Process modelling has a long and established research tradition, in the context of formally capturing sequences of activities, as well as the involved parties and the exchanged data. It will, without a doubt, continue to play a major role in the context of supporting the development of added-value services industry 4.0. In the medical domain, clinical pathways are a specific form of process modelling. They are an evidence-based response to particular problems and care needs in clinics. Current developers and latest technologies, improve and refine, among others, also the expressivity of clinical pathways. As a result, advanced pathways modelling optimises the treatment procedures in clinics (i.e. by reducing the stay of a patient or the mortality rates). However, as a side-effect of this trend, clinical pathways become increasingly complex and it becomes harder to keep up to date with the latest published processes. In oder to address the challenge of analysing clinical pathways, we provide an approach to capture information about activities and annotate the modelled pathways with references to external data sources. We demonstrate ... mehrthe practical applicability of our approach by using our system to model an actual clinical pathway, and enrich it with metainformation and references to external data sources, such as PubMed. We show the use and expressivity of our data model by querying the captured data.