Purpose The purpose of this paper is to define and describe digital curation, an emerging field of theory and practice in the information professions that embraces digital preservation, data curation, and management of information assets over their lifecycle. It dissects key issues and debates in the area while arguing that digital curation is a vital strategy for dealing with the so-called data deluge. Design/methodology/approach This paper explores digital curation’s potential to provide an improved return on investment in data work. Findings A vital counterweight to the problem of data loss, digital curation also adds value to trusted data assets for current and future use. This paper unpacks data, the research enterprise, the roles and responsibilities of digital curation professionals, the data lifecycle, metadata, sharing and reuse, scholarly communication (cyberscholarship, publication and citation, and rights), infrastructure (archives, centers, libraries, and institutional repositories), and overarching issues (standards, governance and policy, planning and data management plans, risk management, evaluation, and metrics, sustainability, and outreach). Originality/value A critical discussion that focusses on North America and the UK, this paper synthesizes previous findings and conclusions in the area of digital curation. It has value for digital curation professionals and researchers as well as students in library and information science who may deal with data in the future. This paper helps potential stakeholders understand the intellectual and practical framework and the importance of digital curation in adding value to scholarly (science, social science, and humanities) and other types of data. This paper suggests the need for further empirical research, not only in exploring the actual sharing and reuse practices of various sectors, disciplines, and domains, but also in considering the the data lifecycle, the potential role of archivists, funding and sustainability, outreach and awareness-raising, and metrics.
