Evolutionary Design of Search and Triage Interfaces for Large Document Sets

This dissertation is concerned with the design of visual interfaces for searching and triaging large document sets. Data proliferation has generated new and challenging information-based tasks across various domains. Yet, as the document sets of these tasks grow, it has become increasingly difficult for users to remain active participants in the information-seeking process, such as when searching and triaging large document sets. During information search, users seek to understand their document set, align domain knowledge, formulate effective queries, and use those queries to develop document set mappings which help generate encounters with valued documents. During information triage, users encounter the documents mapped by information search to judge relevance to information-seeking objectives. Yet, information search and triage can be challenging for users. Studies have found that when using traditional design strategies in tool interfaces for search and triage, users routinely struggle to understand the domain being searched, apply their expertise, communicate their objectives during query building, and assess the relevance of search results during information triage. Users must understand and apply domain- specific vocabulary when communicating information-seeking objectives. Yet, task vocabularies typically do not align with those of users, especially in tasks of complex domains. Ontologies can be valuable mediating resources for bridging between the vocabularies of users and tasks. They are created by domain experts to provide a standardized mapping of knowledge that can be leveraged both by computational- as well as human-facing systems. We believe that the activation of ontologies within user-facing interfaces has a potential to help users when searching and triaging large document sets, however more research is required