Teaching Open Data

December 16, 2015


  • RSS
  • Cite

Mike Smit is a professor in the School of Information Management at Dalhousie University in Halifax, Canada. His research and teaching explore data management for open and big data, data literacy, the effect of open information on civic engagement, and the interaction of information and emerging technology (including cloud computing and the Internet of Things).

One of the great things about open data is that it's not usually released with a specific purpose in mind. We can't predict what uses people will find for raw data; the power of open data is in unanticipated uses which move beyond the interests, scope, or capabilities of governments.

I use open data in my teaching. As a professor in Dalhousie's School of Information Management, I teach courses to students in our Master of Library and Information Studies (MLIS) and mid-career Master of Information Management degrees. Working with data is an important part of both degrees, and the effective visualization of data is one key learning outcome.

I've been asking students to visit open.canada.ca, find a dataset, and use an effective data visualization to tell me something interesting. What does "something interesting" mean? Fortunately for students, I find lots of things interesting. What I want is to learn something I didn't know, and that isn't obvious just by looking at the data.

Every semester, I have been astounded at the creativity of students who scour Canada's Open Data portal in search of a dataset that captures their interest. For students from Canada, it's an opportunity to better understand their home country; for students from outside the country, they learn a bit more about their host country.

Thinking more broadly about the objectives of the assignment, it is worth reflecting on what we expect a modern workforce, and a modern pool of graduates, to know about working with data. The increasing interest in open data, combined with the problem of big data and the power of data science and data analytics, suggests the world is growing more and more data rich. But raw data is of limited use; we unlock the potential of data when we can analyze it, visualize it, create information and knowledge from it, and ultimately inform evidence-based decision making.

I'm part of a team of researchers at Dalhousie that was recently awarded Social Science and Humanities Research Council (SSHRC) funding for an initial look at the question "How can post-secondary institutions in Canada best equip graduates with the knowledge, understanding, and skills required for the data-rich knowledge economy?" What levels of what we call "data literacy" will we want Canadians to have as we consider the future of open data and open government?

These are big questions; for now, I'll say that an open data visualization assignment is a good start. I've linked to a copy of my assignment which anyone is welcome to use and adapt. Below, I've embedded some of the data visualizations MLIS students produced so you can see how students rose to the challenge of distilling complex datasets into easily absorbed messages.

Figure [01]: Seasonal sea ice thickness averages

Figure [01] - Text version

Graph of month-by-month sea ice average thicknesses from 1947 to 2002. Darker lines indicate thicker ice, and the graph shows that, while sea ice thickness varies throughout the year, the overall trend is thinner ice over the time scale.

Emily Colford (MLIS 2015) used data from the Canadian Ice Thickness Program, which measured sea ice thickness from 1947 to 2002. Because she used lighter-colored lines for more recent data, you can clearly see the decline in thickness over time (though each individual line is difficult to identify, the focus is the overall trend).

Figure [02]: Comparison of mortgage rates and average rent in Halifax

Figure [02] - Text version

Graph of mortgage rates expressed in percentage and monthly apartment rental prices for the City of Halifax from 1987 to 2012. The graph shows a trend of increase in rental prices over the time scale for all dwelling types (three bedrooms, two bedrooms, one bedroom, and bachelor) and a declining mortgage rate.

Carlisle Kent (Master of Resource and Environmental Management/MLIS 2016) used CMHC data to compare mortgage rates with average rent in the city of Halifax over the past 25 years; this showcases the value of the opportunity to buy property rather than renting it, and how this value has changed over time.

(Sources: Conventional mortgage lending rate, 5-year term and Average rents for areas with a population of 10,000 and over)

Figure [03]: Internet use by age and income

Figure [03] - Text version

A graph showing what percentage of people have regular internet access, divided into highest quartile income families and lowest quartile income families and by age.

Regular internet access by age and income
  Lowest quartile income family Highest quartile income family
Individuals aged 16 to 24 years 94.65% 99.1%
Individuals aged 25 to 44 years 88.1% 98.35%
Individuals aged 45 to 64 years 61.7% 92.65%
Individuals aged 65 years and over 26.75% 68.6%

Harrison Enman showed us that the digital divide (a separation between people with regular Internet access and those without) is at its greatest among senior citizens whose family incomes are in the lowest quartile (the bottom 25%).

(Source: Canadian Internet use survey, Internet use, by location and frequency of use)

N.B. Ordinarily one would not connect these categories with a line graph, but the visual effect that results excuses this faux pas.

Figure [04]: Marital status for incarcerated men vs. Canadian men over 18

Figure [04] - Text version

A bar chart of the marital status, expressed as percentages, of free versus incarcerated Canadian men over 18, divided into Single, Common law, Married, Previously partnered, and Unknown. Proportionately, more men in prison are single or common law than in the general population, fewer men in prison are married, and approximately the same have been previously partnered.

Keriann Dowling (MLIS 2014) pointed out tongue-in-cheek that as a percentage, far more men in prison are single than in the general population.

(Sources: Offender Profile 2013-2014 and Estimates of population, by marital status, age group and sex for July 1, Canada, provinces and territories)

Figure [05]: Alcohol expenditures compared to unemployment rates

Figure [05] - Text version

A bar chart comparing average annual alcohol expenditures against Unemployment rate percentages in Canada.

Average annual alcohol expenditure Unemployment rate percentage
$622 8.5%
$672 8.7%
$677 8.5%
$712 8.2%
$721 7.7%
$806 7.3%
$837 6.8%

Finally, in another light-hearted analysis, Andrea Kampen (MLIS 2015) wondered if there might be a relationship between the amount of money Canadians spend on alcohol and unemployment levels; at a glance, it certainly appears that when more Canadians have jobs, we spend more money on alcohol. I will leave the reader to form their own conclusions for this one!

(Sources: Survey of household spending (SHS), household spending on tobacco and alcoholic beverages, by province and territory)

Date modified: