Yet there is a lack of specific guidance in the visualization literature that describes holistic methodological approaches for conducting design studies
we conducted an extensive literature review in the fields of HCI and social science in hopes of finding methodologies that we could apply directly to design study research. Instead, we found an intellectual territory full of quagmires where the very issues we ourselves struggled with were active subjects of nuanced debate. We did not find any off-the-shelf answers that we consider suitable for wholesale assimilation.
Design studies are one particular form of the more general category of problem-driven research, where the goal is to work with real users to solve their real-world problems. At the other end of the spectrum is technique-driven research, where the goal is to develop new and better techniques without necessarily establishing a strong connection to a particular documented user need.
automation algorithmic solutions such as machine learning techniques make strong assumptions about crisp task clarity and availability of all necessary information. Because many real-world data analysis problems have not yet progressed to the crisp computer ends of the axes, we argue that design studies can be a useful step towards a final goal of a fully automatic solution.
The second axis is the information location, characterizing how much information is only available in the head of the experts versus what has been made explicit in the computer
this axis characterizes how much of the information and context surrounding the domain problem remains as implicit knowledge in the expert’s head, versus how much data or metadata is available in a digital form that can be incorporated into the visualization