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Assessing Regional Innovation Potential: A Novel Approach Using OpenStreetMaps Data

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.

topic: Others
type: Deliverable, Methodology, Video
language: English
GEO AI - Enhancing rural development decision-making with PoliRuralPlus

Centered around strengthening rural-urban linkages, this video demonstrates how integrated data analysis - powered by geospatial and AI components - can help policymakers and local communities gain a more holistic view of regional development prospects. At the core of the approach is JackDaw, a geo-enabled chat agent that merges location-specific data with large language model (LLM) reasoning. Key themes and features Multi-dimensional spatial insights: By gathering structured data on a variety of spatial attributes - ranging from population distribution to the presence of cultural sites - JackDaw helps users assess the interdependencies between rural and urban areas, highlighting mutual benefits such as tourism flows or service accessibility. Rural-urban linkage analysis: One exemplary scenario shows how to evaluate a location’s weekend tourism potential, taking into account the number of nearby urban residents, local amenities, and driving distances. This data-driven lens underscores the extent to which rural areas can attract visitors (and thus investment) from surrounding cities. Real-time, context-aware decision support: Unlike generic AI solutions, JackDaw dynamically retrieves up-to-date geospatial information before advising on policy or strategic investments. This ensures the conversation remains contextually grounded in current rural-urban realities, whether in planning new facilities or aligning local services with urban demand. Bridging analytical gaps: The video illustrates how bridging the information asymmetry between rural and urban territories can spur proactive solutions - like improved transport connections or marketing campaigns - ultimately enhancing the well-being of both communities. By demonstrating how robust data analysis can expose latent development opportunities - particularly in the context of rural-urban synergies - this video reinforces PoliRuralPlus’s broader goal of empowering decision-makers to adopt targeted, evidence-based measures that foster balanced, sustainable growth in Europe’s diverse regions.

topic: Policy, Others
type: Deliverable, Policy, Products & prototypes, Video
language: English
GeoAI meets LLMs – Intelligent agents for enhanced decision-making

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.

topic: Others
type: Deliverable, Methodology, Products & prototypes, Video
language: English
Pilot 2: Slovakia

A central objective of the pilot is to transform the “Vision for More Attractive Rural Areas in Slovakia, 2040” from a strategic document into a functioning platform for coordinated territorial action. This requires stronger alignment between national ministries, self-governing regions, municipalities, civil society organisations, youth representatives, academia, businesses and sectoral actors around shared development priorities. The pilot seeks to overcome persistent policy fragmentation and institutional silos while strengthening the connection between rural needs and decision-making, financing mechanisms and governance reforms. Particular attention is given to the everyday realities experienced by rural communities, especially regarding access to public services, sustainable mobility, demographic resilience, opportunities for young people, social inclusion and territorial cohesion. The pilot also contributes to the broader debate on the future governance of rural areas in Slovakia by promoting more participatory, evidence-based and place-sensitive policymaking. Through foresight methods, stakeholder engagement and multi-level cooperation, it aims to create stronger links between long-term visioning, practical implementation and public investment planning. The process supports the emergence of a more coherent national narrative on rural development, capable of connecting economic competitiveness, environmental sustainability, quality of life and social resilience within a shared territorial framework.

topic: Policy
type: Video
language: English
Pilot 3: Central Greece

How the Greek Pilot connects Agriculture, Tourism and Digital Innovation? Central Greece is defined by its vibrant agricultural sector, abundant natural resources, varied landscapes, and significant cultural heritage. This video introduces the Greek Pilot, definied within the concept of PoliRuralPlus project, demonstrating how sustainable agritech, smart agriculture, digital skills, and agritourism can come together to build a more resilient rural–urban ecosystem. Through field demonstrations, collaborative events, and digital innovation initiatives, the pilot unites farmers, researchers, advisors, policy-makers, technology providers, tourism stakeholders, and young professionals. It showcases practical solutions to key challenges, including skills gaps, youth migration away from rural areas, and limited digital capacity in agriculture, while opening up new opportunities for local products, rural entrepreneurship, and sustainable agritourism. Their input gathered from the stakeholder, feeds into the development of the Regional Action Plan, ensuring that local needs, priorities and opportunities are reflected in future actions for the region. The Greek Pilot illustrates how place-based collaboration and digital tools, including the GeoAI chatbot Jackdaw, can strengthen evidence-based decision-making and help rural areas become more connected, inclusive, and future-ready. 🔗 More about the Greek pilot: https://www.poliruralplus.eu/pilots/r...

topic: Agriculture, Tourism
type: Video
language: English