Combining Web of Science and Scopus datasets in citation-based literature study

Abstract

Abstract Scientific research builds on previous studies and scientifically proven knowledge. Researchers must master the recent developments in the field when designing research to answer new questions. Today, the accessibility of research literature is abundant due to digitized publications, extensive coverage of citation indexes, and several literature databases. The means for conducting systematic literature reviews have greatly improved. In recent years, a lot of research with methods, such as systematic literature reviews, literature mapping, and visualizing studies, has been published. Despite the tools having been perfected, they still have limitations. Particularly, database selection for a literature search sets a bias, because the citation indexes differ in coverage according to the scientific domain. In this paper, bibliometric data from two citation indexes (Web of Science and Scopus) are combined for the purposes of bibliometric analyses in the context of inter-firm relationships. The combination process requires a lot of unifying and repairing of data in practice that is referred as data wrangling. This study describes the process steps and the lessons learned and considers the amount of effort required.

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No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 266 citations exist upstream.

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