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Towards Evidence-Based Discovery (EBD)

IIS Division of Information & Intelligent Systems.
CSE Directorate for Computer & Information Science & Engineering 

Vast quantities of electronic information provide a unique opportunity for scientists identify candidate solutions for grand challenges as scientists, policy makers, and students have never had access to more electronic information than they do today. The goal in this research is to develop new text mining methods that are consistent with the manual processes that experts currently used to resolve contradictory and redundant evidence. Both discovery and synthesis are difficult activities even for people, so a socio-technical strategy will be required to achieve this goal.

Key outcomes from this study will be:

A longitudinal study of manual discovery and synthesis behaviors of a diverse network of faculty, policy makers, and students from UNC and the Research Triangle Park;

Advances in natural language processing methods that automatically identify concepts and relationships, detect entailment and paraphrasing, and generate multi-document summaries.

A collection of gold standards that reflect diverse and realistic information needs that will drive further research in natural language processing.

Increased understanding of the degree to which text mining methods assist in discovery and synthesis activities through a series of qualitative and quantitative user studies.

A set of "next generation" scientists who are well prepared to explore complex research questions that span disciplines.

Increased awareness and support for the "human side of discovery" through courses, and workshops

This work is sponsored by NSF Award # 0812522.