I am looking to an IoT like system which must deal with a wide range of data complexities. As an example, I'd like to model a 'thing' and I know all things have a location. However, when the actual data arrives from these things (from different vendors), something like latitude can be spelled, it may have different naming standards (vendor1=lat, vendor2=latitude). I want to build an abstract model at the application layer which knows how to manage these gaps. Preferably using an XML data representation (ie, I could use a std like OAGIS/MIMOSA).
Couple of questions:
1) Has anyone done something similar?
2) Seems like it could be done at the data ingestion layer (ie, harmonize all data into 1 def of lat) or it could be done at query time (when someone executes an API, find the right column and return it). Has anyone done a comparison of these two models?