This article reports on Citizen Observatories’ (COs) potential to contribute to the Sustainable Development Goals (SDGs), reflecting on the experience of the GROW Observatory (GROW). The research aims to take the first steps in closing the gap in the literature on COs’ potential contributions to the SDG framework, beyond quantitative data contributions for indicator monitoring. Following an analysis of project activities and outcomes mapped against the SDG framework, the findings reveal GROW’s potential contributions across two dimensions: (i) Actions to advance the implementation of goals and targets through awareness raising and training; participatory methods; multi-stakeholder connections; and supporting citizens to move from data to action and (ii) Data contributions to SDG indicator monitoring through citizen-generated datasets. While earlier research has focused mostly on the latter (dimension ii), CO activities can impact numerous goals and targets, highlighting their potential to relate global SDGs to local level action, and vice versa. These findings align with the growing literature on COs’ ability to bring together policy makers, scientists and citizens, and support changes to environmental policy and practice. Furthermore, this research suggests groundwork activities that address the goal and target level can also enhance sustained data collection to contribute to indicator level monitoring. We conclude with future trends and recommendations for COs wishing to contribute to the SDGs.

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This paper demonstrates the value of transformation design in participatory sensing and describes how design can inform awareness and develop actions for change to tackle environmental issues. Recent research advocates for participatory sensing (open data capture through digital platforms) using technology that can assist and inspire citizens in driving environmental change. This paper examines a study aimed at overcoming some of the challenges

In this paper we examine ways to make data more meaningful and useful for citizens in participatory sensing. Participatory sensing has evolved as a digitally enabled grassroots approach to data collection for citizens with shared concerns. However, citizens often struggle to understand data in relation to their daily lives, and use them effectively. This paper presents a qualitative study on the development of a novel approach to Community Level Indicators (CLIs) during two participatory sensing projects focused on noise pollution. It investigates how CLIs can provide an infrastructure to address challenges in participatory sensing, specifically, making data meaningful and useful for non-experts. Furthermore, we consider how this approach moves towards an ambition of achieving change and impact through participatory sensing and discuss the challenges in this way of working and provide recommendations for future use of CLIs.

Citizen Sensing, a correlative of Citizen Science, employs low-cost sensors to evidence local environmental issues and empowers citizens to use the data they collect. Whilst motivations for participation can vary, communities affected by pollution frequently have changemaking as their goal. Social innovation is closely aligned with citizen sensing, however the process of co-creating practices and solutions with citizens who wish to shape their world can be highly complex to design. Therefore, our research articulates an action-orientated framework which emerges from a 2-year pan European project by which follow-on communities may replicate sensing initiatives more easily. The authors examine five studies and explore the cross-cutting principles, phases, stakeholders, methods, and challenges which form this framework. The authors argue that whilst data collection and data awareness are crucial to the citizen sensing process, there are precursory and subsequent stages which are necessary to equip citizens to address complex environmental challenges and take action on them. Therefore, this paper focuses on the stages and methods which are distinctive to citizen sensing. It concludes with recommendations for future practice for citizen sensing and citizen science.