I would like to know your opinion about the next system:
- with a large CSV file
- convert it's header to RDF schema, in which exists only the CSV columns information and access point. This way there's no need to convert the hole file to RDF triples, eliminating huge conversion overhead.
- launch a web app with SPARQL console, which converts the requests in file searches.
Why, you ask? Because having a 2.5GB cache with triples generated from 100MB CSV file is not useful at all.
In other words, i'm proposing the same system when converting RDB to RDF on p.ex. D2RQ, where all data is kept in the database and what is converted is the relational schema. This saves a lot of space and is a much faster process.
As mentioned in comments and answers below, a similar system might be tarql. The issue with this system is that it converts all the CSV file to rdf, not just the header. The issue with this approach is that a 100mb file is converted into a huge 2.5gb rdf file, which is not practical nor useful.
Here's a diagram that describes what i want to (or aspire to :)) create: