Applications of provenance in performance prediction and data storage optimisation

This paper shows how provenance can be captured from medical applications, stored using a graph database and then used to answer audit questions and enable repeatability. This static provenance will then be combined with performance data to predict future workloads, inform decision makers and reduce latency. Finally, cost models which are based on real world cloud computing costs will be used to determine optimum strategies for data retention over potentially extended periods of time.