Statistical relational learning a.k.a. probabilistic inductive logic programming deals with machine learning and data mining in relational domains where observations may be missing, partially observed, or noisy. In doing so, it addresses one of the central questions of artificial intelligence – the integration of probabilistic reasoning with machine learning and first-order and relational representations – and deals with all related aspects such as reasoning, parameter estimation, and structure learning.