Social Space for Smart Regions

https://www.plan4all.eu/2020/09/challenge-4-rural-attractiveness-visualization/

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Mentors: Otakar Cerba, Sarah Velten, Pavel Kogut

The PoliRural project has prepared the dataset describing rural attractiveness in Europe from various perspectives e.g. demography, natural capital, social capital, economy, agriculture, living conditions.

Task 1
The first task of this challenge is to find relevant methods for assessing rural attractiveness in NUTS 3 regions. Building on the existing techniques (e.g. index calculation, clustering, Multiple-Criteria Decision Analysis), the method should offer new insights and allow easier identification of similarities and differences between the regions. 

To make the results easier to understand by non-experts, the manipulated data should be visualised on a map. Which cartographic parameters and graphic variables to use is at the discretion of the team working on this challenge.

Task 2
The second task focuses on the prototype web application which currently displays rural attractiveness data dynamically for the whole of the EU. The goal is to enable custom selection of individual regions for further comparison. The resulting clusters should be presented as nodes that are grouped together according to common attributes. The figure below shows a hypothetical cluster diagram based on a custom selection of 12 regions. 

For the second objective, the team would need to work with a predefined list of regions:

• BE251 Vlaams Gewest NUTS 2
• CZ02 Strední Cechy NUTS 2
• IE041 Border NUTS 3 
• EL64 Sterea Ellada NUTS 2 
• ES423 Cuenca NUTS 3 
• ITF4 Puglia NUTS 2
• LV008 Vidzeme NUTS 3
• PL913 Warszawski zachodni NUTS 3
• SK Slovakia Slovensko NUTS 1
• FI1C2 Kanta-Häme NUTS 3
• FI1C3 Päijät-Häme NUTS 3
• MK North Macedonia NUTS 1

Task 3

The final task is all about enabling map users to explore the rural situation in different regions in more detail. This should be done by creating a pop-up window with contextual information on e.g. rural challenges, existing policies. The team can work with just one of the above regions for this task. Contextual information should be taken from the pilot fiches and D4.4 Needs-Policies Canvas.

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Your mentors will be

OTAKAR CERBA Assoc. prof. Otakar Čerba, PhD works at the Department of Geomatics (Faculty of Applied Sciences, University of West Bohemia, Plzeň, Czech Republic) and cooperates with Plan4all. He is focused on cartographic visualization of spatial data, Linked Data on the geographic domain and semantic issues of geographic data. He has been involved in many international projects such as Polivisu, Humboldt, SDI4Apps, SmartOpenData, Plan4all or ROSIE. Otakar Čerba is the member of the board of Czech Association of GeoInformation and the chair of the Commission on Maps and the Internet of International Cartographic Association

SARAH VELTEN, PhD,  works for Plan4all and currently contributes to the project Polirural. An environmental scientist by training, she obtained her PhD in social and political sciences at Leuphana University Lüneburg, Germany. Her work has focused on issues of sustainable agriculture, rural development, biodiversity conservation, governance, participation, and stakeholder collaboration, using mainly qualitative and mixed qualitative and quantitative research approaches. She has previously been involved in the ERC-funded project EDGE (Evaluating the Delivery of Environmental Governance using an Evidence-based Research Design) and the RURAGRI ERA-NET project MULTAGRI (Rural development through the governance of multifunctional agricultural land use).

PAVEL KOGUT, MSc, is an experienced researcher and training facilitator who has worked on an extensive portfolio of agriculture related projects e.g. agINFRA, Green Learning Network, PoliRural. He is currently involved in the day-to-day management of an H2020 project PoliVisu, which aims to improve policy making through data and advanced visualisations. Prior to that, Pavel was an assistant analyst at the Hague Centre for Strategic Studies. Pavel’s career in research began in London’s third sector where he helped a number of charities evaluate their projects for the Big Lottery.