Information measures usually involve either Shannon information, sometimes designated thermodynamic information, or semantic information. The first is a mathematical measure on a probability distribution while the second is domain specific and lacks an agreed upon formal measure. The relation between Shannon information and entropy has been utilized by E.T. Jaynes to represent the observer’s ignorance of the microstate of a system (fine graining) when the macrostate is known (coarse graining). This makes entropy a mentalistic notion relating to the observers knowledge. In representing chemicals of intermediary metabolism, we have come to a representation in terms of keys and fingerprints or a bit string description of the structures. This is a kind of semantic information whose measure depends on the keys chosen. This opens a discussion of irreversible statistical mechanics and living systems, which is directed at seeking a theory of core metabolic networks.