However, AI has the potential to enable even more powerful usage of SDMX semantics.
Imagine, for example, a digital concierge – let’s call it the StatsBot – able to quickly fetch and prepare the data needed, with users being able to express and refine their needs through a conversation. I believe that with further research a StatsBot should be possible to implement in the near future. We can think of many more SDMX+AI applications cambodia rcs data in the future, for example to assist data experts with performing their data tasks in a more efficient manner – in classification, editing, imputing, validation tasks for example – thus contributing to increasing data quality or the capacity to combine and use a much wider range of data sources. Those applications of AI techniques to official statistics are of course being explored as such and outside of an SDMX context; the possibility to scale over a large range of diverse sources speaking the same language, as has been experienced with the StatsBot.
Abstract image of a mechanical hand coming out of a laptop screen and shaking hands with a human hand
Looking ahead
By offering a common conceptual toolkit to build model-driven data architectures, data experiences and data ecosystems, SDMX offers a unique opportunity for the global official statistics community – and beyond – to develop.