I am the author of the astronomy and physics ontology mentioned in the original question. The original purpose of that ontology was to improve search for data and articles in astronomy. The idea was to have data sets tables and individual columns in tables marked up with relevant keywords. The rows of data in astronomy are usually different astronomical objects of different types. A search could then be done for a range of values on a property for some type of object and the return would be all relevant data in all astronomical archives. But, as we progressed we thought of many more ways in which such an ontology could be used. A newbie could quickly learn on his/her own from the ontology all the different astronomical species and subspecies,their properties and their brightest or closest examples. One could ask for the latest papers dealing specifically on a particular type of observation of a particular type of object within a range of distances or direction on the sky. I think most of this can carry over into physics as well. One could ask for specific experiments or papers on a topic and then depending on the results ask for results on either broader or narrower terms. Newbies can learn which terms mean nearly the same thing and how they differ, if they do differ. One thing we looked at is whether a complex long paper ca be boiled down to a few simple ontological statements. It helps that a reasoning machine can tell you which statements are repeats of already known things and which are new. Then, with training one could read the results of an entire Physics Review journal in a few minutes. The list goes on and on. However, the funding required to do this is large and right now the only groups that I see doing these kinds of things are Microsoft, Google and Apple and all of that is behind closed doors.

I am the author of the astronomy and physics ontology mentioned in the original question. The original purpose of that ontology was to improve search for data and articles in astronomy. The idea was to have data sets tables and individual columns in tables marked up with relevant keywords. 

The rows of data in astronomy are usually different astronomical objects of different types. A search could then be done for a range of values on a property for some type of object and the return would be all relevant data in all astronomical archives.

But as we progressed, we thought of many more ways in which such an ontology could be used. A newbie could quickly learn on his/her own from the ontology all the different astronomical species and subspecies, their properties and their brightest or closest examples. One could ask for the latest papers dealing specifically on a particular type of observation of a particular type of object within a range of distances or direction on the sky.

I think most of this can carry over into physics as well. One could ask for specific experiments or papers on a topic and then depending on the results ask for results on either broader or narrower terms. Newbies can learn which terms mean nearly the same thing and how they differ, if they do differ.

One thing we looked at is whether a complex long paper can be boiled down to a few simple ontological statements. It helps that a reasoning machine can tell you which statements are repeats of already known things and which are new. Then, with training one could read the results of an entire Physics Review journal in a few minutes. The list goes on and on.

However, the funding required to do this is large and right now the only groups that I see doing these kinds of things are Microsoft, Google and Apple, and all of that is behind closed doors.