Designing distributed collaborative visual analytics systems

Analysts should be able to collaboratively work on enormous amount of available information and share their findings and understandings to effectively and efficiently make sense of the situation under investigation. The general question this thesis addresses is “How can a distributed collaborative analytics system support efficient and effective distributed (in time and space) collaboration among analysts?” and we focus on answering “How can a collaborative analytics system support efficient and effective reuse of the reasoning artefacts such as arguments, causal maps, etc.?” Through deepening our understanding of the individual and collaborative sensemaking processes that analysts go through, we identified design guidelines for enhancing, facilitating collaborative processes, fostering sharing and reuse, and improving collaboration efficiency. The design guidelines informed the design of a collaborative analytics system called AnalyticStream. We validate the proposed guidelines through the evaluation of the system.