Traditional data sources are not sufficient for measuring the United Nations Sustainable Development Goals. New and nontraditional sources of data are required. Citizen science is an emerging example of a non-traditional data source that is already making a contribution. In this Perspective, we present a roadmap that outlines how citizen science can be integrated into the formal Sustainable Development Goals reporting mechanisms. Success will require leadership from the United Nations, innovation from National Statistical Offices and focus from the citizen-science community to identify the indicators for which citizen science can make a real contribution.
Citizen science, broadly defined as public participation in scientific research and knowledge production, is becoming an increasingly well developed and valued approach with global reach and used in a wide range of scientific domains [1][2][3] . Much of this growth is driven by the availability of information technology infrastructures such as mobile phones and low-cost sensors for gathering and reporting data, the internet for sharing data, and cloud storage for hosting and storing data 4,5 . Growing literacy levels and educational attainment in many parts of the world also make it possible for many more people to contribute to knowledge creation in a meaningful way 6,7 .Citizen science initiatives involve the public in the research process to generate genuine scientific outcomes [8][9][10][11] . These outcomes include discoveries, such as in astrophysics 12 and archaeology projects 13 ; new insights, such as in epidemiology 14 and socio-linguistics projects 15 ; evidence-based policymaking, such as in pollution-monitoring initiatives [16][17][18] ; interventions such as in public health research 19 ; and environmental governance, including in ecology and biodiversity monitoring initiatives [20][21][22] . Citizen science research can fill important data gaps across both time and space 23 , which might not otherwise be possible without the contribution of many participants, including people with local and lay knowledge 24,25 or Indigenous knowledge 26,27 .
Citizen science has expanded rapidly over the past decades. Yet, defining citizen science and its boundaries remained a challenge, and this is reflected in the literature—for example in the proliferation of typologies and definitions. There is a need for identifying areas of agreement and disagreement within the citizen science practitioners community on what should be considered as citizen science activity. This paper describes the development and results of a survey that examined this issue, through the use of vignettes—short case descriptions that describe an activity, while asking the respondents to rate the activity on a scale from ‘not citizen science’ (0%) to ‘citizen science’ (100%). The survey included 50 vignettes, of which five were developed as clear cases of not-citizen science activities, five as widely accepted citizen science activities and the others addressing 10 factors and 61 sub-factors that can lead to controversy about an activity. The survey has attracted 333 respondents, who provided over 5100 ratings. The analysis demonstrates the plurality of understanding of what citizen science is and calls for an open understanding of what activities are included in the field.
AcknowledgementsWe are very grateful to the research assistants and field officers in Zambia for facilitating communication with farmers and the implementation of individual interviews as well as the participatory system dynamics model building workshops. Our sincere gratitude goes to the traditional leadership in the workshop communities for their support and to all the farmers who generously shared their time and insight with us. Funding sourcesWork on this article was supported by the Norwegian Research Council through the project "Simulation based tools for linking knowledge with action to improve and maintain food security in Africa" (contract number 217931/F10) and the Peder Sather Center for Advanced Study through the project "Knowledge analysis in coupled social-ecological systems. A pilot study in smallholder farmer communities in Zambia". The views and conclusions expressed in this paper are those of the authors alone and do not necessarily reflect the views of the funding sources. The funding sources had no role in study design, collection, analysis and interpretation of data, in the writing of this article or in the decision to submit this article for publication. Conflicts of interestThe authors declare no conflict of interest. AbstractFood systems will need to undergo considerable transformation. To be better prepared for and resilient to uncertainty and disturbances in the future, resource users and managers need to further develop knowledge about the food and farming system, with its dominating feedback structures and complexities, and to test robust and integrated system-based solutions. This paper investigates how participatory system dynamics modeling can be adapted to groups at the community level with low or no formal educational background. The paper also analyses the refinement of workshop participants' mental models as a consequence of a participatory system dynamics intervention. For this purpose, we ran two workshops with small-scale farmers in Zambia. Analysis of workshop data and postworkshop interviews shows that participatory system dynamics is well adaptable to support an audience-specific learning-by-doing approach. The use of pictures, objects and water glasses in combination with the basic aspects of causal loop diagramming makes for a wellbalanced toolbox. Participants acquire understanding that is also relevant beyond systems thinking in that it offers a range of practical insights such as a critical evaluation of common food security strategies.
Citizen science has expanded rapidly over the past decades. Yet, defining citizen science and its boundaries remained a challenge, and this is reflected in the literature - for example in the proliferation of typologies and definitions. There is a need for identifying areas of agreement and disagreement within the citizen science practitioners community on what should be considered as citizen science activity. This paper describes the development and results of a survey that examined this issue, through the use of vignettes - short case descriptions that describe an activity, while asking the respondents to rate the activity on a scale from ‘not citizen science’ (0%) to ‘citizen science’ (100%). The survey included 50 vignettes, of which 5 were developed as clear cases of not-citizen science activities, 5 as widely accepted citizen science activities, and the others addressing 10 factors and 61 sub-factors that can lead to controversy about an activity. The survey has attracted 333 respondents, who provided over 5,100 ratings. The analysis demonstrates the plurality of understanding of what citizen science is and calls for an open understanding of what activities are included in the field.
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