Asynchronous Data Provenance for Research Data in a Distributed System

Many provenance systems assume that the data flow is being directly orchestrated by them or logs are present which describe it. This works well until these assumptions do not hold anymore. The Coscine platform is a way for researchers to connect to different storage providers and annotate their stored data with discipline-specific metadata. These storage providers, however, do not inform the platform of externally induced changes for example by the user. Therefore, this paper focuses on the need of data provenance that is not directly produced and has to be deduced after the fact. An approach is proposed for dealing with and creating such asynchronous data provenance which makes use of change indicators that deduce if a data entity has been modified. A representation on how to describe such an asynchronous data provenance in the Resource Description Framework (RDF) is discussed. Finally, a prototypical implementation of the approach in the Coscine use-case is described and the future steps for the approach and prototype are detailed.