Towards a robust β research design: on reasoning and different classes of unknowns

ABSTRACT Science and intelligence analysis have a different methodological setting. In science a phenomenon is explained in a general sense, it is in the first place aimed at to explain and to contribute to theory. For that the value of the α is the most critical one: you want to keep the number of incorrect relationships as low as possible. Intelligence analysis is in the first place aimed at not to miss a possible threat. In that research, the value of the β is the most critical one: you want to keep the number of missed relationships as low as possible. Yet, many analytic techniques have been developed in science. These have not been calibrated in order not to miss a relationship. Also reasoning – logic – needs to be reformulated, and calibrated from an α to a β approach. Tooling is needed for a research design into the unknowns.