Institutional ontology for conceptual modeling

Owen Eriksson, Paul Johannesson, Maria Bergholtz
2018 Journal of Information Technology  
Conceptual models are intended to capture knowledge about the world. Hence, the design of conceptual models could be informed by theories about what entities exist in the world and how they are constituted. Further, a common assumption within the field of conceptual modeling is that conceptual models and information systems describe entities in the real world, outside the systems. An alternative view is provided by an ontological commitment that recognizes that the institutional world is
more » ... cted through language use and the creation of institutional facts. Such an ontological commitment implies that there is an institutional reality, which, to a great extent, is constructed using information infrastructures. Accordingly, conceptual models have not only a descriptive role but also a prescriptive one, meaning that modelers set up a framework of rules that restrict and enable people to construct institutional reality using information infrastructures. Understanding the prescriptive role of conceptual models may revive the area of conceptual modeling in the information systems research community. Reviving conceptual modeling through institutional modeling is motivated by the effect that implemented conceptual models have on information infrastructures and institutions. The purpose of this article is to propose an institutional ontology that can support the design of information infrastructures. The ontology is theoretically informed by institutional theory and a communicative perspective on information systems design, as well as being empirically based on several case studies. It is illustrated using a case study in the welfare sector. A number of guidelines for modeling institutional reality are also proposed. . She holds a position as lecturer at Stockholm University. Bergholtz has published work on enterprise modeling, ontology, service modeling, e-commerce systems design, and business models. Institutional ontology for conceptual modeling O Eriksson et al.
doi:10.1057/s41265-018-0053-2 fatcat:dtyudxpdhradndq553nq2u5374