Decisions in commerce and government are driven by data. The provenance of that data – how it’s created, modified, and used – is vitally important when assessing the quality of that data, tracing its origins, and identifying potential intrusions. However, current approaches to managing data provenance do not scale.
The Infer<Proven>ence project aims to create a toolbox of techniques to infer provenance from streamed and analytical data through modelled data networks. Our collaboration with this project will provide a generalised toolset platform for exploring these research issues.