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  • 1. Albrecht, Mario
    et al.
    Kerren, Andreas
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Klein, Karsten
    Kohlbacher, Oliver
    Mutzel, Petra
    Paul, Wolfgang
    Schreiber, Falk
    Wybrow, Michael
    On Open Problems in Biological Network Visualization2009In: Graph Drawing: 17th International Symposium, GD 2009, Chicago, IL, USA, September 22-25, 2009. Revised Papers / [ed] David Eppstein and Emden R. Gansner, Berlin Heidelberg New York: Springer, 2009, p. 256-267Chapter in book (Refereed)
    Abstract [en]

    Much of the data generated and analyzed in the life sciences can be interpreted and represented by networks or graphs. Network analysis and visualization methods help in investigating them, and many universal as well as special-purpose tools and libraries are available for this task. However, the two fields of graph drawing and network biology are still largely disconnected. Hence, visualization of biological networks does typically not apply state-of-the-art graph drawing techniques, and graph drawing tools do not respect the drawing conventions of the life science community.

    In this paper, we analyze some of the major problems arising in biological network visualization.We characterize these problems and formulate a series of open graph drawing problems. These use cases illustrate the need for efficient algorithms to present, explore, evaluate, and compare biological network data. For each use case, problems are discussed and possible solutions suggested.

  • 2.
    Alfalahi, Alyaa
    et al.
    Stockholm University.
    Skeppstedt, Maria
    Linnaeus University, Faculty of Technology, Department of Computer Science. Gavagai AB, Sweden.
    Ahlblom, Rickard
    Stockholm University.
    Baskalayci, Roza
    Stockholm University.
    Henriksson, Aron
    Stockholm University.
    Asker, Lars
    Stockholm University.
    Paradis, Carita
    Lund University.
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Expanding a Dictionary of Marker Words for Uncertainty and Negation Using Distributional Semantics2015In: Proceedings of the 6th International Workshop on Health Text Mining and Information Analysis (Louhi '15): Short Paper Track / [ed] Cyril Grouin, Thierry Hamon, Aurélie Névéol, and Pierre Zweigenbaum, Association for Computational Linguistics , 2015, p. 90-96Conference paper (Refereed)
    Abstract [en]

    Approaches to determining the factuality of diagnoses and findings in clinical text tend to rely on dictionaries of marker words for uncertainty and negation. Here, a method for semi-automatically expanding a dictionary of marker words using distributional semantics is presented and evaluated. It is shown that ranking candidates for inclusion according to their proximity to cluster centroids of semantically similar seed words is more successful than ranking them according to proximity to each individual seed word. 

  • 3.
    Battiato, Sebastiano
    et al.
    Università di Catania.
    Coquillart, SabineInria/ZIRST.Laramee, Robert S.Swansea University.Kerren, AndreasLinnaeus University, Faculty of Technology, Department of Computer Science.Braz, JoséEscola Superior de Tecnologia do IPS.
    Computer Vision, Imaging and Computer Graphics - Theory and Applications: International Joint Conference, VISIGRAPP 2013, Barcelona, Spain, February 21-24, 2013, Revised Selected Papers2014Conference proceedings (editor) (Refereed)
  • 4.
    Battiato, Sebastiano
    et al.
    Università di Catania, Italy.
    Coquillart, SabineInria/ZIRST, France.Pettré, JulienINRIA-Rennes/MimeTIC Team, France.Laramee, Robert S.Swansea University, UK.Kerren, AndreasLinnaeus University, Faculty of Technology, Department of Computer Science.Braz, JoséEscola Superior de Tecnologia do IPS, Portugal.
    Computer Vision, Imaging and Computer Graphics - Theory and Applications: International Joint Conference, VISIGRAPP 2014, Lisbon, Portugal, January 5-8, 2014, Revised Selected Papers2015Collection (editor) (Refereed)
  • 5.
    Borgo, Rita
    et al.
    Kings College London, UK.
    Lee, Bongshin
    Microsoft Research, USA.
    Bach, Benjamin
    Microsoft Research - Inria, France.
    Fabrikant, Sara
    University of Zurich, Switzerland.
    Jianu, Radu
    City University London, UK.
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM), Department of Computer Science.
    Kobourov, Stephen
    University of Arizona, USA.
    McGee, Fintan
    Luxembourg Institute of Science and Technology, Luxembourg.
    Micallef, Luana
    Helsinki Institute for Information Technology, Finland.
    von Landesberger, Tatiana
    Darmstadt University, Germany.
    Ballweg, Katrin
    Darmstadt University, Germany.
    Diehl, Stephan
    University Trier, Germany.
    Simonetto, Paolo
    Swansea University, UK.
    Zhou, Michelle
    Juji, USA.
    Crowdsourcing for Information Visualization: Promises and Pitfalls2017In: Evaluation in the Crowd: Crowdsourcing and Human-Centered Experiments / [ed] Daniel Archambault, Helen Purchase, and Tobias Hoßfeld, Springer Publishing Company, 2017, p. 96-138Chapter in book (Refereed)
    Abstract [en]

    Crowdsourcing offers great potential to overcome the limitations of controlled lab studies. To guide future designs of crowdsourcing-based studies for visualization, we review visualization research that has attempted to leverage crowdsourcing for empirical evaluations of visualizations. We discuss six core aspects for successful employment of crowdsourcing in empirical studies for visualization – participants, study design, study procedure, data, tasks, and metrics & measures. We then present four case studies, discussing potential mechanisms to overcome common pitfalls. This chapter will help the visualization community understand how to effectively and efficiently take advantage of the exciting potential crowdsourcing has to offer to support empirical visualization research.

  • 6. Braz, José
    et al.
    Kerren, AndreasLinnaeus University, Faculty of Technology, Department of Computer Science.Linsen, Lars
    Proceedings of the 6th International Conference on Information Visualization Theory and Applications, IVAPP 2015, Berlin, Germany, March 11-14, 20152015Conference proceedings (editor) (Refereed)
  • 7.
    Braz, José
    et al.
    Escola Superior de Tecnologia de Setúbal, Portugal.
    Laramee, Robert S.Swansea University, U.K..Kerren, AndreasLinnaeus University, Faculty of Technology, Department of Computer Science.
    Proceedings of the 5th International Conference on Information Visualization Theory and Applications, IVAPP 2014, Lisbon, Portugal, 5-8 January, 20142014Conference proceedings (editor) (Refereed)
  • 8.
    Braz, José
    et al.
    Escola Superior de Tecnologia do IPS, Portugal.
    Pettré, JulienINRIA-Rennes/MimeTIC Team, France.Richard, PaulUniversity of Angers, France.Kerren, AndreasLinnaeus University, Faculty of Technology, Department of Computer Science.Linsen, LarsJacobs University, Denmark.Battiato, SebastianoUniversità di Catania, Italy.Imai, FranciscoCanon U.S.A. Inc, USA.
    Computer Vision, Imaging and Computer Graphics - Theory and Applications: International Joint Conference, VISIGRAPP 2015, Berlin, Germany, March 11-14, 2015, Revised Selected Papers2016Collection (editor) (Refereed)
  • 9.
    Cernea, Daniel
    et al.
    Linnaeus University, Faculty of Technology, Department of Computer Science. University of Kaiserslautern.
    Ebert, Achim
    University of Kaiserslautern.
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    A Study of Emotion-triggered Adaptation Methods for Interactive Visualization2013In: UMAP 2013 Extended Proceedings: Late-Breaking Results, Project Papers and Workshop Proceedings of the 21st Conference on User Modeling, Adaptation, and Personalization. Rome, Italy, June 10-14, 2013 / [ed] Shlomo Berkovsky, Eelco Herder, Pasquale Lops & Olga C. Santos, CEUR-WS.org , 2013, Vol. 997, p. 9-16Conference paper (Refereed)
    Abstract [en]

    As the size and complexity of datasets increases, both visual-ization systems and their users are put under more pressure to oer quickand thorough insights about patterns hidden in this ocean of data. Whilenovel visualization techniques are being developed to better cope withthe various data contexts, users nd themselves increasingly often undermental bottlenecks that can induce a variety of emotions. In this paper,we execute a study to investigate the eectiveness of various emotion-triggered  adaptation  methods  for  visualization  systems.  The  emotionsconsidered are boredom and frustration, and are measured by means ofbrain-computer interface technology. Our ndings suggest that less intru-sive adaptive methods perform better at supporting users in overcomingemotional states with low valence or arousal, while more intrusive onestend to be misinterpreted or perceived as irritating.

  • 10.
    Cernea, Daniel
    et al.
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Ebert, Achim
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Visualizing Group Affective Tone in Collaborative Scenarios2014Conference paper (Refereed)
    Abstract [en]

    A large set of complex datasets require the use of collaborative visualization solutions in order to harness the knowledge and experience of multiple experts. However, be it co-located or distributed, the collaboration process is inherently fragile, as small mistakes in communication or various human aspects can quickly derail it. In this paper, we introduce a novel visualization technique that highlights the group affective tone (GAT), also known as the presence of homogeneous emotional reactions within a group. The goal of our visualization is to improve users’ awareness of GAT, thus fostering a positive group affective tone that has been proven to increase effectiveness and creativity in collaborative scenarios. 

  • 11.
    Cernea, Daniel
    et al.
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Ebert, Achim
    Kerren, Andreas
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Morar, Valentina
    R3 - Un dispozitiv de intrare configurabil pentru interacţiunea liberă în spaţiu2010In: Romanian Journal of Human-Computer Interaction, ISSN 1843-4460, Vol. 3, p. 45-50Article in journal (Refereed)
    Abstract [un]

    În ultima perioadă s-a abordat tot mai des problema implementării unor dispozitive de intrare care să sprijine interacţiunea 3D prin oferirea a 6 sau a mai multor grade de libertate (degrees of freedom sau DoF). Cu toate acestea, astfel de dispozitive care să fie disponibile pentru interacţiune liberă în spaţiu - adică fără a fi necesară o suprafaţă ca sistem de referinţă, cum este cazul unui mouse - sunt proiectate doar pentru un tip restrâns de aplicaţii. De asemenea, aparatele de intrare de acest tip sunt rareori intuitive în utilizare şi limitate ca număr. Pentru a combate aceste probleme, în acest articol propunem un dispozitiv de complexitate şi costuri de implementare reduse, care poate fi utilizat în spaţiul liber şi este extrem de configurabil, susţinând nativ o interacţiune intuitivă cu variate medii virtuale. R3 (roll - rostogolire, rotate - rotire, rattle - agitare) oferă acurateţea necesară pentru navigare şi indicare - atât în 2D, cât şi în 3D – în aplicaţii de modelare şi jocuri, dar şi feedback tactil prin prezenţa unui trackball, toate acestea într-o manieră orientată spre utilizator. În plus, dispozitivul poate fi trecut uşor în modul de mouse, oferind astfel oricând suport pentru interacţiunea cu sistemele de operare convenţionale.

  • 12.
    Cernea, Daniel
    et al.
    Linnaeus University, Faculty of Technology, Department of Computer Science. University of Kaiserslautern, Germany.
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    A Survey of Technologies on the Rise for Emotion-Enhanced Interaction2015In: Journal of Visual Languages and Computing, ISSN 1045-926X, E-ISSN 1095-8533, Vol. 31, no A, p. 70-86Article in journal (Refereed)
    Abstract [en]

    Emotions are a major part of the human existence and social interactions. Some might say that emotions are one of the aspects that make us truly human. However, while we express emotions in various life settings, the world of computing seems to struggle with supporting and incorporating the emotional dimension. In the last decades, the concept of affect has gotten a new upswing in research, moving beyond topics like market research and product development, and further exploring the area of emotion-enhanced interaction.

    In this article, we highlight techniques that have been employed more intensely for emotion measurement in the context of affective interaction. Besides capturing the functional principles behind these approaches and the inherent volatility of human emotions, we present relevant applications and establish a categorization of the roles of emotion detection in interaction. Based on these findings, we also capture the main challenges that emotion measuring technologies will have to overcome in order to enable a truly seamless emotion-driven interaction.

  • 13.
    Cernea, Daniel
    et al.
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Kerren, Andreas
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Ebert, Achim
    Detecting Insight and Emotion in Visualization Applications with a Commercial EEG Headset2011In: Proceedings of the SIGRAD 2011 Conference on Evaluations of Graphics and Visualization - Efficiency, Usefulness, Accessibility, Usability, KTH, Stockholm, Sweden., Linköping: Linköping University Electronic Press , 2011, p. 53-60Conference paper (Refereed)
    Abstract [en]

    Insight represents a special element of knowledge building. From the beginning of their lives, humans experience moments of insight in which a certain idea or solution becomes as clear to them as never before. Especially in the field of visual representations, insight has the potential to be at the core of comprehension and pattern recognition. Still, one problem is that this moment of clarity is highly unpredictable and complex in nature, and many scientists have investigated different aspects of its generation process in the hope of capturing the essence of this eureka (Greek, for "I have found") moment.

    In this paper, we look at insight from the spectrum of information visualization. In particular, we inspect the possible correlation between epiphanies and emotional responses subjects experience when having an insight. In order to check the existence of such a connection, we employ a set of initial tests involving the EPOC mobile electroencephalographic (EEG) headset for detecting emotional responses generated by insights. The insights are generated by open-ended tasks that take the form of visual riddles and visualization applications. Our results suggest that there is a strong connection between insight and emotions like frustration and excitement. Moreover, measuring emotional responses via EEG during an insight-related problem solving results in non-intrusive, nearly automatic detection of the major Aha! moments the user experiences. We argue that this indirect detection of insights opens the door for the objective evaluation and comparison of various visualizations techniques.

  • 14.
    Cernea, Daniel
    et al.
    University of Kaiserslautern.
    Mora, Simone
    Norwegian University of Science.
    Perez, Alfredo
    Norwegian University of Science.
    Ebert, Achim
    University of Kaiserslautern.
    Kerren, Andreas
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Divitini, Monica
    Norwegian University of Science.
    Gil de la Iglesia, Didac
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Otero, Nuno
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics. University of Minho, Portugal.
    Tangible and Wearable User Interfaces for Supporting Collaboration among Emergency Workers2012In: Collaboration and Technology: 18th International Conference, CRIWG 2012 Raesfeld, Germany, September 16-19, 2012 Proceedings / [ed] Valeria Herskovic, H. Ulrich Hoppe, Marc Jansen, Jürgen Ziegler, Springer, 2012, Vol. 7493, p. 192-199Conference paper (Refereed)
    Abstract [en]

    Ensuring a constant flow of information is essential for offeringquick help in different types of disasters. In the following, we report on a workin-progress distributed, collaborative and tangible system for supporting crisismanagement. On one hand, field operators need devices that collect information—personal notes and sensor data—without interrupting their work. Onthe other hand, a disaster management system must operate in different scenariosand be available to people with different preferences, backgrounds and roles.Our work addresses these issues by introducing a multi-level collaborative systemthat manages real-time data flow and analysis for various rescue operators.

  • 15.
    Cernea, Daniel
    et al.
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Olech, Peter-Scott
    Ebert, Achim
    Kerren, Andreas
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Controlling In-Vehicle Systems with a Commercial EEG Headset: Performance and Cognitive Load2012In: Visualization of Large and Unstructured Data Sets: Applications in Geospatial Planning, Modeling and Engineering - Proceedings of IRTG 1131 Workshop 2, Schloss Dagstuhl - Leibniz-Zentrum für Informatik , 2012Conference paper (Refereed)
    Abstract [en]

    Humans have dreamed for centuries to control their surroundings solely by the power of theirminds. These aspirations have been captured by multiple science fiction creations, like theNeuromancer novel by William Gibson or the Brainstorm cinematic movie, to name just a few.Nowadays these dreams are slowly becoming reality due to a variety of brain-computer interfaces(BCI) that detect neural activation patterns and support the control of devices by brain signals.

    An important field in which BCIs are being successfully integrated is the interaction withvehicular systems. In this paper we evaluate the performance of BCIs, more specifically a commercialelectroencephalographic (EEG) headset, in combination with vehicle dashboard systemsand highlight the advantages and limitations of this approach. Further, we investigate the cognitiveload that drivers experience when interacting with secondary in-vehicle devices via touchcontrols or a BCI headset. As in-vehicle systems are increasingly versatile and complex, it becomesvital to capture the level of distraction and errors that controlling these secondary systemsmight introduce to the primary driving process. Our results suggest that the control with theEEG headset introduces less distraction to the driver, probably as it allows the eyes of the driverto remain focused on the road. Still, the control of the vehicle dashboard by EEG is efficientonly for a limited number of functions, after which increasing the number of in-vehicle controlsamplifies the detection of false commands.

  • 16.
    Cernea, Daniel
    et al.
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics. University of Kaiserslauten, Germany.
    Olech, Peter-Scott
    University of Kaiserslauten, Germany.
    Ebert, Achim
    University of Kaiserslauten, Germany.
    Kerren, Andreas
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    EEG-based Measurement of Subjective Parameters in Evaluations2011In: HCI International 2011 Posters' Extended Abstracts: International Conference, HCI International 2011, Orlando, FL, USA, July 9-14, 2011, Proceedings, Part II / [ed] Stephanidis, Constantine, Berlin Heidelberg: Springer, 2011, p. 279-283Conference paper (Refereed)
    Abstract [en]

    Evaluating new approaches, be it new interaction techniques, new applications or even new hardware, is an important task, which has to be done to ensure both usability and user satisfaction. The drawback of evaluating subjective parameters is that this can be relatively time consuming, and the outcome is possibly quite imprecise. Considering the recent release of cost-efficient commercial EEG headsets, we propose the utilization of electro-encephalographic (EEG) devices for evaluation purposes. The goal of our research is to evaluate if a commercial EEG headset can provide cutting-edge support during user studies and evaluations. Our results are encouraging and suggest that wireless EEG technology is a viable alternative for measuring subjectivity in evaluation scenarios.

  • 17.
    Cernea, Daniel
    et al.
    University of Kaiserslautern.
    Olech, Peter-Scott
    Ebert, Achim
    Kerren, Andreas
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Measuring Subjectivity: Supporting Evaluations with the Emotiv EPOC Neuroheadset2012In: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987, Vol. 26, no 2, p. 177-182Article in journal (Refereed)
    Abstract [en]

    Since the dawn of the industrial era, modern devices and interaction methods have undergone rigorous evaluations in order to ensure their functionality and quality, as well as usability. While there are many methods for measuring objective data, capturing and interpreting subjective factors—like the feelings or states of mind of the users—is still an imprecise and usually post-event process. In this paper we propose the utilization of the Emotiv EPOC commercial electroencephalographic (EEG) neuroheadset for real-time support during evaluations and user studies. We show in two evaluation scenarios that the wireless EPOC headsets can be used efficiently for supporting subjectivity measurement. Additionally, we highlight situations that may result in a lower accuracy, as well as explore possible reasons and propose solutions for improving the error rates of the device.

  • 18.
    Cernea, Daniel
    et al.
    Linnaeus University, Faculty of Technology, Department of Computer Science. University of Kaiserslautern, Germany.
    Truderung, Igor
    University of Kaiserslautern, Germany.
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Ebert, Achim
    An Interactive Visualization for Tabbed Browsing Behavior Analysis2014In: Computer Vision, Imaging and Computer Graphics: Theory and Applications / [ed] Sebastiano Battiato, Sabine Coquillart, Robert S. Laramee, Andreas Kerren, and José Braz, Springer, 2014, p. 69-84Chapter in book (Refereed)
    Abstract [en]

    Web browsers are at the core of online user experience, enablinga wide range of Web applications, like communication, games, entertainment, development, etc. Additionally, given the variety and complexity of online-supported tasks, users have started parallelizing and organizing their online browser sessions by employing multiple browser windows and tabs. However, there are few solutions that support analysts and casual users in detecting and extracting patterns from these parallel browsing histories. In this paper we introduce WebComets, an interactive visualization for exploring multi-session multi-user parallel browsing logs. After highlighting visual and functional aspects of the system, we introduce a motif-based contextual search for enabling the filtering and comparison of user navigation patterns. We further highlight the functionality of WebComets with a use case. Our investigations suggest that parallel browser history visualization can offer better insight into user tabbed browsing behavior and support the recognition of online navigation patterns.

  • 19.
    Cernea, Daniel
    et al.
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Truderung, Igor
    University of Kaiserslautern, Germany .
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Ebert, Achim
    University of Kaiserslautern, Germany .
    WebComets: A Tab-Oriented Approach for Browser History Visualization2013In: / [ed] S. Coquillart, C. Andujar, R. S. Laramee, A. Kerren, and J. Braz, SciTePress , 2013, p. 439-450Conference paper (Refereed)
    Abstract [en]

    Web browsers are our main gateways to the Internet. With their help we read articles, we learn, we listen to music, we share our thoughts and feelings, we write e-mails, or we chat. Current Web browser histories have mostly no visualization capabilities as well as limited options to filter patterns and information. Furthermore, such histories disregard the existence of parallel navigation in multiple browser windows andtabs. But a good understanding of parallel browsing behavior is of critical importance for the casual user and the behavioural analyst, while at the same time having implications in the design of search engines, Web sites and Web browsers. In this paper we present WebComets, an interactive visualization for extended browser histories. Our visualization employs browser histories that capture—among others—the taboriented, parallel nature of Web page navigation. Results presented in this paper suggest that WebComets better supports the analysis and comparison of parallel browsing and corresponding behavior patterns than common browser histories.

  • 20.
    Cernea, Daniel
    et al.
    Technische Univ. Kaiserslautern .
    Weber, Christopher
    Technische Univ. Kaiserslautern .
    Ebert, Achim
    Technische Univ. Kaiserslautern .
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Emotion Scents: A Method of Representing User Emotions on GUI Widgets2013In: Proceedings  of SPIE 8654: Visualization and Data Analysis 2013, Burlingame, California, USA, February 3, 2013, SPIE - International Society for Optical Engineering, 2013, p. 86540F-Conference paper (Refereed)
    Abstract [en]

    The world of desktop interfaces has been dominated for years by the concept of windows and standardized user interface (UI) components. Still, while supporting the interaction and information exchange between the users and the computer system, graphical user interface (GUI) widgets are rather one-sided, neglecting to capture the subjective facets of the user experience. In this paper, we propose a set of design guidelines for visualizing user emotions on standard GUI widgets (e.g., buttons, check boxes, etc.) in order to enrich the interface with a new dimension of subjective information by adding support for emotion awareness as well as post-task analysis and decision making. We highlight the use of an EEG headset for recording the various emotional states of the user while he/she is interacting with the widgets of the interface. We propose a visualization approach, called emotion scents, that allows users to view emotional reactions corresponding to di erent GUI widgets without in uencing the layout or changing the positioning of these widgets. Our approach does not focus on highlighting the emotional experience during the interaction with an entire system, but on representing the emotional perceptions and reactions generated by the interaction with a particular UI component. Our research is motivated by enabling emotional self-awareness and subjectivity analysis through the proposed emotionenhanced UI components for desktop interfaces. These assumptions are further supported by an evaluation of emotion scents.

  • 21.
    Cernea, Daniel
    et al.
    Linnaeus University, Faculty of Technology, Department of Computer Science. Univ Kaiserslautern, Germany.
    Weber, Christopher
    Univ Kaiserslautern, Germany.
    Ebert, Achim
    Univ Kaiserslautern, Germany.
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Emotion-Prints: Interaction-Driven Emotion Visualization on Multi-Touch Interfaces2015In: Proceedings of SPIE 9397: Visualization and Data Analysis 2015, San Francisco, CA, USA, February 8-12, 2015 / [ed] David L. Kao, Ming C. Hao, Mark A. Livingston, and Thomas Wischgoll, SPIE - International Society for Optical Engineering, 2015, p. 9397-0A-Conference paper (Refereed)
    Abstract [en]

    Emotions are one of the unique aspects of human nature, and sadly at the same time one of the elements that our technological world is failing to capture and consider due to their subtlety and inherent complexity. But with the current dawn of new technologies that enable the interpretation of emotional states based on techniques involving facial expressions, speech and intonation, electrodermal response (EDS) and brain-computer interfaces (BCIs), we are finally able to access real-time user emotions in various system interfaces. In this paper we introduce emotion-prints, an approach for visualizing user emotional valence and arousal in the context of multi-touch systems. Our goal is to offer a standardized technique for representing user affective states in the moment when and at the location where the interaction occurs in order to increase affective self-awareness, support awareness in collaborative and competitive scenarios, and offer a framework for aiding the evaluation of touch applications through emotion visualization. We show that emotion-prints are not only independent of the shape of the graphical objects on the touch display, but also that they can be applied regardless of the acquisition technique used for detecting and interpreting user emotions. Moreover, our representation can encode any affective information that can be decomposed or reduced to Russell’s two-dimensional space of valence and arousal. Our approach is enforced by a BCI-based user study and a follow-up discussion of advantages and limitations. 

  • 22.
    Cernea, Daniel
    et al.
    Linnaeus University, Faculty of Technology, Department of Computer Science. University of Kaiserslautern.
    Weber, Christopher
    UC Davis, Department of Computer Science.
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Ebert, Achim
    University of Kaiserslautern.
    Group Affective Tone Awareness and Regulation through Virtual Agents2014In: Proceedings of the Workshop on Affective Agents: Fourteenth International Conference on Intelligent Virtual Agents (IVA 2014), 2014, p. 9-16Conference paper (Refereed)
    Abstract [en]

    It happens increasingly often that experts need to collaboratein order to exchange ideas, views and opinions on their path towardsunderstanding. However, every collaboration process is inherently fragileand involves a large set of human subjective aspects, including socialinteraction, personality, and emotions. In this paper we present Pogat,an affective virtual agent designed to support the collaboration processaround displays by increasing user awareness of the group affective tone.A positive group affective tone, where all the participants of a groupexperience emotions of a positive valence, has been linked to fosteringcreativity in groups and supporting the entire collaboration process. Atthe same time, a negative or inexistent group affective tone can suggestnegative emotions in some of the group members, emotions that canlead to an inefficient or even obstructed collaboration. A study of ourapproach suggests that Pogat can increase the awareness of the overallaffective state of the group as well as positively affect the efficiency ofgroups in collaborative scenarios.

  • 23. Coquillart, Sabine
    et al.
    Andujar, CarlosLaramee, Robert S.Kerren, AndreasLinnaeus University, Faculty of Technology, Department of Computer Science.Braz, José
    GRAPP 2013 and IVAPP 2013: Proceedings of the International Conference on Computer Graphics Theory and Applications and International Conference on Information Visualization Theory and Applications2013Conference proceedings (editor) (Refereed)
  • 24. 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.

  • 25.
    Golub, Koraljka
    et al.
    Linnaeus University, Faculty of Arts and Humanities, Department of Cultural Sciences.
    Tyrkkö, Jukka
    Linnaeus University, Faculty of Arts and Humanities, Department of Languages.
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Jusufi, Ilir
    Linnaeus University, Faculty of Technology, Department of Media Technology.
    Ardö, Anders
    Lund University.
    Automatic subject classification for improving retrieval in a Swedish repository2017In: ISKO UK Conference 2017: Knowledge Organization: what's the story?, 11 – 12 September 2017, London, 2017Conference paper (Refereed)
    Abstract [en]

    The recent adoption of the Dewey Decimal Classification (DDC) in Sweden has ignited discussions about automated subject classification especially for digital collections, which generally seem to lack subject indexing from controlled vocabularies. This is particularly problematic in the context of academic resource retrieval tasks, which require an understanding of discipline-specific terminologies and the narratives behind their internal ontologies. The currently available experimental classification software have not been adequately tested and their usefulness is unproven especially for Swedish language resources. We address these issues by investigating a unifying framework of automatic subject indexing for the DDC, including an analysis of suitable interactive visualisation features for supporting these aims. We will address the disciplinary narratives behind the DDC in selected subject areas and the preliminary results will include an analysis of the data collection and a breakdown of the methodology. Major visualisation possibilities in support of the classification process are also outlined. The project will contribute significantly to Swedish information infrastructure by improving the findability of Swedish research resources by subject searching, one of the most common yet the most challenging types of searching.

  • 26. Hagen, Hans
    et al.
    Kerren, Andreas
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Computer Science.
    Dannenmann, Peter
    Visualization of Large and Unstructured Data Sets2006Book (Other (popular science, discussion, etc.))
  • 27.
    Jusufi, Ilir
    et al.
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Dingjie, Yang
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Kerren, Andreas
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    The Network Lens: Interactive Exploration of Multivariate Networks Using Visual Filtering2010In: Proceedings of the 14th International Conference on Information Visualisation (IV '10), IEEE, 2010, p. 35-42Conference paper (Refereed)
    Abstract [en]

    Networks are widely used in modeling relational data often comprised of thousands of nodes and edges. This kind of data alone implies a challenge for its visualization as it is hard to avoid clutter of network elements if using traditional node-link diagrams. Moreover, real-life network data sets usually represent objects with a large number of additional attributes that need to be visualized, such as in software engineering, social network analysis, or biochemistry. In this paper, we present a novel approach, called Network Lens, to visualize such attributes in context of the underlying network. Our implementation of the Network Lens is an interactive tool that extends the idea of so-called magic lenses in such a way that users can interactively build and combine various lenses by specifying different attributes and selecting suitable visual representations.

  • 28.
    Jusufi, Ilir
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Computer Science.
    Junuzi, Lulzim
    Kerren, Andreas
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Computer Science.
    Milrad, Marcelo
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Visualization of Content and Semantical Relations of Geonotes2008In: Proceedings of the 8th IASTED International Conference on Visualization, Imaging, and Image Processing (VIIP '08), ACTA Press , 2008, p. 131-136Conference paper (Refereed)
  • 29.
    Jusufi, Ilir
    et al.
    Linnaeus University, Faculty of Technology, Department of Media Technology.
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Network Visualization for Digital Humanities: Two Case Studies of Visual Analyses for Text Analytics2016In: International Symposium on Digital Humanities, Växjö 7-8 November 2016: Book of Abstracts, Linnaeus University , 2016, p. 39-43Conference paper (Refereed)
    Abstract [en]

    Much of the data created nowadays in fields such as Digital Humanities (DH) is of relational nature, such as social or semantic networks. Researchers often decide to depict networks as node-link diagrams to make a better sense of the complex nature of data. Understanding the topology of such a network can be very important. For instance, if we show our friends as network nodes and their friendship as edges between the nodes, it becomes easy to identify groups of friends from different social settings (work friends, high school friends, etc.).

    Networks usually have additional attributes attached to their elements. For instance, we can model a number of documents in a repository as nodes and use edges to describe co-authorship. Additionally, we might want to explore other aspects of such a corpus, like the keywords for each document, its genre, and various other data associated. Here, it is often desirable to get an overview about the network structure and how different data values relate to this structure. In this paper, we present two case studies for visualizations in DH with a focus on publication networks. But first, we will introduce our data sets used in these studies.

  • 30.
    Jusufi, Ilir
    et al.
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Kerren, Andreas
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Aleksakhin, Vladyslav
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Schreiber, Falk
    Martin-Luther University.
    Visualization of Mappings between the Gene Ontology and Cluster Trees2012In: Proceedings of the SPIE 2012 Conference on Visualization and Data Analysis (VDA '12) / [ed] Pak Chung Wong, David L. Kao, Ming C. Hao, Chaomei Chen, Robert Kosara, Mark A. Livingston, Jinah Park, and Ian Roberts, SPIE - International Society for Optical Engineering, 2012Conference paper (Refereed)
    Abstract [en]

    Ontologies and hierarchical clustering are both important tools in biology and medicine to study high-throughput data such as transcriptomics and metabolomics data. Enrichment of ontology terms in the data is used to identify statistically overrepresented ontology terms, giving insight into relevant biological processes or functional modules. Hierarchical clustering is a standard method to analyze and visualize data to find relatively homogeneous clusters of experimental data points. Both methods support the analysis of the same data set, 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 clustering of the data. This paper proposes a new visualization method for this task.

  • 31.
    Jusufi, Ilir
    et al.
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Liu, Jiayi
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Zimmer, Björn
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Visual Exploration of Relationships between Document Clusters2014In: IVAPP 2014: Proceedings od the 5th International Conference on Information Visualization Theory and Applications / [ed] Robert S. Laramee, Andreas Kerren, José Braz, SciTePress, 2014, p. 195-203Conference paper (Refereed)
    Abstract [en]

    The visualization of networks with additional attributes attached to the network elements is one of the ongoing challenges in the information visualization domain. Such so-called multivariate networks regularly appear in various application fields, for instance, in data sets which describe friendship networks or co-authorship networks. Here, we focus on networks that are based on text documents, i.e., the network nodes represent documents and the edges show relationships between them. Those relationships can be derived from common topics or common co-authors. Attached attributes may be specific keywords (topics), keyword frequencies, etc. The analysis of such multivariate networks is challenging, because a deeper understanding of the data provided depends on effective visualization and interaction techniques that are able to bring all types of information together. In addition, automatic analysis methods should be used to support the analysis process of potentially large amounts of data. In this paper, we present a visualization approach that tackles those analysis problems. Our implementation provides a combination of new techniques that shows intra-cluster and inter-cluster relations while giving insight into the content of the cluster attributes. Hence, it facilitates the interactive exploration of the networks under consideration by showing the relationships between node clusters in context of network topology and multivariate attributes.

  • 32.
    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.

  • 33.
    Jusufi, Ilir
    et al.
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Kerren, Andreas
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Wang, Yuanmao
    A New Radial Space-Filling Visualization Approach for Planar st-Graphs2012In: Poster Abstracts of IEEE VisWeek 2012, 2012Conference paper (Refereed)
    Abstract [en]

    Planar st-graphs are used in a number of different application fieldsin the sciences, but also in industry. So far, mainly node-link-basedlayouts have been used to visualize such graphs especially in theGraph Drawing community. One drawback of these standard layoutsis their high consumption of space. In Information Visualization,there exist visualization techniques for graphs which achieveconsiderable space savings, such as matrix-based approaches. Inthis work, we present a novel space-filling representation to visualizeplanar st-graphs.

  • 34.
    Jusufi, Ilir
    et al.
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Zimmer, Björn
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Multivariate Network Exploration with JauntyNets2013In: Proceedings 2013 17th International Conference on Information Visualisation IV 2013: 16-18 July 2013, London, United Kingdom, IEEE, 2013, p. 19-27Conference paper (Refereed)
    Abstract [en]

    The amount of data produced in the world every day implies a huge challenge in understanding and extracting knowledge from it. Much of this data is of relational nature, such as social networks, metabolic pathways, or links between software components. Traditionally, those networks are represented as node-link diagrams or matrix representations. They help us to understand the structure (topology) of the relational data. However in many real world data sets, additional (often multidimensional) attributes are attached to the network elements. One challenge is to show these attributes in context of the underlying network topology in order to support the user in further analyses. In this paper, we present a novel approach that extends traditional force-based graph layouts to create an attribute-driven layout. In addition, our prototype implementation supports interactive exploration by introducing clustering and multidimensional scaling into the analysis process.

  • 35.
    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.

  • 36.
    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
    Interactive Navigation in Interconnected Biochemical Pathways2010Other (Other academic)
    Abstract [en]

    Approaches to investigate biological processes have been of strong interest in the last years and are in the focus of several research areas, especially Systems Biology. Biochemical networks are very important for such a comprehensive understanding of living beings. Drawings of these networks are often visually overloaded and do not scale. A common solution to deal with this complexity is to divide the complete network into a large set of single pathways that are hierarchically structured. In this poster paper, we present a solution of visualizing and navigating interconnected biochemical pathways.

  • 37.
    Kerren, Andreas
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Explorative Analysis of Graph Pyramids Using Interactive Visualization Techniques2005In: Proceedings of the 5th IASTED International Conference on Visualization, Imaging, and Image Processing (VIIP '05), ACTA Press , 2005, p. 985-690Conference paper (Refereed)
    Abstract [en]

    Hierarchies of plane graphs, called graph pyramids, can be used for collecting, storing, and analyzing geographical information based on images or other input data. The visualization of graph pyramids facilitates studies about their structure, such as their vertex distribution or height in relation of a specific input image. Thus, a researcher can debug contraction processes and ask for statistical information. Furthermore, it improves the better understanding of geographical data, like landscape properties or thematical maps. In this paper, we present an interactive visualization tool that supports several coordinated views on graph pyramids, subpyramids, level graphs, thematical maps, etc. We discuss a brief case study on the basis of a small sample image and conclude the paper with future work.

  • 38.
    Kerren, Andreas
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Computer Science.
    Improving Strategy Parameters of Evolutionary Computations with Interactive Coordinated Views2006In: Proceedings of the 6th IASTED International Conference on Visualization, Imaging, and Image Processing (VIIP '06), ACTA Press , 2006, p. 88-93Conference paper (Refereed)
  • 39.
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Information Visualization Courses for Students with a Computer Science Background2013In: IEEE Computer Graphics and Applications, ISSN 0272-1716, E-ISSN 1558-1756, Vol. 33, no 2, p. 12-15Article in journal (Refereed)
    Abstract [en]

    Linnaeus University offers two master's courses in information visualization for computer science students with programming experience. This article briefly describes the syllabi, exercises, and practices developed for these courses.

  • 40.
    Kerren, Andreas
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Interaction and Evaluation Techniques for Information Visualization: Future Directions2013In: Proceedings of the 6th International Symposium on Visual Information Communication and Interaction (VINCI '13), ACM Press, 2013, p. 118-118Conference paper (Other academic)
    Abstract [en]

    Intuitive and efficient interaction techniques are a fundamental component of most visualization tools. The integration of interaction techniques into visual representations (and automatic analysis methods in visual analytics) supports the human-information discourse and can be realized in various ways. But we also have to take care that our interaction and visual representation techniques are validated in order to get a clear understanding of their efficiency and usability. In this talk, I will explore current and identify future trends in the development of novel interaction and evaluation techniques for information visualization and related fields. Here, I especially want to highlight recent findings in the use of brain-computer interfaces to adapt and evaluate visualizations.

  • 41.
    Kerren, Andreas
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Interactive Visualization of Graph Pyramids2005Report (Other academic)
    Abstract [en]

    Hierarchies of plane graphs, called graph pyramids, can be used for collecting, storing and analyzing geographical information based on satellite images or other input data. The visualization of graph pyramids facilitates studies about their structure, such as their vertex distribution or height in relation of a specific input image. Thus, a researcher can debug algorithms and ask for statistical information. Furthermore, it improves the better understanding of geographical data, like landscape properties or thematical maps. In this paper, we present an interactive 3D visualization tool that supports several coordinated views on graph pyramids, subpyramids, level graphs, thematical maps, etc. Additionally, some implementation details and application results are discussed.

  • 42.
    Kerren, Andreas
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Visualization of Workaday Data Clarified by Means of Wine Fingerprints2011In: Human Aspects of Visualization: Second IFIP WG 13.7 Workshop on Human-Computer Interaction and Visualization, HCIV (INTERACT) 2009, Uppsala, Sweden, August 24, 2009, Revised Selected Papers / [ed] Achim Ebert et al., Berlin Heidelberg New York: Springer, 2011, p. 92-107Conference paper (Refereed)
    Abstract [en]

    More and more average users of personal computers, standard software, and web browsers come into contact with (information) visualization techniques. Depending on the task they have to perform, such visualizations are used for communication purposes, to provide a better overview of personal data, for instance pictures or emails, or to provide information of everyday commodities. After a brief outline about properties and characteristics of workaday data and their users, we focus in this paper on the visualization of wine attributes. The decision to buy a specific bottle of wine is a complex process that incorporates many different aspects from own experiences and current desires to various aromas and flavors that the wine promises to keep. We have developed two different visual representations for wine related data, which we call wine fingerprints. Both approaches are able to represent the most used wine attributes in literature and practice and can guide the purchase decision process of customers. Pros and cons of our wine fingerprints are discussed and compared with related approaches.

  • 43.
    Kerren, Andreas
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Visualizations and Animations in Learning Systems2012In: Encyclopedia of the Sciences of Learning / [ed] Norbert M. Seal, Springer, 2012, p. 3419-3421Chapter in book (Other academic)
  • 44.
    Kerren, Andreas
    et al.
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Cernea, DanielAGT International, Germany.Pohl, MargitTechnical University of Vienna, Austria.
    Proceedings of EmoVis 2016: ACM IUI 2016 Workshop on Emotion and Visualization2016Conference proceedings (editor) (Refereed)
  • 45.
    Kerren, Andreas
    et al.
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Cernea, Daniel
    AGT International, Germany.
    Pohl, Margit
    Technical University of Vienna, Austria.
    Workshop on Emotion and Visualization: EmoVis 20162016In: Companion Publication of the 21st International Conference on Intelligent User Interfaces, New York, NY, USA: ACM Digital Library, 2016, p. 1-2Conference paper (Other academic)
  • 46.
    Kerren, Andreas
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Ebert, AchimMeyer, Jörg
    Human-Centered Visualization Environments: GI-Dagstuhl Research Seminar, Dagstuhl Castle, Germany, March 5-8, 2006, Revised Lectures2007Collection (editor) (Refereed)
    Abstract [en]

    This tutorial book presents an augmented selection of the material presented at the GI-Dagstuhl Research Seminar on Human-Centered Visualization Environments, HCVE 2006, held in Dagstuhl Castle, Germany in March 2006.

    The 8 tutorial lectures presented are the thoroughly cross-reviewed and revised versions of the summaries and findings, presented and discussed at the seminar. After an introduction to human-centered visualization environments the fundamental principles and methods in that area are shown such as human-centered aspects, interacting with visualizations, visual representations, as well as challenges and unsolved problems. The book is concluded with lectures on domain-specific visualization describing geographic visualization, algorithm animation, and biomedical information visualization.

  • 47.
    Kerren, Andreas
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering. Computer Science Department.
    Ebert, Achim
    Meyer, Jörg
    Introduction to Human-Centered Visualization Environments2007In: Human-Centered Visualization Environments: GI-Dagstuhl Research Seminar, Dagstuhl Castle, Germany, March 5-8, 2006, Revised Lectures, 2007Chapter in book (Other (popular science, discussion, etc.))
  • 48.
    Kerren, Andreas
    et al.
    Växjö University, Faculty of Mathematics/Science/Technology, School of Mathematics and Systems Engineering.
    Egger, Thomas
    EAVis: A Visualization Tool for Evolutionary Algorithms2005In: Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC '05), IEEE Computer Society Press , 2005, p. 299-301Conference paper (Refereed)
    Abstract [en]

    Evolutionary algorithms (EAs) produce a vast amount of data by recurring processes, e.g., selection, recombination, or mutation, that work on populations of solutions for a specific problem. In order to get a better insight into the progress of EAs a Java-based visualization tool, called EAVis, was developed. Several coordinated views help the user to watch each generation step of the EA and to derive knowledge as well as better understanding of the underlying evolutionary computational models.

  • 49.
    Kerren, Andreas
    et al.
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    Jusufi, Ilir
    Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
    3D Kiviat Diagrams for the Interactive Analysis of Software Metric Trends2010In: Proceedings of the 5th ACM Symposium on Software Visualization (SoftVis '10), ACM Press, 2010, p. 203-204Conference paper (Refereed)
    Abstract [en]

    Previous techniques for visualizing time-series of multivariate data mostly plot the time along additional axes, are often complex, and does not support intuitive interaction. In this poster paper, we present an interactive visualization approach for the analysis of software metric trends that allows users to operate with Kiviat diagrams on 2D planes in the space and to intuitively extend this visual representation into 3D if needed.

  • 50.
    Kerren, Andreas
    et al.
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Jusufi, Ilir
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    A Novel Radial Visualization Approach for Undirected Hypergraphs2013In: EuroVis: Short Papers, Eurographics - European Association for Computer Graphics, 2013, p. 25-29Conference paper (Refereed)
    Abstract [en]

    Hypergraphs are a more generalized concept of graphs where an edge typically connects multiple vertices. They are applicable to many different domains such as the representation of complex biochemical pathways or classification problems with non-empty intersections between different groups, for instance, in social network analysis. There is a need to visualize those relational data structures in such a way that a better understanding of the relationships between vertices as well as their interactive exploration is supported. This paper describes a new radial visualization technique to layout undirected hypergraphs without clutter and to provide methods of interaction and data analysis. 

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