Photo credits: Nation Media Group – The East African
What “data sharing” is, is pretty obvious: it’s sharing data: between organisations, between people, between departments, between governments. Most people in the smart cities movement have heard of data sharing, and that it’s an important thing.
However, there are a number of reasons to put data sharing into the “too hard” basket, or at least – the “think about it later” basket:
For city authorities, the difficulties and challenges outweigh the solutions.
Here are just a few of those challenges:
- Is this data too personally sensitive to share?
- Is there a security risk resulting from opening a specific data set?
- What happens when several non-personal data sets are combined to possible re-identify an individual?
- How should we classify data so that appropriate sharing can be put in place?
- What if the next council (or state or country) has a different classification scheme?
- Are we going to be nationalistic – fine to share within the country but never with other nations?
- Would that mean we can never learn from other countries, or them from us?
In Australia alone there are over 500 local authorities. Add to that New Zealand, South East Asia, Hong Kong, Taiwan and the number of bodies responsible for urban environments, and therefore fro smart cities, starts to grow.
Let’s back up. Why could it be useful to share data? What sort of data? Here’s an example.
A town with a particularly busy shopping centre puts in place a smart parking scheme. Local authorities will know (from a resulting revenue increase!) how many people start to use the scheme, and how frequently.
The town planners also want to know the effect on congestion in an adjacent area – an area where cars used to circle, looking for parking spots. Was the smart parking uptake due to increased total traffic? Has the scheme also been effective in reducing traffic congestion?
It’s good to share
Combining this data with other data about air quality or garbage collection or other things may result in new service and revenue opportunities.
If this data is shared between towns of similar sizes, then other communities considering smart parking can gauge not only the return on their investment, but the possible benefits to pedestrians and cyclists in areas previously dedicated to vulture-like circling vehicles.
The providers of the parking solution could also draw on the data to use in case studies when taking their technology to other countries. Citizens could be concerned about invasion of privacy: that the traffic monitoring, coupled with number-plate recognition, could result in individual motorists’ driving habits being detected.
A model for sharing
However, suppose a code of practice has been agreed, safeguards have been put in place, and that where it makes mutual sense to share data, we’re ready to do so. What next?
Next is to classify the data. A basic model is:
- Classification 3: “Share this – no restriction”;
- Classification 2: “Subject to such-and-such a restriction”;
- Classification 1: “Do not share under any condition”.
So, who does this classification? One scenario is that the thought-leading towns, not wanting to go at the pace of the slowest marcher, work out their own way of classifying data.
Then what if there were 100 different classification models? Or 200? Or 500? This would be like 500 data sharing rail gauges – disaster.
It might not look like disaster early on, but different parties will want to combine their data sets with those of other parties: central government with city authorities’, for example.
Combining and recombining different data sets, usually with analytics applied to the result, provides tremendously valuable insights. In fact, it’s one of the basic tenets of the smart cities movement.
But should we expect an adjudicating authority to cope with engaging with over 500 different sets of rules?
No: there must be consistency. Without this innovation will be stymied. Not to mention the ridiculous waste caused by 500 different attempts at creating rules.
Doing it once, and doing it well, will cost much less overall and enable any good idea in one jurisdiction to be leveraged into others.
