Approximated provenance for complex applications

Many applications now involve the collection of large amounts of data from multiple users, and then aggregating and manipulating it in intricate ways. The complexity of such applications, combined with the size of the collected data, makes it difficult to understand how information was derived, and consequently difficult to asses its credibility, to optimize and debug its derivation, etc. Provenance has been helpful in achieving such goals in different contexts, and we illustrate its potential for novel complex applications such as those performing crowd-sourcing. Maintaining (and presenting) the full and exact provenance information may be infeasible for such applications, due to the size of the provenance and its complex structure. We propose some initial directions towards addressing this challenge, through the notion of approximated provenance.