Academic Positions

  • Present 2010

    Research and teaching assistant

    Vienna University of Technology

  • 2010 2009

    Research assistant

    Danube University Krems

Education & Training

  • PhD 2017

    PhD in Computer Science

    (passed with distinction)

    thesis: Visual Analytics of Dynamic Networks

    Vienna University of Technology

  • MSc2008

    Master in Telecommunication Engineering

    Federico II University of Naples, Italy

Scientific community service

I have been reviewing for several journals (Computer & Graphics, Computer Graphics Forum, IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Visualisation and Computer Graphics, Journal of the American Medical Informatics Association, Transactions on Intelligent Systems and Technology) and conferences (CHI, Eurographics, EuroVA, EuroVis, InfoVis, IVAPP, PacificVis, SIGGRAPH, SouthCHI, VAST). I served in the program committee of the workshop on Visual Analytics in Healthcare.

Research Projects

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    IMMV Interactive Music Mapping Vienna

    Exploring a City, 1945 up to the present day


    FWF, Austria

    The project’s focus is the valorisation and the mediation of the capabilities of music as an urban identification tool. The interaction between music and urban texture (identity, political symbolism, mental determination, imagination) should be made accessible to academic and to a wide audience through interactive Visual Analytic Technologies.

    The questions of how music acts in the urban context as a social identification instrument and how music is functionalized to urban symbolic politics form the starting point of the research project conducted by the MUK (Music and Arts University of The City of Vienna). The music component of mental determination of urbanity is created using the example of City of Vienna: How the "sensual" medium of music, generator of atmosphere and mood, produces not only ideological subjects, but also the notion of specific urban spheres? Linked to the aforementioned are cultural and social practices (habitus) that need to be identified and developed. Vienna’s site-specificity is associated to its acoustic-phonetic structure more than any other European city. Strategies and processes in music will be explored in terms of “politics of emotion” city configuration that shaped Vienna’s image and continues to do so. Concrete subject of research selected are the festivities in the public space of Vienna in a by many considered underexposed period of Austrian history, that of the Second Republic: 1945 up to the present day (under a comparative insertion of retrospect into the period before 1945). City’s spatial configuration with the chronological mode of festivity constructs the axes of a narrative in reciprocal relation. Selected Viennese festivity-events are going to be presented, developed from until now neglected and untapped primary sources of information, extending from text, image and sound data to film, television and radio recordings.

    Creation of multi-medial platform as an interactive dissemination space has been planned with the Institute of Software Technology and Interactive Systems at TU Wien, which using the visual analytic technologies creates the contents synchronous and at the same moment individually accessible. This platform will map all forms of media. Cartographic representations, aesthetic image-strategies and multidimensional artistic translations for the selected events will make the complexity of multiple layers and ambiguity (contingency) of history sensory experience. The visualization mode provides simultaneous media experience (visual, auditory, textual) and differentiates the reception of real and imaginary space constructions. The visual analytic solution is conceived for different user-typologies (for an educated audience as well as for interested laymen and laywomen without previous knowledge in this field).

    The following cooperation partners will accompany the project: Vienna Museum, Austria Film Archive, Vienna City Library, Austrian Media Library, Institute for Contemporary History at the University of Vienna, Ludwig Boltzmann Institute for History and Society, and ORF-Archive. The project has been scheduled for a period of three years. Univ.-Prof. Dr. Susana Zapke has assumed the IMMV’s project management.

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    Towards Integrated Mental Models of Cultural Heritage Data


    FWF, Austria

    This interdisciplinary project investigates the potential of interactive information visualizations for public access to digital cultural collections: Space-Time Cubes are assumed to support casual users in their exploration of such collections, in their comprehension of multidimensional metadata, and in the construction of an integrated mental model. In a user-centered design process information visualizations will be developed and empirically evaluated in a series of experiments.

    Web-based databases of museums’ and cultural institutions’ collections enable fast access to important cultural assets for everyone: Millions of paintings, sculptures, music, and artworks can be reached with only a few clicks. Current research shows that interested visitors like to explore digital collections - often without a concrete goal. They like their observations to add up and make sense and to learn something new. Traditional websites focus on professional users, hence often knowledge of cultural history or the structures of the database are needed to effectively navigate the enormous amount of data. Diagrams and visual overviews can highly improve the accessibility to these collections.

    In the project Towards Integrated Mental Models of Cultural Heritage Data one particular method of visualization will be investigated and further developed: the space-time cube (STC) displays spatial distributions as well as the temporal developments in a combined view. It could provide a good overview of cultural heritage data and show the geographical, chronological or topic-specific context of each single element at a glance. The project team will analyze if this method actually aids in exploring the data and in understanding the relations between the data. In cognitive science this comprehension process is defined as the construction of a mental model. A higher number of connections between single bits of information within the mental model equal a better understanding of the data.

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    Detection and Visualization of unexploded Ordnance Risks


    FFG, Austria

    Analysis of historic air photos (images) with the goal of detecting unexploded bombs is a niche task, yet extremely important for preventing great damage or even loss of life. The computer science techniques and software tools currently available are of general nature, like Geographic Information Systems (GIS) and graphics editing programs. With these tools, the Luftbilddatenbank Dr. Carls GmbH, Vienna (LBDB), works on an even more complex task: the multi-temporal image analysis that takes into account historic prime records and other sources to gain information about air strikes, checking subsequent images for bombardment. The overall outcome is an Unexploded Ordnance (UXO) survey. In the project, interactive software tools will be developed that will support the work of the LBDB employees. These tools will incorporate new methods belonging to the fields of Computer Vision and Visual Analytics.

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    Guiding patients anytime everywhere


    7FP, European Union

    MobiGuide (MG) will develop a patient guidance system that integrates hospital and monitoring data into a Personal Health Record (PHR) accessible by patients and care providers and provide personalized secure clinical-guideline-based guidance also outside clinical environments. MG's ubiquity will be achieved by having a Decision Support System (DSS) at the back end, and on the front end by utilizing Body Area Network (BAN) technology and developing a coordinated light-weight DSS that can operate independently. Personalization will be achieved by considering patient preferences and context. Retrospective data analysis will be used to assess compliance and to indicate care pathways shown to be beneficial for certain patient context.

    MG will be validated on pre-selected clinical domains with intensive vs. sparse monitoring to demonstrate the generality of the design and assess functionality, feasibility, and impact. MG addresses EU priorities: increasing patient safety, ubiquituous secure access to health care, patient empowerment, developing a common platform for healthcare services, and competitiveness of Europe.

    The time is right for MG in view of Europe's vast interest in national PHRs and patient empowerment. MG will leverage this momentum to create a solution that goes beyond local proprietary and stand-alone EMR, DSS, and BAN.

    MobiGuide website

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    EXploratory visualisation of PAtent Network Dynamics


    FFG, Austria

    The EXPAND project addresses highly topical challenges of visual analytics methods in the patent data domain. Aiming on a genuinely dynamical framework for visual analysis and knowledge crystallization, radically new concepts and methods have to be developed to unlock the potential of patent network data, which is characterized by its continuous and event based nature, its richness of attributes and its large scale.

    While these objectives are ranging high on a scientific and technological research agenda, a user-centred design and evaluation approach will ensure the practical utility and usability of the intended methods and concepts, which will be bundled and evaluated in form of a research prototype.

    The advancement and future implementation of the prototype into the business partners IT service portfolio will guarantee the exploitation of results as well as the strengthening of economic advantage in the strategic business intelligence market.

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    Centre for Visual Analytics Science and Technology.


    FFG, Austria

    Due to the proliferating capabilities to generate and collect vast amounts of data and information we face the challenge that users and analysts get lost in irrelevant, or otherwise inappropriately processed or presented information. This phenomenon, commonly known as information deluge, overwhelms traditional methods of data analysis such as spreadsheets, ad-hoc queries, or simple visualizations. At the same time, intelligent usage of increasingly available data offers great opportunities to promote technological progress and business success. On this score, Visual Analytics is an emerging research discipline developing methods and technology that make the best possible use of huge information loads in a wide variety of applications. The basic idea is to appropriately combine the strengths of both, computers' and humans' information processing capabilities. To make complex information structures more comprehensible, facilitate new insights, and enable knowledge discovery, methods of visualization, intelligent data analysis, and mining form a symbiosis with the human user via interactive visual interfaces.

    The goals of the Centre of Visual Analytics Science and Technology (CVAST) are twofold. The first goal is the integration of the outstanding capabilities of humans in terms of visual information exploration with the enormous processing power of computers to form a powerful knowledge discovery environment. The second goal is to scientifically assess the usability and utility of such discovery environments while bridging the gap between theory and practice for selected application scenarios.

    Application scenarios that involve temporal properties are in the focus of our scientific interest. Time - in contrast to other quantitative data dimensions that are usually "flat" - has an inherent structure and distinct characteristics (calendar aspect, natural and social aspects, etc.) which increase its complexity dramatically and demand specialized Visual Analytics methods in order to support proper analysis and visualization. Our expected results will be Innovative, user-oriented, and task-specific Visual Analytics methods and tools with an assessment of their usability and utility. These methods will be used intertwinedly and iteratively to ease the explorative information discovery processes.

    CVAST website

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    Visual Enterprise Network Analytics


    FFG-IT, Austria

    Collaboration is the way work gets done in organisations. Therefore networks of different types, functions and compositions have become an inevitable precondition of organisational performance in the modern corporate world. However, these networks are not static, but changing over time. Organisational analysts such as consultants, enterprise analysts, and strategic and human resource managers are seeking for appropriate tools and methods supporting the information discovery processes of these dynamic networks and the underlying data. In particular, interactive visual and analytic methods to explore the dynamic properties of underlying structures are required to provide empirically grounded decision support for organisational analysts.

    To meet these demands the proposed project "Visual Enterprise Network Analytics" (VIENA) takes on the method of Dynamic Network Analysis (DNA) whose potential for applied use in enterprises is well known. To unlock this potential also to non-domain experts two associated fields of research are leveraged: namely Visual Analytics and Usability Engineering. A constant focus on usability will assure the development of a user-centred software prototype and an intuitive GUI, while the Visual Analytics components will allow the radically new interactive exploration of dynamic network data sets and the retrieval of relevant information. VIENA facilitates the (semi-)automatic analysis of teams and organisations over different periods of time.

    The heterogeneous dynamical data and information sets which get structured, semantically annotated, and visualised by DNA methods get additionally processed using innovative Visual Analytics methods. The aimed integration of selected research prototypes into the industrial partner's business software environment will allow real-user testing and assessments from the application and utility point of view.

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The Role of Explicit Knowledge: A Conceptual Model of Knowledge-Assisted Visual Analytics

P. Federico, M. Wagner, A. Rind, A. Amor-Amoros, S. Miksch, and W. Aigner
Conference PaperIEEE Conference on Visual Analytics Science and Technology (IEEE VAST 2017)


Visual Analytics (VA) aims to combine the strengths of humans and computers for effective data analysis. In this endeavor, humans’ tacit knowledge from prior experience is an important asset that can be leveraged by both human and computer to improve the analytic process. While VA environments are starting to include features to formalize, store, and utilize such knowledge, the mechanisms and degree in which these environments integrate explicit knowledge varies widely. Additionally, this important class of VA environments has never been elaborated on by existing work on VA theory. This paper proposes a conceptual model of Knowledge-assisted VA conceptually grounded on the visualization model by van Wijk. We apply the model to describe various examples of knowledge-assisted VA from the literature and elaborate on three of them in finer detail. Moreover, we illustrate the utilization of the model to compare different design alternatives and to evaluate existing approaches with respect to their use of knowledge. Finally, the model can inspire designers to generate novel VA environments using explicit knowledge effectively.

A Synoptic Visualization Framework for the Multi-Perspective Study of Biography and Prosopography Data

F. Windhager, P. Federico, S. Salisu, M. Schloegl, and E. Mayr
Workshop PaperIEEE VIS Workshop on Visualization for the Digital Humanities (VIS4DH 2017)


The investigation of biography data as consistently time-oriented information connecting multiple data dimensions can be supported by multiple visualization perspectives. Biographical and prosopographical database projects contain temporally structured datasets connecting events, places, people, institutions with a variety of relations between them. We discuss challenges emerging from scholarly reasoning with these complex aggregated data, and present a visualization concept as a basis for future investigations. Specific attention is dedicated to the discussion of visual synergies to combine information and insights from multiple views and perspectives into a more coherent visual analytics environment, supporting the creation of integrated and shared mental models of data from our collective past.

Visual Analytics for Multitemporal Aerial Image Georeferencing

A. Amor-Amoros, P. Federico, S. Miksch, S. Zambanini, S. Brenner, R. Sablatnig
Workshop PaperEuroVis Workshop on Visual Analytics (EuroVA 2017)


Georeferencing of multitemporal aerial imagery is a time-consuming and challenging task that typically requires a high degree of human intervention, and which appears in application domains of critical importance, like unexploded ordnance detection. In order to make a semi-automatic scenario possible, we introduce a Visual Analytics approach for multitemporal aerial image georeferencing designed in close collaboration with real-world analysts that face the problem on a daily basis, and implemented by combining computer vision and interactive visual exploration methods. We report on informal validation findings resulting from the integration of our solution into our users’ GIS platform of choice, which positively illustrate its effectiveness and time-saving potential.

Visual Analytics of Electronic Health Records with a Focus on Time

A. Rind, P. Federico, T. Gschwandtner, W. Aigner, J. Doppler, M. Wagner
Book ChapterNew Perspectives in Medical Records: Meeting the Needs of Patients and Practitioners; Springer, 2017, 65 - 77


Visual Analytics is a field of computer science that deals with methods to perform data analysis using both computer-based methods and human judgment facilitated by direct interaction with visual representations of data. Electronic health record systems that apply Visual Analytics methods have the potential to provide healthcare stakeholders with much-needed cognitive support in exploring and querying records. This chapter presents Visual Analytics projects addressing five particular challenges of electronic health records: (1) The complexity of time-oriented data constitutes a cross-cutting challenge so that all projects need to consider design aspects of time-oriented data in one way or another. (2) As electronic health records encompass patient conditions and treatment, they are inherently heterogeneous data. (3) Scaling from single patients to cohorts requires approaches for relative time, space efficiency, and aggregation. (4) Data quality and uncertainty are common issues that need to be considered in real-world projects. (5) A user-centered design process and suitable interaction techniques are another cross-cutting challenge for each and every Visual Analytics project.

A Survey on Visual Approaches for Analyzing Scientific Literature and Patents

P. Federico, F. Heimerl, S. Koch, and S. Miksch
Journal PaperVisualization and Computer Graphics, IEEE Transactions on, 2017


Online survey:

The increasingly large number of available writings describing technical and scientific progress, calls for advanced analytic tools for their efficient analysis. This is true for many application scenarios in science and industry and for different types of writings, comprising patents and scientific articles. Despite important differences between patents and scientific articles, both have a variety of common characteristics that lead to similar search and analysis tasks. However, the analysis and visualization of these documents is not a trivial task due to the complexity of the documents as well as the large number of possible relations between their multivariate attributes. In this survey, we review interactive analysis and visualization approaches of patents and scientific articles, ranging from exploration tools to sophisticated mining methods. In a bottom-up approach, we categorize them according to two aspects: (a) data type (text, citations, authors, metadata, and combinations thereof), and (b) task (finding and comparing single entities, seeking elementary relations, finding complex patterns, and in particular temporal patterns, and investigating connections between multiple behaviours). Finally, we identify challenges and research directions in this area that ask for future investigations.

A Review of Information Visualization Approaches and Interfaces to Digital Cultural Heritage Collections

F. Windhager, P. Federico, E. Mayr, G. Schreder, and M. Smuc
Workshop PaperForum Media Technology (FMT2016)


After decades of digitization, the web hosts a large scale museum, consisting of millions of digital cultural objects. To balance the drawbacks of parsimonious search-centric interfaces, various approaches have been developed to enable also visual access to these collections, and to browse and explore the cultural richness of existing archives. This paper reviews information visualization approaches to digital cultural heritage collections, reflects on prominent arrangement principles and design choices for digital collection interfaces, and points out options for future research.

A Nested Workflow Model for Design and Validation of Visual Analytics

P. Federico, A. Amor-Amoros, and S. Miksch
Workshop PaperWorkshop on Beyond Time and Errors: Novel Evaluation Methods for Visualisation (BELIV16)


Characterizing the problem domain and understanding users' practices and processes are recognized as important steps in order to design and validate visualization, but are often disregarded in practice, also because of their complexity. We introduce the nested work ow model for design and validation of visual analytics, aimed at providing designers with a powerful and expressive modelling tool. This model enables the description of visual analytics processes, at different design levels, in terms of tasks, data, and users, including complex work ow patterns, data and knowledge flows, and collaboration between users. We discuss its application to two visual analytics projects, demonstrating its usefulness for their design and validation.

Evaluation of two interaction techniques for visualization of dynamic graphs

P. Federico, S. Miksch
Conference PaperInt. Symposium on Graph Drawing and Network Visualization (GD2016)


Several techniques for visualization of dynamic graphs are based on different spatial arrangements of a temporal sequence of node-link diagrams. Many studies in the literature have investigated the importance of maintaining the user's mental map across this temporal sequence, but usually each layout is considered as a static graph drawing and the effect of user interaction is disregarded. We conducted a task-based controlled experiment to assess the effectiveness of two basic interaction techniques: the adjustment of the layout stability and the highlighting of adjacent nodes and edges. We found that generally both interaction techniques increase accuracy, sometimes at the cost of longer completion times, and that the highlighting outclasses the stability adjustment for many tasks except the most complex ones.

Visualization of Cultural Heritage Data for Casual Users

E. Mayr, P. Federico, S. Miksch, G. Schreder, M. Smuc, and F. Windhager
Workshop PaperIEEE VIS Workshop on Visualization for the Digital Humanities (Vis4DH 2016)


A small subset of information visualization and the digital humanities focuses on casual users, that is, users in everyday, non-work contexts. The development of digital cultural heritage collections like for the general public increases the importance of this user group. This position paper reviews parallel findings from both research fields on casual users, their goals and exploration behavior: Casual users often come without concrete information needs, they rather search for something interesting and engaging. They browse through the information until they find something worth exploring in detail. From these characteristic needs and behavior of casual users we delineate design requirements for public information visualizations in the digital humanities. We discuss how further exchange between these two fields of research can bring forward both fields.

Reframing Cultural Heritage Collections in a Visualization Framework of Space-Time Cubes

F. Windhager, E. Mayr, G. Schreder, M. Smuc, P. Federico, S. Miksch
Workshop PaperInternational Workshop on Computational History (HistoInformatics2016)


During the last decades, digitization broadened access to cultural heritage collections for public audiences. Large online databases have been prepared for open access with simple search interfaces or visual exploration methods. In this position paper we discuss new challenges arising from these initiatives with regard to casual users. To meet their specific needs, we introduce a novel method for synoptic collection visualization which makes use of parallel space-time cubes to provide multiple spatiotemporal overviews, support free exploration, and to specifically engage casual audiences.

Visual Encodings of Temporal Uncertainty: A Comparative User Study

T. Gschwandtner, M. Boegl, P. Federico, S. Miksch
Journal Paper Visualization and Computer Graphics, IEEE Transactions on, vol.22, no.1, pp.539-548, Jan. 31 2016


A number of studies have investigated different ways of visualizing uncertainty. However, in the temporal dimension, it is still an open question how to best represent uncertainty, since the special characteristics of time require special visual encodings and may provoke different interpretations. Thus, we have conducted a comprehensive study comparing alternative visual encodings of intervals with uncertain start and end times: gradient plots, violin plots, accumulated probability plots, error bars, centered error bars, and ambiguation. Our results reveal significant differences in error rates and completion time for these different visualization types and different tasks. We recommend using ambiguation - using a lighter color value to represent uncertain regions - or error bars for judging durations and temporal bounds, and gradient plots - using fading color or transparency - for judging probability values.

Visually-supported graph traversals for exploratory analysis

A. Amor-Amoros, P. Federico, S. Miksch
Poster Poster Proceedings of the IEEE Visualization Conference (VIS 2016)


Many real-world problems appearing in diverse application domains involve large multivariate interrelated data. For this reason, graph-based data models have gained popularity in recent years. Graph traversal is a powerful computational paradigm addressing the challenges of graph data management; yet, its complexity and specificity might hinder its use for interactive data exploration by non-expert users in absence of appropriate interfaces. We have designed and implemented a system for visually-supported graph traversal, featuring (1) a graphical block metaphor for traversal formulation and execution, and (2) data probes providing relevant visual feedback about the results. The proposed approach aims at enhancing the usability of graph querying and retrieval techniques, in order to assist users with gaining and interpreting insights during exploratory analysis.

Gnaeus: utilizing clinical guidelines for knowledge-assisted visualisation of EHR cohorts

P. Federico, J. Unger, A. Amor-Amoros, L. Sacchi, D. Klimov, S. Miksch
Workshop PaperEuroVis Workshop on Visual Analytics (EuroVA 2015)


The advanced visualization of electronic health records (EHRs), supporting a scalable analysis from single patients to cohorts, intertwining patient conditions with executed treatments, and handling the complexity of time-oriented data, is an open challenge of visual analytics for health care. We propose an approach that, according to the knowledge-assisted visualization paradigm, leverages the domain knowledge acquired by clinical experts and formalized into computer-interpretable guidelines, in order to improve the automated analysis, the visualization, and the interactive exploration of EHRs of patient cohorts. In this way, the analyst can get insights about the clinical history of multiple patients and assess the effectiveness of their health care treatments.

A Concept for the Exploratory Visualization of Patent Network Dynamics

F. Windhager, A. Amor-Amoros, M. Smuc, P. Federico, L. Zenk, S. Miksch
Conference Paper International Conference on Information Visualization Theory and Applications (IVAPP 2015)


Patents, archived as large collections of semi-structured text documents, contain valuable information about historical trends and current states of R&D fields, as well as performances of single inventors and companies. Specific methods are needed to unlock this information and enable its insightful analysis by investors, executives, funding agencies, and policy makers. In this position paper, we propose an approach based on modelling patent repositories as multivariate temporal networks, and examining them by the means of specific visual analytics methods. We illustrate the potential of our approach by discussing two use-cases: the determination of emerging research fields in general and within companies, as well as the identification of inventors characterised by different temporal paths of productivity.

Knowledge-assisted EHR visualization for cohorts

P. Federico, A. Amor-Amoros, S. Miksch
Workshop Paper IEEE Vis Workshop on Visualizing Electronic Health Record Data (EHRVis 2014)


(not available)

TimeGraph: a data management framework for Visual Analytics of large multivariate time-oriented networks

A. Amor-Amoros, P. Federico, S. Miksch
Poster Poster Proceedings of the IEEE Visualization Conference (VIS 2014)


Large multivariate time-oriented networks have been gaining an increasing relevance in different domains. In order to support Visual Analytics processes on this kind of data, appropriate storage and retrieval methods are needed that take into account the scale, dimensionality, and in particular the complex nature of time. We introduce TimeGraph, a data management framework consisting of a data model and two levels of abstraction. TimeGraph captures both the topology of networks and the inherent structure of time into a property graph data structure, and transparently handles them by graph-based operations. TimeGraph aims to be an expressive, easy-to-use and extensible framework, enabling data reduction by selection and aggregation over both the temporal and the topological properties of data, to foster interactive visualization and analysis.

Qualizon Graphs: Space-Efficient Time-Series Visualization with Qualitative Abstractions

P. Federico, S. Hoffmann, A. Rind, W. Aigner, S. Miksch
Conference Paper International Working Conference on Advanced Visual Interfaces (AVI 2014)


In several application fields, the joint visualization of quantitative data and qualitative abstractions can help analysts make sense of complex time series data by associating precise numeric values with corresponding domain-specific interpretations, such as good, bad, high, low, normal. At the same time, the need to analyse large multivariate time-oriented datasets often calls for keeping visualizations as compact as possible. In this paper, we introduce Qualizon Graphs, a compact visualization that combines quantitative data and qualitative abstractions. It is based on the well known Horizon Graphs, but instead of a predefined number of equally sized bands, it uses as many bands as qualitative categories with corresponding different sizes. In this way, Qualizon Graphs increase the data density of visualized quantitative values and inherently integrate qualitative abstractions. A user study shows that Qualizon Graphs are as fast and accurate as Horizon Graphs for quantitative data, and are an alternative to state-of-the-art visualizations for both quantitative and qualitative data, enabling a trade-off between speed and accuracy.

On Visualizing Knowledge Flows at a University Department

F. Windhager, M. Smuc, L. Zenk, P. Federico, J. Pfeffer, W. Aigner
Journal Paper Procedia - Social and Behavioral Sciences, 100 (2013), 127 - 143


The analysis of dynamic network data has become an increasingly relevant research issue, showing a high potential for applied use in organizations. To unlock its potential also for the target user group of non-domain experts, we introduce a software prototype, which provides different views on network dynamics, intertwining network analytical measures with options of visual exploration. To demonstrate, how this approach can provide new access to questions of knowledge management and accessibility, a case study of a university department will be discussed. By combining multi-relational data of communication networks with attribute data of individual knowledge domains, we show how essential knowledge and change management issues can be reframed from a social network perspective and further developed towards integrated applications in organizations.

Visual Analysis of Compliance with Clinical Guidelines

P. Bodesinsky, P. Federico, S. Miksch
Conference Paper International Conference on Knowledge Management and Knowledge Technologies (i-KNOW 2013)


Clinical guidelines provide recommendations in the form of applicable actions in a specific clinical context. Computer Interpretable Guidelines (CIG) aim to achieve guideline integration into clinical practice to increase health care quality. Analyzing the compliance with a CIG can facilitate the implementation and assist in the design of CIGs, but to help medical experts in the detection of patterns in the wealth of the data is a challenging task. We suggest an approach based on visual analytics, intertwining interactive visualization and automated data analysis i.e. analysis of compliance with a CIG. Our solution covers highlighting and abstraction for time-oriented patient parameters, and aggregation of repeatedly missing actions into intervals; in addition valid, invalid, and missing actions are represented visually. Furthermore, we discuss a case study showing how the applied techniques can assist in the detection of interesting patterns.

How do you connect moving dots? Insights from user studies on Dynamic Network Visualizations

M. Smuc, P. Federico, F. Windhager, W. Aigner, L. Zenk, S. Miksch
Book Chapter Handbook of Human Centric Visualization; Springer, New York, USA, 2013, 623 - 650


In recent years, the analysis of dynamic network data has become an increasingly prominent research issue. While several visual analytics techniques with the focus on the examination of temporal evolving networks have been proposed in recent years, their effectiveness and utility for end users need to be further analyzed. When dealing with techniques for dynamic network analysis, which integrate visual, computational, and interactive components, users become easily overwhelmed by the amount of information displayed-even in case of small sized networks. Therefore we evaluated visual analytics techniques for dynamic networks during their development, performing intermediate evaluations by means of mock-up and eye-tracking studies and a final evaluation of the running interactive prototype, tracing three pathways of development in detail: The first one focused on the maintenance of the user s mental map throughout changes of network structure over time, changes caused by user interactions, and changes of analytical perspectives. The second one addresses the avoidance of visual clutter, or at least its moderation. The third pathway of development follows the implications of unexpected user behaviour and multiple problem solving processes. Aside from presenting solutions based on the outcomes of our evaluation, we discuss open and upcoming problems and set out new research questions.

Challenges of Time-oriented Data in Visual Analytics for Healthcare

W. Aigner, P. Federico, T. Gschwandtner, S. Miksch, A. Rind
Workshop Paper IEEE VisWeek Workshop on Visual Analytics in Healthcare (VACH 2012)


The visual exploration and analysis of time-oriented data in healthcare are important yet challenging tasks. This position paper presents six challenges for Visual Analytics in healthcare: (1) scale and complexity of time-oriented data, (2) intertwining patient condition with treatment processes, (3) scalable analysis from single patients to cohorts, (4) data quality and uncertainty, (5) interaction, user interfaces, and the role of users, and (6) evaluation. Furthermore, it portrays existing and future work by the authors tackling these challenges.

Visual Analysis of Dynamic Networks using Change Centrality

P. Federico, J. Pfeffer, W. Aigner, S. Miksch, L. Zenk
Conference Paper IEEE ACM Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)


The visualization and analysis of dynamic social networks are challenging problems, demanding the simultaneous consideration of relational and temporal aspects. In order to follow the evolution of a network over time, we need to detect not only which nodes and which links change and when these changes occur, but also the impact they have on their neighbourhood and on the overall relational structure. Aiming to enhance the perception of structural changes at both the micro and the macro level, we introduce the change centrality metric. This novel metric, as well as a set of further metrics we derive from it, enable the pairwise comparison of subsequent states of an evolving network in a discrete-time domain. Demonstrating their exploitation to enrich visualizations, we show how these change metrics support the visual analysis of network dynamics.

Visual Knowledge Networks Analytics

F. Windhager, M. Smuc, L. Zenk, P. Federico, J. Pfeffer, W. Aigner, S. Miksch
Book Chapter Knowledge Management Handbook Collaboration and Social Networking, CRC Press, 2012, 187-206


(not available)

ViENA: Visual Enterprise Network Analytics

P. Federico, W. Aigner, S. Miksch, J. Pfeffer, M. Smuc, F. Windhager, L. Zenk
Poster EuroVis Workshop on Visual Analytics (EuroVA 2012)


(not available)

Vertigo zoom: combining relational and temporal perspectives on dynamic networks

P. Federico, W. Aigner, S. Miksch, F. Windhager, M. Smuc
Conference Paper International Working Conference on Advanced Visual Interfaces (AVI 2012)


A well-designed visualization of dynamic networks has to support the analysis of both temporal and relational fea- tures at once. In particular to solve complex synoptic tasks, the users need to understand the topological structure of the network, its evolution over time, and possible interde- pendencies. In this paper, we introduce the application of the vertigo zoom interaction technique, derived from film- making, to information visualizations. When applied to a two-and-a-half-dimensional view, this interaction technique enables smooth transitions between the relational perspec- tive (node-link diagrams and scatter plots) and the time per- spective (trajectories and line charts), supporting a seamless visual analysis and preserving the user´s mental map.

Visual Enterprise Network Analytics - Visualizing Organizational Change

F. Windhager, L. Zenk, P. Federico
Journal Paper Procedia - Social and Behavioral Sciences, 22 (2011), 59 - 68


Despite its well-known potential for applied use in organizations, social network analysis seems to fail relevant business analytical requirements in the areas of organizational change and software usability for non-expert users like managers and consultants. This position paper takes on this challenge by outlining a strategy of user-driven software development which aims to shift analytical procedures from the numerical to the visual realm. As network dynamics can be visualized using various methods, a comparative analysis of their respective strengths and weaknesses lays the basis for the suggested integration of additional visual methods into network exploration and interpretation procedures.

A visual analytics approach to dynamic social networks

P. Federico, W. Aigner, S. Miksch, F. Windhager, L. Zenk
Conference Paper International Conference on Knowledge Management and Knowledge Technologies (i-KNOW 2011)


The visualization and analysis of dynamic networks have become increasingly important in several fields, for instance sociology or economics. The dynamic and multi-relational nature of this data poses the challenge of understanding both its topological structure and how it changes over time. In this paper we propose a visual analytics approach for analyzing dynamic networks that integrates: a dynamic layout with user-controlled trade-off between stability and consistency; three temporal views based on different combinations of node-link diagrams (layer superimposition, layer juxtaposition, and two-and-a-half dimensional view); the visualization of social network analysis metrics; and specific interaction techniques for tracking node trajectories and node connectivity over time. This integration of visual, interactive, and automatic methods supports the multifaceted analysis of dynamically changing networks.

Visual analytics of dynamic networks - a case study

P. Federico, W. Aigner, S. Miksch, F. Windhager, L. Zenk
Workshop PaperUKVAC Workshop on Visual Analytics (VAW 2011)


The investigation of biography data as consistently time-oriented information connecting multiple data dimensions can be supported by multiple visualization perspectives. Biographical and prosopographical database projects contain temporally structured datasets connecting events, places, people, institutions with a variety of relations between them. We discuss challenges emerging from scholarly reasoning with these complex aggregated data, and present a visualization concept as a basis for future investigations. Specific attention is dedicated to the discussion of visual synergies to combine information and insights from multiple views and perspectives into a more coherent visual analytics environment, supporting the creation of integrated and shared mental models of data from our collective past.

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