This segment highlights how rural-urban communities can harness open citizen science data - particularly from OpenStreetMap (OSM) - to better understand, compare, and ultimately enhance their innovation potential. By deploying kernel density estimation (KDE) and other advanced spatial analyses, PoliRuralPlus provides a fine-grained look at the distribution of innovation-related assets - such as research institutions, technology hubs, and digital infrastructure - within and across nine pilot regions ranging from Ireland to Latvia. Traditional methods often rely on broad, aggregated statistics that obscure local nuances. In contrast, PoliRuralPlus’s geospatial approach pinpoints specific innovation “hotspots” and spotlights areas requiring further investment or collaboration. Communities benefit directly from these insights by identifying tangible opportunities - such as clustering similar enterprises, establishing shared R&D facilities, or enhancing connectivity - and pursuing tailored policy interventions based on real-time, crowd-sourced data from OSM. Furthermore, these open datasets pave the way for future AI-driven applications within PoliRuralPlus and beyond. Machine-learning tools, for instance, can draw on these spatial indicators to forecast shifts in regional development, evaluate policy impacts, or suggest new ventures. By merging citizen science data, geospatial analysis, and AI, the video underlines a forward-looking strategy to bridge the innovation gap between urban and rural areas, thereby promoting more balanced and evidence-based territorial growth.
The stakeholders to be identified in this deliverable D2.1 database of the PoliRuralPlus project include local communities, governments, farmers, SMEs, industry associations, research institutions, NGOs, civil society groups, infrastructure providers, digital technology companies, financial institutions, and tourism sector representatives. These stakeholders play crucial roles in driving and shaping rural-urban linkages and opportunities within the project area. The database of the PoliRuralPlus stakeholders in the 9 pilot regions is defined, and how communication channels will be established with them, as the basis for the project’s analysis of the rural-urban linkages and opportunities as well as the Impact of COVID19, to identify the most appropriate integrated urban-rural strategies.
This report presents a comprehensive analysis of rural-urban linkages and opportunities across Europe, focusing on economic, social, and environmental dimensions and the effects of COVID-19. It reviews relevant data sources, models, and standards to ensure interoperability and supports evidence-based policy through an interactive dashboard enabling “what-if” analyses. The study integrates literature reviews, stakeholder consultations, and cross-pilot data evaluation to identify challenges, best practices, and strategies for strengthening territorial cohesion. Findings inform the development of Regional Action Plans (RAPs) under the PoliRuralPlus framework, enhancing foresight, governance, and sustainable development capacities for balanced, inclusive, and resilient rural-urban communities.
Methodological framework and toolbox for the creation of Regional Action Plans for the 9 pilot regions of the project. It is based on the use of Foresight. It includes methods for the co-design of no-code / low-code tools based on AI and automation to support RAP creation and other complex tasks of people working in local administration in rural areas of the EU. This provides a basis for cooperation with WP4. The results of these efforts will provide a basis for the updated RAP methodology guide D3.2 to be provided in M36 of the project.
The PoliRuralPlus Platform Design (D4.1) outlines the development of a modular, scalable digital ecosystem aimed at fostering sustainable, balanced, and inclusive rural-urban development. Building on the foundations of the original PoliRural project, the platform integrates advanced geospatial tools, AI technologies, and data sources to address regional development challenges. Key components include AI-driven models, data management services, and collaborative applications tailored to enhance policy-making, foresight analysis, and stakeholder engagement. The design emphasizes interoperability, real-time data integration, and user-centric development, ensuring adaptability within existing regional infrastructures. The platform supports objectives aligned with the European Green Deal, promoting innovation, resilience, and evidence-based governance strategies across diverse rural and urban regions.
Deliverable D5.1 "Prepared pilot by Stakeholder Multi-Actor Approach" is part of T5.1. collaboration with stakeholders identified in T3.2 is established to contribute to the preparation and development of Regional Action Plans (RAPs). Through the Multi-Actor Approach, communication with stakeholders helps identify gaps, challenges, and opportunities in the pilot regions.
Deliverable D5.2 “Regional Action Plans – Consolidation and Cross-Pilot Synthesis” presents the progress made by the nine PoliRuralPlus pilot regions in 2025 as they moved from the design to the implementation phase of their Regional Action Plans (RAPs). The document consolidates the methodological, governance, and monitoring frameworks developed during the first project period and integrates feedback from the Mid-Term Review. Each RAP has been updated using the harmonised RAP Template 3.0, incorporating Gantt-based roadmaps, a refined KPI framework, and cross-cutting elements such as sustainability, gender and diversity awareness, and policy alignment with the Green Deal, CAP, NEB, and LTVRA. The process has been supported by strong cooperation among work packages—WP2 (foresight and governance), WP3 (methodology), WP4 (digital tools), WP6 (innovation), and WP7 (monitoring and exploitation)—ensuring coherence between regional action, innovation, and impact evaluation. The deliverable also highlights early results in stakeholder engagement, governance integration, and interregional learning. It sets the stage for the final phase of the project, where D5.3 (Effectiveness of the Multi-Actor Approach) and D5.4 (RAP Monitoring – Third Year) will document implementation progress, assess sustainability, and consolidate transferable best practices for replication across Europe.
This report presents exploitation roadmaps to 2030 and beyond, based on Key Exploitable Results (KERs) and tailored to specific regions. The roadmaps encompass societal impact, research and innovation, capacity building, business and financial growth, and policy development, ensuring long-term benefits for rural and urban stakeholders.
This video compares pure large language model (LLM) outputs, such as those generated by ChatGPT, with the JackDaw (agentic tool-calling) approach. Through three real-world use cases, viewers see how incorporating domain-specific data and specialized tools yields more accurate, context-aware, and actionable answers: Weather Query Pure LLM: Provides only a generic explanation or refers to external sources, lacking direct real-time data. JackDaw (Agentic System): Dynamically calls a weather API tied to a specific area on the map, integrating real-time geospatial information. This ensures precise, location-focused forecasts rather than vague or outdated responses. Agricultural Suitability Analysis Pure LLM: Offers broad advice for potato farming, without factoring in specific local attributes like climate or soil characteristics. JackDaw: Merges real-time environmental data (land cover, elevation, weather) and LLM reasoning to assess whether a particular plot is suitable for potatoes. By pinpointing topographical and meteorological conditions, it delivers targeted, evidence-based recommendations. Identifying Water Bodies Pure LLM: May produce incorrect or incomplete references (e.g., citing the wrong river or distant city). JackDaw: Leverages land cover tools to examine hydrological layers in the specified area, accurately detecting water features. This results in data-driven, localized insights and avoids errors that arise when relying on a general model alone. Overall, the video illustrates how the JackDaw approach outperforms a standard LLM in terms of reliability, specificity, and practical utility. By integrating specialized data sources and real-time analysis into the decision-making workflow, the agent-based system consistently delivers more relevant, location-aware responses—demonstrating a clear advantage over purely text-based AI outputs.
Webinar of the PoliRuralPlus series, titled "Lessons Learned Part 1", was held virtually on March 27, 2024. The session aimed to disseminate experiences and knowledge accrued from the PoliRural project, focusing on Foresight methodologies applied across various European regions. The webinar featured insightful contributions from key participants including Gabriel O’Connelll and John O’Flaherty from the Monaghan pilot, Santa Vītola from the Vidzeme pilot, and Tuula Löytty from the Southern Finland pilot. They shared significant feedback based on their extensive experiences with the Foresight process within the PoliRural framework.
The FarmTourist project was carried out as part of the PoliRuralPlus Outreach Call with the goal of connecting small and medium-sized farms, gastronomy, and tourism. The project focused on identifying specific needs and proposing practical solutions. During its implementation, data was collected from stakeholders and analyzed for more effective integration of local producers into the tourism infrastructure. The project’s outcomes provide a basis for the future development of the region and highlight important steps for strengthening economic sustainability.
Scoping Exercise to Identify Opportunities for Job creation and Business Growth in the Circular Economy in County Monaghan IRELAND.
The Agrifusion project seeks to transform the country’s agricultural landscape by integrating digital innovation, policy reform, and stakeholder collaboration.
The DEMO-IT project contributed to the exchange of experiences and the identification of stakeholders’ needs for the promotion and development of Short Food Supply Chain (SFSC) models in the Apulia region (Italy). Representatives of different local actors and experts of the local food system were invited to compile a questionnaire and participate to the focus groups organised by the project. The results of the consultation are reported in this document and will serve as an input for further discussion with regional policy makers about measures to improve and support SFSC models. Similarly, the information collected in this phase will be used in the next phase of the POLIRURALLUS project as a basis to exchange ideas and promote solutions that foster the local food system.
The DigiStake project aimed to support rural development in Slovakia through enhanced stakeholder collaboration and digital transformation. The main output of the project was the development of an online space, accessible at https://atraktivnyvidiek.sk, which facilitated the exchange of ideas, digital innovation, and integration into broader EU strategies. Through stakeholder engagement, user needs assessments, and the implementation of innovative digital solutions, DigiStake enhanced digital literacy and promoted sustainable rural development. The findings highlighted key challenges such as digital literacy gaps and limited stakeholder engagement, while proposed solutions included an interactive platform, participatory vision building, and targeted digital training.
Economic Development Quality Monitoring System for the Vidzeme Region. The VPR EcDevMon project has developed a comprehensive strategy to enhance the quality monitoring system for the economic development of the Vidzeme region, ensuring a structured, data-driven, and effective approach to fostering long-term sustainability. This strategy is anchored in in-depth data analysis and active stakeholder engagement, creating a transparent and evidence-based governance framework.
The PoliRuralPlus project has launched an innovative tool designed to support regional action plans, offering a digital "caddy" to guide stakeholders through complex data and planning processes. This tool, known as the PoliRuralPlus GPT, leverages the capabilities of advanced language models to provide tailored advice and insights specific to the needs of rural-urban regional planners.
The second webinar of the PoliRuralPlus series, entitled "Lessons Learned Part 2," was conducted on April 22, 2024. This session continued the exploration of the advancements and insights gained from the initial phase of the PoliRural project, focusing specifically on the development and application of innovative tools to support rural development. This webinar provided an in-depth discussion on three pivotal tools developed during the PoliRural project, aimed at enhancing the semantic analysis of texts, exploring policy options, and evaluating the attractiveness of rural regions. These tools are essential for stakeholders involved in regional planning and policy-making.
TRAINING WEBINAR The third webinar in the PoliRuralPlus series, focusing on the Rural Area Planning (RAP) methodology, was conducted on May 8, 2024. This session provided an overview of the methodological framework designed to guide participants in developing impactful rural area plans.The workshop was dedicated to the discussion and dissemination of the RAP methodology, a structured approach intended to aid participants in crafting comprehensive and effective rural area plans. The methodology emphasizes the importance of thematic selection, particularly in areas requiring urban-rural policy coordination.