Person:

Braun, Uri

While there has been a great deal of research on provenance systems, there has been little discussion about challenges that arise when making different provenance systems interoperate. In fact, most of the literature focuses on provenance systems in isolation and does not discuss interoperability – what it means, its requirements, and how to achieve it. We designed the Provenance-Aware Storage System to be a general- purpose substrate on top of which it would be “easy” to add other provenance-aware systems in a way that would provide “seamless integration” for the provenance captured at each level. While the system did exactly what we wanted on toy problems, when we began integrating StarFlow, a Python-based workflow/provenance system, we discovered that integration is far trickier and more subtle than anyone has suggested in the literature. This work describes our experience undertaking the integration of StarFlow and PASS, identifying several important additions to existing provenance models necessary for interoperability among provenance systems.

We describe our experiences importing PASS [16] provenance into PLUS [7]. Although both systems import and export provenance that conforms to the Open Provenance Model (OPM) [14], the two systems vary greatly with respect to the granularity of provenance captured, how much semantic knowledge the system contributes, and the completeness of provenance capture. We encountered several problems reconciling provenance between the two systems and use that experience to specify a Common Provenance Framework, that provides a higher degree of interoperability between provenance systems. In each case, the problems stem from the fact that OPM interoperability is a weaker requirement than query interoperability. Our goal in presenting this work is to generate discussion about differing degrees of interoperability and the requirements thereof.

Data is increasingly represented in annotated graphs, but graphs pose novel security and privacy challenges that at present lack solutions. We begin by identifying the new challenges graphs introduce and explain why existing security approaches are insufficient.