Conference Agenda

This paper offers a retrospective analysis of the 2016/17 Data Rescue movement, a grassroots initiative that mobilized librarians, technologists, and activists to preserve at-risk federal environmental data in response to the anticipated threats posed by the Trump administration. Drawing on 16 qualitative interviews conducted in early 2025, the study examines how participants now reflect on their motivations, methods, and the movement’s legacy. It explores the ethical and affective dimensions of emergency curation, the tensions between institutional and community-driven preservation, and the shifting trust in public data infrastructures. Participants expressed a strong sense of civic duty and emotional urgency, but also critical distance from the movement’s limitations, particularly its overreliance on downloading as a preservation strategy. The findings underscore that trust in infrastructure is relational and partial, shaped by both political context and social practice. Ultimately, the paper argues that digital preservation in politically volatile times must be grounded in care, accountability, and long-term infrastructural thinking, rather than reactive interventions alone.

The official and accredited training of data stewards is a relatively new phenomenon worldwide. With the ever-growing presence of the Open Science and Open Data movements within the confines of academia, the need for professionals skilled in state-of-the-art data management and curation is axiomatic.

In Hungary two initiatives started unfolding in almost parallel fashion. The very first graduates of the first higher education level data steward training program at ELTE University received their degree in the autumn of 2024 (after three semesters of attendance). Similarly, the first ’graduates’ (more of an informal, not an accredited program) of the HUN-REN data steward training program received their certificates in January 2025. The HUN-REN data stewards started working in their newly created and acquired positions on the 1st of October.

The evolution of the HUN-REN Data Steward Network reflects a commitment to improving and institutionalizing research data management in Hungary. Each milestone represents a step forward in creating a robust and unified approach to data stewardship, ensuring that research data is managed efficiently and effectively across the network.

As the network continues to grow and develop, it serves as a model for other institutions and countries looking to enhance their own data management practices. The collaborative efforts and progressive initiatives undertaken by HUN-REN demonstrate the importance of data stewardship in the modern research landscape.

Forming the Hungarian national data steward community is based now on the informal collaboration between professionals and beginners from important institutions, marking a step towards the data steward professionalization in Hungary in which both ELTE’s DS training program and HUN-REN informal Data Steward Training program, as well as the HUN-REN Data Steward Network aim to play an important and effective role.

Since 2016, the implementation of the FAIR Principles encouraged re-thinking how data are managed, particularly regarding Indigenous communities which, due to the processes of colonisation, had very little impact on their knowledge and data. Hence, in 2018 the CARE Principles were drafted with the aim to tackle past injustices and support Indigenous communities in governing their data. However, the CARE implementation has not been straightforward as researchers, information experts and Indigenous Peoples faced many challenges starting from the lack of IT infrastructure, skills, funding and metadata. Hence, successful implementation of the CARE Principles requires significant financial and human resources.

It has been six years since the CARE principles were published. The aim of this paper is to analyse the obstacles of implementing them, whilst arguing that the process is one of the biggest contemporary challenges in data curation and the best solutions will eventually be found. The second part of this paper will address these challenges in the UK by analysing data collected in autumn of 2025 from the DataCite UK consortium members and the webinar guest speakers.