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 preserves DOI, title, year, and author count:

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")