Survey on the Analysis of User Interactions and Visualization Provenance

TLDR

The literature on provenance research is rapidly expanding, covering theory, use cases, and techniques for capturing, visualizing, and analyzing provenance data, creating a need to taxonomize existing scholarship. This survey aims to comprehensively map work in data visualization and visual analytics that analyze user interaction and provenance data, thereby providing a complete picture of the field and identifying knowledge gaps. The survey is organized around three key questions: why analyze provenance data, what provenance data to encode and how, and how to analyze it. The concluding discussion offers evidence‑based guidelines and concrete opportunities for future development, and the survey is available for interactive exploration online.

Abstract

Abstract There is fast‐growing literature on provenance‐related research, covering aspects such as its theoretical framework, use cases, and techniques for capturing, visualizing, and analyzing provenance data. As a result, there is an increasing need to identify and taxonomize the existing scholarship. Such an organization of the research landscape will provide a complete picture of the current state of inquiry and identify knowledge gaps or possible avenues for further investigation. In this STAR, we aim to produce a comprehensive survey of work in the data visualization and visual analytics field that focus on the analysis of user interaction and provenance data. We structure our survey around three primary questions: (1) WHY analyze provenance data, (2) WHAT provenance data to encode and how to encode it, and (3) HOW to analyze provenance data. A concluding discussion provides evidence‐based guidelines and highlights concrete opportunities for future development in this emerging area. The survey and papers discussed can be explored online interactively at https://provenance-survey.caleydo.org .