Similar to many educational technology tools, data visualization is still relatively new and it will take some time and perhaps lots of trial and error, before users feel more confident about applying data visualization in a meaningful way.
​
This article discusses the necessary work that should be done on the institutional level and the potential pitfall of not using data visualization correctly.
​
For the chart below, hover over text to read more about each point.
Data Literacy
​
“Most of us need to listen to the music to understand how beautiful it is. But often that’s how we present statistics: we just show the notes, we don’t play the music.” – Hans Rosling.
​
According to Statistic Canada, data literacy is “the ability to derive meaningful information from data” and that includes the skill to analyze and interpret data for decision making. Earlier in the benefits and limitation section, we already touched upon the kind of expertise one has to acquire, before they can extract and communicate data in a meaningful way. The same goes to users who are on the receiving end of reading data too – it can get overwhelming when presenting a set of graph with lots of data for the first time. In order to alleviate the stress and prevent misuse of data, data literacy should be a part of the fundamental training with data visualization.
​
Click here to test your data literacy and share your data personality in the ETEC 522 Launch pad with the class.
Accessibility
When we talk about accessibility and data visualization, the Web Content Accessibility Guidelines (WCAG) provides a clear direction. In short, follow the four guidelines:
Perceivable
Operable
Understandable
Robust