Category Archives: Data Visualization

Finding the Path

When secondary students complete their courses and accumulate credits, they leave a trail of data behind them.  As these same students consider their course options for the the next year, they are making choices about the pathway they will follow. … Continue reading

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Highlights from OERS16

The 11th annual Ontario Education Research Symposium was held from February 9th to February 11th with the theme “Networking & Partnerships: The Core of Achieving Excellence in Education. Over 500 people from networks, organizations and stakeholders across the Education sector … Continue reading

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#OERS15 – Promoting Well-being – Evidence to support Implementation of the Renewed Vision

Last week people from across Ontario came toToronto to attend the 10th annual Ontario Education Research Symposium. Over 400 people from schools, boards, post-secondary institutions, communities and networks met together to learn and share about well-being. The event featured: a … Continue reading

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Data Vis … The Movie

A few years ago I learned 2 important tricks to navigating a movie theatre: 1)      Ask how full the theatre is when you purchase your ticket.  Finding a single seat is easy, two seats is usually no problem, but when … Continue reading

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Revisiting the Healthcare Slopegraph – A Python implementation

Last summer I shared an adaptation of Tufte’s slopegraph using data from the  Institute for Clinical Evaluative Sciences‘ (ICES) 2011 Quality Monitor report in the post Education and Health Care – Using Slopegraphs to Understand Complex Systems.  While this initial … Continue reading

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Census 2011: Ontario Population Pyramid

Statistics Canada has released the Age and Sex data set for 2011.  A traditional visualization for this kind of data is the population pyramid.   The population pyramid is a modified version of a stacked bar chart with the division between … Continue reading

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Reshaping the Country

Maps are one of my favorite approaches to presenting information.  However, they are just as vulnerable to abuse, misuse and overuse as every other form of data visualization.  Traditionally, maps employ color ranges, textures, symbols and boundary widths to describe … Continue reading

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