Over the last years, scientific workflows have become mature enough to be used in a production style. However, despite the increasing maturity, there is still a shortage of tools for searching, adapting, and reusing workflows that hinders a more generalized adoption by the scientific communities. Indeed, due to the limited availability of machine-readable scientific metadata and the heterogeneity of workflow specification formats and representations, new ways to leverage alternative sources of information that complement existing approaches are needed. In this paper we address such limitations by applying statistically enriched generalized trie structures to exploit workflow execution provenance information in order to assist the analysis, indexing and search of scientific workflows. Our method bridges the gap between the description of what a workflow is supposed to do according to its specification and related metadata and what it actually does as recorded in its provenance execution trace. In doing so, we also prove that the proposed method outperforms SPARQL 1.1 Property Paths for querying provenance graphs.
SPARQL -the standard query language for querying RDF- provides only limited navigational functionalities, although these features are of fundamental importance for graph data formats such as RDF. This has led the W3C to include the property path feature in the upcoming version of the standard, SPARQL 1.1.We tested several implementations of SPARQL 1.1 handling property path queries, and we observed that their evaluation methods for this class of queries have a poor performance even in some very simple scenarios. To formally explain this fact, we conduct a theoretical study of the computational complexity of property paths evaluation. Our results imply that the poor performance of the tested implementations is not a problem of these particular systems, but of the specification itself. In fact, we show that any implementation that adheres to the SPARQL 1.1 specification (as of November 2011) is doomed to show the same behavior, the key issue being the need for counting solutions imposed by the current specification. We provide several intractability results, that together with our empirical results, provide strong evidence against the current semantics of SPARQL 1.1 property paths. Finally, we put our results in perspective, and propose a natural alternative semantics with tractable evaluation, that we think may lead to a wide adoption of the language by practitioners, developers and theoreticians.