RDF Access to Relational Databases Ashok Malhotra Oracle Corporation.

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RDF Access to Relational Databases Ashok Malhotra Oracle Corporation

Extracting Information from Relational Databases  There is very valuable data stored in Relational Databases  We should be able to do a much better job of extracting information from this data  There are two basic problems – Related data is often fragmented among many isolated databases – Relational databases have very little semantic information – Semantic information oftem stored on bits of paper or in the minds of the developer – Sometimes encoded in table and column names

Thus, we propose …  Step1 – Collect all the relevant Relational Databases.  Step 2 – Create an ontology or ‘semantic cover’ encompassing the information in the databases – This is a difficult process – More art than science

Relationships between databases  These can take many different forms:  Analogous data in one database might be represented in a different number of tables in another database.  Analogous data in one database might be represented in a different number of columns in another database.  Analogous data in one database might be represented in a different number of rows in another database

Relationships between databases Analogous data in one database might be represented using different values in another database (e.g., one database uses "m" and "f" for "male" and "female", while the other might use "0" and "1", respectively), or the same values in the various databases might mean different things (e.g., one database uses "1" and "0" for "male" and "female", while the other might use "0" and "1", respectively), or the values in the various databases might be incompatible in ways that make the mapping very difficult (e.g., one database uses "0" and "1" for "male" and "female", respectively, which the other database uses values from "0" through "9" to represent medically-significant variations of human sexes, such as types of hermaphrodites).

Thus, we propose …  Step 3 – Write a SQL query to extract data relevant to the class from each participating database – Write an integrating query to integrate the data obtained from the individual databases to create the data for the class  It is now possible to write queries on the semantic cover using SPARQL

Thus, we propose …  Step 4 – Translate SPARQL queries into underlying SQL queries using the queries created for each class