Evaluating CMMN execution capabilities: An empirical assessment based on a Smart Farming case study

Abstract

When integrating technology in every-day activities, new challenges arise. IoT systems have made their way in everyday life, resulting in smart environments enabling humans to make decisions in a more knowledgeable fashion. As smart systems become more complex, the process of using them becomes knowledge-intensive. This type of processes heavily depend on knowledge and experience of humans, that may work in a highly automated environment. In 2016, Case Management Model and Notation (CMMN) was introduced as a standard for modeling and automating human-centric processes. However, existing CMMN execution platforms have not met the full potential of the standard yet. In the paper, we aim to evaluate CMMN execution capabilities based on the experience obtained using two popular, advanced CMMN execution platforms. The evaluation is performed in the context of a smart farming case study based on twenty-five requirements imposed by knowledge-intensive processes, already identified in the literature.