Publication Details

This article was originally published as: Sifer, M, User interfaces for the exploration of hierarchical multi-dimensional data, 2006 IEEE Symposium On Visual Analytics Science and Technology, Baltimore, USA, October 2006, 175-182. Copyright IEEE 2006.


A variety of user interfaces have been developed to support the querying of hierarchical multi-dimensional data in an OLAP setting such as pivot tables and more recently Polaris. They are used to regularly check portions of a dataset and to explore a new dataset for the first time. In this paper, we establish criteria for OLAP user interface capabilities to facilitate comparison. Two criteria are the number of displayed dimensions along which comparisons can be made and the number of dimensions that are viewable at once¿visual comparison depth and width. We argue that interfaces with greater visual comparison depth support regular checking of known data by users that know roughly where to look, while interfaces with greater comparison width support exploration of new data by users that have no apriori starting point and need to scan all dimensions. Pivot tables and Polaris are examples of the former. The main contribution of this paper is to introduce a new scalable interface that uses parallel dimension axis which supports the latter, greater visual comparison width. We compare our approach to both recent table based and parallel coordinate based interfaces. We present an implementation of our interface SGViewer, user scenarios and provide an evaluation that supports the usability of our interface.



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