Our paper "Biblioshiny and the SAAS Workflow: An integrated framework for transparent and reproducible science mapping. A demonstration through the replication of a study" has been published in Journal of Informetrics (Elsevier), together with Massimo Aria, Corrado Cuccurullo and Maria Spano.
Science mapping is now widely used to review and structure scientific literature, but the analytical choices behind a map are often hard to trace and even harder to reproduce. This paper addresses that gap by framing the whole analysis as a structured, documented workflow built on top of Biblioshiny, the no-code, web-based interface of the bibliometrix R package.
A transparent, reproducible workflow
The framework organises a science-mapping study into explicit, sequential stages, so that every decision, from data collection and cleaning to the choice of units, networks, and indicators, is made visible and repeatable. The goal is to let readers understand exactly how a result was produced and to reproduce it end to end.
Learning by replication
To show the workflow in practice, the paper replicates an existing study step by step, reconstructing its analyses within Biblioshiny and discussing where and why choices matter. The replication doubles as a hands-on demonstration of how transparent, reproducible science mapping can be carried out without programming.
Cite: Aria, M., Cuccurullo, C., D'Aniello, L., & Spano, M. (2026). Biblioshiny and the SAAS Workflow: An integrated framework for transparent and reproducible science mapping. A demonstration through the replication of a study. Journal of Informetrics. DOI: 10.1016/j.joi.2026.101837