Problem, build and result — with the detail that doesn't fit on the card.
- Problem
- Ethnobotany research produces a kind of data that's hard to organize: what a person says about a plant — its local name, its uses — has to end up linked to the correct scientific species, without losing what was said in the field. Mercedes, an Avalon partner and biologist, lived this in her thesis: dozens of interviews and thousands of use reports being typed by hand into Excel, with hours of transcription and room for error in every row.
- Build
- We built Padiush, a web platform for ethnobotany research. It designs interview instruments, captures the responses, and — the part Excel doesn't do — reconciles each name reported in the field with its scientific taxon against authorities like World Flora Online and GBIF, always preserving the original name for traceability. From there it calculates the field's quantitative indices (use value, cultural importance, informant consensus factor, among others) and exports tables, charts and matrices ready for R. Laravel and React on the web; a field-capture app is in development.
- Result
- With Padiush, Mercedes processed her thesis data — 89 interviews and 2,457 use reports — and the platform was cited both in her thesis (2025) and in a peer-reviewed scientific article (2026). Together we presented Padiush at the VII Latin American Congress of Ethnobiology (SOLAE) in Tlaxcala, Mexico (2022), and facilitated a course at the VIII Congress, in Antigua Guatemala (2025). We saw the tool was useful beyond ourselves, and wanted to put it within reach of other researchers.
Ethnobotany research — the study of the relationship between people and plants — produces data that's awkward for a spreadsheet. A field interview records what someone says: a plant's local name, what they use it for, in what category. That knowledge has to end up linked to the correct scientific species, but without erasing what the person said. Mercedes, an Avalon partner and biologist, faced this in her thesis: dozens of interviews and thousands of reports being typed by hand into Excel, with hours of transcription and a possible error in every row.
We built Padiush to solve that whole workflow. You design the interview instrument, capture the responses, and then comes the part no spreadsheet does on its own: reconciling each reported name with its scientific taxon, against botanical authorities like World Flora Online and GBIF distribution data, always keeping the original name for traceability. On top of that already-structured data, the platform calculates the field's quantitative indices — use value, cultural importance, informant consensus factor, fidelity level — and exports tables, charts and the matrices the ethnobotanyR package expects. The web app is built in Laravel and React; a field-capture app is in development.
Padiush grew alongside Mercedes's work. It began as the prototype she used to process her thesis in 2021, became the version we presented together at the VII Latin American Congress of Ethnobiology (SOLAE) in Tlaxcala, Mexico, in 2022, and kept maturing through the course we facilitated at the VIII Congress, in Antigua Guatemala, in 2025. Mercedes has also facilitated courses on Padiush at the School of Biology of the University of El Salvador. The platform was cited in her thesis (2025) and in a peer-reviewed scientific article (2026).
It started as an internal tool for a partner's real problem. But the problem wasn't only hers — anyone doing ethnobotany research has it. We saw the tool was useful beyond ourselves, and wanted to put it within reach of other researchers. That's the project: a field problem turned into an instrument others can use.
LARAVEL · REACT · RESEARCH · DATA
