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Data tools

RUSTIK tools and methods for rural development

Across its 14 Living Labs, RUSTIK tested a wide range of methods and digital tools to work with data, evidence and local knowledge in rural territories. This page presents some of the most relevant and transferable examples, focusing on methods that involved specific tools or platforms. These methods may be useful for local actors, practitioners and policymakers in their own rural development processes.

Each method description explains what the approach is, how it was used in RUSTIK, and what concrete tools or platforms were involved, so you can explore them further. All Living Labs applied combinations of methods and tools in their experiments; this page does not aim to document each experiment in full, but rather highlights selected tools and approaches through illustrative examples.

Other methods not listed here, including interviews, focus groups and participatory workshops, were equally important in the RUSTIK Living Labs and contributed significantly to the data experiments. They played a crucial role throughout the process, not only by generating qualitative insights but also by helping to shape and continuously adapt the data experiments:

  • Interviews were particularly valuable during the exploratory phase, providing an in-depth understanding of the local context and helped identifying the transition challenge.
  • Focus groups and participatory workshops supported the development of a shared understanding of the identified challenges and facilitated exchange between stakeholders from different sectors thereby fostering new ways of cooperation.

However, as these methods did not rely on dedicated tools, they are not included in this overview.

Surveys and questionnaires

Surveys are structured questionnaires used to collect information from residents, businesses, organisations or other target groups in a systematic way. They are especially useful when localscale evidence is missing from official statistics or when planners need direct input on needs, perceptions and experiences in rural areas.

RUSTIK Living Labs used surveys to generate evidence that can directly inform local and regional strategies. Examples include:

  • North Karelia (FI) developed a multilingual survey for immigrants and a parallel survey for local businesses to understand integration, wellbeing and employment opportunities. The results are integrated into a longterm process model that is repeated before municipal elections and feeds into municipal strategies.
  • Mazowieckie / Szydłowiec (PL) used separate surveys for residents, entrepreneurs and NGOs, combined with workshops and selfevaluation surveys for entrepreneurs, including experimentation with AI tools for data processing.
  • Świętokrzyskie (PL) carried out surveys among tourists and agritourism farm owners to understand preferences, development trends and expectations, producing new data for rural tourism strategies and promotional materials.
  • Webropol – online survey platform used in North Karelia for structured survey design, collection and reporting.
  • KoBoToolbox – mobile and webbased data collection tool used, for example, in Osona/Sant Miquel de Balenyà for field data that can be linked to locations.
  • Google Forms and similar online form tools – used in several Living Labs for lighter survey deployment where resources were limited.
  • National statistical portals – for example, the Statistics Centre of Finland data interface, combined with survey evidence in North Karelia.

Surveys can generate comparable evidence at local level and are flexible enough to be adapted for different groups such as young people, migrants, entrepreneurs or tourists. Experiences from RUSTIK underline that good survey design, pretesting and collaboration with trusted local intermediaries are crucial to reach the right respondents and obtain meaningful results.

GISbased spatial analysis and participatory mapping

GISbased spatial analysis helps collect, integrate and visualise geographically referenced data such as land use, services, businesses, natural resources or environmental risks. Participatory mapping adds stakeholder input to this process, allowing local actors to identify places, assets, challenges and opportunities directly on maps.

Learn more with the practice abstract on:

  • NockregionOberkärnten (AT) combined spatial analysis of business data with GIS and regional mapping to create an interactive leaflet and brochure that improved the visibility of small rural businesses.
  • Troyan–Apriltsi–Ugarchin (BG) developed a GIS platform to bring together information on local food suppliers and foodtourism relationships, complemented by reallife experiments with restaurants.
  • Garfagnana / Montagna Appennino (IT) used GIS mapping to analyse forestry data, public funding records and management plans, and to estimate carboncredit potential, highlighting territorial disparities and areas of untapped potential.
  • Galicia (ES) combined GIS analysis and field data in a decisionsupport logic to inform new rural settlement initiatives and wildfirerisk reduction.
  • Sant Miquel de Balenyà (ES) used a mix of surveys, participatory mapping and GIS tools to build a Quality of Life framework based on georeferenced data.
  • QGIS – free and opensource GIS software for spatial analysis and map production.
  • Maptionnaire – mapbased survey and participatory mapping platform used for georeferenced surveys and participatory mapping.
  • Google Maps application – used to map agritourism farms, tourism assets or local facilities in combination with other datasets.
  • Locus GIS – mobile GIS application for collecting and editing geodata directly in the field (Android), used in one of the Living Labs to capture and visualise local spatial information.
  • Leaflet (JavaScript library) – used, for example in the Nockregion, to visualise maps interactively on the web and present them to local stakeholders.
  • KoBoToolbox – used to collect field data that can be linked to locations and imported into GIS.

Maps make territorial patterns and inequalities more visible and easier to discuss. In RUSTIK, spatial tools helped identify service gaps, visualise business and forestry patterns, support settlement and riskreduction strategies, and create userfriendly outputs such as brochures, story maps and interactive web maps for local stakeholders.

Dashboards and decisionsupport systems

Dashboards and decisionsupport systems bring together data from multiple sources and present them in a visual, accessible and often interactive way. Their aim is to make complex evidence easier to understand and use, supporting planning, prioritisation and policy decisions at local and regional level.

Learn more with the practice abstract on Smart Dashboard: Empowering Data-Driven Decisions for Rural Communities.

Some Living Labs translated project data and analyses into tools that can continue to support decisionmaking beyond the project period. Examples include:

  • Gloucestershire (UK) worked with dashboardbased approaches that combined local and national datasets on rural communities, exploring AIassisted tools for transcription and qualitative processing to feed into visualisations.
  • Monmouthshire (UK) created an experimental dashboard in Microsoft Excel, combining primary and secondary data with satellite imagery to create an overview of key information in each of the county’s Lower Super Output Areas.
  • Galicia (ES) designed a decisionsupport concept that builds on data analysed in QGIS and R to inform strategic decisions about rural settlement locations and wildfirerisk management.
  • Parma–Piacenza–Ferrara (IT) developed tools to monitor water availability and vulnerability across irrigation districts, combining spatial analysis and dashboard thinking to support adaptation to climate change.
  • Microsoft Power BI – platform for building dashboards and reports, used for example in Monmouthshire and North Karelia.
  • QGIS – used as a base for many mapbased outputs that feed into dashboard or decisionsupport workflows.
  • R Project – statistical computing environment used in combination with GIS and other tools to prepare data for decisionsupport.
  • AIassisted tools such as Otter AI, Gemini or AnywhereLLM – used, for example, in Gloucestershire as supporting tools for transcription, qualitative analysis and experimentation with data interpretation.

Dashboards can make complex evidence more understandable for local authorities and practitioners who need clear overviews rather than raw data tables. When integrated into existing systems and maintained over time, they also increase the likelihood that project results remain useful and visible in everyday policy work.

Web and data scraping

Web and data scraping refers to automated techniques used to collect data from websites or online databases when relevant information is not readily available as a clean download. In rural development, scraping can be used, for example, to collect data on businesses, job offers, services or tourism facilities from online platforms.

Learn more with the practice abstract on Web and Data Scraping.

  • Mazowieckie (PL) and Nockregion (AT) used web scraping to identify and map local businesses. Mazowieckie collected information on registered businesses from websites and online registries, while Nockregion scraped business listings from Google Maps to improve the understanding of the local economic landscape.
  • Osona (ES) collected publicly available online data from platforms such as Airbnb, Strava and Google Maps to map tourism accommodation, sport and recreational activities, and natural and cultural landmarks across the territory.
  • Zajecar (RS) used scraped online information on restaurants and tourism-related services to assess their digital presence, revealing gaps in online visibility and opportunities for improved promotion.
  • Garfagnana (IT) applied web scraping to identify stakeholders in forestry, environmental and tourism sectors and to better understand relationships within local networks.
  • Parma (IT) used web scraping to identify and compile publicly available information on water resources and water management.
  • Apify – used in one Living Lab to automate web data extraction and create structured datasets.
  • BeautifulSoup – Python library for parsing HTML and XML and extracting data from web pages.
  • Scrapy – opensource framework for building web crawlers and largescale web scraping pipelines.

Web scraping can help rural regions obtain datasets that would otherwise not exist, for example on small businesses or tourism offers. It is a more technical method and often requires cooperation with data analysts or partner organisations, but can significantly reduce manual data collection efforts when used responsibly and in line with data protection and website terms of use.

System dynamics modelling for food systems (Slovenian food model)

System dynamics modelling is an approach that represents complex systems (such as regional food systems) through stocks, flows and feedback loops. It allows users to explore how changes in one part of the system may affect others over time and to test “whatif” scenarios.

In the Slovenian Living Lab, a system dynamics model was developed to analyse regional food system dynamics and possible transition pathways. The model supports discussion among stakeholders about how different interventions might affect food production, distribution, consumption and related sustainability outcomes. Based on feedback at the Joint Forum, the model is now being tested in at least one additional region, showing that it is relevant beyond its original context.

  • Insight Maker – online platform for building and sharing system dynamics models and simulations, used to develop the Slovenian food system model.

Building such a model requires specific expertise and is not something most rural regions can do on their own. However, the Slovenian example shows that models developed in one place can be adapted and reused elsewhere. For endusers, the main value lies in accessing and working with an existing model (for example in workshops or strategy processes) rather than building one from scratch.

Tools mentioned in RUSTIK Living Labs

Below you can find an overview of the main software tools, platforms and data services referenced in the examples above. Their inclusion does not imply formal endorsement, but aims to help users explore practical options for similar rural development work.

Tool / platform
Main purpose
Example use in RUSTIK
Webropol
Online survey and reporting platform
North Karelia immigrant and employer surveys.
KoBoToolbox
Mobile and webbased data collection
Field and survey data collection linked to GIS analysis.
Google Forms / online form tools
Online questionnaire tools
Lightweight surveys with residents, entrepreneurs and NGOs where simple tools were sufficient.
National statistical portals
Official data sources
Combination of survey and official data in North Karelia (e.g. Statistics Finland).
QGIS
Opensource GIS software for spatial analysis and mapping
Mapping and analysis in Garfagnana, Osona, Galicia and other Living Labs.
Maptionnaire
Mapbased surveys and participatory mapping
Participatory and georeferenced surveys in several Living Labs.
Locus GIS
Mobile GIS application for field data collection and editing
Collection and visualisation of local spatial information in at least one Living Lab.
Leaflet
JavaScript library for interactive web maps
Interactive visualisation of maps on the web, for example in the Nockregion.
Google Maps application
Web mapping service
Mapping of agritourism farms, tourism assets and local facilities.
Microsoft Power BI
Dashboard and reporting platform
Migration of project dashboards into local authority systems in Monmouthshire and use in North Karelia.
R
Statistical computing software
Data processing and analysis linked to decisionsupport tools.
Apify
Platform for web automation and data extraction
Web and data scraping to build local datasets where no readymade data existed.
BeautifulSoup
Python library for parsing HTML/XML and extracting data
Mentioned as an example for web scraping workflows in methodological work.
Scrapy
Python framework for largescale web scraping
Mentioned as a relevant tool for more advanced web data extraction workflows.
Insight Maker
System dynamics modelling platform
Development of the Slovenian regional food system model, now tested in another region.
Otter AI
Transcription and notetaking tool
Supporting transcription and processing of qualitative material, for example in Gloucestershire.
Gemini, AnywhereLLM and similar AI tools
AIassisted analysis and experimentation
Used in some Living Labs to support qualitative analysis and exploration of new ways of working with data.