What the SDR represent depends on how the program (the HTM system) has been trained. To get labeled categories out of HTM it is trained on labelled data or the output of the HTM is classified by another algorithm.
The HTM algorithm learns spatial and temporal patterns. Similar patterns generate similar SDR and those similarities could be thought of (by the human operator) as features of the inputs.
When relating a set of features with a label this can be considered object recognition. For example, feed a sequence of digits and the feed the output to an SVM decoder that classified the HTM output as a digit.
The HTM algorithm can also be trained to classify, then a simpler decoder can turn the classification represented by an SDR into a label that represents an object.
Regarding introspection (in your next post) check out the video with Hawkins talking about introspection at the beginning.