Relationship to bibliometrix

Acknowledgement

scimapR is inspired by and designed as a complement to the excellent bibliometrix package by Massimo Aria and Corrado Cuccurullo:

Aria, M. & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. doi:10.1016/j.joi.2017.08.007

bibliometrix is the foundational R package for science mapping. It pioneered many of the analyses that scimapR also provides, and its Biblioshiny app set the standard for interactive bibliometric exploration in R.

scimapR is not a fork, not a derivative, and contains no code copied or adapted from bibliometrix. Where the two packages handle the same bibliographic formats (WoS, Scopus, Cochrane, Lens, Dimensions, PubMed), scimapR ships clean-room parsers written from the public format specifications – never from reading bibliometrix source code.

When to use which?

Feature	bibliometrix	scimapR
Classical bibliometrics	Mature	Available
File parsing (WoS, Scopus, …)	Comprehensive	Clean-room native
Interactive app	Biblioshiny	scimapR Shiny
Provenance tracking	–	First-class
Embedding-based clustering	–	Built-in
Research question objects	–	First-class
LLM-grounded screening	–	Built-in
Corpus certificates	–	Built-in
Author trajectory	–	Built-in
Equity auditing	–	Built-in
LLM corpus chat	–	Built-in

Recommendation: If you are already using bibliometrix and it meets your needs, continue using it. If you need embedding-native analysis, provenance tracking, reproducible certificates, equity auditing, or LLM features, scimapR adds those capabilities.

Round-trip interop

scimapR provides first-class interop with bibliometrix:

library(scimapR)
corpus <- sm_example_corpus(n_works = 20, seed = 42)

scimapR to bibliometrix

# Convert to bibliometrix format
M <- sm_to_bibliometrix(corpus)
class(M)

# Use with bibliometrix analysis functions
bibliometrix::biblioAnalysis(M)

bibliometrix to scimapR

# Convert bibliometrix data frame to sm_corpus
corpus2 <- as_sm_corpus(M)
is_sm_corpus(corpus2)

Round-trip preservation

The round trip keeps the DOIs, titles, abstracts and years of the works and the authors of each work with their addresses. Addresses and other text fields, such as source titles, document types and Keywords Plus, come back in upper case, as bibliometrix stores them:

M <- sm_to_bibliometrix(corpus)
corpus_rt <- as_sm_corpus(M)

# Check preservation
all(corpus$works$doi %in% corpus_rt$works$doi, na.rm = TRUE)

Engine delegation

For shared formats, scimapR readers accept engine = "bibliometrix" to delegate parsing to bibliometrix:

# Use scimapR's native parser (default)
corpus1 <- sm_read_wos("data.txt", engine = "native")

# Delegate to bibliometrix
corpus2 <- sm_read_wos("data.txt", engine = "bibliometrix")

Citation guidance

When using scimapR, please cite both packages:

citation("scimapR")