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Government offices are filled with siloed, sector-specific digital systems that strain their capacity to make decisions, use data effectively, and achieve ambitious sustainable development goals. Public investments in digital development, transformation, and infrastructure can only meet citizen needs if data and systems are consolidated and interoperable. While interoperability is a sensible approach to building digital public infrastructure, transforming existing systems is easier said than done. Limited resources and expertise, lack of training, inadequate hardware and software infrastructure, and concerns over data privacy are some of the key factors that limit the impact of systems or lead to their discontinuation. The data that feeds these systems also needs to be standardized using global best practices and common languages and frameworks that can be understood across multiple platforms and adapted to the local context. In increasingly digital economies, systems and their data need to be relevant and responsive to citizens’ specific conditions and needs With emerging challenges like climate change that require more complex data, and new technologies like artificial intelligence (AI) that require large volumes of data, systems need to be agile and scalable to advance solutions and fully harness innovation. This paper discusses, in practical terms, what goes into implementing interoperable solutions in partnership with public administrations. Based on 20+ years of DG’s experience, the paper demystifies key components needed to build robust, resilient, and interoperable data systems, focusing on the “how” of data standardization, data governance, and implementing technical infrastructure.
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