This talk targets challenges associated with managing updates and transactions on probabilistic databases. Traditional DBMSs provide APIs that provide access to the data on the logical level and hide physical representation details. Probabilistic database often employ compact ways to represent large sets of possible worlds, which adds additional layers of abstraction. 

I will present a programming model for uncertain and probabilistic databases that is independent of representation details. Conceptually, we use the
possible worlds semantics, and programs are independently evaluated in
each world. We study a class of programs that appear to the user as if
they are running in a single world rather than on a set of possible worlds.
We present an algorithm for efficiently verifying this property. We discuss
how updates can be implemented in uncertain database management
systems, and propose techniques for optimizing database programs.