Statistical relational learning raises many new challenges and opportunities. Because the statistical model depends on the domain's relational structure, parameters in the model are often tied. This has advantages for making parameter estimation feasible, but complicates the model search. Because the "features" involve relationships among multiple objects, there is often a need to intelligently construct aggregates and other relational features.