Proposing an Ontology for the Innovative Design of Future-Ready Forest Decision Support Systems
Abstract
Forest decision-making is becoming increasingly complex due to shifting environmental conditions, rising uncertainty, and evolving societal demands linked to climate change, stakeholder preferences, and forest multifunctionality. To support sustainable forest management effectively, Decision Support Systems (DSS) must integrate diverse information and knowledge sources, objectives, and decision contexts, which poses a number of challenges in their conceptual design.We developed a shared knowledge base for integrated forest DSS by formalizing a domain ontology, building on a decade-long knowledge repository developed in the context of European network activities (e.g., Community of Practice ForestDSS, COST FORSYS, DSS4ES). Through an expert-driven revision and validation process, we refined concepts and definitions, improved structural coherence, and identified missing elements relevant to both current and future decision contexts.The resulting ForestDSS ontology highlights central components and design elements of forest DSS, with particular focus on climate sensitivity, natural disturbances, ecosystem services, and landscape-scale interactions. By explicitly representing these components (e.g. data, models, methods, user interface) and their relationships, the ontology provides a structured framework to design, document, compare, and evaluate DSS for multifunctional forest management.This ontology-based knowledge structuring supports improved characterization of existing DSS and accelerates the development of next-generation tools. It enables transparent concept reuse, more consistent integration of models, data, and stakeholder inputs, and clearer communication across disciplines. The ForestDSS ontology thus serves as a collaborative knowledge resource for research, education, and practice, supporting sustainable forest management at the landscape scale.
Fields of Study & Subjects
Forest Management and Policy
Semantic Web and Ontologies
Decision Support System Applications
Publication details
- Journal / source
- EGU General Assembly Conference Abstracts
- Publication date
- 14 March 2026
- Language
- EN