Spatial Data Infrastructure (SDI), traditionally conceived as a technical framework — composed of data, standards, policies, and institutional structures — has long enabled the discovery, sharing, and application of geographic information. However, the accelerating pace of digital transformation, the proliferation of artificial intelligence (AI), and the growing complexity of societal challenges demand a reimagining of SDI — not as a static repository of data, but as a dynamic, intelligent, and inclusive ecosystem that operates as a critical layer of broader Digital Public Infrastructure (DPI).
A research paper prepared for this project presents a global assessment of National SDI (NSDI) programs and argues for a strategic shift toward geospatial ecosystems that are embedded within broader digital public infrastructure frameworks. The research draws on the United Nations Integrated Geospatial Information Framework (UN-IGIF), expert interviews, and lessons from international experiences to examine the current landscape of spatial data infrastructures from a national government perspective, including policy and governance trends, emerging technologies, stakeholder roles, and maturity assessment frameworks. Through analysis of global best practices and persistent challenges, the paper identifies critical gaps, lessons learned, and future directions for SDI development. The paper is not meant to be the final word on spatial data infrastructure, and will include future Addenda to address specific, evolving issues around SDI, including case studies.
Many countries have made substantial progress in establishing core geospatial infrastructure; however, SDI remains uneven in maturity and impact, particularly at the national level. Challenges such as institutional fragmentation, limited legal and policy frameworks, inconsistent funding, and outdated systems continue to hinder the ability of SDI to fully support national priorities. At the same time, our evolving understanding of how to integrate diverse digital datasets—coupled with unprecedented opportunities to do so—demands more sophisticated, real-time, and decision-ready geospatial capabilities. The proliferation of digital data across sectors creates new possibilities for addressing societal challenges from environmental change and public health to infrastructure management and disaster response, yet this wealth of information remains largely fragmented and unintegrated. Furthermore, modern cost-benefit perspectives increasingly require SDI development to be more targeted and needs-focused, challenging traditional comprehensive SDI approaches while highlighting the critical importance of strategic data integration.
A central theme emerging from the research is the evolving role of SDI — not simply as a data infrastructure, but as a foundation for educated AI agents that exploit the analysis-ready data coming out of (national) digital transformation. This revolution is leaving behind even modern concepts such as Geospatial Knowledge Infrastructure (GKI). Instead, SDI needs to be rethought and aspects such as decision-ready insights, integration with broader digital ecosystems, and alignment with public value creation, all based on solid, machine-readable and machine-understandable data, are gaining a previously unknown significance. The resulting geospatial ecosystems require countries to build geospatial platforms that serve users across government, business, academia, and civil society — not just through data access, but through insight generation, scenario modeling, and responsive service delivery.
Modern SDI emphasizes the need for seamless integration of geospatial data with emerging technologies, moving beyond the traditional focus on data availability and standardized interfaces. The SDI of the future must embrace semantic interoperability, scenario-centric design, and AI-readiness — enabling geospatial data to be consumed by intelligent systems, integrated into everyday tools like digital assistants and mobile applications, and used to generate real-time insights for decision-making. All of these need to leverage cloud-native APIs and data storage models for efficient integration of geospatial data with data stored in data warehouses.
SDI is entering a pivotal phase of transformation. To remain relevant and impactful, it must evolve from managing data to delivering knowledge—serving as a catalyst for data-informed governance, economic innovation, and digital public services. By re-casting SDI as a living geospatial ecosystem—rather than a standalone infrastructure—this research envisions a future where spatial information is fluid, intelligent, and foundational. One where infrastructure is not an endpoint but a platform for innovation—fueling resilient, inclusive, and knowledge-driven societies. Countries that embrace this vision and invest in future-ready geospatial ecosystems will be better positioned to respond to complex challenges, unlock new opportunities, and build more resilient, inclusive, and sustainable societies.