Big Data Challenge for High School Students

NATIONAL BIG DATA CHALLENGE 2018-2019

BIG DATA de TERRE

MINE SPACE AND SOCIOECONOMIC DATA TO DISCOVER ENVIRONMENTAL, SOCIOECONOMIC SOLUTIONS FOR SUSTAINABLE LIVING ENVIRONMENTS

Go further into predictive analysis of optimal characteristics for sustainable living environments :
Collect and analyse geostatic terrestrial data from the CSA, ESA and NASA along with your city, province and feederal humanitarian open data. Explore Canada's 18 UNESCO Biosphere Reserves.

In partnership with Let's Talk Science
Under the patronage of the Canadian Commission for UNESCO

What is the big data challenge?

The STEM Fellowship Big Data Challenge is a competition that helps high school students get excited about Data Science and its potential to support inquiry-based learning and problem solving with open data. The Big Data Challenge involves STEAM students undertaking independent research projects to tackle real-world problems with the best industry analytical tools while learning about digital citizenship.  

How it works: We present the general competition theme within which you define a research topic of interest.  We supply you with relevant open data and leading data analytics tools with which you carry out your inquiry, come with ideas, develop solutions and present your findings in the form of a research paper.

The best part is you don’t even need to have prior data science knowledge to join! We deliver webinars and workshops teaching you the basics to get you started on your research!

The top 3 finalists will have their full paper published in the STEM Fellowship Journal

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Theme: Big Data de terre

This year’s competition is focused on exploratory data analysis of Canadian Space Agency (CSA)National Aeronautics and Space Administration (NASA) and European Space Agency (ESA) open data to produce descriptive and graphical summaries of data with the goal of revealing the impact of environmental condition on human health and well-being. It invites high school students to go further into predictive analytics of optimal environmental characteristics for long-term, long-distance space travel.

  • Collect and analyse geostatic terrestrial data along with your city, province, federal and humanitarian open data. Explore the Canada’s 18 UNESCO Biosphere Reserves.
  • Discover human health and well-being issues (physical health, public health, mental health, etc.) in the context of local, regional and global environmental problems.
  • Seek and suggest environmental, socioeconomic solutions for sustainable living environments.
Check out our full itinerary here.

Why participate

  • Engage in self-directed learning through trial-and-error. Participate in our workshops to learn the data science skills needed for you to analyse your problems.

Participate in workshops to learn the data science skills needed to analyse problems 

Interact in person and remotely with mentors and students across Canada

Have your work published in the STEM Fellowship Journal! The top 3 finalists have full manuscripts published and all participants have their abstracts published.

Practice your communication skills and present your findings to a panel of judges 

PRIZES: 

Academic prizes:

SciNet Supercomputer Tour

Scholarly publication of all project abstracts and full manuscripts publication of winning project papers in the STEM Fellowship Journal, published by Canadian Science Publishing

Monetary prizes:

$1000 SAS Analytics Talent Award- Toronto

$1000 SAS Analytics Talent Award- Calgary

$1000 RBC Arnold Chan Memorial Award for Student Innovation- Toronto 

$1000 RBC Arnold Chan Memorial Award for Student Innovation- Calgary

$1000 Digital Science Scholarly Communication Award

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we emphasize four key skills

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Computational Thinking

The ability to translate aggregates of data into abstract concepts and conduct data-based reasoning .

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Design Mindset

The ability to create solutions in contexts where only part  of the requirements are known 

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Cognitive Load Management

The ability to discriminate and filter the information needed to produce successful solutions 

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Social Intelligence

The ability to participate in the collaborative  construction of solutions.

Timeline

September 1, 2018

Registration begins via Eventbrite





October 20, 2018

Team Registration Deadline via Eventbrite
Form your team(s) of up to 4 students and register them online.
The Challenge Registration form is here





January 19, 2019

Deadline for Full Project Report submission

February 21, 2019

BIG DATA DAY

Take part in Big Data Day  in Toronto at the SAS Canada Headquarters (280 King St East, Toronto, ON M5A 1K7) or in Calgary (location to be announced!)

Attend in-person or join in online for the presentations! Take part in the expert roundtable, inviting dignitaries and academia experts. Tune in to the award ceremony where the top 3 teams are recognized!

Week of October 2, 2018

Week of Oct. 2, 2018 – Orientation Sessions

 

  1. Toronto (and telepresence): SciNet UofT

MaRS West Tower, 661 University Avenue, Suite 1140, Toronto ON M5G 1M1
October 2nd, 2018- register here.

 

  1. Calgary Cassio A/B, University of Calgary
    October 4th, 2018- register here.

 

*Orientation sessions are run by data science experts from SciNet, IBM Cognitive Class & SAS.

 Orientation session recording will be provided after the sessions end.

Check out our past orientation session here.

October 21, 2018

  1. Form your team(s) of up to 4 students and register them online. The Challenge Registration form will be found on Eventbrite. Pay participation/abstract publication fee of $125 (tax included) per team.
    Crowdsource the knowledge and investigate analytics tools CISCO Academy Python Pandas, SAS Academy Programing and open source data analysis courses and tools- choose one you will learn and use. 
  2. Workshops Covering entrepreneurial innovations, Overleaf, Cisco Python, R, SAS and Tableau.
  3. Organize and plan your project We recruited a good number of industry experts who are willing to mentor student teams. Based on the team choice of data tools we will help to find mentors from amongst the data analytics and scholarly publishing companies/ community. Also, feel free to go through family connections or use orientation session connections.
  4. Work on your data set for 2.5 months: Learn together, from your mentor and online. Slice and dice it, zoom in and out, find patterns, trends, and important segments.
  5. Tell the story of your data discovery through a scientific report. Use Overleaf professional scholarly communication platform to prepare and submit your project report.

Week of February 4, 2019

ANNOUNCEMENT OF FINALISTS

The finalists (top 10 teams) will be announced!

If your team is selected, you will deliver a presentation at Big Data Day, the culminating event for the BDC.

2017/18 Big Data Challenge

  • SAS Award - Tony Xu and Shayan Khalili (Earl Haig Secondary School)