Approximating Certainty in Querying Data and Metadata.

Metadata, such as mappings or constraints, is used in a variety of scenarios to facilitate query answering; these include data integration and exchange, consistent query answering, and ontology-based data access. A common feature of these scenarios is that data and metadata together produce multiple databases, and answers to queries must be certain, i.e., true in all such databases. This usually incurs prohibitively high complexity outside very restricted classes of queries such as conjunctive queries and their unions. To overcome this, we propose to approximate such query answering by reducing it to another scenario where multiple databases need to be taken into account, namely incomplete information in databases. For them, well-behaved approximation schemes exist for much larger classes of queries. We give a generic representation of query answering via incomplete data, and show how it works in the scenarios listed above. We use the connection to show how to effectively approximate several intractable query answering problems, and discuss differences between applying this framework under open and closed world semantics.