  The proliferation of open knowledge graphs has led to a surge in scholarly
research on the topic over the past decade. This paper presents a bibliometric
analysis of the scholarly literature on open knowledge graphs published between
2013 and 2023. The study aims to identify the trends, patterns, and impact of
research in this field, as well as the key topics and research questions that
have emerged. The work uses bibliometric techniques to analyze a sample of 4445
scholarly articles retrieved from Scopus. The findings reveal an
ever-increasing number of publications on open knowledge graphs published every
year, particularly in developed countries (+50 per year). These outputs are
published in highly-referred scholarly journals and conferences. The study
identifies three main research themes: (1) knowledge graph construction and
enrichment, (2) evaluation and reuse, and (3) fusion of knowledge graphs into
NLP systems. Within these themes, the study identifies specific tasks that have
received considerable attention, including entity linking, knowledge graph
embedding, and graph neural networks.
