How Does Citizen Science “Do” Governance? Reflections from the DITOs Project

Abstract

Introduction Citizen Science (CS) is intertwined with public policy in multiple ways, and the question of how CS can be a resource for decision-making is increasingly debated among those who organise projects as well as among politicians. Around the world, CS is considered relevant at various levels of governance from multilateral programmes, such as the United Nations Environment Programme, to supra-national institutions (the European Union) and individual member states exploring the value of CS for environmental reporting, education, and decision-making (POST 2014; Science Communication Unit 2013). Environmental protection agencies are recognising CS by issuing recommendations, cost-benefit analyses, and decision support for when to use CS to support implementation of regulatory environmental policy (NACEPT 2016; Pocock et al. 2014; Vohland et al. 2016). Increasing openness towards CS is also spreading beyond environmental and biodiversity monitoring to include health and food security, disaster response, and research policy (Schade et al. 2017). Policy publications that mention CS typically highlight its potential for multiple fields and implementations (McElfish, Pendergrass, and Fox 2016) as well as data management (Schade and Tsinaraki 2016). State-sponsored capacity building projects or consultations to develop national strategies for CS have been run in Germany (Bonn et al. 2016), France (Houllier and Merilhou-Goudard 2016), and Spain (Fundacion Ibercivis 2017). Finally, the CS practitioner community is starting to connect with decision makers to demonstrate the validity and benefits of CS (Hecker et al. 2018). Existing studies focus on how CS supports policy development, barriers, and regulatory support (e.g., Chapman and Hodges 2016). Haklay (2015) points out that policy dimensions of CS arise from geography, policy application area, and type of engagement. Existing empirical studies analyse CS projects along dimensions such as standards (Ottinger 2010), place (Newman et al. 2017), participation of stakeholders (Gobel, Martin, and Ramirez-Andreotta 2017), and data practices (Gabrys, Pritchard, and Barratt 2016). The literature typically identifies two roles for CS in policy contexts: As a data source for the development, implementation, or monitoring of regulation and as one of the targets for science policy. This idea rests on a set of basic assumptions: Politicians and formal political institutions are considered as central actors. "Science" and "politics" are understood as separate spheres, and policymaking is seen as a linear process where policy makers determine rules that CS feeds into.

Communication and Dissemination in Citizen Science

“…These were organised with the aim of mobilising communities of practitioners, sharing of good practice, and strengthening the science-policy interface by opening up dialogue with decisionmakers. This successful strategy enabled the DITOs project to establish networks and influence national science policy; provide information for policy improvement; promote citizen science as an approach to research and science communication; demonstrate that citizen science can be an instrument to advance political agendas; and use citizen science as a direct governance instrument via non-policy actors (Göbel et al 2019).…”

Urban Living Labs and Citizen Science: From Innovation and Science towards Policy Impacts

“…Although CS is first and foremost seen as a way to collect data and gain scientific knowledge on a specific phenomenon, it is increasingly being recognized as a powerful tool in governance and decision-making processes [35]. Actors from policy spheres are starting to recognize the benefits of CS as a timely and cost-effective source of knowledge that can support policy implementation and complement official reporting [33].…”

“…Actors from policy spheres are starting to recognize the benefits of CS as a timely and cost-effective source of knowledge that can support policy implementation and complement official reporting [33]. More specifically, Göbel et al [35] described CS as feeding into, being affected by, forming part of, and exercising four type of governance: (i) a source of information for policy-making-refers to the fact that CS's outputs are being used to formulate policies, (ii) an object of research policy-here CS is being regulated through policies to advance research, technology and innovation, (iii) a policy instrument-CS is seen as a disruptive innovation, instrumentalized by policies to reach their goal, and (iv) socio-technical governance-CS is seen as a direct type of governance via non-policy actors, answering societal problems through prototypes developed by citizens. Specific to environmental monitoring, it has been demonstrated that environmental CS projects can contribute to a diversity of sustainable development goals (SDGs) and can contribute to different phases of the policy cycle [36].…”

Citizen Science and Policy

“…Collaborations within an ever-changing context may lead to outcomes that are no longer relevant by the time projects produce them because the policy agenda has evolved in the meantime. Similarly, differences in capacities between professional and volunteer participants, for example, when they are available for meetings (during working hours or outside them), need to be addressed to produce successful collaborations (Göbel et al 2019).…”

“…As recently elaborated by Göbel et al (2019), citizen science can play different roles in governance, which is understood as the intention to control and direct the public business of a country, city, group of people, etc. According to the authors, there are four roles for citizen science in policy: as a source of information for policymaking, as an object of research policy, as a policy instrument, or as a form of sociotechnical governance (i.e.…”