Building the Future of Data Science

We can easily see that it's increasing over time. Semantics in this context means the use of formal semantics to give meaning to the disparate and raw data that surrounds us, and also the relationship between signifiers and what they stand for in reality, their denotation. When we talk about semantics in data we normally mean a combination of ontology, linked data, graphs and knowledge-graphs, the data fabric and more. You can read about all of that in the links at the beginning of the article. The thing is that all data modeling statements (along with everything else) in ontological languages for data are incremental, by their very nature.