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Abstract; Arguing for the need of increasing social awareness on the World Wide Web, we describe a user interface based on the metaphor of windows bridging electronic and physical spaces. We present a system that, with the aim of making online activity perceptible in the physical world, makes it possible to hear people visiting one's website. The system takes advantage of the seamless and continuous network connection offered by handheld Web-appliances such as personal digital assistants.

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. Disciplines Business | Social and Behavioral Sciences

Multi-dimensional data occurs in many domains while a wide variety of text based and visual interfaces for querying such data exists. But many of these interfaces are not applicable to OLAP, as they do not support use of dimension hierarchies for selection and aggregation. We introduce an interface technique which supports visual querying of OLAP data, that has been implemented in the SGViewer tool. It is based on a data graph rather than a data cube representation of the data. Our interface presents each dimension hierarchy in a zoomable panel which supports selection and aggregation at multiple levels. Users explore data and query it by making selections in several dimension views. Three view coordinations are identified; progressive, global and result only. Our main contribution, the progressive view coordination provides better support for query refinement than existing interfaces, by helping users decide the next query step with intermediate result overviews, and by helping users change a previous selection decision with retained selection context views. Our interface technique is demonstrated with a web log dataset of visits organised into time, download, visitor and referrer address dimensions.