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Prepare
The purpose of the Prepare phase is to ensure that factors that might prevent sustainable publication of your data are at least considered before investing resources. The needs derived during this phase will become the 'backlog' which you will plan and deliver in subsequent phases.
Having a clear understanding of 'why' this data is being published provides a strong foundation which will inform all subsequent activities.
Understanding the stakeholders is crucial to a successful publication. A stakeholder is defined as someone with an interest in the data being published. Draw up a list of all the key stakeholders, ensuring that you cover the following thoughts:
- Have you identified all key internal stakeholders, including management / board-level as well as staff within other organisational units who have an interest (ownership or usage) in the data.
- Have you included external stakeholders who might have an interest in using the data. This could include journalists, entrepreneurs, developers, researchers or policy makers. Be as specific as possible, especially if there is a strong local or domain-oriented bias to your data release.
- Have you included stakeholders who are the subject of the data. For example, if you are releasing a dataset related to senior citizen travel, have you included senior citizens or groups representing them.
Once you have collated this list, identify the key sponsor or sponsors. These people may prove useful if your project begins to struggle, so it's worth ensuring you take time to build a good working relationship with them early on.
- Context
- Stakeholders
NB to include all potentially interested parties, internal and external - Motiviation to publish
- Stakeholders
- Data
- Catalogue
- Models
- Quality
- Known issues / desired fixes
- Size
- Volatility / rate of growth
- Sensitivity
e.g. sensitive personal information
- Applications
- Potential uses, captured as user stories
As anxI need access to datasetyso that I canz - Audience / end-users
- Additional data required? Linked data?
- Sensitive data by inferrence?
- Summary data?
- Potential uses, captured as user stories
- Constraints
- Legal status
e.g. Governed by DPA, ownership unclear - Technical challenges
- Funding
- Resourcing
- Legal status
Open Data Publishing Framework by Giles Dring is licensed under a Creative Commons Attribution 4.0 International License.
