Topic-based crossing-workflow fragment discovery

Overview & Synopsis

Along with the large and increasing number of scientific workflows publicly accessible on Web repositories, the discovery of workflow fragments is significant to promote the reuse or repurposing of best-practices evidenced in legacy workflows, when novel scientific experiments are to be conducted. This paper proposes a novel crossing-workflow fragment discovery mechanism, where an activity knowledge graph is constructed to capture flat invocation relations between activities, and hierarchical parent–child relations specified upon sub-workflows and their corresponding activities. Semantic relevance of activities and sub-workflows is calculated based on their representative topics, where these topics are generated by applying the biterm topic model. Given a requirement specified in terms of a workflow fragment template, individual candidate activities or sub-workflows are discovered when considering their semantic relevance and short-document descriptions. Candidate fragments are constructed through discovering the relations in activity knowledge graph specified upon candidate activities or sub-workflows. These fragments are evaluated by balancing their structural and semantic similarities. Evaluation results show that our approach is accurate in discovering appropriate crossing-workflow fragments in comparison with the state of art’s techniques.