.

see

http://people.eecs.ku.edu/~jerzy/c97-brighton.pdf

(and other publications by the same author)

.

information which is incomplete is not the same as missing data. In simple terms, "Incomplete information" means that we do not have enough *information* (attributes) to describe the underlying concept in order to be able to say which objects belong to it with certainty. An equivalence relation is used in order to build information 'granules' which can then be used to measure indiscernibility between data objects as a way to try to distinguish between them.  Missing data is just that: data that is not available or has been lost or corrupted in the dataset for whatever reason. RST can still be used to do data imputation based on the indiscernibility but this is a rather different task. 

 The "information system" is a special kind of "data", and the "incomplete information system" is naturally a kind of "incomplete data". When the target data possesses "Objects" and "Features", and together with the corresponding mapping between objects and features, the data can be called an information system. The sentence "RST proposed by prof. Pawlak is a tool to deal with incomplete data" means that the RST has a certain ability to handle specific uncertainty in the incomplete data, it cannot deal with other special incomplete data. Such as: when the data are missing or lost, the classical RST cannot deal with it, and it needs to be generalized by introducing tolerance relation.  It should be pointed out that the word "incomplete" is not the same one.