# Reshaping the Digital Twin Construct with Levels of Digital Twinning (LoDT)
## 4 Assessing the Level of Digital Twinning (LoDT)
### Digital Twinning Dimensions
#### 4.2.5 Non-Geometric Representation  
Like geometric representation, the non-geometric information included in the model should attend to the needs defined by the application's purpose. One of the challenges in this dimension is to understand, right from the beginning of the asset's life cycle, what the non-geometric information requirements should be and how each of them will contribute to various purposes throughout the life cycle of these physical assets. On the one hand, there is a desire to acquire, store, and integrate as much information as possible into the model to prevent data deficits in the future. On the other hand, there is a desire for the model to be agile, with low implementation, operation, and maintenance costs. Thus, a rational weighing of these approaches should exist, preferably from the early stages of the life cycle, to generate the most value from this type of information and its impact on physical asset management. A methodology like MoSCoW [90] can be adopted to achieve this. In this method, information needs are identified and classified according to priority levels (\"Mo\"--\"must have\", \"S\"--\"should have\", \"Co\"--\"could have\", and \"W\"--\"won't have\"), making the process more expedient, objective, and effective. This methodology also makes it easier to evaluate the effective level of non-geometric representation that the model can achieve in relation to global information needs, giving higher weight when priority needs are satisfied (\"must have\" and \"should have\") and lower weight when the opposite occurs. The proliferation of enterprise management systems in organisations is another challenge. This turns data integration and interoperability into a complex task [99]. Additionally, data silos in organisations make the challenge even more complex, as the location and ownership of data are often unknown, resulting in duplicate information. Therefore, agile access to asset data and the expedient identification of information requirements are crucial for a digital twinning strategy. For a digital twinning strategy to maximise its value, it should be built on robust information management processes [14]. Although contributions in this area are still lacking [14], there are initiatives aimed at developing the aspect of information requirements in DTs. For example, [PERSON] et al. [14] propose a library of asset information requirements (AIRs) that covers various phases of the asset life cycle to support the development of DTs in the context of railway assets. The authors use the organisational objectives to find the AIRs through simple and critical questions that ultimately clarify the requirements for each asset type and use. Following the purpose and context identification, the requirements to incorporate the digital space should be mapped. These requirements must be necessary and sufficient to address the various management decisions throughout the life cycle. Since some requirements can only be addressed with data in later phases, the model must be prepared from the outset to receive them. Other requirements, such as those associated with maintenance and repair, require information to flow from the design and construction phases to ensure the effectiveness and efficiency of activities during that phase. Therefore, mapping the non-geometric information requirements according to the expected uses is a key task. The \"non-geometric representation\" dimension seeks to map which non-geometric information requirements were actually integrated into the digital space to support decision making relative to the non-geometric information needs. The UNI-TWIN model contains a qualitative scale of non-geometric information requirements integrated into the virtual space. At the lowest level, the model represents only the necessary requirements (\"Must have\", according to the MoSCoW method) with flaws in quality, quantity, and granularity. At the highest level, the model contains the necessary, the important (\"Should have\") and the nice-to-have (\"Could have\") non-geometric requirements.