SPHINX: rich insights into evidence-hypotheses relationships via parameter space-based exploration

Abstract

We demonstrate our SPHINX system that not only derives but also visualizes evidence-hypotheses relationships on a parameter space of belief and plausibility. SPHINX facilitates the analyst to interactively explore the contribution of different pieces of evidence towards the hypotheses. The key technical contributions of SPHINX include both computational and visual dimensions. The computational contributions cover (a.) flexible computational model selection; and (b.) real-time incremental strength computations. The visual contributions include (a.) sense-making over parameter space; (b.) filtering and abstraction options; (c.) novel visual displays such as evidence glyph and skyline views. Using two real datasets, we will demonstrate that the SPHINX system provides the analysts with rich insights into evidence-hypothesis relationships facilitating the discovery and decision making process.