Text mining and social network analysis of data curation literature

In support of data-intensive research and inquiry, data curation has been recognized as an emerging field of study and practice. The field has evolved rapidly, but knowledge structure and themes of diverse research on data curation is unclear. The purpose of this study is to identify important descriptors, major research themes, and their inter-relationships in the field of data curation. This study employs co-word analysis to map the conceptual space of the field of data curation in terms of topical clusters and frequencies. For this, the most frequently occurring words and phrases in journal articles’ titles were identified. Then the co-occurrences of those words and phrases were analyzed and visualized using social network analysis. It is anticipated that this study will be helpful in setting the research direction and subjects of researchers in the field of data curation