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Abstract When participants share data to a central entity, those who have taken on the responsibility of accepting the data and handling its management may also have control of decisions about the data, including its use, re‐use, accessibility, and more. Such concentrated control of data is often a default practice across many forms of participatory sciences, which can be extractive in some contexts and a way to protect participants in other contexts. To avoid extractive practices and related harms, projects can adopt structures so that those who make decisions about the data set and/or each datum are different from those responsible forexecutingthe subsequent decisions about data management. We propose two alternative models for improving equity in data governance, each model representing a spectrum of options. With an individualized control model, each participant can place their data in a central repository while still retaining control of it, such as through simple opt‐in or opt‐out features or through blockchain technology. With a shared control model, representatives of salient participant groups, such as through participant advisory boards, collectively make decisions on behalf of their constituents. These equitable models are relevant to all participatory science systems, and particularly necessary in contexts where dominant‐culture institutions engage marginalized peoples. 

In citizen science, data stewards and data producers are often not the same people. When those who have labored on data collection are not in control of the data, ethical problems could arise from this basic structural feature. In this Perspective, we advance the proposition that stewarding data sets generated by volunteers involves the typical technical decisions in conventional research plus a suite of ethical decisions stemming from the relationship between professionals and volunteers. Differences in power, priorities, values, and vulnerabilities are features of the relationship between professionals and volunteers. Thus, ethical decisions about open data practices in citizen science include, but are not limited to, questions grounded in respect for volunteers: who decides data governance structures, who receives attribution for a data set, which data are accessible and to whom, and whose interests are served by the data use/re-use. We highlight ethical issues that citizen science practitioners should consider when making data governance decisions, particularly with respect to open data. 

Citizen science is an important vehicle for democratizing science and promoting the goal of universal and equitable access to scientific data and information. Data generated by citizen science groups have become an increasingly important source for scientists, applied users and those pursuing the 2030 Agenda for Sustainable Development. Citizen science data are used extensively in studies of biodiversity and pollution; crowdsourced data are being used by UN operational agencies for humanitarian activities; and citizen scientists are providing data relevant to monitoring the sustainable development goals (SDGs). This article provides an International Science Council (ISC) perspective on citizen science data generating activities in support of the 2030 Agenda and on needed improvements to the citizen science community's data stewardship practices for the benefit of science and society by presenting results of research undertaken by an ISC-sponsored Task Group.