Architectural research and its enemies

Like the Research Assessment Exercise (RAE) that preceded it, the UK government's proposed Research Excellence Framework (REF) is a means of allocating funding in higher education to support research. As with any method for the competitive allocation of funds it creates winners and losers and inevitably generates a lot of emotion among those rewarded or penalised. More specifically, the 'winners' tend to approve of the method of allocation and the 'losers' denigrate it as biased against their activities and generally unfair. An extraordinary press campaign has been consistently waged against research assessment and its methods by those involved in architectural education, which I will track over a decade and a half. What follows will question whether this campaign demonstrates the sophistication and superior judgment of those who have gone into print, or conversely whether its mixture of misinformation and disinformation reveals not just disenchantment and prejudice, but a naivety and a depth of ignorance about the fundamentals of research that is deeply damaging to the credibility of architecture as a research-based discipline. With the recent consultation process towards a new cycle of research assessment, the REF, getting under way, I aim to draw attention to the risk of repeating past mistakes. Copyright © Cambridge University Press 2010.

Improving data quality in DSM modelling: A structural comparison approach

The Dependency Structure Matrix (DSM) has proved to be a useful tool for system structure elicitation and analysis. However, as with any modelling approach, the insights gained from analysis are limited by the quality and correctness of input information. This paper explores how the quality of data in a DSM can be enhanced by elicitation methods which include comparison of information acquired from different perspectives and levels of abstraction. The approach is based on comparison of dependencies according to their structural importance. It is illustrated through two case studies: creation of a DSM showing the spatial connections between elements in a product, and a DSM capturing information flows in an organisation. We conclude that considering structural criteria can lead to improved data quality in DSM models, although further research is required to fully explore the benefits and limitations of our proposed approach.