Promoting ethical and responsible data management within a toolkit for scaling Citizen Science projects

Molina-Maturano, J., Laso Bayas, J.-C., See, L. ORCID: https://orcid.org/0000-0002-2665-7065, Hager, G., & Fritz, S. (2020). Promoting ethical and responsible data management within a toolkit for scaling Citizen Science projects. In: International FAIR Convergence Symposium.

[img]
Preview
Text
Toolkit for scaling Citizen Science projects_JanetMolina_IIASA_UGent.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial.

Download (8MB) | Preview

Abstract

Citizen Science (CS) has great potential for contributing to the achievement of the UN Sustainable Development Goals (SDGs) by providing data to indicators monitoring and tracking, and implementing the targets [1–3]. However, an outstanding challenge is to demonstrate CS impacts at scale and to devise indicators that are meaningful for stakeholders [4]. Comprehensive assessments that allow researchers to systematically align anticipated outcomes with SDGs, and design for scale in the early phases of a CS project are not currently available. At the same time, research on data ownership, access and use, and ethics in digitizing are becoming relevant and urgent for the inclusion of smallholder farmers and other stakeholders to close the digital divide [5].

An interactive toolkit was developed as a way for researchers and CS teams in agriculture to define scaling ambitions that are sustainable and responsible. A responsible ambition accounts for potential unintended negative effects in the outcome that it might produce [6,7]. The toolkit is based on a logical framework, and integrates both a tool for systems change at scale, and a sustainability assessment [8,9]. The toolkit was tested with senior researchers for content, usability, and preferred format via a hypothetical case, where researchers indicated that the toolkit is of most use in early CS project stages, and that workshops as well as its implementation as a web-based tool would enhance its impact, bringing together as many views and information as possible, and decreasing the inherent subjectivity, which is part of every sustainability assessment.

An additional module within the toolkit, called ‘Guidelines for ethical and responsible data management’, is being tested to gather insights into how data management plans can be embedded into a ‘design for scale’ and SDGs-impact process early on when designing a CS project. The module is based on ‘FAIR Guiding Principles for scientific data management and stewardship’, and the Responsible Data Guidelines (CGIAR, 2020) to manage data ethically. For instance, in an app for farmers where personally identifiable information (e.g. name, address) is being collected, practitioners can acquire an overall understanding of the best practices to manage their data. Equally, if georeferenced information is to be collected (e.g. plots, crops), the FAIR Guiding Principles act as a compass. If researchers have identified a potential contribution to a specific SDG indicator, the toolkit suggests to align this plan with the aforesaid guidelines. Researchers are asked to indicate a status against 15 criteria. If there is a defined plan for a given criterion, a green colour is indicated; if there is a plan but it is not completely defined, the criterion is marked yellow, while red is shown if there is no plan. Detailed descriptions of each guideline can be found via links provided within the toolkit. Additional references to external resources are also included. These tools include the Data Ethics Canvas (theodi.org), as well as the data code of conduct developed by leading institutions (EU CoC on agricultural data sharing, 2018).

The toolkit and the ethical and responsible data management modules are currently in the form of a spreadsheet, and will be implemented as a web-based tool. Furthermore, its application will be expanded from agricultural to include all kinds of CS projects. Future research could involve matching the proposed guidelines with the required CS data quality criteria defined by local and regional statistical offices that are responsible for SDG monitoring and implementation.

Item Type: Conference or Workshop Item (Paper)
Research Programs: Ecosystems Services and Management (ESM)
Young Scientists Summer Program (YSSP)
Depositing User: Luke Kirwan
Date Deposited: 15 Dec 2020 22:10
Last Modified: 15 Dec 2020 22:11
URI: http://pure.iiasa.ac.at/16936

Actions (login required)

View Item View Item

International Institute for Applied Systems Analysis (IIASA)
Schlossplatz 1, A-2361 Laxenburg, Austria
Phone: (+43 2236) 807 0 Fax:(+43 2236) 71 313