Why do we need RDB2RDF?
The need to map relational data to RDF is increasing. With the rise of Linked Data, more and more people want to publish their data on the web following the Linked Data principles and most probably the data is in relational databases. RDF can also be used for data integration. Using a common standard data model, with a standard query language (SPARQL) is very attractive.
The two use cases for RDB2RDF is to publish relational data as RDF on the web or combining a relational data with existing RDF.
Use Case 1: This use case exemplifies the desire of people wanting to join the Semantic Web by publishing their data as RDF and offering a SPARQL endpoint to their database. The next step would be either to create links from their dataset to other RDF datasets on the web, however this is not in the scope of RDB2RDF.
Use Case 2: This use case is oriented to data integration. This can be divided in three sub use cases where we would like to combine our relational data with:
● Structured data (relational databases, spreadsheets, csv, etc).
● Existing RDF data on the web (Linked Data)
● Unstructured data (HTML, PDF, etc).
We assume that the other sources we would like to combine have already been converted to RDF.
