  Natural language user interfaces to database systems have been studied for
several decades now. They have mainly focused on parsing and interpreting
natural language queries to generate them in a formal database language. We
envision the reverse functionality, where the system would be able to take the
internal result of that translation, say in SQL form, translate it back into
natural language, and show it to the initiator of the query for verification.
Likewise, information extraction has received considerable attention in the
past ten years or so, identifying structured information in free text so that
it may then be stored appropriately and queried. Validation of the records
stored with a backward translation into text would again be very powerful.
Verification and validation of query and data input of a database system
correspond to just one example of the many important applications that would
benefit greatly from having mature techniques for translating such database
constructs into free-flowing text. The problem appears to be deceivingly
simple, as there are no ambiguities or other complications in interpreting
internal database elements, so initially a straightforward translation appears
adequate. Reality teaches us quite the opposite, however, as the resulting text
should be expressive, i.e., accurate in capturing the underlying queries or
data, and effective, i.e., allowing fast and unique interpretation of them.
Achieving both of these qualities is very difficult and raises several
technical challenges that need to be addressed. In this paper, we first expose
the reader to several situations and applications that need translation into
natural language, thereby, motivating the problem. We then outline, by example,
the research problems that need to be solved, separately for data translations
and query translations.
