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# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "songR" in publications use:'
type: software
license: MIT
title: 'songR: Self-Organizing Nebulous Growths for Dimensionality Reduction'
version: 0.1.0
abstract: A SONG-inspired tool for nonlinear dimensionality reduction and data visualization
  in R, implementing the Self-Organizing Nebulous Growths (SONG) algorithm of Senanayake
  et al. (2021) <https://doi.org/10.1109/TNNLS.2020.3023941> natively in R and C++
  and staying as close to the reference implementation as is feasible across the two
  ecosystems. SONG is a parametric method that supports incremental addition of new
  data to existing visualizations without reinitialization, handles both homogeneous
  and heterogeneous data increments, and is robust to noise and highly mixed clusters.
  Clustering quality matches the reference closely (validated by reference-parity
  tests); the default visualization is close in global structure but not identical
  in absolute layout. Includes an interactive Shiny application for comparing SONG,
  t-SNE, and UMAP visualizations side-by-side.
authors:
- family-names: Heller
  given-names: R.
  email: raban.heller@uni-ulm.de
  orcid: https://orcid.org/0000-0001-8006-9742
preferred-citation:
  type: manual
  title: 'songR: Self-Organizing Nebulous Growths for Dimensionality Reduction'
  authors:
  - family-names: Heller
    given-names: R.
    email: raban.heller@uni-ulm.de
    orcid: https://orcid.org/0000-0001-8006-9742
  year: '2026'
  notes: R package version 0.1.0
  url: https://github.com/cttir/songR
repository: https://cttir.r-universe.dev
repository-code: https://github.com/cttir/songR
commit: b8572dd53f2b52d1ac32c2dd31995d38552e432e
url: https://cttir.github.io/songR/
date-released: '2026-10-28'
contact:
- family-names: Heller
  given-names: R.
  email: raban.heller@uni-ulm.de
  orcid: https://orcid.org/0000-0001-8006-9742
references:
- type: article
  title: Self-Organizing Nebulous Growths for Robust and Incremental Data Visualization
  authors:
  - family-names: Senanayake
    given-names: Damith A.
  - family-names: Wang
    given-names: Wei
  - family-names: Naik
    given-names: Shalin H.
  - family-names: Halgamuge
    given-names: Saman
  journal: IEEE Transactions on Neural Networks and Learning Systems
  year: '2021'
  volume: '32'
  issue: '10'
  doi: 10.1109/TNNLS.2020.3023941
  start: '4588'
  end: '4602'