Exploring Rural Data Landscapes – A Benchmark of Performance and Costs in the EU and beyond

Through collaboration with and input from regional, national, and international data providers, Living Labs, and statistical offices, we evaluated the performance and costs associated with acquiring data relevant for rural territories at various geographical scales. The resulting document presents a compilation of 27 data fiches, a comprehensive exploration of data costs and dimensions through a survey, and nine inspirational examples of data, tools, and approaches. The document seeks to inform GRANULAR's Living and Replication Labs, as well as data users and providers from various levels, about practical insights into data collection types and costs for rural territories, their challenges, and opportunities. The outlined cost categories, spanning data infrastructure, governance, model training, security, and more, provide a robust framework for understanding and managing the complexities associated with enriching knowledge and advancing data-driven initiatives for policy making in rural contexts. 

The Survey engaged national statistical offices and data providers, yielding 17 responses from 16 different countries, and focused on data availability, costs, and user information. The survey delves into the landscape of data accessibility applied to rural development across several European countries. The report highlights key open databases, data domains, and types of data available at no cost, revealing variations in resolution and thematic coverage. The majority of surveyed offices make over 500 data files freely accessible, with primary domains including demography, economy, agriculture, and tourism. While most respondents adhere to Eurostat guidelines, data types vary, encompassing tabular, grid-level, vector, and raster data. Notably, the report touches upon the diverse bases for user charges, with some offices levying fees for data compilation or structuring. The analysis underscores the crucial role of individuals, research organizations, and the private sector as the main users of these datasets, emphasizing the multifaceted demand for demographic, economic, and development-focused information.

Data fiches were compiled for 27 datasets that capture a wide range of rural data types, and include a description of the data, including indicator class, data class, spatial and temporal information, a short description and how to cite it. Cost information include data infrastructure costs, e.g. software or hardware needed or costs for data repositories / storage. Data Governance & Management costs, i.e. costs needed to work with the data e.g. comprises information about staff costs needed to work with / access the data, for data analysis, quality assurance and “cleaning” data. Authors also reflect on data documentation costs. Data covered the 4 rural functions identified in the Rural Compass (productive, residential, environmental, recreational), with a variety of domains, such as accessibility, agriculture, climate, demography, digitalization, economic development, energy, health, infrastructure, mobility, recreation, and transversal.

The inspirational examples showcase data collection and provision methodologies that have been implemented at local and international scales. Each example was documented with a structured overview including costs, photos, and a matrix of key insights, policy implications, and future considerations. The aim is to inform actors on the diversity of methods and data that can be collected and the costs that are associated with such initiatives. Examples include:

• Indicator to monitor the subjective well-being of the rural population during the CAP programming period in
• Finland (National)
• Rural Barometer Finland (National)
• Monitoring mobility and road traffic at local scale in France (Local)
• Telecare for the elderly at home – Galicia / Spain (Local)
• Functional & spatial diagnosis for social revitalization – Poland (National)
• Scottish National Islands Plan Survey (Regional)
• Web-mapping tool to visualize proximity to different services - Nordic countries (International)
• Enhancing accessibility & understanding of rural land use data – EU (International)
• Earth Observation & Citizen Science – Geo-Wiki (Locally informed, international coverage)

The holistic approach chosen in this document with three focus areas enables a comprehensive understanding of rural data, costs, and innovative examples for evidence-based policy-making.

Effectively utilizing open data in rural territories within the EU demands strategic investments in capacity building, with an emphasis on training local personnel in Geographic Information System (GIS) and data management. The estimated annual cost of employing entry-level GIS technicians ranges from €30,000 to €40,000, reflecting the necessity to bridge the skills gap for meaningful spatial data analysis. Additionally, ensuring the reliability of open data for decision-making requires rigorous quality assessment processes, including validation with local databases and complementary data collection, with associated annual expenses ranging from €25,000 to €35,000.