The potential of open data as a resource for driving citizen-led urban innovation relies not only on a suitable technical infrastructure but also on the skills and knowledge of the citizens themselves. In this chapter, we describe how a smart city project in Milton Keynes, UK, is supporting multiple stages of citizen innovation, from ideation to citizen-led smart city projects. The Our MK initiative provides support and funding to help citizens develop their ideas about making their communities more sustainable into reality. This approach encounters challenges when engaging with citizens in identifying and implementing data-driven solutions to urban problems. The majority of citizens have little practical experience with the types of data sets that might be available or possess the appropriate skills for their analysis and utilisation for addressing urban issues or finding novel ways to hack their city. We go on to describe the Urban Data School, which aims to offer a long-term solution to this problem by providing teaching resources around urban data sets aimed at raising the standard of data literacy amongst future generations. Lesson resources that form part of the Urban Data School have been piloted in one primary and three secondary schools in Milton Keynes. This work has demonstrated that with the appropriate support, even young children can begin to develop the skills necessary to work with large complex data sets. Through our two approaches, we illustrate some of the barriers to citizen participation in urban innovation and detail our solutions to overcoming those barriers.

Choosing the right technologies to build an urban-scale IoT system can be challenging. There is often a focus on low-level architectural details such as the scalability of message handling. In our experience building an IoT information system requires a high-level holistic approach that mixes traditional data collection from vendor-specific cloud backends, together with data collected directly from embedded hardware and mobile devices. Supporting this heterogeneous environment can prove challenging and lead to complex systems that are difficult to develop and deploy in a timely fashion. In this paper we describe how we address these challenges by proposing a three-tiered DevOps model which we used to build an information system that is capable of providing real-time analytics of Electric Vehicle (EV) mobility usage and management within a smart city project.

A bottom-up approach to smart cities places citizens in an active role of contributing, analysing and interpreting data in pursuit of tackling local urban challenges and building a more sustainable future city. This vision can only be realised if citizens have sufficient data literacy skills and experience of large, complex, messy, ever expanding data sets. Schools typically focus on teaching data handling skills using small, personally collected data sets obtained through scientific experimentation, leading to a gap between what is being taught and what will be needed as big data and analytics become more prevalent. This paper proposes an approach to teaching data literacy in the context of urban innovation tasks, using an idea of Urban Data Games. These are supported by a set of training data and resources that will be used in school trials for exploring the problems people have when dealing with large data and trialling novel approaches for teaching data literacy.

Sustainability has been an important topic in UK schools for some time, most notably since the Sustainable School Strategy was proposed by the UK Department for Education (DFES) in 2006. However, as smart city technologies emerge and show real promise in contributing to a more sustainable future, it is becoming apparent that new skills for working with the big urban data sets that drive these innovations must be taught to upcoming generations to ensure that they can be active smart city citizens. Current practice within schools is to distribute teaching of different aspects of data skills across the curriculum. We ask the question how can data skills be taught using a more unified and practical approach, which facilitates application of skills in genuine, smart city contexts. We propose to use Urban Data Games to set a context for learning, and demonstrating, practical application of skills for handling large complex data sets. This paper focuses on an Appathon challenge, which will shortly be trialled in a Milton Keynes school, in which participants are tasked to design a novel App from real satellite data after first learning and applying data skills to data about home energy consumption.