To properly frame the encoding problem, I think we can start with the data characteristics of architectural elements. In digital models, each architectural element is represented by geometries with certain points, dimensions and type (such as nurbs and mesh). In construction documents, each element is tagged with its functional identifiers (such as door id), along with spreadsheets that associate more elaborate information (such as fire-resistance). In more advanced BIM softwares many of these features are linked together through some data structures. Before we jump onto building any kind of predictive or inference models, we need to acknowledge that our data is dual-natured:
- Numeric properties : dimensions (length, height, width), material properties (light transparencies, reflectiveness, thermal conductivity)
To model using data like this, we are facing the curse of dimensionality. For every new invention of architectural elements out there, new material features may be inven