A Knowledge-Driven Framework for a Decision Support Platform in Sustainable Viticulture: Integrating Climate Data and Supporting Stakeholder Collaboration

Viticulture in Montenegro faces significant challenges due to fragmented data management, limited access to high-resolution climate predictions, and the lack of systematic integration between stakeholders. This study addresses these issues by proposing a knowledge-driven system architecture that consolidates climate and phenology data, facilitates multi-level data sharing, and supports informed decision-making for sustainable vineyard management. Using Montenegro as a case study, the proposed decision support platform integrates data from Internet of Things-enabled climate pilots, existing databases, and predictive modeling tools to address limitations in existing datasets, such as low resolution and inaccurate downscaling methods, and to tackle the broader challenges posed by climate change, including shifting weather patterns and phenological cycles. The system architecture provides a framework for stakeholders, including researchers, winegrowers, and policymakers, to collaborate effectively, bridging the gap between localized data collection and high-level decision-making. The paper outlines the current state of viticulture in Montenegro and the EU, highlights the need for a systematic approach to data management, and details the benefits of such a system at various levels. The proposed platform architecture and implementation steps outlined in this study serve as a robust framework, offering valuable guidance for other countries seeking to establish similar systems to enhance the efficiency, sustainability, and resilience of their viticulture sectors. This research contributes to the broader understanding of knowledge-driven systems in precision agriculture and provides a scalable model for regions facing similar challenges.