Having a model and being able to implement open-ended evolutionary systems is important for advancing our understanding of open-endedness. Complex systems science and newest generation high-level programming languages provide intriguing possibilities to do so, respectively. Here, some recent advances in modelling and implementing open-ended evolutionary systems are reviewed first. Then, the so-called allagmatic method to describe, model, implement, and interpret complex systems is introduced. After highlighting some current modelling and implementation challenges, model building blocks of open-ended evolutionary systems are identified, a system metamodel of open-ended evolution is formalised in the allagmatic method, and an implementation prototype with a high-level programming language is outlined. The proposed approach shows statistical characteristics of open-ended evolutionary systems and provides a promising starting point to interpret novelty generated at runtime.