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By Luc Moreau, Deborah L. McGuinness, James R. Michaelis
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Pract. Exper. 18, 1039–1065 (2006) 4. : Taverna: lessons in creating a workflow environment for the life sciences. Concurr. : Pract. Exper. 18, 1067–1100 (2006) 5. : Tackling the provenance challenge one layer at a time. : Pract. Exper. 20, 473–483 (2008) 6. : Efficient provenance storage. In: SIGMOD (2008) 7. : Kepler/pPOD: Scientific workflow and provenance support for assembling the tree of life. , Moreau, L. ) IPAW 2008. LNCS, vol. K. Anand et al. 8. : The Lorel query language for semistructured data.
Complete invocation dependency view Fig. 1. (a) Workflow for the fMRI image analysis of the first provenance challenge; (b) Trace showing the first invocations of each actor (for a typical run); (c) Implied fine-grain data dependency graph for the data items in (b); and (d) Implied invocation dependency graph for the run, with the first invocations of each actor shown in gray provenance models (including the Open Provenance Model [1]), and incorporates storage and query optimization that makes browsing and querying over (often large and complex [6]) provenance graphs feasible.
The query result can also be further queried, as shown by the second query in Fig. 5(c) whose result is shown in Fig. 5(b). Query History. The browser automatically captures the sequence of queries issued by the user (where the initial view is denoted as “T” in the query window). Users can return to a previous query result at any time by selecting the query from the query history or using the forward-backward buttons within the query window. In our example, selecting the first query (denoted query 2, since the initial trace is treated as query 1) would return the view from Fig.