Pattern analysis refers to the detection of patterns in data or logs. Such analysis often comes in two forms. First, Automated Pattern Analysis often consists of the stages leading up to a prediction or classification, mapping the detected patterns in the provenance data to an outcome either as part of a continuing automated process or as a preprocessing step before an analyst begins exploration of the patterns. Second, Manual Pattern Analysis refers to user-driven exploration and analysis of patterns in provenance data. When considering the analysis of provenance data, detecting patterns in interaction logs by either the manual or automated approach can enable systems to predict future interactions, as well as providing users with insight into their own behaviors. In this section, we identify publications that examine large-scale patterns in provenance data, classifying these works into automated or manual groups by the initiator of the analysis.