The Missing Piece of the OpenData / OpenGov Puzzle: Education

Yesterday, I tweeted a quick thought that I had, while walking the dog:

Picture 5

A few people asked me to expand on this, so let’s give it a try:

We are facing a very different data-related problem today than we were facing only a few years ago. Back then, the call was solely for more information. Since then, corporations and governments have started to answer this call and the result has been a flood of data of all shapes and sizes. While it’s important to remain on track with the goal of making data available, we are now faced with a parallel and perhaps more perplexing problem: What do we do with it all?

Of course, an industry has developed around all of this data; start-ups around the world are coming up with new ideas and data-related products every day. At the same time, open-sourcers are releasing helpful tools and clever apps by the dozen. Still, in a large part these groups are looking at the data with fiscal utility in mind. It seems to me that if we are going to make the most of this information resource, it’s important to bring more people in on the game – and to do that requires education.

At the post-secondary level, efforts should be made to educate academics for whom this new pile of data could be useful: journalists, social scientists, historians, contemporary artists, archivists, etc. I could imagine cross-disciplinary workshops teaching the basics:

  1. A survey of what kind of data is available, and how to find it.
  2. A brief overview of common data formats (CSV, JSON, XML, etc).
  3. An introduction to user-friendly exploration tools like ManyEyes & Tableau
  4. A primer in Processing and how it can be used to quickly prototype and build specialized visualization tools.

The last step seems particularly important to me, as it encourages people to think about new ways to engage with information. In many cases, datasets that are becoming available are novel in their content, structure, and complexity – encouraging innovation in an academic framework is essential. Yes, we do need to teach people how to make bar graphs and scatter charts; but let’s also facilitate exploration and experimentation.

Why workshops? While this type of teaching could certainly be done through tutorials, or with a well-written text book, it’s my experience that teaching these subjects is much more effective one-on-one. This is particularly true for students who come at data from a non-scientific perspective (and these people are the ones that we need the most).

The long-term goal of such an initiative would be to increase data-literacy. In a perfect world, this would occur even earlier – at the highschool level. Here’s where I put on my utopian hat: teaching data literacy to young people would mean that they could find answers to their own questions, rather than waiting for the media to answer those questions for them. It also teaches them, in a practical way, about transparency and accountability in government. The education system is already producing a generation of bloggers and citizen journalists – let’s make sure they have the skills they need to be dangerous. Veering a bit to the right, these are hugely valuable skills for workers in an ‘idea economy’ – a nation with a data-literate workforce is a force to be reckoned with.

Ideally this educational component would be build in to government projects like or (are you listening, Canada?). More than that, it would be woven into the education mandate of governments at federal and local levels. Of course, I’m not holding my breath.

Instead, I’ve started to plan a bit of a project for the summer. Like last year, I taught a series of workshops at my studio in Vancouver, which were open to people of all skill levels. This year, I’m going to extend my reach a bit and offer a couple of free, online presentations covering some of the things that I’ve talked about in this post. One of these workshops will be specifically targeted to youth. At the same time, I’ll be publishing course outlines and sample materials for my sessions so that others can host similar events.

Stay tuned for details – and if you have any questions or would like to lend a hand, feel free to leave a comment or get in touch.

5 thoughts on “The Missing Piece of the OpenData / OpenGov Puzzle: Education”

  1. I couldn't agree more. I would even like to extend your reasoning to business contexts, where tons of money are spent gathering data but only a small subset of people knows how to deal with it.

    I look forward to your material and would be interested to host local sessions in Belgium as well…


  2. This sounds great! I'm a high school teacher and I'd love to use resources like you describe in a math or info-tech class. (I'm still mostly an on-call teacher so I can't promise a room full of beta testers though.)

  3. Hi Jer I really like the idea. You have a talent to make visualizations look easy and fun. When people 'play' with data to bring forth a visualization they will also gain a much better understanding of the material in the process.
    From my experience with teaching students will learn better if they have relatively 'easy' tools explained to them with which they then need to solve a small problem themselves.
    This could perhaps be the tool to first find/retrieve and then handle data in XLM or JSON form. While CSV is easy to grasp/process there is an additional markup hurdle for XML and JSON. Maybe give a tool for that with an example. Then give simple ways of how to analyze and display the data using set pieces i.e. a small number of representation types that are really basic. This is just from my own experience taking little baby steps as you (involuntarily/unconsciously (^_^) ) taught me my first bits in processing. In that case I used your example including the design. That way the 2 variables of the approach and the way how to make it look good/aesthetic are excluded and one can concentrate on learning the rest. On my own the representation probably would have been atrocious. If I can help let me know.

  4. Jer,

    I'm a student headed toward my undergraduate thesis in urban policy, and I've been searching for exactly what you describe. I'm eager to get going with Processing and other tools, but it's all a bit daunting for those with no background in programming or computer science. Anything to make these types of tools for working with public data more accessible to a broader audience is exactly what is needed right now. Looking forward to your next post!

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