The vision of the Cluster of Excellence Integrative Computational Design and Construction for Architecture (EXC IntCDC) is to harness the full potential of digital technologies in order to rethink design, fabrication and construction based on integration and interdisciplinarity, with the goal of enabling game-changing innovation in the building sector as it can only occur through highly integrative fundamental research in an interdisciplinary, large-scale research undertaking.

The Cluster aims to lay the methodological foundations for a profound rethinking of the design and building process and related building systems by adopting an integrative computational approach based on interdisciplinary research encompassing architecture, structural engineering, building physics, engineering geodesy, manufacturing and system engineering, computer science and robotics, social sciences and humanities. We aim to bundle the internationally recognised competencies in these fields of the University of Stuttgart and the Max Planck Institute for Intelligent Systems to accomplish our research mission.

The Cluster’s Industry Consortium will ensure direct knowledge exchange, transfer and rapid impact. Taking into account the significant difference between the building industry and other industries, we will tackle the related key challenges of achieving a higher level of integration, performance and adaptability, and we will address the most important building typologies of multi-storey buildings, long-span buildings, and the densification of urban areas.

The Cluster’s broad methodological insights and interdisciplinary findings are expected to result in comprehensive approaches to harnessing digital technologies, which will help to address the ecological, economic and social challenges that current incremental approaches cannot solve.

We envision IntCDC to significantly shape the future of architecture and the building industry through a higher-level integration of computational design and engineering methods, effective cyber-physical (tightly interlinked computational and material) robotic construction processes and new forms of human-machine collaboration, efficient and sustainable next-generation building systems, and socio-cultural and ethical reflection. Thus, the Cluster will have significant impact on creating the conditions required for a liveable and sustainable future built environment, high-quality yet affordable architecture and a novel digital building culture.
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Tabular Data - 5.1 KB - 11 Variables, 80 Observations - UNF:6:uU7oOJnqPUSdF956iTJCRw==
Shear strength (Fv) and fiber breakage (FB) data for specimens corresponding to the horizontal surfaces of alternative A. Strength in MPa and fiber breakage in percent (%). Definition of variables: - 'surf_type': type of surface, i.e. either "upper" (U), "lower" (L) or "vertical" (V). - 'surface_num': number of the wide side finger surface. - 'surf...
Tabular Data - 1.4 KB - 6 Variables, 43 Observations - UNF:6:yJ+IZvnsQz6jI5xRHGruww==
Shear strength (Fv) and fiber breakage (FB) data for specimens corresponding to the vertical surfaces of alternative A. Strength in MPa and fiber breakage in percent (%). Definition of variables: - 'surf_type': type of surface, i.e. either "upper" (U), "lower" (L) or "vertical" (V). - 'side': side from which the block shear specimens were extracted...
Tabular Data - 5.6 KB - 11 Variables, 88 Observations - UNF:6:ynTDasRZTZ90YDSQOzEiSw==
Shear strength (Fv) and fiber breakage (FB) data for specimens corresponding to the horizontal surfaces of alternative B. Strength in MPa and fiber breakage in percent (%). Definition of variables: - 'surf_type': type of surface, i.e. either "upper" (U), "lower" (L) or "vertical" (V). - 'surface_num': number of the wide side finger surface. - 'surf...
Sep 20, 2021 - EXC IntCDC 'Research Data Management'
Braun, Matthias, 2021, "EXC IntCDC - Data Management Plan Template for Research Projects", https://doi.org/10.18419/DARUS-2116, DaRUS, V1, UNF:6:Al3ljb79iWiURj4OdonArw== [fileUNF]
This Data Management Plan describes the data management life cycle for the data, a Research Project of EXC IntCDC will collect, process and/or generate. Moreover, it describes whether and how this data is being used and/or made publicly available for verification and re-use and how the data will be curated and preserved after the end of the project...
Adobe PDF - 180.1 KB - MD5: 8677cecafac0cf9f8beda26b4c4f97c2
Documentation
This how-to covers the responsibilities and procedures for creating and maintaining the Data Management Plan for a respective research project of IntCDC.
Tabular Data - 1.9 KB - 2 Variables, 15 Observations - UNF:6:Al3ljb79iWiURj4OdonArw==
SourceTemplate
Template file containing required meta data of a data set that is referenced within the DMP.
application/vnd.iccprofile - 3.0 KB - MD5: 4b699a4c3a7d97acf0a356aed883fd85
Source
Colour profile for PDF/A creation.
MS Word - 146.3 KB - MD5: 0250de66e1b773c35995a2d79745b2e5
SourceTemplate
Open Office XML source file generated via https://www.pdf2go.com/pdf-to-word from PDF/A file generated from LaTex source. For this template "Track Changes" should be enabled within Word and "Lock Tracking" should be set with password.
Adobe PDF - 214.8 KB - MD5: ab43cc682e8b5971bd764e0a6c9df726
Documentation
Generic example template of the final Data Management Plan for the first funding period of IntCDC.
LaTeX - 76.7 KB - MD5: 789874eb3a99112e600753324c6916ab
SourceTemplate
The LaTeX source file.
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