Open-source Raman and FTIR analysis

Free Raman & FTIR analysis, right in your browser.

OpenSpecy helps researchers, students, laboratories, and communities process, identify, visualize, and share spectra through a free browser app and a reproducible R package.

  • No installationUse the hosted browser app
  • Raman + FTIRIndividual, batch, and map data
  • Open and reusableInspect, export, and reproduce results

Choose your route

Start where you are.

Use the browser app for an approachable workflow, follow a guided lesson, or build a scripted analysis with the R package.

Analyze in the browser

OpenSpecy web app

Upload your data or begin with the included test spectra. The interface below runs through Shinylive and WebAssembly in a modern browser.

Interactive workspace Loading application...
Open separately

Loading OpenSpecy

WebR is starting. You can keep reading this page while the application loads.

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

From instrument output to interpretable evidence.

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.

  1. Read

    Import individual, batch, and map spectra from supported instrument and open data formats.

  2. Process

    Apply traceable smoothing, baseline correction, range restriction, alignment, normalization, and quality checks.

  3. Identify

    Compare spectra with managed reference libraries and inspect candidate match evidence.

  4. Quantify

    Summarize materials, ratios, regional area, or intensity measurements for downstream interpretation.

  5. Share

    Export spectra, results, plots, and metadata or reproduce the workflow in R.

Learn OpenSpecy

Follow the full video tutorial.

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

Open tools make spectral evidence easier to inspect, teach, and reuse.

Accessible

Begin in a browser without configuring a local R environment, then move to the package when a scripted workflow is needed.

Transparent

Inspect preprocessing choices, quality information, reference matches, and exported results instead of relying on a closed analysis path.

Reproducible

Use the same core OpenSpecy object model and analysis functions in R for documented, reviewable research.

Community-built

Contribute code, methods, reference spectra, testing, training, or scientific review through an open project.

Peer-reviewed foundation

Publications behind OpenSpecy

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.

2021 · Analytical Chemistry

Microplastic Spectral Classification Needs an Open Source Community: Open Specy to the Rescue!

Win Cowger and collaborators. The foundational paper describing a shared, open approach to spectral classification.

Read via DOI: 10.1021/acs.analchem.1c00123

Reproducible by design

Take the workflow into R.

Install OpenSpecy from CRAN, launch the bundled local app, or compose package functions into an analysis that colleagues can inspect and rerun.

R console
install.packages("OpenSpecy")

library(OpenSpecy)
run_app()

The package website contains written tutorials, reference documentation, release notes, and citation guidance.

Partners and contributors

OpenSpecy grows through shared support.

Financial support, contributed spectra, software expertise, teaching, testing, and scientific review help keep this public resource useful.

See every monetary and in-kind partner

Monetary partners

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).

In-kind partners

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

Help shape what comes next.

Questions, bug reports, new spectra, teaching ideas, scientific feedback, and partnership conversations are all welcome.