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Research beyond Data

The final speaker (that went fast) at the CCC Symposium is Annette Markham, who begins by posing the question "What counts as data?" An answer to that question might provide an opportunity to bridge 'big data' and qualitative research - because what counts as data also defines what is considered to be viable, credible, or interesting findings.

The focus on 'data' results in a focus on the process of data collection, which minimises the other phases of inquiry that are vital to the production of knowledge and understanding. What's missing here are the other aspects of research which are also important to its outcomes. A focus on 'small data' doesn't make any difference to this, incidentally - it, too, can obscure the invisible practices of everyday research. Instead, we must generally strive for more clarity and transparency about our research, whatever kind of data it draws on.

Similarly, a drive for more 'evidence-based' research can constrain innovation, and in some cases is in direct conflict with the need for maintaining strong research ethics. The push for sharing research data, and for transparently presenting research outcomes, can be in inherent conflict with the need to protect the privacy of the research subjects whose activities such data represent, often in minute detail.

Data simply are 'the stuff we collect'. This stuff is collectible, observable, material, measurable, quantifiable, verifiable - but what isn't included here are the other outputs of research activities: fieldwork, notes, mindwork, doodling, drawing, exploring possibilities, and rendering various representations. That stuff is very personal and practice-oriented, in contrast to the object-oriented data; it's not merely data – or metadata – but generative of new data.

The research process can be represented as a path with several decision points, and each of these points also offers a number of paths not taken which would result in very different outcomes; at these decision points, interpretation takes place. Maybe what we need to do in our quest for understanding is not to refine the data, then – but returning to the question of why we're doing it in the first place, and why we're taking which specific decisions as we pursue our research.

This means going back to basics: what do we do when we do inquiry? We interrogate, move, play, generate; and in doing so we don't only focus on data, but on all the points along the paths of our research. Labelling this as qualitative or quantitative provides us with convenient categories, but does not begin to describe the full complexity of what we do.