Now showing items 73-92 of 190

    • Learning and Teaching in Co-Adaptive Guidance for Mixed-Initiative Visual Analytics 

      Sperrle, Fabian; Jeitler, Astrik; Bernard, Jürgen; Keim, Daniel A.; El-Assady, Mennatallah (The Eurographics Association, 2020)
      Guidance processes in visual analytics applications often lack adaptivity. In this position paper, we contribute the concept of co-adaptive guidance, building on the principles of initiation and adaptation. We argue that ...
    • Lessons learned while supporting Cyber Situational Awareness 

      Blasilli, Graziano; Paoli, Emiliano De; Lenti, Simone; Picca, Sergio (The Eurographics Association, 2021)
      The increasing number of cyberattacks against critical infrastructures has pushed researchers to develop many Visual Analytics solutions to provide valid defensive approaches and improve the situational awareness of the ...
    • Lessons on Combining Topology and Geography - Visual Analytics for Electrical Outage Management 

      Jäger, Alexander; Mittelstädt, Sebastian; Oelke, Daniela; Sander, Sonja; Platz, Axel; Bouwman, Gies; Keim, Daniel A. (The Eurographics Association, 2016)
      Outage management in electrical networks is a complex task for operators and requires comprehensive overviews of the topology. At the same time valuable information for detecting the root cause may have geographical context ...
    • LFPeers: Temporal Similarity Search in Covid-19 Data 

      Burmeister, Jan; Bernard, Jürgen; Kohlhammer, Jörn (The Eurographics Association, 2021)
      While there is a wide variety of visualizations and dashboards to help understand the data of the Covid-19 pandemic, hardly any of these support important analytical tasks, especially of temporal attributes. In this paper, ...
    • A Methodology for Task-Driven Guidance Design 

      Pérez-Messina, Ignacio; Ceneda, Davide; Miksch, Silvia (The Eurographics Association, 2023)
      Mixed-initiative Visual Analytics (VA) systems are becoming increasingly important; however, the design of such systems still needs to be formulated. We present a methodology to aid and structure the design of guidance for ...
    • Mind the Time: Unleashing the Temporal Aspects in Pattern Discovery 

      Lammarsch, T.; Aigner, W.; Bertone, A.; Miksch, S.; Rind, A. (The Eurographics Association, 2013)
      Temporal Data Mining is a core concept of Knowledge Discovery in Databases handling time-oriented data. Stateof- the-art methods are capable of preserving the temporal order of events as well as the information in between. ...
    • Modeling Incremental Visualizations 

      Angelini, Marco; Santucci, Giuseppe (The Eurographics Association, 2013)
      An increasing number of applications call for the incremental/iterative drawing of a visualization. That is an obvious requirement when dealing with continuously changing data, like the emerging field of data streams or ...
    • Moving Together: Towards a Formalization of Collective Movement 

      Buchmüller, Juri; Cakmak, Eren; Andrienko, Natalia; Andrienko, Gennady; Jolles, Jolle W.; Keim, Daniel A. (The Eurographics Association, 2019)
      While conventional applications for spatiotemporal datasets mostly focus on the relation between movers and environment, research questions in the analysis of collective movement typically focus more on relationships and ...
    • Multi-Ensemble Visual Analytics via Fuzzy Sets 

      Piccolotto, Nikolaus; Bögl, Markus; Miksch, Silvia (The Eurographics Association, 2023)
      Analysis of ensemble datasets, i.e., collections of complex elements such as geochemical maps, is widespread in science and industry. The elements' complexity arises from the data they capture, which are often multivariate ...
    • Multi-resolution Analysis for Vector Plots of Time Series Data 

      Nguyen, Bao; Hewett, Rattikorn; Dang, Tommy (The Eurographics Association, 2021)
      Vector plots can directly visualize both temporal variation and spatial distribution, so it is interesting to use this type of plot for displaying multivariate time series. However, vector plots cannot reveal global temporal ...
    • Multigraph Visualization for Feature Classification of Brain Network Data 

      Wang, Jiachen; Fang, Shiaofen; Li, Huang; Goñi, Joaquín; Saykin, Andrew J.; Shen, Li (The Eurographics Association, 2016)
      A Multigraph is a set of graphs with a common set of nodes but different sets of edges. Multigraph visualization has not received much attention so far. In this paper, we introduce a multigraph application in brain network ...
    • MultiLayerMatrix: Visualizing Large Taxonomic Datasets 

      Dang, Tuan Nhon; Cui, Hong; Forbes, Angus G. (The Eurographics Association, 2016)
      Adjacency matrices can be a useful way to visualize dense networks. However, they do not scale well as the network size increases due to limited screen space, especially when the number of rows and columns exceeds the pixel ...
    • MultiNode-Explorer: A Visual Analytics Framework for Generating Web-based Multimodal Graph Visualizations 

      Ghani, Sohaib; Elmqvist, Niklas; Ebert, David S. (The Eurographics Association, 2012)
      We propose MultiNode-Explorer, a visual analytics framework that is capable of transforming multidimensional datasets into an entity-relationship (E-R) model and visualizing the data as node-link diagrams. The framework ...
    • Multivariate Time Series Retrieval with Symbolic Aggregate Approximation, Regular Expression, and Query Expansion 

      Yu, Yuncong; Becker, Tim; Behrisch, Michael (The Eurographics Association, 2022)
      We present SAXRegEx, a method for pattern search in multivariate time series in the presence of various distortions, such as duration variation, warping, and time delay between signals. For example, in the automotive ...
    • The News Auditor: Visual Exploration of Clusters of Stories 

      Behrisch, Michael; Krstajic, Milos; Schreck, Tobias; Keim, Daniel A. (The Eurographics Association, 2012)
      In recent years, the quantity of content generated by news agencies and blogs is constantly growing, making it difficult for readers to process and understand this overwhelming amount of data. Online news aggregators present ...
    • Nonparametric Dimensionality Reduction Quality Assessment based on Sortedness of Unrestricted Neighborhood 

      Pereira-Santos, Davi; Neves, Tácito Trindade Araújo Tiburtino; Carvalho, André C. P. L. F. de; Paulovich, Fernando V. (The Eurographics Association, 2023)
      High-dimensional data are known to be challenging to explore visually. Dimensionality Reduction (DR) techniques are good options for making high-dimensional data sets more interpretable and computationally tractable. An ...
    • On Quality Indicators for Progressive Visual Analytics 

      Angelini, Marco; May, Thorsten; Santucci, Giuseppe; Schulz, Hans-Jörg (The Eurographics Association, 2019)
      A key component in using Progressive Visual Analytics (PVA) is to be able to gauge the quality of intermediate analysis outcomes. This is necessary in order to decide whether a current partial outcome is already good enough ...
    • Ontology Visualization: One Size Does Not Fit All 

      Silva, Isabel da; Santucci, Giuseppe; Freitas, Carla del Sasso (The Eurographics Association, 2012)
      Visualization techniques have been used for ontology representation to allow the comprehension of concepts and properties in specific domains. Due to the complexity and size of ontologies such techniques need to be efficient ...
    • Patent Retrieval: A Multi-Modal Visual Analytics Approach 

      Seebacher, Daniel; Stein, Manuel; Janetzko, Halldór; Keim, Daniel A. (The Eurographics Association, 2016)
      Claiming intellectual property for an invention by patents is a common way to protect ideas and technological advancements. However, patents allow only the protection of new ideas. Assessing the novelty of filed patent ...
    • PCDC - On the Highway to Data - A Tool for the Fast Generation of Large Synthetic Data Sets 

      Bremm, Sebastian; Heß, Martin; Landesberger, Tatiana von; Fellner, Dieter W. (The Eurographics Association, 2012)
      In this paper, we present Parallel Coordinates for Data Creation (PCDC), a new visual-interactive method for the fast generation of labeled multidimensional data sets. Multivariate data need to be analyzed in various domains ...