Causal dependencies of provenance data in healthcare environment

Open Provenance Model (OPM) is a provenance model that can capture provenance data in terms of causal dependencies among the provenance data model components. Causal dependencies are relationships between an event (the cause) and a second event (the effect), where the second event is understood as a physical consequence of the first. Causal dependencies can represent a set of entities that are necessary and sufficient to explain the presence of another entity. A provenance model is able to describe the provenance of any data at an abstract layer, but does not explicitly capture causal dependencies that are a vital challenge since the lacks of the relations in OPM, especially in healthcare environment. In this paper, we analyse the causal dependencies between entities in a medical workflow system with OPM graphs.