A Socio-Economic Decision-Support Tool for Sustainable Agricultural Policy
Journal
12th International Conference on Remote Sensing and Geoinformation of Environment
Type
conference contribution
Date Issued
2026-04-27
Author(s)
Abstract
Sustainable agricultural policy increasingly depends on timely, integrated socio-economic evidence that extends beyond traditional global statistical systems. While such systems provide extensive datasets, they rarely offer operational tools capable of translating data into structured, standardized, decision- and policy-ready insights. This paper presents a socio-economic decision-support tool developed within the Horizon Europe project Nostradamus, designed to strengthen evidence-informed policymaking in agricultural sustainability governance.
The tool forms part of the broader Nostradamus Data Cube infrastructure, which integrates environmental, agricultural and socio-economic data within an analytical environment across five countries (Cyprus, Germany, Serbia, Slovenia, Switzerland). Within this ecosystem, the socio-economic module provides a structured analytical layer that translates large-scale indicator datasets into standardised, policy-related outputs.
The tool operationalises more than 16,000 World Bank socio-economic indicators spanning 1960 to the present. Through automated bulk processing implemented in R, indicators of agricultural and non-agricultural relevance are harmonised, grouped by country and systematically evaluated using reproducible statistical routines. For each indicator and territory, the tool generates: (1) the most recent available value, (2) historical minimum and maximum values, (3) long-term averages, and (4) short-, medium-, and long-term trend estimations based on linear regression analyses (one-, five- and ten-year horizons). These outputs enable rapid assessment of structural socio-economic developments relevant to rural resilience, agricultural productivity, governance capacity and market dynamics.
Going beyond data aggregation, this work establishes a operational, policy-aligned analytical framework within the Nostradamus data infrastructure. The tool supports alignment with major sustainability frameworks, including the Common Agricultural Policy (CAP), the EU Biodiversity Strategy 2030, the Farm-to-Fork Strategy, and international biodiversity and climate commitments. By enabling systematic comparison of socio-economic trajectories across countries and over time, it facilitates anticipatory governance rather than retrospective reporting. In doing so, the approach contributes to emerging research on digital sustainability governance, integrated policy analytics and early detection of structural socio-economic shifts.
Methodologically, the tool emphasises reproducibility, scalability and interoperability within digital policy infrastructures. Its modular architecture allows integration into dashboards, monitoring systems and analytical workflows used by policymakers and advisory bodies. By linking socio-economic trends with environmental and agricultural indicators within the Nostradamus platform, the tool facilitates cross-sectoral policy analysis and supports coherent sustainability governance.
In practice, the socio-economic decision-support tool enhances policymakers’ capacity to detect emerging socio-economic shifts through structured and regular multi-horizon trend monitoring assess long-term development patterns, and calibrate policy interventions accordingly. It demonstrates how socio-economic modelling can be embedded within integrated data ecosystems to provide structured, transparent and actionable information for sustainable agricultural policy.
This abstract contributes a transferable framework for operationalising socio-economic trend analytics within integrated sustainability data platforms, helping to bridge the persistent gap between data availability and effective policy application.
The tool forms part of the broader Nostradamus Data Cube infrastructure, which integrates environmental, agricultural and socio-economic data within an analytical environment across five countries (Cyprus, Germany, Serbia, Slovenia, Switzerland). Within this ecosystem, the socio-economic module provides a structured analytical layer that translates large-scale indicator datasets into standardised, policy-related outputs.
The tool operationalises more than 16,000 World Bank socio-economic indicators spanning 1960 to the present. Through automated bulk processing implemented in R, indicators of agricultural and non-agricultural relevance are harmonised, grouped by country and systematically evaluated using reproducible statistical routines. For each indicator and territory, the tool generates: (1) the most recent available value, (2) historical minimum and maximum values, (3) long-term averages, and (4) short-, medium-, and long-term trend estimations based on linear regression analyses (one-, five- and ten-year horizons). These outputs enable rapid assessment of structural socio-economic developments relevant to rural resilience, agricultural productivity, governance capacity and market dynamics.
Going beyond data aggregation, this work establishes a operational, policy-aligned analytical framework within the Nostradamus data infrastructure. The tool supports alignment with major sustainability frameworks, including the Common Agricultural Policy (CAP), the EU Biodiversity Strategy 2030, the Farm-to-Fork Strategy, and international biodiversity and climate commitments. By enabling systematic comparison of socio-economic trajectories across countries and over time, it facilitates anticipatory governance rather than retrospective reporting. In doing so, the approach contributes to emerging research on digital sustainability governance, integrated policy analytics and early detection of structural socio-economic shifts.
Methodologically, the tool emphasises reproducibility, scalability and interoperability within digital policy infrastructures. Its modular architecture allows integration into dashboards, monitoring systems and analytical workflows used by policymakers and advisory bodies. By linking socio-economic trends with environmental and agricultural indicators within the Nostradamus platform, the tool facilitates cross-sectoral policy analysis and supports coherent sustainability governance.
In practice, the socio-economic decision-support tool enhances policymakers’ capacity to detect emerging socio-economic shifts through structured and regular multi-horizon trend monitoring assess long-term development patterns, and calibrate policy interventions accordingly. It demonstrates how socio-economic modelling can be embedded within integrated data ecosystems to provide structured, transparent and actionable information for sustainable agricultural policy.
This abstract contributes a transferable framework for operationalising socio-economic trend analytics within integrated sustainability data platforms, helping to bridge the persistent gap between data availability and effective policy application.
Language
English
HSG Classification
contribution to scientific community
Refereed
Yes
Subject(s)
Division(s)