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.