Multiple different understandings and uses exist of what granularity is and how to implement it, where the former influences success of the latter with regards to storing granular data and using granularity for reasoning over the data or information. We propose a taxonomy of types of granularity and discuss for each leaf type how the entities or instances relate within its granular level. Such unambiguous distinctions can guide a conceptual modeler to better distinguish between the types of granularity and the software developer to improve on implementations of granularity.
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