It is no newsflash that governments at all levels are using data more to improve public policy and meet both the increasingly complex challenges they face and the expectations of a more data literate business sector and citizenry. Much of this data comes from what might be termed traditional sources – official statistics, surveys and censuses, etc.
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We have grown used to reading and hearing about the enormous potential of artificial intelligence (AI). The rapidly evolving nature of the technology makes it difficult to pinpoint specific shifts in the relationship between AI and open data.
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Finding what you need in the landscape of data can sometimes feel like a daunting task. But what if there was a way to make all that data more easily discoverable and usable? That’s where Data Catalogue Vocabulary (DCAT) is essential. This standard, recommended by the World Wide Web Consortium (W3C), aims to bring order to the chaos by providing a common language for describing datasets.
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Open data has major benefits for AI. But it is not enough for that data to be open and shareable, it also needs to be quality data.
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