An R ecosystem for large-scale, on-disk access to OpenAlex — the open catalogue of global scholarly work.

OpenAlex provides free, comprehensive metadata on over 250 million scholarly works, authors, institutions, and concepts. The openalexPro ecosystem is built around a single design principle: process data on disk rather than in memory, so workflows scale to millions of records without hitting RAM limits.

Package	Description	CI	Docs	Install
openalexPro	Core API client — query OpenAlex, page through results, and store everything in Parquet files for efficient downstream use		📖
openalexSnowball	Snowball citation searches — iteratively expand a seed set by following forward and backward citations across the graph		📖
openalexConvert	Export a Parquet corpus to BibTeX, BibLaTeX, CSL JSON, Markdown, LaTeX, HTML, or PDF via Pandoc		📖
openalexSnapshot	Bulk snapshot tools — convert the full OpenAlex JSON.GZ snapshot to Parquet, build ID-lookup indexes, and extract records at scale using a Rust back-end		📖
openalexVectorComp	Text embedding, cosine-distance scoring, and threshold calibration — backend-neutral (HuggingFace, OpenAI, TEI)		📖

Package	Description	CI	Docs	Release
openalex-snapshot	Compiled Rust CLI and library powering openalexSnapshot's hot path (JSON→Parquet conversion, indexing, ID extraction). Downloaded automatically as a pre-built static library on install — no manual Rust setup required for most users.		📖

All R packages are available from the openalexPro r-universe:

install.packages(
  c("openalexPro", "openalexSnowball", "openalexConvert",
    "openalexSnapshot", "openalexVectorComp"),
  repos = c("https://openalexpro.r-universe.dev", "https://cloud.r-project.org")
)

library(openalexPro)

# 1. Query OpenAlex and store results as Parquet
fetch_works(
  query = '"biodiversity" AND "ecosystem services"',
  output = "my_corpus"
)

# 2. Or work directly with the bulk OpenAlex snapshot
library(openalexSnapshot)
oa_snapshot_to_parquet(
  snapshot_dir = "/data/openalex-snapshot",
  parquet_dir  = "/data/openalex-parquet"
)

# 3. Snowball-expand a seed set (optional)
library(openalexSnowball)
snowball(corpus = "my_corpus", depth = 1, output = "my_corpus_expanded")

# 4. Export to BibTeX, CSL JSON, etc.
library(openalexConvert)
corpus_to_csljson("my_corpus", output = "csl/")
csljson_convert_pandoc("csl/", "refs/", to = "bibtex")

• On-disk processing — results are paged and written to Parquet; memory use stays flat regardless of corpus size.
• Arrow / DuckDB throughout — all data manipulation uses columnar formats; SQL queries run in-process.
• Composable — each package has a single responsibility and speaks the same Parquet dialect, so they chain naturally.
• Rust where it matters — the bulk snapshot converter delegates hot-path work to a compiled Rust back-end (openalex-snapshot), with a pure-R/DuckDB fallback for environments without a Rust toolchain.

Issues and pull requests are welcome on the individual package repositories. Please open an issue before starting large changes.

This ecosystem builds on the excellent openalexR package and the OpenAlex team's commitment to open scholarly infrastructure.

The packages are provided as is. The authors are not affiliated with OpenAlex.