Tree-ring research helps us reconstruct past climates, understand how forests respond to environmental change, and provide long-term perspectives for ecology and climate science. New digital imaging tools and machine-learning based analysis methods are now capable of producing tree-ring data at an unprecedented level of detail and scale. However, these valuable datasets are often hard to share and reuse. There is no dedicated repository that can handle their complex structure and metadata while still making them easy to find, explore, and combine. For data producers, collecting and preparing these detailed datasets is very time‑consuming, and it is difficult to publish them in a way that both meets FAIR principles and ensures good visibility and proper recognition. This project addresses these challenges by building and showcasing an online platform for tree-ring intra-annual and anatomy data (the TRIA platform). The platform provides a modern repository for tree-ring data and images, with clear metadata, built-in quality checks, and easy tools for exploring and visualising the data. It is built using open-source technologies (such as PostgreSQL, R and Shiny), is interactive and user-friendly, and supports both public and temporarily embargoed datasets. By assigning DOIs to public datasets and making citation and license information explicit, the platform improves recognition for data producers and encourages sharing. In this way, the project offers a concrete example of how ORD practices can be implemented in a specific scientific community, while creating a sustainable, community-driven resource for future research.