, 9 tweets, 4 min read Read on Twitter
1/9 Data semantization is often perceived as an abstract and jargon-ish concept and it's a shame because... #thread cc @opendatasoft
2/9 once your data is semantized, it is easier to find, as search engines do not rely exclusively on metadata anymore
3/9 once your data is semantized, it is easier to understand, as it has become self explanatory
4/9 once your data is semantized, it is easier to maintain: the person who will be managing your data in 5 years will not have to look for a PDF document you some day uploaded to your company document archive
5/9 once your data is semantized, it is easier to enrich. For example, if you know you are dealing with U.S. counties, it becomes faster to gather missing information such as population size, unemployement rates, geo-shapes
6/9 once your data is semantized, it is used more often, a direct consequence of the point explained above: people can use your data to enrich theirs...
7/9 semantizing your data is far from trivial so far only experts have seen the benefits of it. That's what we are trying to change at @opendatasoft with a complete semantic stack readily available
8/9 learn more with the complete article kitchen.opendatasoft.com/its-time-to-ma… and feel free to reach out to discuss it 😄
9/9 and of course the best is to try the semantic chatbot directly chatbot.opendatasoft.com or go check the source code on GitHub : github.com/opendatasoft/o…
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