Workflow management systems represent today a key technological infrastructure for advanced applications. An aspect of workflows which has not so far received much attention even though it is crucial for the forthcoming scenarios of large scale applications on the web is discovering the most frequent patterns of executions, i.e., the workflow substructures that have been scheduled more frequently by the system. This problem, called workflow mining, is investigated using various data mining algorithms and an intuitive and original graph formalization of a workflow schema and its occurrences. Another problem connected with workflow is process mining. In this case the goal is to analyze transaction logs of a given process to derive a workflow schema, capable of supporting effective enactments of the process.