Business processes compliance monitoring can be viewed as a task of detecting and reacting to the compliance of running business processes with compliance rules, which are the semantic constraints originated from norms, standards, and laws, etc. Normally, compliance rules not only refer to normal process perspectives, like control ow, data ow, and time, but also perspectives of data aggregation as well as their mixtures. Such characteristics as well as potentially high number of concurrently running process instances, post challenges for processes compliance monitoring from the aspects of specification and monitoring efficiency. In this work, we address these challenges by proposing a compliance monitoring framework (bpCMon), including an event-based compliance language (ECL) and event reaction system (ERS), wherein ECL is a formal language enabling specifying compliance rules of multi-perspective, and ERS is a powerful rule-based system enriched with events indexing structure, and fully supports the monitoring for compliance rules in ECL. Experiments on a real life datasets indicate the applicability of bpCMon, and the comparisons with three related works over benchmarks demonstrate the efficiency of bpCMon
