TY - GEN
T1 - Abstract provenance graphs
T2 - 3rd International Provenance and Annotation Workshop, IPAW 2010
AU - Zinn, Daniel
AU - Ludäscher, Bertram
PY - 2010
Y1 - 2010
N2 - Provenance graphs capture flow and dependency information recorded during scientific workflow runs, which can be used subsequently to interpret, validate, and debug workflow results. In this paper, we propose the new concept of Abstract Provenance Graphs (APGs). APGs are created via static analysis of a configured workflow W and input data schema, i.e., before W is actually executed. They summarize all possible provenance graphs the workflow W can create with input data of type τ, that is, for each input ν ∈ τ there exists a graph homomorphism ℋν between the concrete and abstract provenance graph. APGs are helpful during workflow construction since (1) they make certain workflow design-bugs (e.g., selecting none or wrong input data for the actors) easy to spot; and (2) show the evolution of the overall data organization of a workflow. Moreover, after workflows have been run, APGs can be used to validate concrete provenance graphs. A more detailed version of this work is available as [14].
AB - Provenance graphs capture flow and dependency information recorded during scientific workflow runs, which can be used subsequently to interpret, validate, and debug workflow results. In this paper, we propose the new concept of Abstract Provenance Graphs (APGs). APGs are created via static analysis of a configured workflow W and input data schema, i.e., before W is actually executed. They summarize all possible provenance graphs the workflow W can create with input data of type τ, that is, for each input ν ∈ τ there exists a graph homomorphism ℋν between the concrete and abstract provenance graph. APGs are helpful during workflow construction since (1) they make certain workflow design-bugs (e.g., selecting none or wrong input data for the actors) easy to spot; and (2) show the evolution of the overall data organization of a workflow. Moreover, after workflows have been run, APGs can be used to validate concrete provenance graphs. A more detailed version of this work is available as [14].
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U2 - 10.1007/978-3-642-17819-1_23
DO - 10.1007/978-3-642-17819-1_23
M3 - Conference contribution
AN - SCOPUS:78651078724
SN - 3642178189
SN - 9783642178184
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 206
EP - 215
BT - Provenance and Annotation of Data and Processes - Third International Provenance and Annotation Workshop, IPAW 2010, Revised Selected Papers
Y2 - 15 June 2010 through 16 June 2010
ER -