Linking forestry concepts, models, and experimental findings via a Knowledge Graph

Dr. Kim Martin has a background in mammalian tissue morphogenesis and a passion for computational modelling of living systems and structures. Kim completed her B.Sc. (Biochemistry; Genetics & Development) and B.Sc.(Med)Hons (Cell Biology) at UCT, Cape Town, and  her Ph.D. in Biomedical Science at the University of Edinburgh, Scotland. During her time at EucXylo she focused on approaches to manage data and setting up modelling frameworks for xylogenesis in eucalypts.

The EuXBrain project is a knowledge graph–based tool developed to support research in Eucalyptus wood formation and ecophysiology. It enables researchers to integrate and explore concepts, datasets, and computational models across multiple biological scales, from cellular processes driving xylogenesis to empirical models of whole-tree growth under varying environmental conditions.

EuXBrain facilitates linked data exploration, allowing users to compare model structures, identify reusable datasets, and assess how different models can be combined. This supports advanced research questions such as model interoperability, data reuse for validation, and cross-scale integration of forest growth simulations.

By adopting common metadata standards and controlled terminology, the platform promotes open science practices and improves knowledge sharing within the forestry modelling community. It also provides a framework for collaborative hypothesis generation and integrated knowledge capture.

Ongoing development focuses on scaling EuXBrain into a fully functional research tool for EucXylo members and collaborators. This includes iterative user testing, refinement based on researcher feedback, and expansion of its ontology framework to ensure compatibility with existing external databases and long-term interoperability.