During the design and engineering process of buildings and structures an enormous amount of data and information is produced. Logic, knowledge and experience is employed during this process by the designers and engineers to finally come to the design result. Because this information can not be fully recorded by software, a huge amount of information and a potential resource for further investigation in the design process is lost. One reason among others being that the current systems are not able to support the subprocesses in the design process and hold the information stack consisting of data, information, knowledge, etc. If a computational infrastructure would be available which would be able to hold and record the stack produced, an important opportunity exists for learning from this information and producing better designs,manage buildings better, etc. Furthermore, advanced computational technology has a number of additional advantages which at the moment cannot be fully benefited from, such as better coordinated and more optimised design, more understanding of complex behaviour, information management and digital manufacturing. This is because the current life cycle of the building or structure cannot be completely followed through in computational systems and therefore gaps in the essential steps of the design and engineering process appear and therefore loss of information. Again, an infrastructure which would be able to support development of tools, applications, frameworks and systems and which would be able to carry data across processes and tools potentially could improve this situation. This research project envisions this infrastructure as a conceptual base for development of the tools and systems of the future. The term ‘infrastructure’ has been chosen due to the aimed similarity with other infrastructures which acted as a platform technology for a variety of innovations, such as the mobile network infrastructure and glass-fibre network infrastructure. When developing such an infrastructure an important barrier arises which is the fact that it is not trivial to define what the users (designers and engineers) require from such an infrastructure to be able to work closely with it during the design process. An computational and conceptual infrastructure is a very abstract concept for end-users. End-users often are not aware of all technological possibilities and usually can only define immediate short term requirements but not long term development requirements or map out complex abstract concepts. To resolve this issue application of a custom methodology has been proposed and used for the studies in which conceptshave been derived from observations in practice through a process called Empathic Design (Leonard and Rayport, 1997) (note that observations include any data derived observing practice, so also include active derivation of observations, such as discussions, or even observed critique of available systems and paradigms active in practice) and are linked to technological concepts which have been derived from various technological sources of development. Finally, this results in a first step toward a computational design theory which sets out the conceptual direction for development and future research. The process of abstraction of theory from observations through concepts and conceptualisation has been based on the research methodology Grounded Theory (Glaser and Strauss, 1967). To develop the theory a study has been performed into structural design and engineering, its key values and its key characteristics in relationship to their pitfalls for computation. Furthermore, technological concepts have been studied and reported on in this dissertation which provide inspiration and direction to be linked to the concepts from the design and engineering domain. A number of existing technologies has been studied to identify strengths and shortcomings to establish further reaching concepts. The first attempt to meet the requirements established in the computational design theory was made by making use of parametric and associative design, which appears in software applications such as GenerativeComponents (Aish, 2005) and Grasshopper (McNeel, 2008). This paradigm has a various features closely matching the concepts of design, such as the ability to follow through change, the ability to define and process logic and decomposition. However, closer study showed that modifications and extensions had to be made to make it applicable in structural design and engineering. These modifications and extensions are discussed in this dissertation and various published papers. However, finally, a set of concepts remained which required fundamental modification of the paradigm. Therefore, a new infrastructure has been proposed under the name ‘NetworkedDesign’ which includes new concepts unavailable in previous studied paradigms, such as multi-directionality, solving by choice, meta-process and meta-knowledge, as well as a large number of previously existing concepts in a novel combination of a single infrastructure. A first implementation of this infrastructure in the form of a prototype demonstration design system has been used to demonstrate the concepts of the infrastructure in a variety of situations. This infrastructure opens new opportunities for the application of computation in practice as well as new areas of research previously largely unrelated to the building industry such as collective intelligence, computational intelligence and embedded design intelligence. In the practice of the application of computation in structural design and engineering this infrastructure will open new opportunities for new design tools, such as StructuralComponents (Rolvink et al., 2010), as well as partial resolution of the issues with interoperability.