How to Open up Data¶
This section forms the core of this handbook. It gives concrete, detailed advice on how data holders can open up data. We’ll go through the basics, but also cover the pitfalls. Lastly, we will discuss the more subtle issues that can arise.
There are three key rules we recommend following when opening up data:
Keep it simple. Start out small, simple and fast. There is no requirement that every dataset must be made open right now. Starting out by opening up just one dataset, or even one part of a large dataset, is fine – of course, the more datasets you can open up the better.
Remember this is about innovation. Moving as rapidly as possible is good because it means you can build momentum and learn from experience – innovation is as much about failure as success and not every dataset will be useful.
Engage early and engage often. Engage with actual and potential users and re-users of the data as early and as often as you can, be they citizens, businesses or developers. This will ensure that the next iteration of your service is as relevant as it can be.
It is essential to bear in mind that much of the data will not reach ultimate users directly, but rather via ‘info-mediaries’. These are the people who take the data and transform or remix it to be presented. For example, most of us don’t want or need a large database of GPS coordinates, we would much prefer a map. Thus, engage with infomediaries first. They will re-use and repurpose the material.
Address common fears and misunderstandings. This is especially important if you are working with or within large institutions such as government. When opening up data you will encounter plenty of questions and fears. It is important to (a) identify the most important ones and (b) address them at as early a stage as possible.
There are four main steps in making data open, each of which will be covered in detail below. These are in very approximate order - many of the steps can be done simultaneously.
Choose your dataset(s). Choose the dataset(s) you plan to make open. Keep in mind that you can (and may need to) return to this step if you encounter problems at a later stage.
Apply an open license.
- Determine what intellectual property rights exist in the data.
- Apply a suitable ‘open’ license that licenses all of these rights and supports the definition of openness discussed in the section above on ‘What Open Data’
- NB: if you can’t do this go back to step 1 and try a different dataset.
Make the data available - in bulk and in a useful format. You may also wish to consider alternative ways of making it available such as via an API.
Make it discoverable - post on the web and perhaps organize a central catalog to list your open datasets.
