Research data management challenges in citizen science projects and recommendations for library support services. A scoping review and case study.

Citizen science (CS) projects are part of a new era of data aggregation and harmonisation that facilitates interconnections between different datasets. Increasing the value and reuse of CS data has received growing attention with the appearance of the FAIR principles and systematic research data management (RDM) practises, which are often promoted by university libraries. However, RDM initiatives in CS appear diversified and if CS have special needs in terms of RDM is unclear. Therefore, the aim of this article is firstly to identify RDM challenges for CS projects and secondly, to discuss how university libraries may support any such challenges. A scoping review and a case study of Danish CS projects were performed to identify RDM challenges. 48 articles were selected for data extraction. Four academic project leaders were interviewed about RDM practices in their CS projects. Challenges and recommendations identified in the review and case study are often not specific for CS. However, finding CS data, engaging specific populations, attributing volunteers and handling sensitive data including health data are some of the challenges requiring special attention by CS project managers. Scientific requirements or national practices do not always encompass the nature of CS projects. Based on the identified challenges, it is recommended that university libraries focus their services on 1) identifying legal and ethical issues that the project managers should be aware of in their projects, 2) elaborating these issues in a Terms of Participation that also specifies data handling and sharing to the citizen scientist, and 3) motivating the project manager to good data handling practises. Adhering to the FAIR principles and good RDM practices in CS projects will continuously secure contextualisation and data quality. High data quality increases the value and reuse of the data and, therefore, the empowerment of the citizen scientists

9 things to make citizen science data FAIR. A research librarian’s guide.

This guide aims to support research librarians serve citizen science projects with the competencies already embedded in many university libraries; they have long been the hub for knowledge of Open Science, they have a multidisciplinary outreach and organise activities connecting students, faculty and the public. Citizen science has a broad scope, and involve voluntary and active public engagement. Embedding citizen science projects in academia may prove useful for many reasons: expanding and improving current research activities and strengthening the interaction of scientists with the public. Citizen Science belongs to the Open Science domain, and is therefore, perceived as a discipline, where research data are shared openly, with open access to publications and full transparency of data availability. However, in some cases, data use have to be limited to comply with ethical and legal conditions, for example due to privacy concerns. For many scientists, major obstacles to share data openly with citizens are the concern of handling personal data, but also the academic reward system weighing publications over data sharing. The FAIR principles are applicable to data regardless of their public availability. The four elements, Findable, Accessible, Interoperable and Reusable are designed to help lower barriers to access generated research and to facilitate potential new findings by promoting the availability and reuse of data. With this guide, we aim to show how research data management in citizen science can benefit from the FAIR principles. The 9 things of this guide are based on research data management challenges identified for citizen science projects (Holmstrand et al. 2020). Understanding these challenges is an important foundation for guidance provided by the research librarian to any citizen science project manager. The 9 things are structured with the FAIR elements in focus, highlighting practical aspects and benefits of FAIR data in citizen science projects

FAIR data in a Citizen Science project “Fangstjournalen”

In this video Researcher Christian Skov from DTU Aqua tells about the Citizen Science project “Fangstjournalen” and how Research Data Management, data sharing and following the FAIR guiding principles for research data can increase the impact and the value of the research - even beyond the scope of the project. This video is produced by four Danish Universities as part of a project financially supported by DEFF. The aim of the project is to identify the role of Danish Research Libraries in the dissemination and support of Citizen Science

Introduction to citizen science. The case of Fangstjournalen.dk

DTU Library is celebrating Love Data Week 2020 with the mission to raise awareness about the data surrounding us and library-based research data services. In this video Researcher Christian Skov from DTU Aqua tells about the Citizen Science project “Fangstjournalen” and how Citizens engage in collecting data and co-creating knowledge. A knowledge- creation helping us to learn more about the world we live in. This video is produced by four Danish Universities as part of a project financially supported by DEFF. The aim of the project is to identify the role of Danish Research Libraries in the dissemination and support of Citizen Science

9 things to make citizen science data FAIR. A research librarian’s guide.

This guide aims to support research librarians serve citizen science projects with the competencies already embedded in many university libraries; they have long been the hub for knowledge of Open Science, they have a multidisciplinary outreach and organise activities connecting students, faculty and the public. Citizen science has a broad scope, and involve voluntary and active public engagement. Embedding citizen science projects in academia may prove useful for many reasons: expanding and improving current research activities and strengthening the interaction of scientists with the public. Citizen Science belongs to the Open Science domain, and is therefore, perceived as a discipline, where research data are shared openly, with open access to publications and full transparency of data availability. However, in some cases, data use have to be limited to comply with ethical and legal conditions, for example due to privacy concerns. For many scientists, major obstacles to share data openly with citizens are the concern of handling personal data, but also the academic reward system weighing publications over data sharing. The FAIR principles are applicable to data regardless of their public availability. The four elements, Findable, Accessible, Interoperable and Reusable are designed to help lower barriers to access generated research and to facilitate potential new findings by promoting the availability and reuse of data. With this guide, we aim to show how research data management in citizen science can benefit from the FAIR principles. The 9 things of this guide are based on research data management challenges identified for citizen science projects (Holmstrand et al. 2020). Understanding these challenges is an important foundation for guidance provided by the research librarian to any citizen science project manager. The 9 things are structured with the FAIR elements in focus, highlighting practical aspects and benefits of FAIR data in citizen science projects