Open Data: the basics for newbies
There are loads of examples of open data. It can come in loads of formats. It’s data that’s open and free in accessible formats, that is machine readable. It can be any format – like a jpeg or a PDF, but that latter has become a joke in the community. PDFs are hard to get the data out of in a usable format. It’s great for people but a bit rubbish for computers.
Open data also has a licence, which makes it open. Everything else is just the icing on the cake. OGL or creative commons are common examples.
When does it stop being open data? Can poor quality data stop it being open? The open data license isn’t a stamp of approval or quality, just of openness and restrictions.
Is all open data numerical? No. For example: mapping data, lists of landfill sites. How about lists of library books and when they were last borrowed. For one person, totals and averages are the biggest switch-offs in open data.
More and more academic research is being published as open data. There are efforts underway to make books that are out of copyright as open data. A museum in France has opened up its entire collection as open data.
It’s a value exchange. If you exchange, say, health data, there’s a value to you in getting insight and analysis from your data.
Broadly, the aims are better products and services, through data-based better understanding. This is true in both the private and public sector. In the car of public sector data, it’s already ours. We own it! So it should be opened up because we paid for it to be created.
We don’t always know the benefit of opening data – it’s taking a punt and seeing what emerges, and there’s not chance of that happening if it stays closed.
In general, open data shouldn’t contain personally identifiable information. However, some personal data is somewhat acceptable – like public sector job titles or MPs expenses data.
Have there been negative consequences of opening data? In the US, there have been some examples of class actions based on open data. For example, Netflix released some data that people were able to combine with other data to identify people within it. While it’s pretty easy to anonymise data, sometimes edge cases makes it possible to identify people.
