Ontology for Data Science

When I returned to university to do a graduate degree, I was interested to discover how certain terms are subject to "intellectual interpretation." A word that I was asked to explain during one of my earliest classes was "ontology." Since this term was absent from my dictionary, I originally confused it with "oncology." I faintly recall that oncology involves the study of tumors. After consulting a few sources, I said that ontology is the study of how things come to exist or into being. I came across another perspective although I don't recall the source: ontology is the study of how things gain relevance or become recognized, indicating that existence can be regarded as a matter of recognition. Perhaps there is no monopoly on the exact meaning. However, I would say of ontology in relation to data science, it explains how meaning is attached to data and therefore how that data gains and retains meaning. For example, if I were asked to count the number of trucks in a parking lot, it isn't obvious what should be included: small pick-ups, tow-trucks, commercial hauling vehicles, dump trucks, and maybe heavy construction trucks.