We investigate the design of ontology-supported, progressively disclosed visual analytics interfaces for searching and triaging large document sets.The goal is to crb concept distill a set of criteria that can help guide the design of such systems.We begin with a background of information search, triage, machine learning, and ontologies.We review research on the multi-stage information-seeking process to distill the criteria.To demonstrate their utility, we apply the criteria to the design of a prototype visual analytics interface: VisualQUEST (Visual interface for QUEry, Search, and Triage).
VisualQUEST allows users to plug-and-play document sets and expert-defined ontology files within a domain-independent environment for multi-stage information search and il2510 triage tasks.We describe VisualQUEST through a functional workflow and culminate with a discussion of ongoing formative evaluations, limitations, future work, and summary.