A few years ago, our session host, Rory Gianni, through being involved with several open data initiatives, saw that some went on to great success and some weren’t sustainable. One factor that seemed to make a difference was engagement – if you are not involving people outside te organisation, why are you doing it? Even if you’re being driven by the stick of legislation, you could still capture why others would be interested.
What is the professional background of the people who have found themselves working in open data? And how are their careers likely to develop in the future?
The answer to the first question is that: it’s very diverse. A session at Open Data Camp 5 heard from people who had started out as foresters, commercial under-writers and as architects. And from people who had begun their careers in large DIY chains and councils.
Just one participant had been recruited to an open data project from university. And he had studied history while he was there.
It’s OK to accept that bright, engaged people might not know what Open Data is. So, here’s a beginner’s guide for them, liveblogged at Open Data Camp 5 in Belfast.
Datopolis is a board game, created by Jeni Tennison and Ellen Broad from the Open Data Institute. At the outset of the session, Ellen explained that the game has been in development for around 12 months, and is still being prototyped.
The aim, naturally, is to explain the principles of open data and how they can be put to work. Jeni took a keen – if slightly apprehensive – set of players through the basics. The key pieces are hexagonal data tiles, she said, which represent data sets of different types. Clouds, for example, are weather data. Trains are transport. The tiles have two sides: a closed side and an open side.
This has been liveblogged. Sorry for mistakes, they’ll be fixed.
The concept of data literacy is touted as the be-all-and-end-all solution to all information issues, but it’s pretty loosely defined, and may not be entirely viable for the wider public.
The ODcamp Data Literacy discussion on Saturday afternoon was challenged to define the term, and figure out all that it entails.
— Steve U (@Steve_Upton) February 21, 2015
Does that compute?
To attain the sort of data literacy that can decode huge sets – interrogate and interpret – you require, to an extent, mastery of both a subject and computing. That second skill, the computing one, is from where most of the problems emerge. It’s not feasible to computer-skill up everyone, but an understanding of how to use data is pretty important.
Sure, data can be better designed, made more useable for the uninitiated, but literacy really comes into play when the brick wall of bad data is hit. The combination of field and computing expertise enables you to articulate what is bad data, why it’s so bad, and figuring out how to circumvent that wall.
It’s about asking the right questions, the group agreed.
The english-plumbing divide
But the extent to which “problematic” computer skills are required depends on how critically you view the whole thing. Data skills were described alternately as equivalent to both:
- learning the english language – an absolutely necessity
- learning the trade of plumbing – useful but something you’re likely to outsource.
Perhaps one to file under politics > being more engaged with the world
How to teach it
Broud with her Australian brogue used her Saturday morning session at ODcamp to crowdsource ideas for what data could be used in the prospective board game, how, and, significantly, the wider benefits of using it.
The room was asked to feedback what types of open data would:
- help to establish some sort of utopia
- best fit the board game framework.
She used the example of energy efficiency, with prospective gamers using information to achieve greater savings. The game would highlight to non-data geeks how open data is a really important thing.
First, the group tried deciding what kind of game it would:
- Old school (as in actually on an board)
- Augmented reality.
It was mostly agreed that such a data-driven game would probably be more at home on a device, though they also stressed how they didn’t just want to make another Sim City.
The Complexity Crisis
Next question: complexity. The clever data types in the room have an expertise well beyond the gamers they’re pitching to. So how do you take that expertise and translate it? Do you try for a one-size fits all? Do you have different versions for different subjects?
Broud recalled her struggles learning to code using the hard-to-understand Ruby Warrior. The board game shouldn’t be like that. After some hemming and hawing, the game turned out like a crazy version of Sim City, but that’s not really a board game.
One audience closed the session by saying:
It should show that no data is bad. And that you should feel bad.