Our primary training objective is to provide foundational and interdisciplinary training that promotes a more data-literate Canada, and better prepare citizens to participate meaningfully in our rapidly changing world.

About our training

Through our members’ teaching and training experience, we offer training in introductory and advanced data literacy, research data management, advanced statistical methods, web scraping, basic programming, and data visualization. Each of these training courses can be tailored to target students, faculty members, professionals, and others.

Our members’ expertise also positions the Institute to offer fee-based consulting services for data analysis, research design, data communication, knowledge mobilization, and data management. Consulting services will be available to help researchers in all stages of their projects.

Through our different projects and initiatives, we aim to create:

  • for-credit courses on data literacy to improve student data literacy skills;
  • Develop data literacy professional development training for professionals in industry and public service;
  • Provide workshops, seminars, and consulting services to support researchers (and their students) in addressing their data-related research needs (e.g., data management and advanced analyses).

Contact us to discover how we can help you.

Current Education Projects and Initiatives

Interdisciplinary Working Group on Statistics Education

Formed via interdisciplinary discussions among Data Literacy Research Institute members in June 2025, this group aims to rethink quantitative methods curricula across academic fields. By uniting teaching professors, pedagogical experts, and methodologists from five different faculties, the group develops innovative and accessible teaching frameworks designed to combat student math anxiety.

  • To support this mission, the group spawned initiatives such as the New Directions in Data and Statistics Education Conference, a one-day event co-presented by the DLRI and the Provost's Office on February 19, 2026, which brought together roughly 60 participants (including pedagogical experts, methodologists, and administrative leaders) featuring a keynote by Dr. Alison Gibbs, active-learning workshops, and operational roles for undergraduate students. The working group plans to have another conference in February 2027.

  • The working group also drives pedagogical resources like the Murder Mystery project, an interdisciplinary learning resource designed to increase student engagement in introductory data analysis courses through a 10-episode audiobook and classroom series where students listen to episodes and analyze datasets in class to solve a suspicious campus death while learning core concepts like distributions and hypothesis testing.

Data Literacy and Analytical Reporting Workshops

A professional training series conducted between August 2025 and June 2026 for the Office of the Provost, Finance and Administration, Financial Resources, and Human Resources. Encompassing 50 participants across three workshops, the program scaled practical data training directly into the university's operational and everyday institutional reporting infrastructure.

Applied Workshop Series

Rooted in a two-year collaboration with uOttawa Career Development and Experiential Learning (CDEL) focused on equipping students with workforce-ready competencies, this applied extracurricular workshop series has delivered eight hands-on workshops introducing students to the R programming language and foundational data interpretation strategies while building a scalable blueprint for future experiential learning expansion. Broadening these efforts, the program delivers accessible, hands-on training sessions led by qualified instructors to help students quickly build in-demand technical skills, featuring specialized offerings such as the Exploring the Power of Data workshop, which teaches basic statistics and visualization using StatsCloud, and the Unlock Data with R workshop, a 12-hour session introducing students with no prior programming background to R interface basics, data cleaning, and ggplot2 visualizations.