Semi-automatic web service composition for the life sciences using the BioMoby semantic web framework.

Researchers in the life-sciences are currently limited to small-scale informatics experiments and analyses because of the lack of interoperability among life-sciences web services. This limitation can be addressed by annotating services and their interfaces with semantic information, so that interoperability problems can be reasoned about programmatically. The Moby semantic web framework is a popular and mature platform that is used for this purpose. However, the number of services that are available to select from when building a workflow is becoming unmanageable for users. As such, attempts have been made to assist with service selection and composition. These tasks fall under the general label of automated service composition. We present a prototype workflow assembly client that reduces the number of choices that users have to make by (1) restricting the overall set of services presented to them and (2) ranking services so that the the most desirable ones are presented first. We demonstrate via an evaluation of this prototype that a unification of relatively simple techniques can rank desirable services highly while maintaining interactive response times.

Challenges in precisely aligning models of human anatomy using generic schema matching.

This paper describes how we used generic schema matching algorithms to align the Foundational Model of Anatomy (FMA) and the GALEN Common Reference Model (CRM), two large models of human anatomy. We summarize the generic schema matching algorithms we used to identify correspondences. We present sample results that highlight the similarities and differences between the FMA and the CRM. We also identify uses of aggregation, transitivity, and reification, for which generic schema matching fails to produce an accurate mapping and present manually constructed solutions for them.