A Qualitative Study of Bibliographic Data Sources and Retrieval Mechanisms for Computational Research

In the era of big data, selecting appropriate bibliographic data sources is crucial for researchers. However, differences in database functionalities, accessibility, and ease of use pose challenges for large-scale bibliometric analysis. APIs are key for automating data retrieval, but their varying performance and availability complicates selection. This study provides a comparative analysis of eight data sources—Scopus, Web of Science (WoS), Dimensions, OpenAlex, Semantic Scholar (SS), Google Scholar (GS), Scite.ai, and Open Research Knowledge Graph (ORKG)—and their APIs. We examine accessibility, search functionalities, metadata availability, and ease of use. Our results show that while each API supports core research needs, OpenAlex and SS offer the most user-friendly experiences with minimal technical requirements, while the GS API is the most cumbersome. These insights help researchers and developers select appropriate bibliometric data sources for computational research.