---
title: "Relationship to bibliometrix"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{Relationship to bibliometrix}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
resource_files:
- figures/logo.svg
- figures/logo-dark.svg
---
[](https://github.com/CTTIR/scimapR/actions/workflows/R-CMD-check.yaml)
[](https://cttir.github.io/scimapR/)
[](https://CRAN.R-project.org/package=scimapR)
[](https://app.codecov.io/gh/CTTIR/scimapR?branch=main)
[](https://cran.r-project.org/package=scimapR)
[](https://cran.r-project.org/package=scimapR)
[](https://opensource.org/licenses/MIT)
[](https://lifecycle.r-lib.org/articles/stages.html#experimental)
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
```
## 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:
```{r setup}
library(scimapR)
corpus <- sm_example_corpus(n_works = 20, seed = 42)
```
### scimapR to bibliometrix
```{r to-bib, eval = FALSE}
# Convert to bibliometrix format
M <- sm_to_bibliometrix(corpus)
class(M)
# Use with bibliometrix analysis functions
bibliometrix::biblioAnalysis(M)
```
### bibliometrix to scimapR
```{r from-bib, eval = FALSE}
# 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:
```{r roundtrip, eval = FALSE}
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:
```{r engine, eval = FALSE}
# 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:
```{r citation, eval = FALSE}
citation("scimapR")
```
