A bitwise clique detection approach for accelerating power graph computation and clustering dense graphs

Graphs are at the essence of many data representations. The visual analytics over graphs is usually difficult due to their size, which makes their visual display challenging, and their fundamental algorithms, which are often classified as NP-hard problems. The Power Graph Analysis (PGA) is a method that simplifies networks using reduced representations for complete subgraphs (cliques) and complete bipartite subgraphs (bicliques), in both cases with edge reductions. The benefits of a power graph are the preservation of information and its capacity to show essential information about the original network. However, finding an optimal representation (maximum edges reduction) is also an NPhard problem. In this work, we propose BCD, a greedy algorithm that uses a Bitwise Clique Detection approach to finding power graphs. BCD is faster than competing strategies and allows the analysis of bigger graphs. For the display of larger power graphs, we propose an orthogonal layout to prevent overlapping of edges and vertices. Finally, we describe how the structure induced by the power graph is used for clustering analysis of dense graphs. We demonstrate with several datasets the results obtained by our proposal and compare against competing strategies.Os grafos são essenciais para muitas representações de dados. A análise visual de grafos é usualmente difícil devido ao tamanho, o que representa um desafio para sua visualização. Além de isso, seus algoritmos fundamentais são frequentemente classificados como NP-difícil. Análises dos grafos de potência (PGA em inglês) é um método que simplifica redes usando representações reduzidas para subgrafos completos chamados cliques e subgrafos bipartidos chamados bicliques, em ambos casos com una redução de arestas. Os benefícios da representação de grafo de potência são a preservação de informação e a capacidade de mostrar a informação essencial sobre a rede original. Entretanto, encontrar uma representação ótima (a máxima redução de arestas possível) é também um problema NP-difícil. Neste trabalho, propomos BCD, um algoritmo guloso que usa um abordagem de detecção de bicliques baseado em operações binarias para encontrar representações de grafos de potencia. O BCD é mas rápido que as estratégias atuais da literatura. Finalmente, descrevemos como a estrutura induzida pelo grafo de potência é utilizado para as análises dos grafos densos na detecção de agrupamentos de nodos

Interaction for Immersive Analytics

International audienceIn this chapter, we briefly review the development of natural user interfaces and discuss their role in providing human-computer interaction that is immersive in various ways. Then we examine some opportunities for how these technologies might be used to better support data analysis tasks. Specifically, we review and suggest some interaction design guidelines for immersive analytics. We also review some hardware setups for data visualization that are already archetypal. Finally, we look at some emerging system designs that suggest future directions

Interactive Visualization Lenses:: Natural Magic Lens Interaction for Graph Visualization

Information visualization is an important research field concerned with making sense and inferring knowledge from data collections. Graph visualizations are specific techniques for data representation relevant in diverse application domains among them biology, software-engineering, and business finance. These data visualizations benefit from the display space provided by novel interactive large display environments. However, these environments also cause new challenges and result in new requirements regarding the need for interaction beyond the desktop and according redesign of analysis tools. This thesis focuses on interactive magic lenses, specialized locally applied tools that temporarily manipulate the visualization. These may include magnification of focus regions but also more graph-specific functions such as pulling in neighboring nodes or locally reducing edge clutter. Up to now, these lenses have mostly been used as single-user, single-purpose tools operated by mouse and keyboard. This dissertation presents the extension of magic lenses both in terms of function as well as interaction for large vertical displays. In particular, this thesis contributes several natural interaction designs with magic lenses for the exploration of graph data in node-link visualizations using diverse interaction modalities. This development incorporates flexible switches between lens functions, adjustment of individual lens properties and function parameters, as well as the combination of lenses. It proposes interaction techniques for fluent multi-touch manipulation of lenses, controlling lenses using mobile devices in front of large displays, and a novel concept of body-controlled magic lenses. Functional extensions in addition to these interaction techniques convert the lenses to user-configurable, personal territories with use of alternative interaction styles. To create the foundation for this extension, the dissertation incorporates a comprehensive design space of magic lenses, their function, parameters, and interactions. Additionally, it provides a discussion on increased embodiment in tool and controller design, contributing insights into user position and movement in front of large vertical displays as a result of empirical investigations and evaluations.Informationsvisualisierung ist ein wichtiges Forschungsfeld, das das Analysieren von Daten unterstützt. Graph-Visualisierungen sind dabei eine spezielle Variante der Datenrepräsentation, deren Nutzen in vielerlei Anwendungsfällen zum Einsatz kommt, u.a. in der Biologie, Softwareentwicklung und Finanzwirtschaft. Diese Datendarstellungen profitieren besonders von großen Displays in neuen Displayumgebungen. Jedoch bringen diese Umgebungen auch neue Herausforderungen mit sich und stellen Anforderungen an Nutzerschnittstellen jenseits der traditionellen Ansätze, die dadurch auch Anpassungen von Analysewerkzeugen erfordern. Diese Dissertation befasst sich mit interaktiven „Magischen Linsen“, spezielle lokal-angewandte Werkzeuge, die temporär die Visualisierung zur Analyse manipulieren. Dabei existieren zum Beispiel Vergrößerungslinsen, aber auch Graph-spezifische Manipulationen, wie das Anziehen von Nachbarknoten oder das Reduzieren von Kantenüberlappungen im lokalen Bereich. Bisher wurden diese Linsen vor allem als Werkzeug für einzelne Nutzer mit sehr spezialisiertem Effekt eingesetzt und per Maus und Tastatur bedient. Die vorliegende Doktorarbeit präsentiert die Erweiterung dieser magischen Linsen, sowohl in Bezug auf die Funktionalität als auch für die Interaktion an großen, vertikalen Displays. Insbesondere trägt diese Dissertation dazu bei, die Exploration von Graphen mit magischen Linsen durch natürliche Interaktion mit unterschiedlichen Modalitäten zu unterstützen. Dabei werden flexible Änderungen der Linsenfunktion, Anpassungen von individuellen Linseneigenschaften und Funktionsparametern, sowie die Kombination unterschiedlicher Linsen ermöglicht. Es werden Interaktionstechniken für die natürliche Manipulation der Linsen durch Multitouch-Interaktion, sowie das Kontrollieren von Linsen durch Mobilgeräte vor einer Displaywand vorgestellt. Außerdem wurde ein neuartiges Konzept körpergesteuerter magischer Linsen entwickelt. Funktionale Erweiterungen in Kombination mit diesen Interaktionskonzepten machen die Linse zu einem vom Nutzer einstellbaren, persönlichen Arbeitsbereich, der zudem alternative Interaktionsstile erlaubt. Als Grundlage für diese Erweiterungen stellt die Dissertation eine umfangreiche analytische Kategorisierung bisheriger Forschungsarbeiten zu magischen Linsen vor, in der Funktionen, Parameter und Interaktion mit Linsen eingeordnet werden. Zusätzlich macht die Arbeit Vor- und Nachteile körpernaher Interaktion für Werkzeuge bzw. ihre Steuerung zum Thema und diskutiert dabei Nutzerposition und -bewegung an großen Displaywänden belegt durch empirische Nutzerstudien

Determinantes político-institucionais na formação de redes de inovação em tecnologias emergentes

O desenvolvimento do sistema de inovação em nanotecnologia no Espaço Europeu de Investigação foi moldado pelas políticas públicas europeias e nacionais. Em particular, os Programas Quadro promovidos pela Comissão Europeia a par de outras instituições europeias, tiveram e continuam ter um papel preponderante no desenvolvimento científico e tecnológico dos Estados-membros. Esta investigação propõe um modelo de análise institucional aos sistemas de inovação europeus, no setor da nanotecnologia, determinado pelas relações e interligações, entre todos os atores institucionais dos sistemas socioeconómicos e políticos. Numa abordagem, sui generis ao neo-institucionalismo, foi possível identificar três dimensões institucionais impactantes dos sistemas de inovação. A implementação de métodos estatísticos baseados na família de grafos aleatórios exponenciais (i.e. Exponential Random Graph Models ou ERGMs), permitiu avaliar o impacto das três dimensões institucionais dos sistemas de inovação. Os resultados empíricos, revelam a importância de determinados por estes fatores institucionais, nas configurações de rede entre os atores, que integram os projetos de inovação do 7º Programa-Quadro em nanotecnologia. Os resultados, demonstram ainda que a introdução de técnicas avançadas em Análise de Redes Sociais, permitem a compreensão dos fenómenos de interação entre atores dos sistemas de inovação e a avaliação das políticas públicas, ao nível institucional.The development of the nanotechnology innovation system in the European Research Area has been shaped by European and national public policies. Particularly, the Framework Programs promoted by the European Commission, alongside other European institutions have had and continue to play a leading role in the scientific and technological development of the EU Member States. This research proposes a model of institutional analysis for European innovation systems in the nanotechnology sector, determined by the relationships and interconnections, among all institutional actors of socioeconomic and polítical systems. In a sui generis approach to neo-institutionalism, it was possible to identify three major institutional dimensions of innovation systems. The deployment of statistical methods based on the Exponential Random Graph Models (ERGMs) allowed us to evaluate the impact of these three institutional dimensions of innovation systems. The empirical results reveal the importance of this institutional factors in the network configurations, between the actors that are part innovation projects of the 7th Framework Program on nanotechnology. The results also show that, the introduction of advanced techniques in Social Network Analysis, allow the understanding the interaction phenomena between actors of innovation systems and the evaluation of public policies at institutional level