This volume explores these questions and introduces the principles and practice of a quietly growing field: systems thinking. With roots in disciplines as varied as biology, cybernetics, and ecology, systems thinking provides a way of looking at how the world works that differs markedly from the traditional reductionistic, analytic view. Why is a systemic perspective an important complement to analytic thinking? One reason is that understanding how systems work – and how we play a role in them – lets us function more effectively and proactively within them. The more we understand systemic behavior, the more we can anticipate that behavior and work with systems (rather than being controlled by them) to shape the quality of our lives.

Purpose should govern the choice of dataset to focus on Standards should be the primary guide to the design of the datasets User engagement should influence engagement activities ‘on top of’ published data to secure prioritised outcomes New user needs should feed into standard extension and development User engagement should shape the initiatives built on top of data

The call for ‘raw data now‘ was not without purpose: but it was about the purpose of particular groups of actors: not least semantic web reseachers looking for a large corpus of data to test their methods on. This call configured open data towards the needs and preferences of a particular set of (technical) actors, based on the theory that they would then act as intermediaries, creating a range of products and platforms that would serve the purpose of other groups. That theory hasn’t delivered in practice

They describe a process that started with a purpose (“get better bids on contract opportunities”), and then engaged with vendors to discuss and test out datasets that were useful to them.

Call out the risks of new technologies. Understanding technologies often makes you uniquely equipped to explain their risks. Investigate the technologies others are proposing, make sure you understand them, and if necessary sound the alarm bells.

Respond to technological and nontechnological calls to action.

Finally, consider whom your project shifts power away from and whom it shifts power to. Ownership of data is a form of power: Do you provide meaningful opt-in to data collection? Whom are you giving access to this data?