A Data Model and Query Language to Explore Enhanced Links and Paths in Life Science Sources George A. Mihaila, Felix Naumann, Louiqa Raschid, and Maria-Esther Vidal   View Paper (PDF)   Return to Poster Papers Abstract Links in life science sources capture important domain knowledge. However, current simple physical link implementations are not rich in either representation or semantics. This paper proposes the e-link framework and tools to assist scientists in exploring and exploiting the knowledge that should be captured in links. ©2006 Association for Computing Machinery