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Created by
Sara Stewart, last updated on 21 Nov, 2024
5 minute read
Welcome back to INGEST, our blog series on integrating statistical and geospatial information. We have another exciting guest blog post for you which has been written by Mr Javier Carranza Torres, Director of GeoCensos, a dedicated NGO focused on empowering governments and organizations through technical support, particularly in developing countries. Utilising a grassroots approach, GeoCensos enhances the capacity of striving nations to manage and leverage geospatial data effectively. By promoting active stakeholder participation, it plays a vital role in sustainable development, ensuring that local perspectives are integrated into decision-making processes. In this blog post, GeoCensos will discuss the value of institutionalising data integration in developing economies and how this can harness data's potential to foster a more sustainable future for all. Are you ready to hear more? Let's get started!
Enhancing decision-making and policy impact through data integration
To unlock the full power of data in developing countries, the integration of geospatial data into official statistics is being increasingly recognised by incumbent parties as a vital component for improving decision-making processes, especially in the expectations of developing countries to achieve their sustainable development goals. As nations strive to address complex social, economic, and environmental challenges, the ability to analyse and utilise geospatial information alongside traditional statistical data becomes essential. The case studies of Kenya and Paraguay (discussed in more detail below) demonstrate that establishing formal and technical arrangements for data integration not only enhances the quality of data but also provides a comprehensive understanding of various phenomena, leading to more informed and less biased policy-making.
Furthermore, institutionalising the bonds of statistics and geospatial data is vital for creating inclusive policies that effectively address the complex challenges faced by increasingly diverse populations. Benefits of this kind of institutionalisation, when disaggregating and integrating statistics and other valuable data facilitate data-driven decision-making, enhance interoperability, improve resource allocation and advance monitoring and evaluation of policy impacts. In short, it can represent a leapfrog change in the realm of policy-making.
Building capacity through the adoption of global policy frameworks
Currently, there is a pressing need to equip National Statistical Offices (NSOs) in middle-income countries with the knowledge and skills to implement effective data management models, like those outlined in the principles of the Global Statistical Geospatial Framework (GSGF). This framework (discussed in an earlier blog post) was developed through a collaborative effort spearheaded by the United Nations Committee of Experts on Global Geospatial Information Management (UN-GGIM). This framework functions as a directional document that outlines best practices for integrating geospatial and statistical data, ensuring that countries can leverage their data resources effectively. The GSGF is not an institution per se, it is more a propositae construct consented among committed experts from selected countries. While not a binding formulation, it acts as a high-level precedent.
However, some countries have taken the next step, institutionalising GSGF’s implementation by linking it to traditional processes at official entities. For example, Australia has developed the GSGF to enhance its national statistical system by integrating geospatial information into its census processes. The Australian Bureau of Statistics (ABS) employs advanced geocoding techniques to link statistical data with geographic locations, facilitating better insights into demographic trends and service disaggregation delivery needs across different regions.
The Global Statistical Geospatial Framework (PARIS21, p. 16)
At this point, it is relevant to highlight the relationship between the UN Integrated Geospatial Information Framework (UN-IGIF) (also explored in a previous blog post) and the GSGF. Both frameworks complement each other and share a common goal: to enhance synergies between geospatial and statistical data, ultimately improving decision-making processes. Collaboration between these domains allows countries to create robust datasets reflecting real-world conditions. The primary idea behind these two recommended models, which do not consist of mandated rigid frameworks by international organisations, is to promote the enhancement of integrating statistical and geospatial information. No more, no less.
One developed country that has greatly benefited from the synergy between the UN-IGIF and the GSGF is Germany. The country has implemented these two frameworks to enhance its national geospatial information management, which supports various sectors including urban planning, environmental monitoring, and disaster management.
Advancing integration through innovation
In developing countries, by providing alternatives and methodologies for improving geospatial management, NSOs can significantly elevate geostatistical decision-making processes. For instance, countries can adopt innovative practices to build long lasting commitments for data sharing and at the same produce concrete results. NSOs may produce initiatives like ATLAS de GENERO in Paraguay, which focuses on empowering women in various sectors, particularly in rural areas, working out complex institutional and technical issues.
Moreover, by focusing on practical applications and real-world case studies, nations can gain insights into successful development strategies. For example, lower- and middle-income countries like Kenya have utilized geospatial data to improve agricultural practices by mapping land use patterns and optimizing resource allocation. Such examples illustrate how effective integration can lead to tangible benefits, including increased agricultural productivity and enhanced food security.
Data integration as a key to inclusive and data-driven policy for sustainable development
Institutionalising the integration of statistical and geospatial information is not merely an administrative task; it plays a crucial role in data governance, and it fosters rightful inclusivity for many case studies by supporting broader policy objectives. By harnessing geospatial data, countries can monitor progress towards commitments like the Sustainable Development Goals (SDGs) and the OECD's 2016 Action Plan of Better Policies for 2030 more accurately, identifying areas that require targeted interventions. Geospatial integration operated through institutionalised arrangements is paramount for enhancing and sustaining decision-making processes in developing countries.
By empowering NSOs and other key data stakeholders with the tools and knowledge needed to implement frameworks like GSGF and UN-IGIF, trusted institutionalisation can be granted. By adopting tailored frameworks, countries can foster data-driven decision-making that addresses local challenges and achieves policy goals. The initiatives like ATLAS de GENERO in Paraguay and improvements in agricultural data practices in Kenya serve as gripping examples of how data integration in developing economies can maximise potential. We encourage countries to engage with these frameworks and learn from the successes of their peers, thereby unlocking their potential for more informed and inclusive policy-making.
