DRI Learning Resources

  • Compute Ontario provides funding to the DRI community for the development of open-access learning resources to support researchers in using DRI tools effectively. Self-guided training modules, reference materials, templates and tools are available on a range of topics from how to access and use national DRI systems to principles and tools for research data management to machine learning skills and methods.

ADVANCED RESEARCH COMPUTING, AI and ML

Introduction to advanced research computing using Digital Research Alliance of Canada resources, Carleton University

Instructional book in English, Covering:

  • Digital Research Alliance of Canada Resource Overview

  • Introduction to the Unix Shell

  • Parallel and Distributed Computing

  • General Purpose Computing Using a GP

Introduction to SciNet and Trillium, SciNet

Self-guided Moodle course in English for new Niagara/SciNet users

Introduction to GIT Version Control, SciNet

Self-guided Moodle course in English.

  • Includes a general introduction to version control

Introduction to AI and ML, with RDM integration, University of Ottawa

Eight structured, self-guided modules in French and English, each including a Jupyter Notebook, datasets and additional curated resources:

  • Data cleaning and linear regression

  • Decision trees and random forests

  • Naive Bayes

  • Support vector machines

  • K-nearest neighbours

  • Natural language processing

  • Transfer learning and introduction to convolutional neural networks

  • Dataset analysis, model shortlisting and model determination

Introduction to advanced research computing in fluid dynamics, University of Waterloo

A 16-hour online, asynchronous course in English to help learners with a basic understanding of fluid dynamics and CFD bridge the knowledge gap towards the effective utilization of CFD on modern ARC resources.

RESEARCH DATA MANAGEMENT

Good data handling practices for researchers, University of Ottawa Heart Institute and Ottawa Hospital Research Institute

Self-guided courses, templates and other resources in English (some also in French) related to:

  • Ethics and harmonized consent language

  • Data management planning

  • Data handling

Research Data Management (RDM) knowledge, skills, tools and best practices, Canadian Bioinformatics Workshops, Ontario Institute for Cancer Research, McGill University, Pan-Canadian Genome Library

Coming soon.

  •  7 self-guided modules, available in French and English:

  • Introduction

  • Principles for Research Data Management

  • Big Data, Ontologies and Knowledge Graphs

  • Towards Implementation: Schemas and Validation

  • Health Data Models

  • Data Discovery with Public Databases and Ontologies

  • Conclusion

Research data management in the college and small institution context, Heads of Applied Research and the Ontario Colleges RDM Community of Practice

Six self-guided modules in French or English:

  • Data Management Planning in the College Context 

  • Data Deposit from a College Perspective

  • Data Curation

  • Data Sharing and Data Governance

  • Data Deposits and Repositories

  • Industry Data and Research Partnerships

Selecting the right data repository, Toronto Metropolitan University

Two learning resources in English:

Data-sharing best practices health care/medicine, University of Toronto and McMaster University

Three self-guided modules in English:

  • Big Data and Data Sharing: A Canadian Perspective on Risks, Benefits, and Principles

  • Big Data: Promise or Peril for Learners, Communities, and Privacy

  • Better Data > Big Data

RDM and text data mining in JupyterHub, University of Windsor

Supporting materials from a 2023 workshop series:

  • Introduction to Jupyterub (PowerPoint and code)

  • Text Data Mining of Newspapers in JupyterHub  (video)

  • RDM in Jupyter: The Importance of Keeping your Data Reproducible 

RESEARCH SOFTWARE

Stewarding research software from proposal to deposit and publication, McMaster University

A guide in English, covering:

  • Understanding FAIR principles

  • Developing a software management plan

  • Choosing technical/coding strategies to enhance reproducibility

  • Building a computing site using Minima

Applying technologies such as computational notebooks and open application programming interfaces to facilitate and support open research, McMaster University

A guide in English, covvering:

  • A primer on computational notebooks (CNs) for the new or novice user

  • How to use computational notebooks (CNs) to access the OpenAlex AP (a free database of scholarly works, authors, and institutions) and read/transform/export the data