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Dear Klaus, Ken, Don and all, Apologies in advance for the length of the following and any misspellings and grammatical errors - written in one pass under time pressure The discussion below has three roles: a reply to Klaus; a suggestion of an alternative to the way that design research has been coined in terms of basic, applied and clinical research by Ken; and a suggestion that we have misunderstood how to gain radical innovations from simple observations such as user testing. The requirement is to see these things in a very different way. One way is via tools that were developed in the 70s and 80s and were lost in a 'change of guard' of design researchers and design practice. Much of what is described below is in the literature hidden in full view The core of the following is from my own design research developments as an undergrad student, from discussions in the mid-70s with John Woollatt of Northumbria University supplemented from design research analyses published in Design Studies, RED, AIDAM, some books on design practice and some developments in design theory that occurred in the North of England and Cambridge at around that time. From observation, when these development are mentioned in current literature they are reinterpreted by reviewers to fit with what is implied by them as a limited contemporary view of design and design research. There are three starting premises: 1. That currently design and design research are viewed too naively. To understand the phenomena better requires a much more sophisticated picture of the situations of both. 2. That we have mistakenly focused attempts to understand and improve design on subjective and objective observations of the activities of humans undertaking design activity 3. That we have limited the approaches to understanding design and design research by the way we see the world in 3 dimensions plus time. I suggest the 'small world' view outlined in the above three premises has led to many false dead ends as shown in the design practice and design research literatures. One is the apparently obvious assumption that research and user testing cannot be a method to identifying radical innovations. An example of a design method that goes beyond what is addressed by conventional views on design as an activity and design research might be called 'Solutions Set Space Dynamics'. The design method is straightforward: use sophisticated mapping approaches to identify the n- dimensional behaviour, factors and influences of the solution space relating to a design. From this, identify interesting regions of the solution set space and also those regions in which there are no solutions. This opens the design situation up to identifying regions of solution set space in which there are radical innovations. It also provides information about the scope of these regions (important for example in terms of whether one is looking for a unique design or a platform solution). The role of the human-centred research approaches in the above (including aesthetics, marketing, affect-based design, social-dynamics as well as traditional HCD approaches) is in conjunction with technical, legal, financial and related research inputs to identify the n-dimensional shape and dynamics of the solutions set space. Yes, the maths can be tough. In early days, however, the approach proved to be usable and successful even with limited technology. It was relatively easy to program in Fortran 66 in the early 70s using a few seconds of processor time on an ICL 1900 running Minimops and George2 operating system. An extension of this approach, is to make an additional dynamic model (n+m dimensional) of the dynamics of the characteristics and behaviour of the 'interesting solution set space'. This offers an automated way for identifying radical design solutions and optimal design solutions directly from the research. In effect, the research identifies the potential designs, and radical designs too. Even more usefully, it reveals the full spectrum of potential designs - including the radical ones, whereas human designers have to laboriously use subjective creativity to identify individual radical designs one by one. The machine learning community and games designers are already working in this realm of design research and practice. Architecture and urban planning moved into the arena in the 80s and then backed out presumably due to a shortage of mathematicians. Chris Alexander of course was dipping his toe in and Chuck and Mary Owen developed useful tools, methods and designs. This 'Solution Set Space Dynamics' approach and arena of design research and practice is useful and interesting. Perhaps it is most interesting because like a black swan it exposes many or most current perspectives on design and design research as overly limited. It suggests that design research can generate radical outcomes, it can also identify regions of radical design solutions that human designers would be hard put to creatively identify. It identifies a research approach that spans all basic, applied and clinical categories as well as identifying designs. It provides a PhD-level research approach that includes HCD to create design solutions. Best wishes, Terry === Refs. Klaus> re-search in the sense of searching for patterns among available data .... cannot generate anything new (except for new generalizations). Ken> Basic research involves a search for general principles ... Applied research adapts the findings of basic research to classes of problems... Clinical research involves specific cases Don> Incremental Innovation... This is where design research hits its stride.