The telecommunications sector is devoting an initial interest in the representation of complex networks as Digital Twins. The concept of a Digital Twin Network (DTN) is a research topic, but it promises to be an important step for harmonizing different models of the Edge-Cloud Continuum. The DTN software framework aims at helping network operations by providing updated and complete views on the network or parts of it, and it also introduces the possibility to simulate the network behavior or to learn from network events history (Machine Learning) without jeopardizing the actual operations of resources. In addition, thanks to the representation capabilities of the DT, its usage in the network promises to support different stakeholders' views on their virtualized and physical infrastructure. This work tries to consolidate a DTN data model representing the elements of the Edge-Cloud Continuum by providing a layered (horizontal) and segmented (vertical) view of the infrastructure to all the involved stakeholders. The DTN model is an ontology where the linked classes represent properties and relations of networked components. This work aims to design a flexible and extensible ontology that describes the Edge-Cloud continuum usable in the telecommunications as well in the Cloud (IT and web) industries creating a bridge between the two.