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  • 1. Einsfeld, Katja
    et al.
    Ebert, Achim
    Kerren, Andreas
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Deller, Matthias
    Knowledge Generation Through Human-Centered Information Visualization2009In: Information Visualization, ISSN 1473-8716, E-ISSN 1473-8724, Vol. 8, no 3, p. 180-196Article in journal (Refereed)
    Abstract [en]

    One important intention of human-centered information visualization is to represent huge amounts of abstract data in a visual representation that allows even users from foreign application domains to interact with the visualization, to understand the underlying data, and finally, to gain new, application-related knowledge. The visualization will help experts as well as non-experts to link previously or isolated knowledge-items in their mental map with new insights.Our approach explicitly supports the process of linking knowledge-items with three concepts. At first, the representation of data items in an ontology categorizes and relates them. Secondly, the use of various visualization techniques visually correlates isolated items by graph-structures, layout, attachment, integration, or hyperlink techniques. Thirdly, the intensive use of visual metaphors relates a known source domain to a less known target domain. In order to realize a scenario of these concepts, we developed a visual interface for non-experts to maintain complex wastewater treatment plants. This domain-specific application is used to give our concepts a meaningful background.

  • 2. Elmqvist, Niklas
    et al.
    Vande Moere, Andrew
    Jetter, Hans-Christian
    Cernea, Daniel
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Reiterer, Harald
    Jankun-Kelly, TJ
    Fluid Interaction for Information Visualization2011In: Information Visualization, ISSN 1473-8716, E-ISSN 1473-8724, Vol. 10, no 4, p. 327-340Article in journal (Refereed)
    Abstract [en]

    Despite typically receiving little emphasis in visualization research, interaction in visualization is the catalyst for the user’s dialogue with the data, and, ultimately, the user’s actual understanding and insight into these data. There are many possible reasons for this skewed balance between the visual and interactive aspects of a visualization. One reason is that interaction is an intangible concept that is difficult to design, quantify, and evaluate. Unlike for visual design, there are few examples that show visualization practitioners and researchers how to design the interaction for a new visualization in the best manner. In this article, we attempt to address this issue by collecting examples of visualizations with ‘best-in-class’ interaction and using them to extract practical design guidelines for future designers and researchers. We call this concept fluid interaction, and we propose an operational definition in terms of the direct manipulation and embodied interaction paradigms, the psychological concept of ‘flow’, and Norman’s gulfs of execution and evaluation.

  • 3. Gleicher, Michael
    et al.
    Albers, D.
    Walker, R.
    Jusufi, Ilir
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Hansen, C. D.
    Roberts, Jonathan C.
    Visual Comparison for Information Visualization2011In: Information Visualization, ISSN 1473-8716, E-ISSN 1473-8724, Vol. 10, no 5-4, p. 289-309Article in journal (Refereed)
    Abstract [en]

    Data analysis often involves the comparison of complex objects. With the ever increasing amounts and complexity of data, the demand for systems to help with these comparisons is also growing. Increasingly, information visualization tools support such comparisons explicitly, beyond simply allowing a viewer to examine each object individually. In this paper, we argue that the design of information visualizations of complex objects can, and should, be studied in general, that is independently of what those objects are. As a first step in developing this general understanding of comparison, we propose a general taxonomy of visual designs for comparison that groups designs into three basic categories, which can be combined. To clarify the taxonomy and validate its completeness, we provide a survey of work in information visualization related to comparison. Although we find a great diversity of systems and approaches, we see that all designs are assembled from the building blocks of juxtaposition, superposition and explicit encodings. This initial exploration shows the power of our model, and suggests future challenges in developing a general understanding of comparative visualization and facilitating the development of more comparative visualization tools.

  • 4. Isenberg, Petra
    et al.
    Elmqvist, Niklas
    Scholtz, Jean
    Cernea, Daniel
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Ma, Kwan-Liu
    Hagen, Hans
    Collaborative Visualization: Definition, Challenges, and Research Agenda2011In: Information Visualization, ISSN 1473-8716, E-ISSN 1473-8724, Vol. 10, no 4, p. 310-326Article in journal (Refereed)
    Abstract [en]

    The conflux of two growing areas of technology – collaboration and visualization – into a new research direction, collaborative visualization, provides new research challenges. Technology now allows us to easily connect and collaborate with one another – in settings as diverse as over networked computers, across mobile devices, or using shared displays such as interactive walls and tabletop surfaces. Digital information is now regularly accessed by multiple people in order to share information, to view it together, to analyze it, or to form decisions. Visualizations are used to deal more effectively with large amounts of information while interactive visualizations allow users to explore the underlying data. While researchers face many challenges in collaboration and in visualization, the emergence of collaborative visualization poses additional challenges, but it is also an exciting opportunity to reach new audiences and applications for visualization tools and techniques.

    The purpose of this article is (1) to provide a definition, clear scope, and overview of the evolving field of collaborative visualization, (2) to help pinpoint the unique focus of collaborative visualization with its specific aspects, challenges, and requirements within the intersection of general computer-supported cooperative work and visualization research, and (3) to draw attention to important future research questions to be addressed by the community. We conclude by discussing a research agenda for future work on collaborative visualization and urge for a new generation of visualization tools that are designed with collaboration in mind from their very inception.

  • 5.
    Jusufi, Ilir
    et al.
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Schreiber, Falk
    Univ Halle Wittenberg, Inst Comp Sci, D-06108 Halle, Germany.
    Exploring Biological Data: Mappings between Ontology- and Cluster-based Representations2013In: Information Visualization, ISSN 1473-8716, E-ISSN 1473-8724, Vol. 12, no 3-4, p. 291-307Article in journal (Refereed)
    Abstract [en]

    Ontologies and hierarchical clustering are both important tools in biology and medicineto study high-throughput data such as transcriptomics and metabolomics data. Enrichmentof ontology terms in the data is used to identify statistically overrepresented ontology terms,giving insight into relevant biological processes or functional modules. Hierarchical clusteringis a standard method to analyze and visualize data to find relatively homogeneousclusters of experimental data points. Both methods support the analysis of the same dataset, but are usually considered independently. However, often a combined view is desired:visualizing a large data set in the context of an ontology under consideration of a clusteringof the data. This article proposes new visualization methods for this task. They allow forinteractive selection and navigation to explore the data under consideration as well as visualanalysis of mappings between ontology- and cluster-based space-filling representations. Inthis context, we discuss our approach together with specific properties of the biological inputdata and identify features that make our approach easily usable for domain experts.

  • 6.
    Jusufi, Ilir
    et al.
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Klukas, Christian
    Kerren, Andreas
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Schreiber, Falk
    Guiding the Interactive Exploration of Metabolic Pathway Interconnections2012In: Information Visualization, ISSN 1473-8716, E-ISSN 1473-8724, Vol. 11, no 2, p. 136-150Article in journal (Refereed)
    Abstract [en]

    Approaches to investigate biological processes have been of strong interest in the past few years and are thefocus of several research areas, especially Systems Biology. Biochemical networks as representations ofprocesses are very important for a comprehensive understanding of living beings. Drawings of these networksare often visually overloaded and do not scale. A common solution to deal with this complexity is to divide thecomplete network, for example, the metabolism, into a large set of single pathways that are hierarchicallystructured. If those pathways are visualized, this strategy generates additional navigation and explorationproblems as the user loses the context within the complete network.

    In this article, we present a general solution to this problem of visualizing interconnected pathways anddiscuss it in context of biochemical networks. Our new visualization approach supports the analyst in obtainingan overview to related pathways if they are working within a particular pathway of interest. By usingglyphs, brushing, and topological information of the related pathways, our interactive visualization is ableto intuitively guide the exploration and navigation process, and thus the analysis processes too. To deal withreal data and current networks, our tool has been implemented as a plugin for the VANTED system.

  • 7.
    Kucher, Kostiantyn
    et al.
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Schamp-Bjerede, Teri
    Lund University.
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Paradis, Carita
    Lund University.
    Sahlgren, Magnus
    Gavagai AB.
    Visual Analysis of Online Social Media to Open Up the Investigation of Stance Phenomena2016In: Information Visualization, ISSN 1473-8716, E-ISSN 1473-8724, Vol. 15, no 2, p. 93-116Article in journal (Refereed)
    Abstract [en]

    Online social media are a perfect text source for stance analysis. Stance in human communication is concerned with speaker attitudes, beliefs, feelings and opinions. Expressions of stance are associated with the speakers' view of what they are talking about and what is up for discussion and negotiation in the intersubjective exchange. Taking stance is thus crucial for the social construction of meaning. Increased knowledge of stance can be useful for many application fields such as business intelligence, security analytics, or social media monitoring. In order to process large amounts of text data for stance analyses, linguists need interactive tools to explore the textual sources as well as the processed data based on computational linguistics techniques. Both original texts and derived data are important for refining the analyses iteratively. In this work, we present a visual analytics tool for online social media text data that can be used to open up the investigation of stance phenomena. Our approach complements traditional linguistic analysis techniques and is based on the analysis of utterances associated with two stance categories: sentiment and certainty. Our contributions include (1) the description of a novel web-based solution for analyzing the use and patterns of stance meanings and expressions in human communication over time; and (2) specialized techniques used for visualizing analysis provenance and corpus overview/navigation. We demonstrate our approach by means of text media on a highly controversial scandal with regard to expressions of anger and provide an expert review from linguists who have been using our tool.

  • 8. Lin, Xia
    et al.
    Kerren, Andreas
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Zhang, Jiajie
    Challenges in Human-Centered Information Visualization: Introduction to the Special Issue2009In: Information Visualization, ISSN 1473-8716, E-ISSN 1473-8724, Vol. 8, no 3, p. 137-138Article, review/survey (Other academic)
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