With a huge volume of geospatial information being collected and a huge number of domain-specific functions being developed for processing these geospatial information, an increasing number of Open Geospatial Consortium Web services (OWSs) are built and being available on the Web for the accessibility and processing of these information. Given the specific requirement specified by a certain user, normally, a composition (or chain) of OWSs, rather than a single OWS, can fulfill this requirement. Consequently, retrieving and recommending sub-chains of possible service invocations is an important research challenge. Leveraging the semantic similarity between the name and text description of parameters, a degree that represents the invocation possibility between operations in OWSs is calculated. Thereafter, a service network model is constructed for capturing possible invocations between operations. Given a user's requirement which is represented in terms of a pair of initial and ending operations, possible sub-chains of operations are retrieved, ranked and recommended. Based on which the user can select the most appropriate sub-chain with respect to her specific requirement. The result of evaluation leveraging a real OWSs set indicates that our technique is applicable in real applications from both the functional and performance perspectives.
This article proposes to identify and recommend scientific workflows for reuse and repurposing. Specifically, a scientific workflow is represented as a layer hierarchy that specifies the hierarchical relations between this workflow, its sub-workflows, and activities. Semantic similarity is calculated between layer hierarchies of workflows. A graph-skeleton based clustering technique is adopted for grouping layer hierarchies into clusters. Barycenters in each cluster are identified, which serve as core workflows in this cluster, for facilitating the cluster identification and workflow ranking and recommendation with respect to the requirement of scientists.
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