Hierarchical Aggregation for Information Visualization: Overview, Techniques, and Design Guidelines <s> Drill-Down and Roll-Up <s> Big information worlds cause big problems for interfaces. There is too much to see. They are hard to navigate. An armada of techniques has been proposed to present the many scales of information needed. Space-scale diagrams provide an analytic framework for much of this work. By representing both a spatial world and its different magnifications explicitly, the diagrams allow the direct visualization and analysis of important scale related issues for interfaces. <s> BIB001 </s> Hierarchical Aggregation for Information Visualization: Overview, Techniques, and Design Guidelines <s> Drill-Down and Roll-Up <s> Our ability to accumulate large, complex (multivariate) data sets has far exceeded our ability to effectively process them in searching for patterns, anomalies and other interesting features. Conventional multivariate visualization techniques generally do not scale well with respect to the size of the data set. The focus of this paper is on the interactive visualization of large multivariate data sets based on a number of novel extensions to the parallel coordinates display technique. We develop a multi-resolution view of the data via hierarchical clustering, and use a variation of parallel coordinates to convey aggregation information for the resulting clusters. Users can then navigate the resulting structure until the desired focus region and level of detail is reached, using our suite of navigational and filtering tools. We describe the design and implementation of our hierarchical parallel coordinates system which is based on extending the XmdvTool system. Lastly, we show examples of the tools and techniques applied to large (hundreds of thousands of records) multivariate data sets. <s> BIB002 </s> Hierarchical Aggregation for Information Visualization: Overview, Techniques, and Design Guidelines <s> Drill-Down and Roll-Up <s> In Web data, telecommunications traffic and in epidemiological studies, dense subgraphs correspond to subsets of subjects (i.e. users, patients) that share a collection of attributes values (i.e. accessed Web pages, email-calling patterns or disease diagnostic profiles). Visual and computational identification of these "clusters" becomes useful when domain experts desire to determine those factors of major influence in the formation of access and communication clusters or in the detection and contention of disease spread. With the current increases in graphic hardware capabilities and RAM sizes, it is more useful to relate graph sizes to the available screen real estate S and the amount of available RAM M, instead of the number of edges or nodes in the graph. We offer a visual interface that is parameterized by M and S and is particularly suited for navigation tasks that require the identification of subgraphs whose edge density is above certain threshold. This is achieved by providing a zoomable matrix view of the underlying data. This view is strongly coupled to a hierarchical view of the essential information elements present in the data domain. We illustrate the applicability of this work to the visual navigation of cancer incidence data and to an aggregated sample of phone call traffic <s> BIB003
While zoom and pan merely control the geometric properties of the display, the drill-down and roll-up operations govern the level of detail at which the data is displayed BIB002 (Fig. 4) . In other words, drill-down moves the rendering traversal deeper into the aggregate hierarchy, showing increasing amounts of detail, whereas roll-up moves up in the hierarchy, showing less detail. These operations are usually coupled with above rendering traversals of the aggregate hierarchy, although level traversals can be used to show a specific level in the hierarchy, and below traversals for showing the aggregation structure. In some cases, drilling and rolling should be restricted to the current geometric zoom and pan, or coupled with geometric zoom (see Section 3.5.5): drilling down further may not make sense if individual visual entities become smaller than a single pixel, and rolling may analogously not be useful if the entities become larger than the screen. While geometric zoom is typically implemented as continuous BIB001 , the level-of-detail of an aggregated visualization is clearly discrete. To facilitate user perception of the interaction technique changing the detail level, animated transitions between aggregation levels, like in the Matrix Zoom BIB003 system, can come in useful. Many times, the viewer may want to perform drilling and rolling on a specific subtree of the aggregation hierarchy, instead, of on the whole tree. See the next section for more details.