Boeykens, S., Wouters, N., & Vande Moere, A. (2013). BIM , Big Data and Mashup in Architectural Computing – Experimenting with Digital Technologies in Teaching (pp. 1–2). London: UCL, The Bartlett College.
The Architectural Computing course at the Department of Architecture, Urbanism and Planning (AUP), supervised by Prof. Andrew Vande Moere and Dr. Stefan Boeykens, introduces students to digital design tools. Architectural Computing I introduces CAD drafting including BIM, rendering, digital documentation, freeform modeling. Architectural Computing II focuses on parametric design, digital fabrication, real-time architecture and web mashups. This abstract illustrates two exercises (BIM and Mashup), pertaining to, respectively, BIM and big data. The BIM exercise consists of 1) a semester-long introduction where students learn to model, annotate and publish digital building models via ArchiCAD (i.e. little BIM) and 2) a group assignment where students collaboratively construct shared building models. In addition, teams appoint model evaluators to perform qualitative and quantitative model analyses using Solibri Model Checker. Teams collaborate with students in engineering who perform energy evaluations and design ventilation systems using Autodesk Revit. Since collaboration requires multiple software tools and interoperability, we highlight OpenBIM concepts. The required team coordination also reflects existing collaborations in building industry. Evaluation consists of 1) project-based feedback providing students with simulation results to optimize designs, 2) process-based feedback where students reflect on the design process and ttools for collaboration and communication, and 3) peer assessment. The Mashup exercise offers students theoretical and practical insight into networked datasets, and the relevance for architectural design. Exercises encompass topics such as open data, Internet of Things and locative technologies. Two approaches have been introduced: 1) bottom-up, where large datasets of geolocated urban features are collaboratively constructed, and a personal online front-end for exploring the data is built (using Google APIs, HTML5, jQuery), and 2) top-down, involving topics such as parametric design, integrating real time sensor data that closely resemble environmental data or movement patterns. By integrating real time sensor data with architectural prototypes (via Grasshopper), students can experience continuously reshaping designs, virtually without borders, yet limited in design through self-defined constraints. In both approaches, evaluation focuses on the emergence of forms and data, creativity and representation. We observed students and design studio teachers regularly need convinced about the relevance of our approaches. The relevance of digital technologies as part of the design process needs to be experienced to appreciate, rather than to be used merely as representational tools. By providing well-structured scenarios