Introduction #

In this module, we will assume that the data has already been collected and processed and we will tackle the problem of making a semantic web of knowledge such that the process of adding, querying, updating and viewing the data is more accessible.

In summary the aim of this module is to discuss,

• the advantages of using HBIM and semantic web of knowledge
• how to build a semantic web of knowledge and HBIM as flexible as possible such that that adding new data and features are as easy as possible.
• various components of the proposed model such such as the API, database design, etc.
• to incorporate new machine learning models or algorithms into the already collected and processed data, and
• finally discuss data migration in face of a potentially new design.

With this we will also discuss the pitfalls and arguments for doing the things the way have done and how we approach the potential problems with the design we have at hand.