Cyber situational awareness: from geographical alerts to high-level management

This paper focuses on cyber situational awareness and describes a visual analytics solution for monitoring and putting in tight relation data from network level with the organization business. The goal of the proposed solution is to make different security profiles (network security officer, network security manager, and financial security manager) aware of the actual network state (e.g., risk and attack progress) and the impact it actually has on the business tasks, making clear the relationships that exist between the network level and the business level. The proposed solution is instantiated on the ACEA infrastructure, the Italian company that provides power and water purification services to cities in central Italy (millions of end users

A parent-centered radial layout algorithm for interactive graph visualization and animation

We have developed (1) a graph visualization system that allows users to explore graphs by viewing them as a succession of spanning trees selected interactively, (2) a radial graph layout algorithm, and (3) an animation algorithm that generates meaningful visualizations and smooth transitions between graphs while minimizing edge crossings during transitions and in static layouts. Our system is similar to the radial layout system of Yee et al. (2001), but differs primarily in that each node is positioned on a coordinate system centered on its own parent rather than on a single coordinate system for all nodes. Our system is thus easy to define recursively and lends itself to parallelization. It also guarantees that layouts have many nice properties, such as: it guarantees certain edges never cross during an animation. We compared the layouts and transitions produced by our algorithms to those produced by Yee et al. Results from several experiments indicate that our system produces fewer edge crossings during transitions between graph drawings, and that the transitions more often involve changes in local scaling rather than structure. These findings suggest the system has promise as an interactive graph exploration tool in a variety of settings

Professional judgement and decision making in adventure sports coaching: The role of interaction

This qualitative study presents the view that coaching practice places demands on the coach’s adaptability and flexibility. These requirements for being adaptive and flexible are met through a careful process of professional judgement and decision making based on context-appropriate bodies of knowledge. Adventure sports coaches were selected for study on the basis that adventure sports create a hyper-dynamic environment in which these features can be examined. Thematic analysis revealed that coaches were generally well-informed and practiced with respect to the technical aspects of their sporting disciplines. Less positively, however, they often relied on ad-hoc contextualization of generalised theories of coaching practice to respond to the hyper-dynamic environments encountered in adventure sports. We propose that coaching practice reflects the demands of the environment, individual learning needs of the students, and the task at hand. Together, these factors outwardly resemble a constraints led approach but, we suggest, actually reflect manipulation of these parameters from a cognitive rather than an ecological perspective. This process is facilitated by a refined judgement and decision-making process, sophisticated epistemology and an explicit interaction of coaching components

GraphMaps: Browsing Large Graphs as Interactive Maps

Algorithms for laying out large graphs have seen significant progress in the past decade. However, browsing large graphs remains a challenge. Rendering thousands of graphical elements at once often results in a cluttered image, and navigating these elements naively can cause disorientation. To address this challenge we propose a method called GraphMaps, mimicking the browsing experience of online geographic maps. GraphMaps creates a sequence of layers, where each layer refines the previous one. During graph browsing, GraphMaps chooses the layer corresponding to the zoom level, and renders only those entities of the layer that intersect the current viewport. The result is that, regardless of the graph size, the number of entities rendered at each view does not exceed a predefined threshold, yet all graph elements can be explored by the standard zoom and pan operations. GraphMaps preprocesses a graph in such a way that during browsing, the geometry of the entities is stable, and the viewer is responsive. Our case studies indicate that GraphMaps is useful in gaining an overview of a large graph, and also in exploring a graph on a finer level of detail.Comment: submitted to GD 201

How to Display Group Information on Node-Link Diagrams: An Evaluation

We present the results of evaluating four techniques for displaying group or cluster information overlaid on node-link diagrams: node coloring, GMap, BubbleSets, and LineSets. The contributions of the paper are three fold. First, we present quantitative results and statistical analyses of data from an online study in which approximately 800 subjects performed 10 types of group and network tasks in the four evaluated visualizations. Specifically, we show that BubbleSets is the best alternative for tasks involving group membership assessment; that visually encoding group information over basic node-link diagrams incurs an accuracy penalty of about 25 percent in solving network tasks; and that GMap's use of prominent group labels improves memorability. We also show that GMap's visual metaphor can be slightly altered to outperform BubbleSets in group membership assessment. Second, we discuss visual characteristics that can explain the observed quantitative differences in the four visualizations and suggest design recommendations. This discussion is supported by a small scale eye-tracking study and previous results from the visualization literature. Third, we present an easily extensible user study methodology

Fast filtering and animation of large dynamic networks

Detecting and visualizing what are the most relevant changes in an evolving network is an open challenge in several domains. We present a fast algorithm that filters subsets of the strongest nodes and edges representing an evolving weighted graph and visualize it by either creating a movie, or by streaming it to an interactive network visualization tool. The algorithm is an approximation of exponential sliding time-window that scales linearly with the number of interactions. We compare the algorithm against rectangular and exponential sliding time-window methods. Our network filtering algorithm: i) captures persistent trends in the structure of dynamic weighted networks, ii) smoothens transitions between the snapshots of dynamic network, and iii) uses limited memory and processor time. The algorithm is publicly available as open-source software.Comment: 6 figures, 2 table