I'm working on a data model which, I think, produces more accurate and valid results than some of previous works by others, including my supervisor, who by the way supports my work. But so far, the relevant community in general hasn't paid enough attention to the need for such more accurate results in this field.
When presenting my work (verbal/poster/paper), I need to emphasise the importance of the problem and the need to using better models, and that if we used less valid models (such as some of the existing ones) we should expect less accurate results.
Is it rude to use the computer science axiom "garbage in, garbage out" (or similar phrases) when referring to others' works in this context?
Edit: I missed important details. In my case, by 'garbage' I specifically mean the low-quality data usually used to solve the problem, which makes other models less valid. Even though, I would never use it as it might be misinterpreted as evaluation of the works per se, rather than the resources used!
But I was surprised and not comfortable to read the analogy in a published comment which criticised another author's results for using unreliable data!