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

A Sparse Stress Model

Force-directed layout methods constitute the most common approach to draw general graphs. Among them, stress minimization produces layouts of comparatively high quality but also imposes comparatively high computational demands. We propose a speed-up method based on the aggregation of terms in the objective function. It is akin to aggregate repulsion from far-away nodes during spring embedding but transfers the idea from the layout space into a preprocessing phase. An initial experimental study informs a method to select representatives, and subsequent more extensive experiments indicate that our method yields better approximations of minimum-stress layouts in less time than related methods.Comment: Appears in the Proceedings of the 24th International Symposium on Graph Drawing and Network Visualization (GD 2016

Design of chemical space networks incorporating compound distance relationships

Networks, in which nodes represent compounds and edges pairwise similarity relationships, are used as coordinate-free representations of chemical space. So-called chemical space networks (CSNs) provide intuitive access to structural relationships within compound data sets and can be annotated with activity information. However, in such similarity-based networks, distances between compounds are typically determined for layout purposes and clarity and have no chemical meaning. By contrast, inter-compound distances as a measure of dissimilarity can be directly obtained from coordinate-based representations of chemical space. Herein, we introduce a CSN variant that incorporates compound distance relationships and thus further increases the information content of compound networks. The design was facilitated by adapting the Kamada-Kawai algorithm. Kamada-Kawai networks are the first CSNs that are based on numerical similarity measures, but do not depend on chosen similarity threshold values

The politics of the German company network

For over 100 years, the German company network was a major feature of organized corporate governance in Germany. This paper uses network visualization techniques and qualitative-historical analysis to discuss the structure, origins and development of this network and to analyze the reasons for its recent erosion. Network visualization makes it possible to identify crucial entanglement patterns that can be traced back historically. In three phases of network formation - the 1880s, 1920s and the 1950s -, capital entanglement resulted from the interplay of company behavior and government policy. In its heyday, the company network was de facto encompassing and provided its core participants, especially the banks, with a national, macroeconomic perspective. In the 1970s, a process of increased competition among financial companies set in. In the 1980s and 1990s, declining returns from blockholding and increased opportunity costs made network dissolution a thinkable option for companies. Because of the strategic reorientation of the largest banks toward investment banking, ties between banks and industry underwent functional changes. Since the year 2000, the German government's tax policy has sped up network erosion. Vanishing capital ties imply a declining degree of strategic coordination among large German companies. -- Ausgehend von einer Kombination von Netzwerkvisualisierung und historischer Analyse werden in diesem Papier Struktur, Entstehung und Entwicklung des deutschen Unternehmensnetzwerks sowie die Gründe für seine Erosion diskutiert. Die Visualisierungstechnik ermöglicht die Identifikation auffälliger Merkmale des Netzwerks, die anschließend geschichtlich zurückverfolgt werden können. In den drei Phasen der Netzwerkentstehung - den 1880er, 1920er und 1950er Jahren - resultierten Unternehmensverflechtungen aus einem Zusammenspiel von strategischen Unternehmensentscheidungen und Unterstützung auf politischer Ebene. In seiner Blütezeit umfasste das Netzwerk die größten deutschen Unternehmen und führte dazu, dass die Banken im Verflechtungskern eine nationale, makroökonomische Orientierung entwickelten. In den siebziger Jahren setzte ein Prozess zunehmender Konkurrenz unter Finanzunternehmen ein. In den achtziger und neunziger Jahren machten sinkende Erträge aus dem Halten großer Aktienpakete und gestiegene Opportunitätskosten die Netzwerkauflösung zu einer strategischen Option. Wegen der Umorientierung der Großbanken zum Investmentbanking unterlagen Verbindungen zwischen Banken und Industrie einem funktionalen Wandel. Seit dem Jahr 2000 unterstützte die Bundesregierung die Netzwerkauflösung steuerpolitisch. Dieser Prozess resultiert in einer rückläufigen strategischen Koordinierung zwischen großen deutschen Unternehmen.

Exploring the relative importance of crossing number and crossing angle

Recent research has indicated that human graph reading performance can be affected by the size of crossing angle. Crossing angle is closely related to another aesthetic criterion: number of edge crossings. Although crossing number has been previously identified as the most important aesthetic, its relative impact on performance of human graph reading is unknown, compared to crossing angle. In this paper, we present an exploratory user study investigating the relative importance between crossing number and crossing angle. This study also aims to further examine the effects of crossing number and crossing angle not only on task performance measured as response time and accuracy, but also on cognitive load and visualization efficiency. The experimental results reinforce the previous findings of the effects of the two aesthetics on graph comprehension. The study demonstrates that on average these two closely related aesthetics together explain 33% of variance in the four usability measures: time, accuracy, mental effort and visualization efficiency, with about 38% of the explained variance being attributed to the crossing angle. Copyright © 2010 ACM

Applying social network analysis to the examination of interruptions in healthcare

Examinations of interruptions in healthcare often focus on a single clinical discipline, and solutions are targeted accordingly. This approach does not take into account the inter-disciplinary dependencies and other sociotechnical aspects that make up the healthcare work system, and suggested solutions may not meet the needs of all stakeholders. In this article a sociotechnical systems perspective is used to uncover the interdependencies between 16 unique work roles that result in interruptions in an intensive care unit (ICU). By applying social network analysis techniques to data collected using the Dual Perspectives Method, we identified targeted systems-based interventions that may reduce unnecessary interruptions while avoiding unintended consequences that impose additional burden on ICU staff. The rich insights gained into the interruptive communication patterns in the ICU work system stand in contrast to findings that would have otherwise been obtained by focusing only on a single clinical discipline or a single perspective