Update ontology.md

docs/Data_Standardization/ontology.md

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-To evolve towards a findable and federatable data future, projects are adopting an ontology framework layer which essentially attempts to externalise as much of the language a dataset uses as possible, enabling it to join a larger semantically interoperable community of datasets.  Other benefits accrue - database development personnel reuse 3rd party structured vocabulary rather than unwittingly maintaining mirrored semblances of them, for example.  We begin with a short discussion of what ontologies are, how they differ from simpler kinds of structured vocabulary, and why certain features of them are needed to achieve a federated data future.  We also cover tips and training resources about how to locate and reuse ontologies in study metadata and data schemas. 
+To evolve towards a findable and federatable data future, projects are adopting an ontology framework layer which essentially attempts to externalise as much of the language a dataset uses as possible, enabling it to join a larger semantically interoperable community of datasets.  Other benefits accrue - database development personnel reuse 3rd party structured vocabulary rather than unwittingly maintaining mirrored semblances of them, for example.  We begin with a short discussion of what ontologies are, how they differ from simpler kinds of structured vocabulary, and why certain features of them are needed to achieve a federated data future.  We also cover tips and training resources about how to locate and reuse ontologies in study metadata and data schemas.   Much standardization work can be done on a data schema before introducing ontology ids into it, but the schema is the practical tree on which ontology terms hang, and they then provide the comparable fruits of interoperability. 
 
 The definition of "**ontology**" in Wikipedia speaks to its historical roots as an area of philosophy dedicated to the "study of being in reality", and dives into how things can be categorized and identified through time.  Our focus is on "**applied ontology**", which makes use of categorization and formal logic work in philosophy, but turns to description of **material entities** (things), their **characteristics** (attributes), **processes** or events that they are involved in, and **roles, functions or dispositions** they may have.  All this formality is in an effort to come to a shared agreement about how to categorize scientific terms systematically, once and for all - but recognizing that science itself makes room for hypotheses, revisions, and paradigm shifts, and so needs ontologies to evolve.