CSV to RDF KG and back

[Demirrr]

We should implement two features that one transforms a CSV file into RDF Knowledge Graph (KG) and the other transforms RDF KG into a CSV file.

Let's take a look at the transformation from a CSV file into RDF KG

1. The i-th row represents the first hop information (simplified CBD) of the i-th owl named individual.
2. A column represents a property (data property or type).
3. A value represents either a Literal or an OWL Class.

CSV Datasets: datasets from sklearn and fairlearn

[LckyLke]

I also added the kg to csv functionality (ie the inverse of csv to kg) here.

I also thought that maybe it makes sense to treat values that are strings and maybe are given as a parameter as type assertions:

https://github.com/dice-group/owlapy/blob/7972d4f6946c6597a59fbb7197d1c22ffc352230/owlapy/util_owl_static_funcs.py#L117C1-L126C67

For instance if we look at the following data - if a user says that genre is a type assertion this would create the kg graph accordingly:

Movie Title	Genre	Rating	Release Year	Duration (mins)	Director	IMDb Score
The Shawshank Redemption	Drama	R	1994	142	Frank Darabont	9.3

RDF Graph Representation

Node: :individual_0
Type: :Drama

data Properties:

• :hasTitle → "The Shawshank Redemption"
• :hasRating → "R"
• :hasReleaseYear → 1994^^xsd:gYear
• :hasDuration → 142^^xsd:integer
• :hasDirector → "Frank Darabont"
• :hasIMDbScore → 9.3^^xsd:float

[LckyLke]

also maybe it would make sense to allow for a column to set the individual URI?
-> if using the title here this would lead to http://example.org/#the_shawshank_redemption