Efficient Provenance Storage Over Nested Data Collections

Scientific workflow systems are increasingly used to automate complex data analyses, largely due to their benefits over traditional approaches for workflow design, optimization, and provenance recording. Many workflow systems employ a simple dependency model to represent the provenance of data produced by workflow runs. Although commonly adopted, this model does not capture explicit data dependencies introduced by "Provenance-aware" processes, and it can lead to inefficient storage when workflow data is complex or structured.