This course will equip students with the skills to design more effective cross-disciplinary workflows and to develop data strategies that capture value from information already being produced. Students will explore tools such as Speckle Systems, the Common Data Environment (CDE), the International Foundation Class (IFC), GraphQL, and related Python-based APIs.


Syllabus

Collaborative Workflows & Data Strategy


Source: Seminar Collaborative Workflows and Data Strategy, Libny Pacheco, Christoph Berkmiller and Vladimir Ondejcik, 2025-2026.

The rapid growth of digital technology in the AEC industry has significantly transformed how stakeholders interact. Yet despite the promise of Building Information Modelling, BIM files have essentially become coordination tools rather than true collaboration platforms. Teams export 2D PDFs for markup in Bluebeam and 3D IFCs for clash detection—treating the model as a source for deliverables rather than a shared environment for design development.

Compounding this issue is the vast amount of data generated within BIM files that remains untapped. This data is typically seen as a by-product of the modelling process rather than a strategic asset that could improve company processes, inform decision-making, and enable new services and business offerings. We find ourselves at a crossroads: how do we move from coordination to genuine collaboration, and how do we shift our perspective on data from by-product to asset?

This seminar is designed to address both challenges. We will examine the current state of coordination workflows—from conventional exports to advanced data pipelines and cloud-based automation—before exploring what true collaboration and strategic data management could look like. The course will equip students with the skills to design more effective cross-disciplinary workflows and to develop data strategies that capture value from information already being produced.

The seminar will explore tools such as Speckle Systems, the Common Data Environment (CDE), the International Foundation Class (IFC), GraphQL, and related Python-based APIs. It will cover best practices for BIM coordination and collaboration, data architectures (including concepts like Single Source of Truth and Multiple Versions of Truth), automating tasks through webhooks and design automation, and bridging the gap between customisation and standardisation—with an emphasis on applying these concepts to real-world projects.


Source: Seminar Collaborative Workflows and Data Strategy, Libny Pacheco, Christoph Berkmiller and Vladimir Ondejcik, 2025-2026.

 

Learning Objectives

The course aims to offer the following learning objectives:

  • Identify and address the challenges of cross-disciplinary work, data sharing and strategy between different actors.
  • Recognise how to bridge customisation and standardisation in digital collaboration.
  • Learn how to design workflows and interoperability schemes.
  • Implement best practices for BIM coordination and troubleshooting.
  • Develop an understanding of the opportunities for task automation and data processing in the AEC.

Faculty


Faculty Assistants


Projects from this course

How much kgCO2e does our HyperBuilding weight?

Introduction Life Cycle Assessment (LCA) is increasingly required in the building industry, yet it remains difficult to integrate into the design workflow. The challenge is that LCA operates across multiple scales, from macro-level building decisions to micro-level material choices. This is especially relevant for designers, since they have to engage with these considerations from the … Read more

Automated Cloud-Based Metadata Extraction: HB01 – Program Team

An automated pipeline that transforms raw 3D model metadata into structured cloud spreadsheets. This makes complex geometric data easily accessible and adaptable for various end-uses, from simple data reading to feeding live web platforms. Problem Statement Streamlining Complex Metadata Communication Communication across large design teams presents a significant challenge due to the massive volume of … Read more

Automated workflow to extract KPIs from versioned models in Speckle

Automated Workflow for KPI Extraction from Versioned Models in Speckle Why KPI Tracking Breaks Down During Iterative Design In the current studio workflow, KPI extraction and performance evaluation depend on repeated manual operations across design iterations. This slows down feedback, introduces version mismatch risks, and disconnects analytical outputs from the model itself. This tool was … Read more

FluxFaçade

Our project is Flux Façade, a collaborative workflow for data-driven parametric façade design.The project was developed by Team 3.2 as part of the Collaborative Workflow Seminar in the Master in Advanced Computation for Architecture. Flux Façade focuses on improving how environmental analysis and façade geometry interact within the design workflow. Problem Statement In large architectural … Read more

Collaborative Workflow: Structure/Facade-HB01

Introduction – Defining the Volume   Problem Statement & Context  Target User Proposed Solution An automated pipeline that instantly extracts, organizes, and delivers your 3D model data to your entire team the moment a new design version is published no manual steps, no shared files, no delays. Success Criteria Demo Success Criteria Limitation & Future Scope … Read more

Computational Bucketing: Turning BIM Data into Visual Insight with Speckle Automate

We developed a property-driven bucketing pipeline for BIM models using Speckle Automate that automatically groups building elements by numeric ranges and visualizes them as gradient-colored 3D models on a live website — making performance data accessible without needing to open Speckle. In collaborative design projects, reviewing building performance data is often a bottleneck. Team members … Read more