While working on ontology engineering for about 25 years, I think I unconsciously acquired my own methodology in ontology engineering. It is what I call ‘state-centric’ methodology. My background is in AI and Engineering rather than logic or philosophy, and it must have been driving me to understand reality in terms of states which are the heart of General Problem Solver (GPS). All my results on roles, functions, processes/events and causation (published in Applied Ontology) clearly show the utility of the state-centric methodology. My treatment of context seems rather unique since I claim that any object as a whole provides a context to its parts, and each of these play their assigned role to make the collection a unitary whole. The notion of ‘non-intentional goal’ together with the systemic context as its concretization works very well to capture temporal entities. The success of the unified definition of biological and artifact functions is largely based on this idea. The device ontology, which I have devised for enabling to capture dynamic and complex phenomena in a consistent manner, has been exploited in many of my works on function. It is a role assignment system and fully state-centric. In my recent work on causation, I have realized that any causation C → E can be mapped onto a function in which E is a non-intentional goal in the systemic context associated with C → E. The new functional talk of causation is fully state-centric which contrasts with the common idea that states should be excluded from the relata of causation. I found that the essence of causation exists in an occurrent in the form <Event cause State> where State is the resultant state of the Event. In my keynote, I discuss the state-centric methodology through typical achievements on roles, function, processes/events and causation.
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