## 1 Introduction  
Since the early 2000s, the architecture, engineering, construction, and operation (AECO) industry has experienced strong growth [1]. The field of building information modeling (BIM) has especially seen a noticeable increase in research publications since 2010, reflecting the rising interest and adoption of BIM within the AECO sector [2]. As a result, BIM has become increasingly used across the industry [3, 4]. With BIM, project information is enriched within a digital model. The data can be used to communicate information among different stakeholders and tools, supporting a consistent and coherent exchange of information and reducing delays and mistakes during the planning and construction of a building. This allows for tasks, such as structural calculations, quantity and cost determination, or construction scheduling, to be optimized. However, BIM's implementation challenges remain significant, and overall adoption still lags in many regions. While the exchange of information at the geometric level already works well, especially for structural and quantity calculations, there are problems associated with the exchange of data between energy simulation tools, especially involving alphanumeric information. Inconsistent naming of properties, proprietary exchange formats, and complex requirements lead to complications, especially when exchanging data between BIM and energy simulation tools. A lack of interoperability--the ability to exchange information between different tools as seamlessly as possible--presents a significant barrier. These challenges lead to unreliable and inconsistent data management within BIM tools, and post-processing steps are required, hindering the potential of BIM [5]. BIM review papers repeatedly emphasize interoperability as a fundamental challenge for the AECO industry. The most common problems identified include inconsistent data, a lack of semantic precision, and the absence of standardized data exchange formats. Addressing these interoperability issues is considered essential for the full adoption of BIM [6; 7]. In particular, the transfer of BIM data to building energy models (BEMs) or building energy performance simulations (BEPS) is a challenge. Although converting a digital planning model's geometry for energy simulation is itself a separate hurdle, this paper focuses instead on the exchange of alphanumeric information (metadata such as a wall's thermal transmittance). For BIM-to-BEM workflows, solving semantic challenges is critical for the implementation of early design optimization. Each project, company, and BIM and BEM tool has its own alphanumeric information, and in order for different programs to communicate this information with each other, two things are necessary. Firstly, it must be available and exportable, and, secondly, it must be understandable (i.e., semantic). Standards can be helpful here for both requirements. Standards can help define what information should be available and how this information should be labeled. This ensures the completeness and comprehensibility of exchange requirements. By tackling these semantic issues, we can significantly improve the interoperability of BIM to BEM workflows [8]. While semantics are a fundamental problem of interoperability in BIM to BEM exchange, the correct provision, maintenance, and coordination of alphanumeric information in the model is another major challenge. Standards help to define requirements and describe properties, but managing this information in the models (BIM and BEM) and between the models, as well as in the database, remains a problem. Databases for parameters are used to standardize the exchange requirements. However, this approach does not fully reflect the current state of software and practice. Standardization efforts do not adequately address the large number of complex requirements and associated volumes of alphanumeric information. Many aspects of the AECO sector are not covered, and the standards cannot map the project- and tool-specific requirements.