I think the Rossman dataset is covered in class and in the forums anyways but of course there could be more experimenting on it. And while of course it is time related, it is not the kind of univariate time series we have discussed in this thread. It is more a regression problem of taking a lot of columnar information in and then predicting “the missing column”. So this can also be seen as time independent. In the datasets in the UCR it is always only the time and therefore sequence of values that is the key to the problem, not how well other features can be related to some output at some point in time. And the problems are classification problems where as Rossman wants a regression value for the total sales of a store as a result.
What would be kind of interesting though is transforming the Data into the time series type of problem (meaning you would for example get one time series per store location and item group). Then it would fit the kind of time series discussed here so far (although it still would not be a classification problem).