Web services can be broadly classified into two types, namely effect providing (EP) services and data providing (DP) services. In this work, we address DP service composition problem that intends to satisfy user preference specified at the instance level, namely the expected occurrence. We first use the query rewriting method to identify a composition of service types that satisfies user¡¦s requirement and employ Bayesian Network model to express the causal relationship between exchange variables of DP service types. Service selection is then conducted by computing the posterior probability in the Bayesian Network. We conduct experiments to show that our proposed Bayesian Network-based method outperforms the other baseline methods in terms of execution success rate and data quality. It also has reasonable execution time.