A Decade of Scholarly Research on Open Knowledge Graphs

TL;DR

This bibliometric study analyzes a decade of scholarly research on open knowledge graphs, highlighting growth trends, key topics, and influential research themes in the field.

Contribution

It provides a comprehensive overview of research patterns, key topics, and influential works in open knowledge graphs from 2013 to 2023 using bibliometric analysis.

Findings

Increasing publication trend, especially in developed countries

Identification of three main research themes

Focus on tasks like entity linking and graph neural networks

Abstract

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.