Mapping non-RDF data to a graph: An introduction

In this video, I talk about what it means to map non-RDF data to an RDF graph. We will have a look at a simple CSV file and discover the things a machine cannot figure out on its own.
In the next episode, we will walk through the example in here base on our Expressive RDF Mapper XRM, you can check it out and download it here zazuko.com/products/expressiv...

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It seems that "Semantic Web" has become more like a sect.
This technology is more than 20 years old, which was mainly pushed by the “computational logic”/”semantic” community.
In turn, RDF(s)/OWL as well as SPARQL are too academic and too far away from any practical applicability.
Furthermore, it does not map to any proper Object Model in most of OOP languages (owlready2 in Python may be an exception), i.e., you have to work with “Subject”/”Predicate”/”Object”.
So, it is quite an exaggeration to say that RDF is more understandable than CSV. Basically, RDF is a mixture of several technologies like XML DOM/HTML, which puts a lot of “textual” (sematic schema)
information around each “literal” and “relation”. I.e., translation of any CSV file to RDF will explode the size of your file to one hundred times. Finally, in order to handle any RDF file you need special libraries, like RDFLib or DotNetRDF, which are far away from any standards. Conclusion = “as soon as you develop something professionally, keep away from this so-called technology”.