Interaction Design: Foundations, Experiments

Interaction Design: Foundations, Experiments is the result of a series of projects, experiments and curricula aimed at investigating the foundations of interaction design in particular and design research in general. The first part of the book - Foundations - deals with foundational theoretical issues in interaction design. An analysis of two categorical mistakes -the empirical and interactive fallacies- forms a background to a discussion of interaction design as act design and of computational technology as material in design. The second part of the book - Experiments - describes a range of design methods, programs and examples that have been used to probe foundational issues through systematic questioning of what is given. Based on experimental design work such as Slow Technology, Abstract Information Displays, Design for Sound Hiders, Zero Expression Fashion, and IT+Textiles, this section also explores how design experiments can play a central role when developing new design theory

Beyond words: Aesthetic knowledge and knowing in design

Aesthetic knowledge comes from practitioners understanding the look, feel, smell, taste and sound of things. It is vital to work in many organizational contexts. In this paper, we explore aesthetic knowledge and knowing in organizations through detailed observation of design work in the architectural practice Edward Cullinan Architects. Through our research, we explore aesthetic knowledge in the context of architectural work, we unpack what it is, how it is generated, and how it is applied in design projects, shared between practitioners and developed at the level of the organization. Our analysis suggests that aesthetic knowledge plays an important part in organizational practice, not only as the symbolic context for work, but as an integral part of the work that people do. It suggests that aesthetic reflexivity, which involves an opening up and questioning of what is known, is experienced as part of practice as well as a `time out' from practice

The discipline of Natural Design

If we define design work as those cognitive and practical things to which designers give their valuable effort, then our Natural Design framework allows the recording and replaying of design work. Natural Design provides a meta-structural framework that has developed through our observations of engineering design in safety and mission critical industries, such as aircraft design. Our previous work has produced parametrisable models of design work for software intensive systems, and we now look to make an initial assessment of our natural design framework for its fit to the more creative design practices. In this paper we briefly sketch the framework and subsequently attempt to locate ‘creativity’ in it. We find that, although there are good strong hooks for what the designer does, we are forced to find a role for the community of the designer in the creative process in our framework, something that was only implicit in our previous work. Keywords: Natural design; Engineering design; Creativity</p

Plotting the Centre: Bramante’s Drawings for the New St. Peter’s Basilica

This paper examines the concept of 'centre' in the design and symbolism of the new St Peter's Basilica, executed by Donato Bramante in the early 16th century. Drawing upon theological and philosophical notions of centre in late Medieval and Renaissance culture (specifically Nicolas Cusanus), the study argues that Bramante's drawings for the project reveal a particular understanding of centre, and its constellations of sub-centres, that broadly follow Platonic cosmological principles highlighted in the Timaeus. The paper considers how this understanding of space was also communicated in the iconography of the frescoes in the Stanza della Segnatura in the Vatican Palace, executed by Raphael at the same time as Bramante's design for the new basilica, in which Bramante is also credited as the author of the perspective construction

Reconstructive Sparse Code Transfer for Contour Detection and Semantic Labeling

We frame the task of predicting a semantic labeling as a sparse reconstruction procedure that applies a target-specific learned transfer function to a generic deep sparse code representation of an image. This strategy partitions training into two distinct stages. First, in an unsupervised manner, we learn a set of generic dictionaries optimized for sparse coding of image patches. We train a multilayer representation via recursive sparse dictionary learning on pooled codes output by earlier layers. Second, we encode all training images with the generic dictionaries and learn a transfer function that optimizes reconstruction of patches extracted from annotated ground-truth given the sparse codes of their corresponding image patches. At test time, we encode a novel image using the generic dictionaries and then reconstruct using the transfer function. The output reconstruction is a semantic labeling of the test image. Applying this strategy to the task of contour detection, we demonstrate performance competitive with state-of-the-art systems. Unlike almost all prior work, our approach obviates the need for any form of hand-designed features or filters. To illustrate general applicability, we also show initial results on semantic part labeling of human faces. The effectiveness of our approach opens new avenues for research on deep sparse representations. Our classifiers utilize this representation in a novel manner. Rather than acting on nodes in the deepest layer, they attach to nodes along a slice through multiple layers of the network in order to make predictions about local patches. Our flexible combination of a generatively learned sparse representation with discriminatively trained transfer classifiers extends the notion of sparse reconstruction to encompass arbitrary semantic labeling tasks.Comment: to appear in Asian Conference on Computer Vision (ACCV), 201