An ontology for representing and annotating data flows to facilitate compliance verification
In this paper we argue that there is a gap to be bridged between the development and maintenance of services and the various internal and external policies that emerge and evolve outside of these systems. To bridge this gap, we propose a semantic model, i.e. ontology, for representing Data Flows and linking them with structured representations of the data that is processed (datasets, databases, queries, etc.). Data Flow Diagramming is a technique for capturing the various data and information flows between an information system and external stakeholders as well as within such a system. This technique is used in the analysis phase of information systems development and captures the inputs and outputs of various processes. Our model allows these data flows to be presented and linked with structured representations of the data that is to be used, consulted, processed, etc. We demonstrate that this model can facilitate compliance verification processes of (intelligent) systems by allowing these flows to be analyzed. Next to the ontology, which has been made available according to best practices in the field, we furthermore posit our contributions within the state of the art.
Publication Reference
An ontology for representing and annotating data flows to facilitate compliance verification Debruyne, C., Riggio, J., De Troyer, O. & O'Sullivan, D., 1 May 2019, Proceedings - International Conference on Research Challenges in Information Science. IEEE Computer Society, (Proceedings - International Conference on Research Challenges in Information Science; vol. 2019-May).