The workflow iteratively simplifies large temporal event sequence datasets (such as EHRs or play-by-play logs) in EventFlow to balance visual comprehensibility with analytic fidelity. Starting from given event records, analysts specify sentinel events and time windows that define a relative-time context; EventFlow then aligns records, aggregates similar sequences into a tree, and visualises an overview plus individual timelines. Visual complexity metrics (e.g., number of visual elements and average aggregation level) together with human judgment are used to assess whether the display remains too cluttered. If further simplification is needed, analysts use interactive filters (by record, category, time, and attributes) and transformation-based operations (interval merging, category merging, marker insertion, and pattern-based Find & Replace) to rewrite the sequences into more compact, semantically meaningful representations. After each simplification, the system realigns and reaggregates the modified records, and this loop continues until the display is both interpretable and sufficient to answer the study questions, at which point analysts interpret domain patterns and formulate explicit findings and recommendations.