Information flow analysis of scientific workflows

Recently, scientific workflows have emerged as a platform for automating and accelerating data processing and data sharing in scientific communities. Many scientific workflows have been developed for collaborative research projects that involve a number of geographically distributed organizations. Sharing of data and computation across organizations in different administrative domains is essential in such a collaborative environment. Because of the competitive nature of scientific research, it is important to ensure that sensitive information in scientific workflows can be accessed by and propagated to only authorized parties. To address this problem, we present techniques for analyzing how information propagates in scientific workflows. We also present algorithms for incrementally analyzing how information propagates upon every change to an existing scientific workflow.