Brousseau
DOI: 10.5683/sp3/vqaric
title: Replication Data and Code for: Mandatory Minimum Sentencing and its Effect on Sentencing Distributions: Evidence from Canada

description: The data and programs replicate tables and figures from "Mandatory Minimum Sentencing and its Effect on Sentencing Distributions: Evidence from Canada", by Penney, Lehrer, and Galan. Please see the ReadMe file for additional details.
DOI: 10.5683/sp3/iajbvw
title: Replication Data for: Measurements of perfluoro-n-hexane and perfluoro-2-methylpentane infrared absorption cross-sections from 298 to 350 K

description: This dataset includes the infrared absorption cross-section measurements used in 'Measurements of perfluoro-n-hexane and perfluoro-2-methylpentane absorption cross-sections from 298 to 350 K' by Ishtiak et al. (2023b). The dataset includes (1) the absorption cross-sections for perfluoro-n-hexane [n-C6F14], labeled as nPFC6. (2) the absorption cross-sections for perfluoro-2-methylpentane [i-C6F14], labeled as iPFC6. Nine absorption cross-sections are provided for each compound, labeled by the sample temperature from 298 to 350 K. All measurements were made using an ABB Bomem DA8 Fourier Transform InfraRed (FTIR) spectrometer. The original cross-section files have an uncertainty at 3 standard deviations, while the updated files (tagged V2) have an uncertainty at 2 standard deviations (consistent with the description in the published paper).
DOI: 10.5683/sp3/ceuqoz
title: Integrated approaches to management of wireworm and Colorado potato beetle in field tomatoes

description: &lt;p&gt;The project "Integrated approaches to management of wireworm and Colorado potato beetle in field tomatoes" consisted of three experiments including:&lt;/p&gt;
&lt;p&gt;&lt;li&gt;&lt;b&gt;TO22T1: Insecticide-herbicide tank mixes on weed control&lt;/b&gt; - Determine the impact of tank-mixing common herbicides and foliar insecticides for CPB on product efficacy and crop injury.&lt;/li&gt;&lt;/p&gt;
&lt;p&gt;&lt;li&gt;&lt;b&gt;22-TOM-CPB-F1: Insecticide-herbicide tank mixes on Colorado potato beetle control&lt;/b&gt; - Determine the impact of tank-mixing common herbicides and foliar insecticides use for CPB on product efficacy and crop injury.&lt;/li&gt;&lt;/p&gt;
&lt;p&gt;&lt;li&gt;&lt;b&gt;22-TOM-WW-G1: Random plant stand loss, cultivar, and planting density on tomato yield&lt;/b&gt; - Evaluate the potential for processing tomato planting density as a cultural control tool to mitigate yield loss. This work will also serve to determine the level of uneven plant stand loss required to incur yield losses in processing tomatoes.&lt;/li&gt;&lt;/p&gt;
DOI: 10.5683/sp3/6b1vxm
title: Turner Valley Gas Plant -- Town of Turner Valley -- Laser Scanning -- 2020

description: This dataset contains the three-hundred-and-eleven (311) scans of Turner Valley Gas Plant, National Historic Site. The data was collected by MiraCAD between May and October, 2020, with the Leica Scan Station P40 laser scanner. All data was registered and processed through Leica Cyclone v.2020 and saved in LAS format in CloudCompare v.2.9.1. The dataset covers the exterior and interior of multiple buildings that form part the Turner Valley Gas Plant.
description: Lecia Cyclone, 2020
description: CloudCompare, 2.9.1
description: Published under the Creatives Common License CC BY-NC 4.0.
DOI: 10.5683/sp3/fjcgcg
title: CIMP187: Shrub Stem Data, 2018-2019

description: This data provides characteristics of shrub stems measured and sampled in 2018 and 2019 as part of a project aimed at characterizing the nature of woody plant dynamics across the treeline ecotone in central Northwest Territories, Canada. Two types of sites were targeted for sampling: "Greening" sites, where satellite remote sensing detected a significant increase in maximum productivity since year 2000, and "No Change" sites where no change had been detected. A total of 29 sites (15 'Greening' and 14 'No Change') were sampled. Four 100 metre transects were established at each site. Each transect was comprised of 11 sampling points separated by 10 metres yielding 44 sampling points per site. Measurements associated with each stem contained in the database include species, size (diameter and length), year of establishment, and vertical growth rate. Details on sample collection and processing used in the generation of the data are described in the associated publication. The data were collected as part of Project #187 (Changes in Vegetation Productivity and Phenology Across the Bathurst Caribou Range) of the Government of the Northwest Territories Department of Environment and Natural Resources Cumulative Impact Monitoring Program.
description: CIMP187
DOI: 10.5683/sp3/bgvieu
title: GrantED

description: GRANTED Model Test
DOI: 10.5683/sp3/yfxhwd
title: Census of Population, 2016 [Canada]: Aboriginal Population Profile [B2020]

description: This dataset is on the Aboriginal Population Profile from the 2016 Census. Data are provided at various levels of geography.
description: Census of Population
DOI: 10.5683/sp3/7fr88o
title: Census of Population, 2016 [Canada]: COVID-19 Supplement [CSV & B2020]

description: Statistics Canada, in collaboration with the Public Health Agency of Canada and Natural Resources Canada, is presenting selected 2016 Census data to help inform Canadians on the public health risk of the COVID-19 pandemic and to be used for modelling analysis. Data are provided for selected data indicators at various levels of geography.
description: Census of Population
DOI: 10.5683/sp3/cofxya
title: Broadening your Perspective in Assessing Team Activities

description: A look at perspectives, as in Point-of-View, for assessing team-based learning activities. 
Standard observation techniques miss much of the density of interaction.
Findings from multiple projects, including HSVO, Hockey Lines,
DOI: 10.15468/dl.w46me5
title: Occurrence Download

description: A dataset containing 328 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Pinus densata",
 "Year 1970-2025"
 ]
}

 The dataset includes 328 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046679-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5683/sp3/jhrlyy
title: Replication Data for: Fearfulness in commercial laying hens: A meta-analysis comparing brown and white egg layers

description: This meta-analysis aimed to evaluate differences in brown versus white laying hens’ TI and NO test results (as two unique metrics of fearfulness) to assess systematic genetic effects.
DOI: 10.5683/sp3/wxd64r
title: Team-Based Learning and OLab

description: 1. All team-based marking schemes look at the whole team
2. None assess team member contributions
3. Global rating encourages the Cheerleading Coasters
4. Known problem with all forms of groupwork
OLab contains a number of functions to address all of these problems.
DOI: 10.5683/sp3/vd9hxt
title: Spelling Robotics Manipulation Dataset for "See, Plan, Predict: Language-guided Cognitive Planning with Video Prediction"

description: The spelling simulation dataset for the paper "See, Plan, Predict: Language-guided Cognitive Planning with Video Prediction".
DOI: 10.5683/sp3/8fngtj
title: Golf Player Technology Usage

description: Three-hundred and thirteen golfers fully completed an online survey. This data was collected through the online survey software Opinio, where all responses were anonymous. For more information, please see related article: https://doi.org/10.1177/17479541221148719.