TAMC-PLANTAS derived dataset: pipeline-ready plant electrophysiology recordings for reproducible multiband bioelectrical analysis

This record contains a derived, attribution-preserving and pipeline-ready dataset package for TAMC-PLANTAS, a reproducible multiband analysis pipeline for plant bioelectrical recordings. The raw plant electrophysiology recordings are derived from the public source-data package associated with: Madariaga, D., Arro, D., Irarrázaval, C., Soto, A., Guerra, F., Romero, A., Ovalle, F., Fedrigolli, E., DesRosiers, T., Serbe-Kamp, É., & Marzullo, T. (2024). A library of electrophysiological responses in plants – A model of transversal education and open science. Plant Signaling & Behavior, 19(1), 2310977. Associated article: https://doi.org/10.1080/15592324.2024.2310977 Original source data: https://figshare.com/s/65447c618656565467e6 Original license: Creative Commons Attribution 4.0 International (CC BY 4.0) This Zenodo package does not replace the original Figshare source-data release and does not claim authorship over the original recordings. Full credit for the original data collection, experimental work and public release belongs to the original authors. The purpose of this derived package is to provide a stable, citable, Zenodo-hosted dataset suitable for automated reproducibility checks, independent pipeline execution and audit-oriented verification workflows. Changes made in this derived package: - reorganized the recordings into a deterministic TAMC-PLANTAS species-level folder structure; - removed nested-archive ambiguity by providing a direct pipeline-ready data/raw_plants/ structure; - added SHA-256 checksums; - added machine-readable file manifests; - added species-level metadata; - added provenance documentation; - added source attribution and license notes; - prepared the dataset for direct reproducible execution of the TAMC-PLANTAS pipeline. The original Figshare ZIP is not embedded in this package in order to avoid nested-archive ambiguity during automated reproducibility checks. Instead, this record provides a direct pipeline-ready data/raw_plants/ structure together with source attribution, provenance metadata, SHA-256 checksums and machine-readable manifests. Users of this dataset should cite both the original Madariaga et al. (2024) article/source data and this derived Zenodo dataset.