Abstract:

The importance of understanding the process by which a result was
generated in an experiment is fundamental to science. Without such
information, other scientists cannot reproduce, analyse or validate
experiments.  Provenance is therefore important to enable a scientist
to trace how a particular result has been arrived at.

Based on the common sense definition of provenance, we propose a new
definition of provenance that is suited to the computational model
underpinning service oriented architectures: the provenance of a piece
of data is the process that led to the data.  Since our aim is to
conceive a computer-based representation of provenance that allows us
to perform useful reasoning about the origin of results, we examine
the nature of such representation, which is articulated around the
documentation of execution.

We then examine the architecture of a provenance system, centered
around the notion of a provenance store designed to support the
provenance lifecycle: during a recording phase some documentation of
execution is archived in the provenance store, whereas a reasoning
phase operates over the archived documentation.  Then, we successively
discuss a protocol for recording execution documentation, a query
facility to gain access to the contents of the store, and a reasoning
system to make inferences.  The realisation of such an architecture is
particularly challenging in the presence of e-Science experiments
since it must be scalable.

The presentation will draw upon our experience in the PASOA
(www.pasoa.org) and EU Provenance (www.gridprovenance.org) projects
and will rely on explicit use cases derived from e-Science
applications in the domain of bioinformatics, high energy physics,
organ transplant management and aerospace engineering.