Image: Autodesk AEC Data Model, https://aps.autodesk.com/autodesk-aec-data-mod­el-api

starting point:

How are practice data (BIM, GIS, Lidar models, etc.) structured to enable knowledge accessibility, interoperability, and security?  How are errors, risks, and file sharing handled?

This topic may include consideration of: vocabulary and semantics/ontology across architectural sectors and how it is covered by standards; the impacts of interfaces and communication methods needed to feed analysed practice data back to practice.

project summary: 

The research focuses on the data fragmentation issues between the designer and building product supplier. During the design stage, architects search and select product/materials based on both functional and visual qualities. However, the current procedure suffers from inefficiencies in material data management and product assembly design, which results in design delays. The experienced challenges can be summarised as:  

• File-based exchanges – material information is scattered across suppliers in proprietary formats (PDF, Excel, RVT files), creating vendor lock-in and limiting accessibility, and lacking a unified & standardised data management. 

• Inadequate search capabilities – current material platforms (such as BIMobject) only provide rough-level filtering, making it difficult to perform complex queries that balance multiple factors. 

• Classification limitations – traditional construction material classification systems are function-oriented rather than attribute-based, missing crucial material characteristics such as physical properties, appearance attributes, economic data, and sustainability metrics, etc. IFC schema defines rich product entities and material property sets but still cannot fully cover granular material property requirements. 

• Complex query approaches – systems, when available, require extended technical skill to perform sophisticated searches involving multiple-table join, and AND/OR logic combinations needed for effective material comparison. leading to incorrect material selection. 

This research aims to develop an integrated platform that addresses these challenges through three key components:  

• improved material classification framework – extending existing construction classification systems to include granular material property groups essential for design-stage decision making based on material selection workflow. 

• appropriate database management schema – designing and implementing a data schema for a relational database system to represent information of material hierarchies and their relationships.  

• user-friendly front-end – incorporating Large Language Model (LLM) technology to enable natural language queries. 

The platform will enable architects to efficiently search, compare, and select materials based on multiple criteria including performance requirements, aesthetic preferences, and sustainability metrics.