New users and students
Analyze with visual guidance
Load a spectrum in the browser, explore each processing choice, inspect candidate matches, and download your results.
Open-source Raman and FTIR analysis
OpenSpecy helps researchers, students, laboratories, and communities process, identify, visualize, and share spectra through a free browser app and a reproducible R package.
Choose your route
Use the browser app for an approachable workflow, follow a guided lesson, or build a scripted analysis with the R package.
New users and students
Load a spectrum in the browser, explore each processing choice, inspect candidate matches, and download your results.
Researchers and laboratories
Process individual spectra, batches, or hyperspectral maps; assess quality; compare references; summarize materials; and export evidence.
Funders and collaborators
Help maintain accessible spectral tools, shared reference data, training resources, and transparent methods for a growing community.
Analyze in the browser
Upload your data or begin with the included test spectra. The interface below runs through Shinylive and WebAssembly in a modern browser.
The hosted edition uses compact medoid and model libraries selected for browser delivery. The local R package can also access larger reference libraries. Reference matches support interpretation and should be reviewed alongside instrument quality assurance, controls, and domain expertise.
An open analysis path
OpenSpecy organizes Raman and Fourier-transform infrared spectra into a visible, reusable workflow. The same project supports approachable browser analysis and composable R functions.
OpenSpecy supports scientific judgment; it does not replace appropriate controls, expert review, or validation for a specific application.
Import individual, batch, and map spectra from supported instrument and open data formats.
Apply traceable smoothing, baseline correction, range restriction, alignment, normalization, and quality checks.
Compare spectra with managed reference libraries and inspect candidate match evidence.
Summarize materials, ratios, regional area, or intensity measurements for downstream interpretation.
Export spectra, results, plots, and metadata or reproduce the workflow in R.
Learn OpenSpecy
See the app workflow from start to finish, then use the written documentation when you want a step-by-step reference or function-level detail.
Prefer a new tab? Watch on YouTube.
Why the project matters
Begin in a browser without configuring a local R environment, then move to the package when a scripted workflow is needed.
Inspect preprocessing choices, quality information, reference matches, and exported results instead of relying on a closed analysis path.
Use the same core OpenSpecy object model and analysis functions in R for documented, reviewable research.
Contribute code, methods, reference spectra, testing, training, or scientific review through an open project.
Peer-reviewed foundation
Cite the 2025 Open Specy 1.0 paper when using the current software. The 2021 paper introduced the open-source community approach to microplastic spectral classification.
2025 · Analytical Chemistry
Win Cowger and collaborators. Analytical Chemistry, 97(32), 17345–17356.
Read via DOI: 10.1021/acs.analchem.5c009622021 · Analytical Chemistry
Win Cowger and collaborators. The foundational paper describing a shared, open approach to spectral classification.
Read via DOI: 10.1021/acs.analchem.1c00123Reproducible by design
Install OpenSpecy from CRAN, launch the bundled local app, or compose package functions into an analysis that colleagues can inspect and rerun.
install.packages("OpenSpecy")
library(OpenSpecy)
run_app()
The package website contains written tutorials, reference documentation, release notes, and citation guidance.
Partners and contributors
Financial support, contributed spectra, software expertise, teaching, testing, and scientific review help keep this public resource useful.
Thriving monetary partners $10,000–$100,000
Maintaining ($1,000–$10,000): University of California, Riverside; National Science Foundation; Alfred Wegener Institute; Hawai'i Pacific University; National Institute of Standards and Technology; University of Toronto; University of Koblenz-Landau; Thermo Fisher Scientific.
Supporting ($100–$1,000): Jennifer Gadd.
Saving (under $100): Anne Jefferson; Heather Szafranski; Gwendolyn Lattin; Collin Weber; Gregory Gearhart; Anika Ballent; Shelly Moore; Susanne Brander (Oregon State University); Jeremy Conkle (Texas A&M University–Corpus Christi).
Thriving ($10,000–$100,000): Win Cowger; Zacharias Steinmetz.
Maintaining ($1,000–$10,000): Garth Covernton; Jamie Leonard; Shelly Moore; Rachel Kozloski; Katherine Lasdin; Aleksandra Karapetrova; Laura Markley; Walter Yu; Walter Waldman; Vesna Teofilovic; Monica Arienzo; Mary Fey Long Norris; Cristiane Vidal; Scott Coffin; Charles Moore; Aline Carvalho; Shreyas Patankar; Andrea Faltynkova; Sebastian Primpke; Andrew Gray; Chelsea Rochman; Orestis Herodotu; Hannah De Frond; Keenan Munno; Hannah Hapich; Jennifer Lynch.
Supporting ($100–$1,000): Alexandre Dehaut; Gabriel Erni Cassola.
Contact and community
Questions, bug reports, new spectra, teaching ideas, scientific feedback, and partnership conversations are all welcome.