Wicked societal problems, such as environmental issues and climate
change, are complex, networked problems involving numerous intertwined issues,no optimal solutions, and a wide range of stakeholders. Cities are problem owners and living labs for finding solutions through design-enabled innovation initiatives. However, to reach collective impact, it is paramount that these initiatives can learn from one another and align efforts through collaborative sensemaking. In the MappingDESIGNSCAPES project, we piloted a participatory collaboration mapping approach for cross-case sensemaking across design-enabled urban innovation initiatives. We used the CommunitySensor methodology for participatory community network mapping together with the Kumu online network visualization tool to help representatives of three urban prototype cases share and collectively make sense of their design lessons learnt. In this second of two papers, we build on the participatory mapping foundation introduced in [1]. We describe the collaborative sensemaking approach used, then present the core collaboration patterns and
common perspectives that form the sensemaking scaffolding. We show how we
collaboratively made sense by first taking individual perspectives, then making
common sense together. An extended discussion puts our findings in a larger context of how an approach like MappingDESIGNSCAPES can be used to move from collaborative sensemaking to collective impact in design-driven urban innovation.@en

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.

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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.

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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.

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The technological focus of many Smart City projects relies on top-down innovations, ignoring the role that citizens can play in improving their local communities. In this paper we outline our approach to supporting citizens in playing an active role in urban innovation, from the crowdsourcing of initial ideas through to facilitating citizen involvement in the realization of community projects. This extends previous work in the field by exploring how to go beyond identifying issues and ideas to securing a commitment from citizens to assisting a project intended to address an identified issue.

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