“The primary purpose…is to define a common vocabulary that will allow inter-operability and minimize any problems with data integration.” Maybe I am misinterpreting the statement, in which case it would be beneficial to have an ontology for papers on ontology. From what I gather, ontology strives to describe data in a standardized, easily translatable manner. Would that not require culling the outlying definitions, or creating an entirely new definition to categorize. In which case, do we not lose the small nuances and differences? Why are those not as valuable as the opportunity to integrate?
This runs head long as a counter argument to the pro-integration sentiment in Academic Autocorrelation. It is the differences that GIS benefits from. Given our current methods of capturing data, and the sheer scale on which projects are now attempted, it is unlikely that one will ever capture the truth. Rather, it is a representation of the truth from the instant we perceive it. Our interface with our environment consists of no more than five senses, which when compared with other species are rudimentary at best. Furthermore, it is is surprisingly easy to replace reality with something that is not, in which case, though, it still is, according to the viewer, their reality. Thus, the broad range of subjectivity in interpretation is a beneficial burden.
If an ontology were to be imposed on our knowledge set it would constrain our perception, as limited as it is, and yet facilitate transfer across parties. If truth is sacrificed in favor of knowledge transfer, it is the responsibility of the individual to balance accordingly. Unless I am lost myself, in which case I look forward to further clarification.
AMac
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