  In this decade astronomy is undergoing a paradigm shift to handle data from
next generation observatories such as the Square Kilometre Array (SKA) or the
Vera C. Rubin Observatory (LSST). Producing real time data streams of up to 10
TB/s and data products of the order of 600 Pbytes/year, the SKA will be the
biggest civil data producing machine of the world that demands novel solutions
on how these data volumes can be stored and analysed. Through the use of
complex, automated pipelines the provenance of this real time data processing
is key to establish confidence within the system, its final data products, and
ultimately its scientific results.
  The intention of this paper is to lay the foundation for making an automated
provenance generation tool for astronomical/data-processing pipelines. We
therefore present a use case analysis, specific to the astronomical needs which
addresses the issues of trust and reproducibility as well as other ulterior use
cases which are of interest to astronomers. This analysis is subsequently used
as the basis to discuss the requirements, challenges, and opportunities
involved in designing both the tool and the associated provenance model.
