Re: Information Preserving and ISSUE-41

Juan,

1) About R2RML: We have a requirement that it be possible to suppress certain tables and columns from the RDF output. Therefore, R2RML cannot, and in fact must not be information preserving.

2) About the direct mapping: Consider an empty table. It will not produce any triples in the direct mapping, and hence cannot be reconstructed if one doesn't have schema knowledge. This shows that information preservation is only possible if the direct mapping includes schema information. You correctly pointed out that with schema knowledge, translating NULLs is not necessary for information preservation. Therefore, the perceived need for information preservation in the direct mapping is neither an argument for nor against translating NULLs.

Best,
Richard


On 17 May 2011, at 19:01, Juan Sequeda wrote:

> Group,
> 
> By information preserving, I mean that given the RDF data, I can reconstruct the relational table with all its values. Informally, given an identity SQL query (a query that outputs the whole table: SELECT * FROM table), there exist a SPARQL query which is executed on the RDF data and will return the same results of the identity SQL query.
> 
> There are two cases for information preserving
> 
> 1) We have knowledge the schema
> 
> If the relational schema is directly mapped to RDFS/OWL, then we DO NOT need to translate nulls in order to preserve information. For example, consider the table R with attributes A and B and instances:
> 
> R(Bob, NULL)
> R(Alice, 25)
> 
> 
> The ontology from this schema is
> 
> <R> <type> <class>
> <A> <type> <property>
> <A> <domain> <R>
> <A> <range> <whatever datatype>
> <B> <type> <property>
> <B> <domain> <R>
> <B> <range> <whatever datatype>
> 
> And the RDF data, without translating nulls:
> 
> <row1> <R#A> "Bob"
> <row2> <R#A> "Alice"
> <row2> <R#B> "25"
> 
> The identity SQL query is
> 
> SELECT A, B FROM R
> 
> Given that we know the schema, we can construct a SPARQL query:
> 
> SELECT ?a ?b
> WHERE{
> ?x <R#A> ?a
> OPTIONAL{
>  ?x <R#B> ?B
> }
> }
> 
> There we go... with that SPARQL query, we can reconstruct the the original relational table. No need of nulls. If we did triples for NULL values, then the SPARQL query wouldn't have OPTIONALS. The issue here is that we don't need triples for NULL values. 
> 
> 2) We don't have knowledge of the schema
> 
> If we do not have knowledge of the schema, then we can't create a SPARQL query like the previous example. Just imagine that you can only look at the RDF data. For example, consider the following RDF:
> 
> <row1> <R#A> "Bob"
> <row2> <R#A> "Alice"
> <row2> <R#B> "25"
> 
> 
> Given that one of the row 2 has <R#B> and row 1 doesn't, I could guess that the value of row 1 for attribute B is null. But what if the original table has a column C and every single row has a NULL value for that column. In this case, it would be necessary to explicitly translate NULL values into an RDF triple. Otherwise, then the mapping would not be information preserving.
> 
> 
> CONCLUSION:
> 
> - At this moment, neither the Direct Mapping or R2RML consider the schema, therefore in order for the mappings to be Information Preserving we must explicitly translate NULL values to an RDF triple. 
> - We need to figure out how is this triple going to show up?
> - From a theoretical side, if we do not generate triples for NULL values, them mapping monotonic. On the other hand, generating triples for NULL values will make the mapping non-monotonic. Do we care? Not really. But implementation and performance-wise, there can be some overhead when dealing with non-monotonicity 
> 
> 
> Juan Sequeda
> +1-575-SEQ-UEDA
> www.juansequeda.com

Received on Tuesday, 17 May 2011 18:29:43 UTC