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"The Internet is often likened to an organic entity and this analogy seems particularly appropriate in the light of some striking new visualizations of the complex mesh of Internet pathways. The images are results of a new graph visualization tool, code-named Walrus, being developed by researcher, Young Hyun, at the Cooperative Association for Internet Data Analysis (CAIDA) [1]. Although Walrus is still in early days of development, I think these preliminary results are some of the most intriguing and evocative images of the Internet's structure that we have seen in last year or two. A few years back I spent an enjoyable afternoon at the Monterey Bay Aquarium and I particularly remember a stunning exhibit of jellyfish, which were illuminated with UV light to show their incredibly delicate organic structures, gently pulsing in tanks of inky black water. Jellyfish are some of the strangest, alien, and yet most beautiful, living creatures [2]. Having looked at the Walrus images I began to wonder, perhaps the backbone networks of the Internet look like jellyfish? The image above is a screengrab of a Walrus visualization of a huge graph. The graph data in this particular example depicts Internet topology, as measured by CAIDA's skitter monitor [3] based in London, showing 535,000-odd Internet nodes and over 600,000 links. The nodes, represented by the yellow dots, are a large sample of computers from across the whole range of Internet addresses. Walrus is an interactive visualization tool that allows the analyst to view massive graphs from any position. The graph is projected inside a 3D sphere using a special kind of space based hyperbolic geometry. This is a non-Euclidean space, which has useful distorting properties of making elements at the center of the display much larger than those on the periphery. You interact with the graph in Walrus by selecting a node of interest, which is smoothly moved into the center of the display, and that region of the graph becomes greatly enlarged, enabling you to focus on the fine detail. Yet the rest of the graph remains visible, providing valuable context of the overall structure. (There are some animations available on the website showing Walrus graphs being moved, which give some sense of what this is like.) Hyperbolic space projection is commonly know as "focus+context" in the field of information visualization and has been used to display all kinds of data that can be represented as large graphs in either two and three dimensions [4]. It can be thought of as a moveable fish-eye lens. The Walrus visualization tool draws much from the hyperbolic research by Tamara Munzner [5] as part of her PhD at Stanford. (Map of the Month examined some of Munzner's work from 1996 in an earlier article, Internet Arcs Around The Globe.) Walrus is being developed as a general-purpose visualization tool able to cope with massive directed graphs, in the order of a million nodes. Providing useful and interactively useable visualization of such large volumes of graph data is a tough challenge and is particularly apposite to the task of mapping of Internet backbone infrastructures. In a recent email Map of the Month asked Walrus developer Young Hyun what had been the hardest part of the project thus far. "The greatest difficulty was in determining precisely what Walrus should be about," said Hyun. Crucially "... we had to face the question of what it means to visualize a large graph. It would defeat the aim of a visualization to overload a user with the large volume of data that is likely to be associated with a large graph." I think the preliminary results available show that Walrus is heading in right direction tackling these challenges.

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The View From Above Browsing for a particular piece on information on the Web can often feel like being stuck in an unfamiliar part of town walking around at street level looking for a particular store. You know the store is around there somewhere, but your viewpoint at ground level is constrained. What you really want is to get above the streets, hovering half a mile or so up in the air, to see the whole neighbourhood. This kind of birds-eye view function has been memorably described by David D. Clark, Senior Research Scientist at MIT's Laboratory for Computer Science and the Chairman of the Invisible Worlds Protocol Advisory Board, as the missing "up button" on the browser [3] . ET-Map is a nice example of a prototype for Clark's "up-button" view of an information space. The goal of information maps, like ET-Map, is to provide the browser with a sense of the lie of the information landscape, what is where, the location of clusters and hotspots, what is related to what. Ideally, this 'big-picture' all-in-one visual summary needs to fit on a single standard computer screen. ET-Map is one of my favourite examples, but there are many other interesting information maps being developed by other researchers and companies (see inset at the bottom of this page). How does ET-Map work? Here is a sequence of screenshots of a typical browsing session with ET-Map, which ends with access to Web pages on jazz musician Miles Davis. You can also tryout ET-Map for yourself, using a fully working demo on the AI Lab's website [4] . We begin with the top-level map showing forty odd broad entertainment 'subject regions' represented by regularly shaped tiles. Each tile is a visual summary of a group of Web pages with similar content. These tiles are shaded different colours to differentiate them, while labels identify the subject of the tile and the number in brackets telling you how many individual Web page links it contains. ET-Map uses two important, but common-sense, spatial concepts in its organisation and representation of the Web. Firstly, the 'subject regions' size is directly related to the number of Web pages in that category. For example, the 'MUSIC' subject area contains over 11,000 pages and so has a much larger area than the neighbouring area of 'LIVE' which only has 4,300 odd pages. This is intuitively meaningful, as the largest tiles are visually more prominent on the map and are likely to be more significant as they contain the most links. In addition, a second spatial concept, that of neighbourhood proximity, is applied so 'subject regions' closely related in term of content are plotted close to each other on the map. For example, 'FILM' and 'YEAR'S OSCARS', at the bottom left, are neighbours in both semantic and spatial space. This make senses as many things in the real-world are ordered in this way, with things that are alike being spatially close together (e.g. layout of goods in a store, or books in a library). Importantly, ET-Map is also a multi-layer map, with sub-maps showing greater informational resolution through a finer degree of categorization. So for any subject region that contains more than two hundred Web pages, a second-level map, with more detailed categories is generated. This subdivision of information space is repeated down the hierarchy as far as necessary. In the example, the user selected the 'MUSIC' subject region which, not surprisingly, contained many thousands of pages. A second-level map with numerous different music categories is then presented to the user. Delving deeper, the user wants to learn more about jazz music, so clicking on the 'JAZZ' tile leads to a third-level map, a fine-grained map of jazz related Web pages. Finally, selecting the 'MILES DAVIS' subject region leads to more a conventional looking ranking of pages from which the user selects one to download.
Research Prototypes Visual SiteMap Developed by Xia Lin, based at the College of Library and Information Science, Drexel University. CVG Cyberspace geography visualization, developed by Luc Girardin, at The Graduate Institute of International Studies, Switzerland. WEBSOM Maps the thousands of articles posted on Usenet newsgroups. It is being developed by researchers at the Neural Networks Research Centre, Helsinki University of Technology in Finland. TreeMaps Developed by Brian Johnson, Ben Shneiderman and colleagues in the Human-Computer Interaction Lab at the University of Maryland. Commercial Information Maps: NewsMaps Provides interactive information landscapes summarizing daily news stories, developed Cartia, Inc. Web Squirrel Creates maps known as information farms. It is developed by Eastgate Systems, Inc. Umap Produces interactive maps of Web searches. Map of the Market An interactive map of the market performance of the stocks of major US corporations developed by SmartMoney.com."