Step 1

[paulopperman]

What's the first step? Discuss!!

[paulopperman]

From the open data handbook

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.

[paulopperman]

Choose Dataset(s)

Choosing the dataset(s) you plan to make open is the first step – though remember that the whole process of opening up data is iterative and you can return to this step if you encounter problems later on.

If you already know exactly what dataset(s) you plan to open up you can move straight on to the next section. However, in many cases, especially for large institutions, choosing which datasets to focus on is a challenge. How should one proceed in this case?

Creating this list should be a quick process that identifies which datasets could be made open to start with. There will be time at later stages to check in detail whether each dataset is suitable.

There is no requirement to create a comprehensive list of your datasets. The main point to bear in mind is whether it is feasible to publish this data at all (whether openly or otherwise) - see this previous section.

[micaelaw]

Step 1. Choose and ANALYZE if it is a good candidate:

• Could the data be of interest to the community?
• Is it now, or can it be transformed into, a usable format? (csv, Excel, etc)
• Are there privacy concerns with the dataset?
• What is the ease of release for this dataset? Is there a process, bureaucracy, number of signatures needed to allow it to be made public?
• Is the data of a meaningful sample size? (That cutoff size will be different for different types of data... How to decide if enough data is enough to be meaningful?)