TRIA — Tree Ring Intra-annual and Anatomical data — is a curated repository for quantitative wood anatomy (QWA) datasets produced with ROXAS and ROXAS AI.
High-resolution, cell-level tree-ring data hold immense potential for advancing climate science, ecology, and dendrochronology. TRIA ensures these datasets are preserved, discoverable, and properly credited.
TRIA is currently in early access. Some features are still in development and content may change.
Standardized QWA datasets with validated, structured metadata.
Visualise and assess data quality directly in the browser before downloading.
Every dataset is citable, public datasets will receive a DOI. Data producers are acknowledged for their work.
Optional embargo periods and clear licensing protect contributors while promoting open science.
Intra-annual tree-ring datasets are collected at significant effort---requiring specialised equipment, software, and expertise. Yet much of this data remains inaccessible to the wider community, stored on local hard drives and at risk of being lost or underutilised. At the same time, the effort of producing and publishing QWA data is rarely acknowledged in proportion to the work involved.
TRIA addresses both problems: a dedicated platform that makes QWA data findable and reusable, while ensuring contributors receive the recognition they deserve through transparent licensing and citable DOIs. By aligning with FAIR principles, TRIA supports cutting-edge research and fosters collaboration across disciplines.
To get started,
TRIA is a modern, flexible repository tailored to intra-annually resolved wood cell anatomical data and associated images.
TRIA is designed to facilitate research on dendrochronology at intra-annual resolution by promoting the sharing of high-quality, well-documented datasets following FAIR principles. It is a modern, flexible repository hosted and curated by the Dendrosciences research group at the Swiss Federal Institute for Forest, Snow and Landscape Research WSL . Currently, TRIA supports quantitative wood anatomy (QWA) data produced via the ROXAS or ROXAS AI software.
TRIA provides a community-specific, user-friendly platform where researchers can deposit, discover, and reuse QWA datasets. Core features include:
Explore datasets and assess quality before downloading.
Every open dataset will receive a citable, persistent identifier.
Standardized structure and validation allows for quality assessment of each dataset.
Protect data linked to ongoing publications until you're ready to share.
Quantitative wood anatomy (QWA) investigates how the variability in xylem anatomical features of trees, shrubs, and herbaceous species is related to plant functioning, growth, and environment. Anatomical features — including lumen dimensions, wall thickness of conducting cells, and ray properties — can be localised within annual growth rings, enabling intra-annual structure-function relationships to be established and their sensitivity to environmental variability to be assessed ( von Arx et al., 2026 ).
Tree-ring research has played a pivotal role in reconstructing past environmental conditions, understanding climate variability, and tracking ecological change. Advances in imaging technology and AI — embodied in tools like ROXAS and ROXAS AI — now make it possible to produce intra-annual, cell-level anatomical data at unprecedented scale and quality.
Despite this, valuable QWA datasets frequently go unpublished. Collection is resource-intensive, and the incentive structures for sharing data openly remain weak. TRIA was created to change that.
TRIA is developed and maintained at the WSL .
The project has received funding from the ORD Program of the ETH Domain Measure 1 Call . Questions? Contact us at tria@wsl.ch .
Image analysis software for quantifying xylem anatomy in angiosperms and conifers. Learn more →
R package to prepare ROXAS / ROXAS AI output files for TRIA submission. Learn more →
Database schema · Metadata JSON schema · Attribute and parameter definitions (coming soon)
For annually resolved tree-ring data. Visit ITRDB →
Environmental data portal and repository of WSL. Visit EnviDat →
The policies below outline the responsibilities and conditions for researchers submitting QWA data to the repository or using datasets distributed via the platform. These policies are subject to change by the TRIA platform owners at any time and without notice. The updated policies will be posted on the platform website www.webapps.wsl.ch/tria . For any questions, please contact tria@wsl.ch .
Draft; last updated 05.2026
This section describes how TRIA handles personal data.
This section describes the policies governing metadata associated with datasets in the TRIA repository.
This section describes the policies governing all content items in the TRIA repository, including data and supporting materials.
This section describes the policies governing the submission of datasets to the TRIA repository.
rxs2tria
R package prior to submission.
As TRIA expands to support additional data types, corresponding extensions to the package will be made available.
This section describes the policies governing the long-term retention, accessibility, and integrity of metadata and content items in the TRIA repository.
This policy is based on the EnviDat policy v.2.0 .
TRIA is a community resource. Whether you're here to access datasets for your research or to contribute your own, here's how to get started.
Browse, explore, and download QWA datasets for your research.
Go to usage guidelines →Share your QWA datasets with the community and get a citable DOI.
Go to submission guide →All datasets on TRIA are freely accessible through the Browse tab. No registration is required to explore the platform or download publically available data.
Each dataset is published under a license chosen by the contributor. Check the license displayed on the dataset page before using the data. Usage must comply with its terms.
Always use the citation information provided (including the DOI if available) in any publication or output that makes use of TRIA data. This directly supports the contributors who produced it.
Where appropriate, acknowledge TRIA as the data source. Suggested citation formats are shown on each dataset page.
See the Data policy section on the About page for full details on acceptable use.
TRIA is in early access but open to contributions. The initial focus is on QWA datasets generated with ROXAS or ROXAS AI. If you have such data you wish to contribute, please contact us .
We currently welcome submissions of QWA datasets produced with ROXAS or ROXAS AI.
All submissions are required to be standardized and validated with the
rxs2tria
R package.
To do so, follow the instructions of the
rxs2tria
R package
here →
Structure your data and metadata according to the submission requirements below.
Use the
rxs2tria
R package on your raw ROXAS or ROXAS AI output files.
Choose a license, set an embargo period if needed,
and confirm authorship and citation details in the
rxs2tria
Shiny app.
Upload your prepared dataset to a file sharing service of your choice (e.g. Google Drive, Dropbox, institutional FTP). Send the download link to tria@wsl.ch . You will receive confirmation once we have validated your submission.
Your dataset is added to TRIA, credited to you, and---if open---will be assigned a DOI.
Datasets must be produced with ROXAS or ROXAS AI and prepared with
rxs2tria
.
Raw or processed images may also be included with the submission.
Complete provenance information is required: species, site location, sampling year, coordinate system, and processing details. The metadata must comply with the TRIA JSON schema .
Submissions are checked for formal consistency by the TRIA team. Datasets that do not meet minimum quality standards will not be accepted. Data contributors are solely responsibly for the quality and accuracy of their data.
All submissions must comply with the Data policy
Contributors choose a Creative Commons license at submission. CC BY 4.0 is recommended — it maximises reusability while ensuring attribution. More restrictive licenses (e.g. CC BY-NC) are available if needed.
An optional embargo period of up to 10 years is available for datasets linked to manuscripts in preparation or under review. Embargoed datasets are not yet elligible for a DOI. The embargo can be lifted at any time.
Step-by-step instructions for preparing and submitting a dataset. Read →
Full list of required and optional metadata fields with definitions. Read →
Source code, issue tracker, and technical documentation. View repository →
Questions or issues? Reach us at tria@wsl.ch or open an issue on GitHub.