Robert Woodbury

Abstract: Driven by new computer and digital fabrication tools, the architectural designs that are being built are pushing boundaries of form, customization and construction. Pushed by practices wanting and needing to produce novelty, computer-aided design systems are increasingly parametric - that is, they represent designs that change with their input data. Such systems give more control and capability to designers, but require much more comprehensive understanding if they are to be used effectively.

Abstract: Data surrounds each and every one of us in our daily lives, ranging from exercise logs, to archives of our interactions with others on social media, to online resources pertaining to our hobbies. There is enormous potential for us to use these data to understand ourselves better and make positive changes in our lives. Visualization (Vis) and visual analytics (VA) offer substantial opportunities to help individuals gain insights about themselves, their communities and their interests; however, designing tools to support data analysis in non-professional life brings a unique set of research and design challenges. We investigate the requirements and research directions required to take full advantage of Vis and VA in a personal context. We develop a taxonomy of design dimensions to provide a coherent vocabulary for discussing personal visualization and personal visual analytics. By identifying and exploring clusters in the design space, we discuss challenges and share perspectives on future research. This work brings together research that was previously scattered across disciplines. Our goal is to call research attention to this space and engage researchers to explore the enabling techniques and technology that will support people to better understand data relevant to their personal lives, interests, and needs.

Abstract: Parametric design systems model a design as a constrained collection of schemata. Designers work in such systems at two levels: definition of schemata and constraints; and search within a schema collection for meaningful instances. Propagation-based systems yield efficient algorithms that are complete within their domain, require explicit specification of a directed acyclic constraint graph and allow relatively simple debugging strategies based on antecedents and consequents. The requirement to order constraints appears to be useful in expressing specific designer intentions and in disambiguating interaction. A key feature of such systems in practice appears to be a need for multiple views onto the constraint model and simultaneous interaction across views. We describe one multiple-view structure, its development and refinement through a large group of architecture practitioners and its realization in the system Generative Components.

Abstract: Design space exploration is a long-standing focus in computational design research. Its three main threads are accounts of designer action, development of strategies for amplification of designer action in exploration, and discovery of computational structures to support exploration. Chief among such structures is the design space, which is the network structure of related designs that are visited in an exploration process. There is relatively little research on design spaces to date. This paper sketches a partial account of the structure of both design spaces and research to develop them. It focuses largely on the implications of designers acting as explorers.

Abstract: This paper describes the overall goals of SEED, the approach taken by its developers to achieve these goals, and the subprojects that comprise the entire project. SEED aims at providing computation...

Abstract: A prevalent and pervasive view of designing is that it can be modeled using variables and decisions made about what values should be taken by these variables. The activity of designing is carried out with the expectation that the designed artifact will operate in the natural world and the social world. These worlds impose constraints on the variables and their values; so, design could be described as a goal-oriented, constrained, decision- making activity. However, design distinguish- es itself from other similarly described activities not only by its domain but also by additional necessary features. Designing involves exploration, exploring what variables might be appropriate. The process of explo- ration involves both goal variables and deci- sion variables. In addition, designing involves learning: Part of the exploration activity is learning about emerging features as a design proceeds. Finally, design activity occurs within two contexts: the context within which the designer operates and the context produced by the developing design itself. The designer’s perception of what the context is affects the implication of the context on the design. The context shifts as the designer’s perceptions change. Design activity can be now characterized as a goal-oriented, con- strained, decision-making, exploration, and learning activity that operates within a con- text that depends on the designer’s percep- tion of the context.

Abstract: 3. Classes should hide their data, we call this encapsulation, only providing a small number of controlled methods or functions in the interface for accessing that data. These factors taken together enable separation of interface from implementation. The actual designs of the algorithms employed inside the classes can be changed as better, more efficient algorithms are found. After a design is complete, changes in a class implementation must not affect its interface. The effect on current and future users is then only in terms of efficiency: their applications need not be recoded to take advantage of the new class implementation. The advantages of separation of interface from implementation include rapid prototyping and graceful refinement. See Fig. 3.