From State Changes to Creative Decisions: Documenting and Interpreting Traces Across Creative Domains
This work aims to improve the understanding and analysis of creative processes for researchers and practitioners across various creative domains by preserving intent and higher-level relationships in activity traces.
The paper addresses the challenge of analyzing creative activity traces by proposing three domain-specific approaches to capture and interpret creative moves beyond simple state changes. These include a node-based interface for GenAI, a vocabulary of visual cues for visualization authoring, and a programming model for semantic histories in programmatic environments.
Analyzing creative activity traces requires capturing activity at appropriate granularity and interpreting it in ways that reflect the structure of creative practice. However, existing approaches record state changes without preserving the intent or relationships that define higher-level creative moves. This decoupling manifests differently across domains: GenAI tools lose non-linear exploration structure, visualization authoring obscures representational intent, and programmatic environments flatten interaction boundaries. We present three complementary approaches: a node-based interface for stateful GenAI artifact management, a vocabulary of visual cues as higher-level creative moves in visualization authoring, and a programming model that embeds semantic histories directly into interaction state.