# Geo-Spatial Context Provision for Digital Twin Generation
## 4 Related Work
### Methodologies for the Creation of Digital Twins  
Next, we review existing research contributions aimed towards establishing and applying methodologies for the creation of Digital Twins. The authors in [45] conducted a review of articles that address the development of digital twins, specifically evaluating approaches from the domains of product life-cycle management, manufacturing, and predictive maintenance. They consequently synthesized three domain-specific development models, which were consolidated into a single model. The integrated model presented by the authors encompasses nine development steps: Prepare, Design, Verify/Validate, Deploy, Use, Evaluate, Maintain, Tune, and Rebuild. The authors in [46] proposed a multi-level design methodology for the creation of digital twins, allowing for different levels of abstractions for the same models. The methodology takes an AutomationML (see [[https://www.automationml.org/about-automationml/automationml/](https://www.automationml.org/about-automationml/automationml/)]([https://www.automationml.org/about-automationml/automationml/](https://www.automationml.org/about-automationml/automationml/)), retrieved 18 October 2022) description of a production system as input and subsequently creates a model of the plant topology and a communication infrastructure to connect the used simulators (plant and process). A general and domain-independent design methodology was proposed in [47]. The design starts with a purpose definition for the DT, which is followed by an identification of the process or asset that should be twinned, a DT usage specification, identification of fitting technologies, and the definition of input and output parameters. These steps are followed by development, performance measurement, and, based on the results of the measurement, deployment or the revisiting of design activities. A more technology-centered approach, accompanying a corresponding reference architecture, was proposed in [48]. The authors outlined a design and deployment methodology using specifically AutomationML and web services. AutomationML is used to first model physical devices and then the DT itself. Subsequently, the parameters of the DT are configured and it is possible to repeat the previous steps for further refinement. Finally, the created models are used as input for deployment via a custom Python script. The authors in [49] proposed an approach for the creation of digital models as a preparatory and enabling step for the subsequent creation of DTs. The specific types of models addressed are physics-based and the outlined methodology consists of three phases. First, the dynamic behavior of a machine is modeled. Then, virtual sensors are modeled next, which are used to obtain data from the model during simulation. Finally, the modeling parameters are defined that are required to adjust the model to reflect the real machine. In [50], a development methodology for the DTs was proposed that was based on the V-model. This model originated in the field of Software Engineering and was later adapted and specified for mechatronic systems and CPS in the guideline VDI 2206 issued by the Association of German Engineers (see [[https://www.vdi.de/richtlinien/programme-zu-vdi-richtlinien/vdi-2206/](https://www.vdi.de/richtlinien/programme-zu-vdi-richtlinien/vdi-2206/)]([https://www.vdi.de/richtlinien/programme-zu-vdi-richtlinien/vdi-2206/](https://www.vdi.de/richtlinien/programme-zu-vdi-richtlinien/vdi-2206/)), retrieved 18 October 2022). The authors outlined that their approach is intended for physical IoT-based products, with a focus on improving overall sustainability. They additionally considered four different initiation scenarios (simultaneous development of product, services, and DT; successive development of a DT for an existing product, with simultaneous upgrade of product to next version;...) and allowed for multiple development cycles with different foci (product, DT, service), with each having its own V-model.