
Under the Patronage of the Canadian Commission for UNESCO
WHY PARTICIPATE?
SCHEDULE
E-LEARNING MODULES
AWARDS
FAQ

We call upon all students and teachers to use computational thinking skills, combined with math, science, geography and climate change knowledge to find solutions for the UN Sustainable Development Goal 11 – “Make cities and human settlements inclusive, safe, resilient and sustainable”
As Canada and the World find its way out of the COVID pandemic and new ways for sustainable development, the need for fair and equitable housing has become increasingly apparent. The Canada Mortgage and Housing Corp. projects the nation will need an additional 5 million housing units by 2030 to accommodate a growing population. Average Canadian house prices soared to $816,720 in March 2022, representing a 20% increase in a single year.
Fair housing is far reaching, covering many subtopics including (but not limited to):
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- Determining the role of co-living and co-working arrangements in the future of housing
- Increasing survivability of housing structures in the uptick in natural disasters as a result of climate change;
- Analyzing the future of housing in urban centres, the prairies and the newly-thawed permafrost in the Arctic;
- Determining the role of smart home and metaverse technologies in the modern home;
- Lowering the cost of housing as Canada enters a potential economic recession.
- Improving heating, ventilation and air conditioning (HVAC) technologies to prevent the spread of airborne viruses, such as COVID-19 and to ensure high standards of living;
- Ensuring accessibility for individuals with disabilities in new housing developments;
- Creating safe and enjoyable spaces to play, unwind and socialize; and,
- Designing beautiful and appreciable architecture for all, including reflections of Indigenous cultures.
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Sign In First – Get It All
Let’s Talk Science is sponsoring the participation fee of the first 250 teams. Following that, the participation fee is $45 per student.
WHY PARTICIPATE?
This academic year we organize an Open Data inquiry and experiential learning program — High School Big Data Challenge (HSBDC) to engage secondary school and CEGEP students across the country and beyond to direct their computational thinking efforts towards development of ideas and solutions for UNESCO Sustainable Development Goal 11 (SDG 11) “Sustainable Cities and Communities”. Participants will use the National Research Council of Canada housing and climate change data, as well as any Open Data
Computational Thinking
Develop analytical and computational thinking by using computational techniques in the context of current, real-world challenges in clean energy.
Data Analysis
Learn data visualization to present student-found results from Big Data analytics.
Interdisciplinary Mindset
Engage in an interdisciplinary, problem space led by student-driven inquiry.
Scientific Communication
Practice scientific writing and publish your ideas in the peer-reviewed STEM Fellowship Journal, through the largest national scientific publishing group.
Networking
Network with academics, industry professionals, and other forward-thinking students.
Note: Prior knowledge of coding is NOT required to participate. Students from all backgrounds are welcome to participate
Through this challenge, students will:
- Collect and Investigate Data on access to sustainable and clean energy and culture around it.
- Analyze the role of various factors including gender, race, geographical region, and socioeconomic conditions on access and use of Clean energy.
- Hypothesize and Formulate innovative solutions to improve access to affordable, reliable, sustainable and modern energy for all
- Present Findings through scientific and scholarly writing in the form of a research project report.
Teams of 2 to 5 students will be provided with datasets, workshops, learning resources, mentorship, and tools for data analysis to undertake exploratory analysis of fair and equitable housing. Data analysis is combined with scientific writing, insofar that the teams present their research findings in the form of scientific manuscripts, which are then evaluated by academics and industry professionals. All aspects of the BDC, including delivery of workshops, resources and mentorship be available online, making them accessible to all students regardless of their location or other circumstances. However, there may be opportunities to present findings at an in-person final event.
At the end of the program, the research abstracts of all teams are published in a conference proceedings in the peer-reviewed NRC Research Press STEM Fellowship Journal
The top teams are then invited to defend their findings in front of a panel of experts in competing for monetary and academic prizes at the culminating final event.
Sign In First – Get It All
Let’s Talk Science is sponsoring the participation fee of the first 250 teams. Following that, the participation fee is $45 per student.
AWARDS
The High School Big Data Challenge awards high school students for their achievements in Big Data Inquiry and Computational Thinking. It encourages them to pursue their studies in analytics and computational science. Award recipients are selected based on demonstrated research, computational methods, and science communication. It is our intention to organize in-person finals this year if the public health situation remains favorable for Canada East (Toronto), and Canada West (Calgary). As our awards fund grows, monetary prizes now reach $15,000, as well as open access scholarly publishing awards worth $12,000.
IN COOPERATION WITH
SCHEDULE
Registration WindowSeptember 1, 2022 – October 29, 2022 Students form teams of 2-5 and register them online.
Information SessionsSeptember 17, 2022 – October 8, 2022
Challenge PeriodOctober 29, 2022 – January 15, 2023 During this time, students will: Crowdsource resources and investigate analytics tools (SAS, Python, R, etc.), choosing one to learn and leverage. Educational resources and workshops will be provided covering various data science topics to help with this. Attend mentor sessions and ask questions to learn more about anything within the realm of data science, its applications, topic ideation and academic writing. Work on a chosen dataset for 3 months. Work together in a team setting, making use of mentors, teachers and the provided resources to analyze a dataset and propose solutions. Tell the story of the data discovery through a scientific report. Use Overleaf to prepare the project report, and submit it through the Google Classroom submission dropbox.
Literature Review Submission DeadlineNovember 26, 2022 Students must submit a literature review, as a progress check, before the deadline (11:59 pm PT) for evaluation and feedback.
Abstract Submission DeadlineDecember 10, 2022 Students must submit an abstract, as a progress check, before the deadline (11:59 pm PT) for evaluation and feedback.
Project Submission DeadlineJanuary 15, 2023 Students submit their project reports developed in Overleaf before the deadline (11:59 pm PT) for evaluation by a team of academics and industry experts.
Finalist AnnouncementJanuary 29, 2023 The finalists (top 20 teams) will be announced! Successful student teams will have the opportunity to present at Big Data Day.
High School Big Data DayThe Big Data Day will occur in-person, providing finalist teams with the opportunity to present their findings to a panel of judges. February 11, 2023 @ 10:00 AM ET – Toronto – SciNet Space in the MARS Building February 26, 2023 @ 10:00AM MT – Calgary – University of Calgary |
SYNCHRONOUS EVENTSThe following events and workshops will be hosted live throughout the competition period at these updated dates: Kickoff Event and Theme Information October 30, 2022 @ 11:00 am – 12:00 pm PT Workshop 1: Expectations and Submission Perquisites* November 5, 2022 @ 12:00 – 1:30 pm PT Workshop 2: Project Management* Workshop 3: Introduction to Statistics Workshop 4: Basics of Data Science in Python Workshop 5: Ethical AI Part B: November 20, 2022 @ 4:00-5:00 pm PT Workshop 6: Blueprint to a Literature Review* Workshop 7: Reference Management Workshop 8: Starting a Manuscript* Workshop 9: Editing 101* Workshop 10: The Introduction and Conclusion Sections * Workshop 11: The Discussion Section*
Attendance is mandatory at Workshop 1. Your team must also attend at least 2 out of 4 of Workshops 8-11. Attending all other workshops is entirely optional. |
E-LEARNING MODULES
This year, we are offering many workshops in an online, e-learning format. Our participants are able to access the content at any time, and learn at their own pace, while getting help from experienced mentors. The following e-learning modules will be offered:
- What is Data Science?
- Data Privacy and GDPR
- Setting up the Environment
- Relational Databases in SQL
- Concepts of Dashboarding and Data Visualization
- Clustering
- Classification and Logistic Regression
- Fundamentals of Neural Networks
- Natural Language Processing
- Geospatial Analysis
- Network Science