What CSV is
CSV is a text file where each line is a row and commas separate the fields. There is no type system, no formatting and no second sheet. Every value is text until something downstream decides otherwise.
Almost every database, analytics tool and spreadsheet can read and write it, which is why exports default to it.
What RDF is
RDF in Turtle syntax: subject, predicate, object triples describing each row.
Linked data and semantic web projects.
What changes when you convert CSV to RDF
Reading CSV means deciding three things the file does not state: which character separates fields, how quotes work, and what encoding the bytes are in. Tablizer sniffs the delimiter from the first few lines, handles quoted fields containing commas and newlines, and reads the file as UTF-8.
Each row becomes a subject with one predicate per column, under an example.org namespace you will want to change.
What carries over from CSV to RDF
One property of the CSV has no home in RDF, and it is worth knowing which before you convert.
RDF wants a type for each column, and CSV does not record one, so each column is typed from what its values look like. A column of digits that should stay text - a zip code, a phone number, a leading-zero id - is the usual thing to check afterwards.
RDF has no header row. The column names are repeated as keys on every record instead, which is why the result is bigger on disk than the table it came from.
The identifier 007 comes out of the RDF as 007. Reading it as a number would have made it 7, and an id that changes value is worse than one that stays text.
The role "Analyst, data" survives with its comma, in one cell rather than split across two. That is the first thing to check in any converted table, and the usual place a RDF file goes wrong.
The quotes around Jonah "Jo" Pryce are escaped with a backslash in the RDF.