BIM, Big Data and Mashup in Architectural Computing – Experimenting with Digital Technologies in...

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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

Transcript of BIM, Big Data and Mashup in Architectural Computing – Experimenting with Digital Technologies in...

BIM, Big Data and Mashup in

Architectural ComputingExperimenting with Digital Technologies

in Teaching

Dr. Stefan Boeykens, Niels Wouters, Prof. Andrew Vande Moere

The Bartlett Pedagogy meets Big Data and BIM Conference 24-

25 June 2013, UCL London (UK)

* Parts of the work presented here were funded by the “Education Development Fund” of the KU Leuven Association, with reference OOF 2011/24

PART 1

BIM & PEDAGOGY

From Little BIM...

• 1st Semester

• Recreate house

• ArchiCAD

• model

• annotate

• publish

Student: S. Simoens (2012)

Student: E. Devos (2012)

To BIG BIM *

• 2nd Semester

• Collaborate

• ArchiCAD TeamWork

• Solibri Model Checker

• Autodesk Revit MEP

• openBIM workflow

* Jernigan, F. E. (2008). BIG BIM, Little BIM (2nd ed., p. 328). 4Site Press.

Student: R. Mertens (2012)

source: Jared Banks (shoegnome.com)

Technological Challenges

• Software differences (platform,

software versions, …)

• File formats (proprietary vs. open)

Organizational Challenges

• Project structure

• Building & Design practices

• Roles in a Building team

• designer, architect, engineer, consultant,

administration, owner, contractor,

constructor, ...

Evaluation/Feedback

• Project Based > architectural design,

building performance, visualization

• Process Based > working in a building

team, questionnaires, peer

assessment

Modeled after POLO-IRS-Grontmij-A’Prom (Students Residence @KU Leuven)

PART 2

MASHUPS & BIG DATA

-Students individually

create descriptive

datasets

-Geotagging

-Online front-end

Big and Realtime Data

BOTTOM-UP

-Students integrate

realtime sensor values in

designs

-Environment and

movement

-Parametric design

TOP-DOWN

Big and Realtime Data

TOP-DOWNBOTTOM-UP

PART 3: DIDACTIC APPROACH

BIM versus the design studio?

• Tradition of 2D drafting & 3D visualization

• Hesitation or negative attitude towards BIM

BIM > software

BIM = methodology

BIM = process

Didactic Approach for BIM

• Learning concepts, but also software

• Lifted outside Design Studio work

• From little BIM to BIG BIM

• Early in curriculum (but not too soon)

• Experience scenario of collaboration

Didactic Approach for Mashup/Data

• Not a course in programming or

electronics

• Stimulate exploration and emergence

- Code examples

- Tutors deploy data gathering devices

Concluding Remarks

• Need to experience digital

technologies as part of design process

• Scenarios, learning material, positive

attitude

• Supported by social network

Thank you for your attention

Questions? More information?

http://archcomp.asro.kuleuven.be

Dr. Stefan Boeykens (@stefkeB)

Niels Wouters (@mediatecture)

Prof. Andrew Vande Moere (@infosthetics)

* Parts of the work presented here were funded by the “Education Development Fund” of the KU Leuven Association, with reference OOF 2011/24