As a discipline, ‘Knowledge Engineering’ is geared toward building applications that specifically solve complex, knowledge-intensive tasks. In order to accomplish this, we may use cutting edge approaches from Artificial Intelligence, such as processing biomedical ontologies, knowledge representation and reasoning systems, machine learning and natural language processing. But the singular focus of the BIRN Knowledge Engineering WG is on solving real knowledge-oriented challenges in the biomedical domain.
These challenges require intermediate technology solutions, which we now are building directly or in collaboration with other research groups. For example, BIRN is developing new approaches to pragmatic, problem-solving Knowledge Representation and Reasoning (KR&R) systems for biology.
We focus on helping biocurators, or individuals responsible for entering data into biomedical databases, become more efficient through cutting-edge text mining techniques. By incorporating data visualization and navigation tools, we can provide new, innovative ways for users to interact with their knowledge. Finally, we work directly with research groups and consortia, as well as disease foundations, to build tools that specifically model their experimental designs in valuable new ways.
The team consists of researchers from the University of Southern California’s College of Letters, Arts and Sciences, the USC Information Sciences Institute, the University of California at Los Angeles, ScienceCommons, Montana State University, the University of Utah, the University of Colorado and Indiana University. We also work closely with BIRN partners in the initial Function BIRN and Mouse BIRN testbeds.
