Data Warehouses and the Semantic Web - Data Warehouse Systems: Design and Implementation - page 533

a

SalesKey ProductKey CustomerKey TimeKey Quantity
s1 p1 c1 t1 100

s2 p1 c2 t2 100

··· ··· ··· ··· ···

b

ProductKey ProductName QuantityPerUnit UnitPrice Discontinued CategoryName
p1 prod1 25 60 No c1

p2 prod2 45 60 No c1

··· ··· ··· ··· ··· ···

Fig. 14.2 An excerpt of a simplified version of the Northwind data warehouse.
( a ) Sales fact table. ( b ) Product dimension table

The World Wide Web Consortium (W3C) has proposed two ways of
mapping relational data to RDF: the direct mapping and the R2RML
mapping, which we present next.

Direct Mapping

The direct mapping 7 defines an RDF graph representation of the data in a
relational database. This mapping takes as input the schema and instance of a
relational database and produces an RDF graph called the direct graph ,whose
triples are formed concatenating column names and values with a base IRI .
In the examples below, the base IRI is < http://example.org/ > . The mapping
also accounts for the foreign keys in the databases being mapped. The direct
mapping for the Sales fact table and the Product dimension table in Fig. 14.2
results in an RDF graph, from which we show below some triples:
@base < http://example.org/ >
@prefix rdf: < http://www.w3.org/1999/02/22-rdf-syntax-ns# >

< Sales/SalesKey= '' s1 '' > rdf:type < Sales > .
< Sales/SalesKey= '' s1 '' >< Sales#SalesKey > '' s1 '' .
< Sales/SalesKey= '' s1 '' >< Sales#ProductKey > '' p1 '' .
< Sales/SalesKey= '' s1 '' >< Sales#ref-ProductKey >< Product/ProductKey= '' p1 '' > .
< Sales/SalesKey= '' s1 '' >< Sales#CustomerKey > '' c1 '' .
< Sales/SalesKey= '' s1 '' >< Sales#ref-CustomerKey >
< Customer/CustomerKey= '' c1 '' > .
< Sales/SalesKey= '' s1 '' >< Sales#TimeKey > '' t1 '' .
< Sales/SalesKey= '' s1 '' >< Sales#ref-TimeKey >< Time/TimeKey= '' t1 '' > .
< Sales/SalesKey= '' s1 '' >< Sales#Quantity > '' 100 '' .
...

7 http://www.w3.org/TR/rdb-direct-mapping/