Signpost - a semiotics-based process mining methodology

The era of big data research poses new challenges to the IS community. Nefarious underlying assumptions limit the potential of methods and techniques, both in practice and in theory. This is also the case for the field of process mining, a specialised area within the field of big data where data resulting from process
executions is analysed to achieve real-world process insights and improvements. In order to deal with problematic and limiting assumptions in this field, it is proposed to develop a methodology inspired by semiotics so that data is better understood in context and to learn from an established theory-informed
big data methodology to go beyond classical, project-focused, process mining, toward theory building for other disciplines. An initial high-level version of the resulting Signpost methodology is presented in this paper.