Route maps, which depict a path from one location to another, have emerged as one of the most popular applications on the Web. Current computer-generated route maps, however, are often very difficult to use. In this paper we present a set of cartographic generalization techniques specifically designed to improve the usability of route maps. Our generalization techniques are based both on cognitive psychology research studying how route maps are used and on an analysis of the generalizations commonly found in handdrawn route maps. We describe algorithmic implementations of these generalization techniques within BeeLine, a real-time system for automatically designing and rendering route maps. We show that Bee-Line produces route maps that are much more usable than those produced by current computer-based route map rendering systems. Feedback from over 1100 users indicates that over 99 % believe BeeLine maps are preferable to using standard computer-generated route maps alone.

Today’s system administrators, burdened by rapidly increasing network activity, must quickly perceive the security state of their networks, but they often have only text-based tools to work with. These tools often provide no overview that would help users grasp the big-picture. Our interviews with administrators have revealed that they need visualization tools. Thus we present VISUAL (Visual Information Security Utility for Administration Live), a network security visualization tool that allows users to perceive communications patterns between their home (or internal) networks and external hosts. VISUAL is part of our Network Eye security visualization architecture, also described in this paper. We have designed and tested a new computer security visualization that gives a quick overview of current and recent communication patterns in the monitored network to the users. Many tools can detect and show fan-out and fan-in, but VISUAL shows network events graphically, in context. Visualization helps users comprehend the intensity of network events more intuitively than text-based tools can. VI-SUAL provides insight for networks with up to 2,500 home hosts and 10,000 external hosts, shows the relative activity of hosts, displays them in a constant relative position, and reveals the ports and protocols used.

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The contribution presents a computational modeling approach to geographic knowledge processing in mind. Geographic knowledge is assumed to be stored in a piecemeal manner. Spatial knowledge fragments form a hierarchical structure of lean knowledge. An actual mental image representation is constructed when needed to perform a specific task. In this construction process missing information is complemented to create a determinate mental image. -- First, the artificial intelligence perspective taken is elaborated. After a short review of conceptions on mental processing of spatial knowledge from psychology and artificial intelligence we outline the model MIRAGE. The internal structure and the operating of the model is elaborated using an exemplary scenario. Problems in constructing mental images from given pieces of knowledge are demonstrated and discussed. The paper concludes with a discussion of the approach with respect to its modeling objective. We point to further research questions and to potential applications.

A route map depicting a path from one location to another

The cognitive maps that humans compute as representations of the spatial environment they have visited are rarely even close approximations to what was actually experienced. When we experience the environment we seem to see it all so perfectly, yet rarely are we able to reproduce from memory an exact description of the places visited. Yet these vague, muddled descriptions of the places visited are adequate for many spatial reasoning tasks. But how is such an impoverished representation computed from what is initially delivered by one's senses? And what effect does this representation have on the construction of the cognitive map? We present one method for computing a vague description of each local space visited. It is derived from the initially accurate description needed for the actions the viewer might perform within the local space. We show the effect of this representation on the structure of the cognitive map. Introduction Urban planners, geographers and environm...

Suppose that you are required to describe a route step-bystep to somebody who does not know the environment. A major question in this context is what kind of spatial information must be integrated in a route description. This task generally refers to two cognitive abilities: Visual perception and natural language. In this domain, a computational model for the generation of incremental route descriptions is presented. Central to this model is a distinction into a visual, a linguistic, and a conceptual-spatial level. Basing on these different levels a software agent, called MOSES, is introduced who moves through a simulated 3D environment from a starting-point to a destination. He selects visuospatial information and generates appropriate route descriptions. It is shown how MOSES adopts his linguistic behavior to spatial and temporal constraints. The generation process is based on a corpus of incremental route descriptions which were collected by field experiments. The agent and the 3D...

Within psychology, at least two research communities study spatial cognition. One community studies systematic errors in spatial memory and judgement, accounting for them as a consequence of and clue to normal perceptual and cognitive processing. The other community studies navigation in real space, isolating the contributions of various sensory cues and sensori-motor systems to successful navigation. The former group emphasizes error, the latter, selective mechanisms, environmental or evolutionary, that produce fine-tuned correct responses. How can these approaches be reconciled and integrated? First, by showing why errors are impervious to selective pressures. The schematization that leads to errors is a natural consequence of normal perceptual and cognitive processes; it is inherent to the construction of mental spaces and to using them to make judgments in limited capacity working memory. Selection can act on particular instances of errors, yet it is not clear that selection can act on the general mechanisms that produce them. Next, in the wild, there are a

The quality of an object localization depends essentially on the adequate selection of a suitable reference. In most computational approaches developed so far only the distance between the located object and a potential reference object has been used as a decision criterion. However many other criteria have to be considered for a cognitive plausible selection of adequate reference points. In this paper we investigate how object and context dependent properties, like referentiality, visual salience, functional dependencies, or prior knowledge, influence the quality of a reference object. Each factor is quantitatively determined and scaled by relevance to a certain context. The scaling permits the necessary comparability of the different quality criteria. Finally, on the basis of these factors a computational model is presented which permits a context dependent determination of the optimal reference object in a particular spatial configuration.

Abstract. This article suggests a second thought on two papers published in Cognitive psychology in 1978 and 1981. Both articles deal with systematic distortions in cognitive mapping and both are based on experiments conducted along the North American West Coast. The first, by Stevens and Coupe, deals with distortions due to hierarchical organization while the second, by Tversky, with distortions due to rotation. Our second thought follows a set empirical results from a study conducted along the (West) coast of Israel. These results suggest that the experiments, on the basis of which the above two forms of systematic distortions were determined, could have resulted from another form of systematic distortion that we term the edge effect. 1.