Mapping the scientific research on open data: A bibliometric review

Abstract

This paper presents a review of open data research based on bibliometric analysis of publications in Web of Science from 1998 to 2016. It shows that research on open data has grown rapidly since 2009 with the development of various open data initiatives. We identify the different themes using science mapping and performance analysis. The most important themes are semantic web, open government, and crowdsourcing. The basic and transversal themes are data sharing and public sector information. As for the emerging themes, these are Big Data and open government data. In addition, data journalism, monitoring, and recommender systems are specific themes that deserve special attention. The UK and the USA are the leading publishing countries, both in theoretical and practical research on open data. In China, most researchers focus on practical research, and there have been efforts to promote the development of open data. Papers introducing large‐scale projects receive more attention and citation quickly. Recently, researchers have been publishing more on objective topics, including possible issues and dilemmas in the era of Big Data and many problems such as budgets, ownership, licensing, culture, and sustainable development.

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Stored only when both papers are in the corpus — 35 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.