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Toward Making Online Biological Data Machine Understandable
Cui Tao
Brigham Young University, Provo, Utah 84602, U.S.A.ctao@cs.byu.edu
Abstract. Huge amounts of biological data are available online. To obtain needed information, biologists sometimes have to traverse different Web sources and combine their data manually. We introduce a system that can automatically interpret the structures of heterogeneous Web pages, extract useful information from them, and also transform them to machine-understandable pages for the Semantic Web, so that a Semantic Web agent can automatically find the information of interest.
LNCS 4273, p. 992 f.
lncs@springer.com
© Springer-Verlag Berlin Heidelberg 2006