The increasing availability of tree physiological data provides unique opportunities for exploring tree and forest function, health, and resilience to ongoing environmental changes. However, processing such datasets is challenging, due to data quantity and quality, labor-intensive data cleaning, user-specific assumptions, and methodological uncertainties. Within this workshop we aim at addressing some of these issues though a toolbox of novel R packages geared towards comprehensive tree physiological data processing. We provide participants hands-on training on free software tools and their synergies for tree physiological data processing, spanning from interactive visual inspection and cleaning of raw data to advanced data analyses and uncertainty quantification. Three main topics are covered: (1) Interactive data cleaning with ‘datacleanr’ (https://the-hull.github.io/datacleanr/), an R package designed to ensure best data-handling practices of spatiotemporal tree ecophysiological data. (2) Sap flow data processing with the ‘TREX’ (https://the-hull.github.io/TREX/), including gap-filling thermal dissipation data, converting heat metrics to sap flow, and estimating data-processing uncertainties. (3) Dendrometer data processing with ‘treenetproc’ (https://github.com/treenet/treenetproc/), an R package with advanced functionalities on partitioning stem growth and hydraulic signals from dendrometer data and on detecting growing season dynamics. Guided by example datasets, this workshop presents a toolbox for interactive and reproducible tree physiological data processing in R. Participants should bring their own laptops with pre-installed R/RStudio (https://rstudio.com/). Data files and codes for this workshop will be made publicly available, so participants and those unable to attend will have access to these resources.