@article{wu-2020-tvcg, title = "Multi-level Area Balancing of Clustered Graphs", author = "Hsiang-Yun Wu and Martin N\"{o}llenburg and Ivan Viola", year = "2020", abstract = "We present a multi-level area balancing technique for laying out clustered graphs to facilitate a comprehensive understanding of the complex relationships that exist in various fields, such as life sciences and sociology. Clustered graphs are often used to model relationships that are accompanied by attribute-based grouping information. Such information is essential for robust data analysis, such as for the study of biological taxonomies or educational backgrounds. Hence, the ability to smartly arrange textual labels and packing graphs within a certain screen space is therefore desired to successfully convey the attribute data . Here we propose to hierarchically partition the input screen space using Voronoi tessellations in multiple levels of detail. In our method, the position of textual labels is guided by the blending of constrained forces and the forces derived from centroidal Voronoi cells. The proposed algorithm considers three main factors: (1) area balancing, (2) schematized space partitioning, and (3) hairball management. We primarily focus on area balancing, which aims to allocate a uniform area for each textual label in the diagram. We achieve this by first untangling a general graph to a clustered graph through textual label duplication, and then coupling with spanning-tree-like visual integration. We illustrate the feasibility of our approach with examples and then evaluate our method by comparing it with well-known conventional approaches and collecting feedback from domain experts.", month = nov, doi = "https://doi.org/10.1109/TVCG.2020.3038154", journal = "IEEE Transactions on Visualization and Computer Graphics (TVCG)", volume = "x", pages = "1--15", keywords = "Graph drawing, Voronoi tessellation, multi-level, spatially-efficient layout", URL = "https://www.cg.tuwien.ac.at/research/publications/2020/wu-2020-tvcg/", } @article{cmolik-2020-tvcg, title = "Mixed Labeling: Integrating Internal and External Labels", author = "Ladislav \v{C}mol\'{i}k and V\'{a}clav Pavlovec and Hsiang-Yun Wu and Martin N\"{o}llenburg", year = "2020", abstract = "In this paper, we present an algorithm capable of mixed labeling of 2D and 3D objects. In mixed labeling, the given objects are labeled with both internal labels placed (at least partially) over the objects and external labels placed in the space around the objects and connected with the labeled objects with straight-line leaders. The proposed algorithm determines the position and type of each label based on the user-specified ambiguity threshold and eliminates overlaps between the labels, as well as between the internal labels and the straight-line leaders of external labels. The algorithm is a screen-space technique; it operates in an image where the 2D objects or projected 3D objects are encoded. In other words, we can use the algorithm whenever we can render the objects to an image, which makes the algorithm fit for use in many domains. The algorithm operates in real-time, giving the results immediately. Finally, we present results from an expert evaluation, in which a professional illustrator has evaluated the label layouts produced with the proposed algorithm.", month = sep, doi = "10.1109/TVCG.2020.3027368", journal = "IEEE Transactions on Visualization and Computer Graphics (TVCG)", volume = "x", pages = "1--14", URL = "https://www.cg.tuwien.ac.at/research/publications/2020/cmolik-2020-tvcg/", } @inproceedings{Purchase-2020-gd, title = "The Turing Test for Graph Drawing Algorithms", author = "Helen C. Purchase and Daniel Archambault and Stephen Kobourov and Martin N\"{o}llenburg and Sergey Pupyrev and Hsiang-Yun Wu", year = "2020", abstract = "DoalgorithmsfordrawinggraphspasstheTuringTest?That is, are their outputs indistinguishable from graphs drawn by humans? We address this question through a human-centred experiment, focusing on ‘small’ graphs, of a size for which it would be reasonable for someone to choose to draw the graph manually. Overall, we find that hand-drawn layouts can be distinguished from those generated by graph drawing al- gorithms, although this is not always the case for graphs drawn by force- directed or multi-dimensional scaling algorithms, making these good can- didates for Turing Test success. We show that, in general, hand-drawn graphs are judged to be of higher quality than automatically generated ones, although this result varies with graph size and algorithm.", month = sep, event = "28th International Symposium on Graph Drawing and Network Visualization ", booktitle = "Proceedings of the 28th International Symposium on Graph Drawing and Network Visualization (GD2020)", pages = "1--16", URL = "https://www.cg.tuwien.ac.at/research/publications/2020/Purchase-2020-gd/", } @WorkshopTalk{wu-2019-visworkshop, title = "Graph Models for Biological Pathway Visualization: State of the Art and Future Challenges", author = "Hsiang-Yun Wu and Martin N\"{o}llenburg and Ivan Viola", year = "2019", abstract = "The concept of multilayer networks has become recently integrated into complex systems modeling since it encapsulates a very general concept of complex relationships. Biological pathways are an exam- ple of complex real-world networks, where vertices represent biolog- ical entities, and edges indicate the underlying connectivity. For this reason, using multilayer networks to model biological knowledge allows us to formally cover essential properties and theories in the field, which also raises challenges in visualization. This is because, in the early days of pathway visualization research, only restricted types of graphs, such as simple graphs, clustered graphs, and others were adopted. In this paper, we revisit a heterogeneous definition of biological networks and aim to provide an overview to see the gaps between data modeling and visual representation. The contribution will, therefore, lie in providing guidelines and challenges of using multilayer networks as a unified data structure for the biological pathway visualization. ", month = oct, event = "Vis 2019 Workshop", location = "Canada", keywords = "Graph drawing, multilayer network, biological pathway", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-visworkshop/", } @bachelorsthesis{rinortner_susanne-2019-vpicc, title = "Visualizing Protein Interactions in Corresponding Compartments", author = "Susanne Rinortner", year = "2019", abstract = "The visualization of networks for protein interactions is an important step to understand them. There are already many approaches for this task, but most of them do not show any information about the compartment of the cell the proteins belong to. Since the placement of proteins inside a cell is important information, because it helps to understand their interactions, this thesis proposes a method to visualize protein inside cell compartments. The objective of this project is a clear and understandable visualization of interactions between proteins and where these interactions or reactions happen inside the cell. This project uses a three-dimensional model of a cell as a base and intersects it using cutting planes. Then the intersection surface is sampled and reconstructed using Delaunay triangulation. To the mesh created by the triangulation, a force-directed algorithm is applied. This algorithm is used to scale single-cell parts in order to fit all proteins inside. This ensures that none of the cell parts get overfilled. The result is a new method that makes it possible to visualize not only protein-protein interactions but also in which compartment of the cell the proteins are located.", month = oct, address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", school = "Research Unit of Computer Graphics, Institute of Visual Computing and Human-Centered Technology, Faculty of Informatics, TU Wien ", keywords = "Biological pathways", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/rinortner_susanne-2019-vpicc/", } @inproceedings{Sbardellati-2019-vcbm, title = "Interactive Exploded Views for Molecular Structures", author = "Maximilian Sbardellati and Haichao Miao and Hsiang-Yun Wu and Eduard Gr\"{o}ller and Ivan Barisic and Ivan Viola", year = "2019", abstract = "We propose an approach to interactively create exploded views of molecular structures with the goal to help domain experts in their design process and provide them with a meaningful visual representation of component relationships. Exploded views are excellently suited to manage visual occlusion of structure components, which is one of the main challenges when visualizing complex 3D data. In this paper, we discuss four key parameters of an exploded view: explosion distance, direction, order, and the selection of explosion components. We propose two strategies, namely the structure-derived exploded view and the interactive free-form exploded view, for computing these four parameters systematically. The first strategy allows scientists to automatically create exploded views by computing the parameters from the given object structures. The second strategy further supports them to design and customize detailed explosion paths through user interaction. Our approach features the possibility to animate exploded views, to incorporate ease functions into these animations and to display the explosion path of components via arrows. Finally, we demonstrate three use cases with various challenges that we investigated in collaboration with a domain scientist. Our approach, therefore, provides interesting new ways of investigating and presenting the design layout and composition of complex molecular structures.", month = sep, event = "VCBM 2019", booktitle = "Proceedings of the 9th Eurographics Workshop on Visual Computing for Biology and Medicine", pages = "103--112", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/Sbardellati-2019-vcbm/", } @unknown{wu-2019-vcbm, title = "Map of Metabolic Harmony", author = "Hsiang-Yun Wu and Martin N\"{o}llenburg and Ivan Viola", year = "2019", abstract = "As the human body is healthy when the metabolic harmony is maintained, the human metabolic pathways are interpretable when its visual representation is harmonized. We developed an automatic approach to hierarchically decompose the screen space to multiple functional regions and embed sub-pathways into their corresponding regions to unveil complex metabolite relationships.", month = sep, URL = "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-vcbm/", } @article{mizuno-2019-eurovis, title = "Optimizing Stepwise Animation in Dynamic Set Diagrams", author = "Kazuyo Mizuno and Hsiang-Yun Wu and Shigeo Takahashi and Takeo Igarashi", year = "2019", abstract = "A set diagram represents the membership relation among data elements. It is often visualized as secondary information on top of primary information, such as the spatial positions of elements on maps and charts. Visualizing the temporal evolution of such set diagrams as well as their primary features is quite important; however, conventional approaches have only focused on the temporal behavior of the primary features and do not provide an effective means to highlight notable transitions within the set relationships. This paper presents an approach for generating a stepwise animation between set diagrams by decomposing the entire transition into atomic changes associated with individual data elements. The key idea behind our approach is to optimize the ordering of the atomic changes such that the synthesized animation minimizes unwanted set occlusions by considering their depth ordering and reduces the gaze shift between two consecutive stepwise changes. Experimental results and a user study demonstrate that the proposed approach effectively facilitates the visual identification of the detailed transitions inherent in dynamic set diagrams.", month = jul, journal = "Computer Graphics Forum", volume = "38", note = "Best Paper Honorable Mention at EuroVis 2019", doi = "https://doi.org/10.1111/cgf.13668", pages = "13--24", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/mizuno-2019-eurovis/", } @article{wu-2019-bmc, title = "Metabopolis: Scalable Network Layout for Biological Pathway Diagrams in Urban Map Style", author = "Hsiang-Yun Wu and Martin N\"{o}llenburg and Filipa L. Sousa and Ivan Viola", year = "2019", abstract = "Background Biological pathways represent chains of molecular interactions in biological systems that jointly form complex dynamic networks. The network structure changes from the significance of biological experiments and layout algorithms often sacrifice low-level details to maintain high-level information, which complicates the entire image to large biochemical systems such as human metabolic pathways. Results Our work is inspired by concepts from urban planning since we create a visual hierarchy of biological pathways, which is analogous to city blocks and grid-like road networks in an urban area. We automatize the manual drawing process of biologists by first partitioning the map domain into multiple sub-blocks, and then building the corresponding pathways by routing edges schematically, to maintain the global and local context simultaneously. Our system incorporates constrained floor-planning and network-flow algorithms to optimize the layout of sub-blocks and to distribute the edge density along the map domain. We have developed the approach in close collaboration with domain experts and present their feedback on the pathway diagrams based on selected use cases. Conclusions We present a new approach for computing biological pathway maps that untangles visual clutter by decomposing large networks into semantic sub-networks and bundling long edges to create space for presenting relationships systematically.", month = may, doi = "http://doi.org/10.1186/s12859-019-2779-4", journal = "BMC Bioinformatics", number = "187", volume = "20", pages = "1--20", keywords = "Biological pathways, Graph drawing, Mapmetaphor, Orthogonallayout, Floorplanning, Edgerouting", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-bmc/", } @WorkshopTalk{wu-2019-smw, title = " A Survey on Computing Schematic Network Maps: The Challenge to Interactivity", author = "Hsiang-Yun Wu and Benjamin Niedermann and Shigeo Takahashi and Martin N\"{o}llenburg", year = "2019", abstract = "Schematic maps are in daily use to show the connec- tivity of subway systems and to facilitate travellers to plan their journeys effectively. This study surveys up-to-date algorithmic approaches in order to give an overview of the state of the art in schematic network mapping. The study investigates the hypothesis that the choice of algorithmic approach is often guided by the requirements of the mapping application. For example, an algorithm that computes globally optimal solutions for schematic maps is capable of producing results for printing, while it is not suitable for computing instant layouts due to its long running time. Our analysis and discussion, therefore, focus on the compu- tational complexity of the problem formulation and the running times of the schematic map algorithms, including algorithmic network layout techniques and station labeling techniques. The correlation between problem complexity and running time is then visually depicted using scatter plot diagrams. Moreover, since metro maps are common metaphors for data visualization, we also investigate online tools and application domains using metro map representations for analytics purposes, and finally summarize the potential future opportunities for schematic maps.", month = apr, doi = "https://www.ac.tuwien.ac.at/files/pub/smw19-position-5.pdf", event = "The 2nd Schematic Mapping Workshop 2019", location = "Vienna, Austria", keywords = "Metro Maps, Graph Drawing, Metaphors", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-smw/", } @techreport{wu-2019-report, title = "From Cells to Atoms - Biological Information Visualization (in Chinese)", author = "Hsiang-Yun Wu and Haichao Miao and Ivan Viola", year = "2019", month = mar, number = "TR-193-02-2019-1", address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", institution = "Research Unit of Computer Graphics, Institute of Visual Computing and Human-Centered Technology, Faculty of Informatics, TU Wien ", note = "human contact: technical-report@cg.tuwien.ac.at", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-report/", } @article{YOGHOURDJIAN2019, title = "Exploring the limits of complexity: A survey of empirical studies ongraph visualisation", author = "Vahan Yoghourdjian and Daniel Archambault and Stephan Diehl and Tim Dwyer and Karsten Klein and Helen C. Purchase and Hsiang-Yun Wu", year = "2019", abstract = "For decades, researchers in information visualisation and graph drawing have focused on developing techniques for the layout and display of very large and complex networks. Experiments involving human participants have also explored the readability of different styles of layout and representations for such networks. In both bodies of literature, networks are frequently referred to as being ‘large’ or ‘complex’, yet these terms are relative. From a human-centred, experiment point-of-view, what constitutes ‘large’ (for example) depends on several factors, such as data complexity, visual complexity, and the technology used. In this paper, we survey the literature on human-centred experiments to understand how, in practice, different features and characteristics of node–link diagrams affect visual complexity.", month = jan, doi = "https://doi.org/10.1016/j.visinf.2018.12.006", issn = "2468-502X", journal = "Visual Informatics", number = "4", volume = "2", pages = "264--282", keywords = "Graph visualisation, Network visualisation, node–link diagrams, Evaluations, Empirical studies, Cognitive scalability", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/YOGHOURDJIAN2019/", } @article{kouril-2018-LoL, title = "Labels on Levels: Labeling of Multi-Scale Multi-Instance and Crowded 3D Biological Environments", author = "David Kou\v{r}il and Ladislav \v{C}mol\'{i}k and Barbora Kozlikova and Hsiang-Yun Wu and Graham Johnson and David Goodsell and Arthur Olson and Eduard Gr\"{o}ller and Ivan Viola", year = "2019", abstract = "Labeling is intrinsically important for exploring and understanding complex environments and models in a variety of domains. We present a method for interactive labeling of crowded 3D scenes containing very many instances of objects spanning multiple scales in size. In contrast to previous labeling methods, we target cases where many instances of dozens of types are present and where the hierarchical structure of the objects in the scene presents an opportunity to choose the most suitable level for each placed label. Our solution builds on and goes beyond labeling techniques in medical 3D visualization, cartography, and biological illustrations from books and prints. In contrast to these techniques, the main characteristics of our new technique are: 1) a novel way of labeling objects as part of a bigger structure when appropriate, 2) visual clutter reduction by labeling only representative instances for each type of an object, and a strategy of selecting those. The appropriate level of label is chosen by analyzing the scene's depth buffer and the scene objects' hierarchy tree. We address the topic of communicating the parent-children relationship between labels by employing visual hierarchy concepts adapted from graphic design. Selecting representative instances considers several criteria tailored to the character of the data and is combined with a greedy optimization approach. We demonstrate the usage of our method with models from mesoscale biology where these two characteristics-multi-scale and multi-instance-are abundant, along with the fact that these scenes are extraordinarily dense.", month = jan, journal = "IEEE Transactions on Visualization and Computer Graphics", volume = "25", note = "SciVis Best Paper Honorable Mention", doi = "10.1109/TVCG.2018.2864491", pages = "977--986", keywords = "labeling, multi-scale data, multi-instance data", URL = "https://www.cg.tuwien.ac.at/research/publications/2019/kouril-2018-LoL/", } @techreport{wu-2018-shonan, title = "Lost in Translation: Alignment of Mental Representations for Visual Analytics, Reimagining the Mental Map and Drawing Stability (NII Shonan Meeting Seminar 127)", author = "Daniel Archambault and Jessie Kennedy and Tatiana von Landesberger and Mark McCann and Fintan McGee and Benjamin Renoust and Hsiang-Yun Wu", year = "2018", month = dec, number = "TR-193-02-2018-1", address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", institution = "Institute of Computer Graphics and Algorithms, Vienna University of Technology ", note = "human contact: technical-report@cg.tuwien.ac.at", URL = "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-shonan/", } @misc{wu-2018-metabo, title = "A Visual Comparison of Hand-Drawn and Machine-Generated Human Metabolic Pathways", author = "Hsiang-Yun Wu and Martin N\"{o}llenburg and Ivan Viola", year = "2018", abstract = "This poster abstract presents a visual comparison between three hand-drawn and one machine-generated human metabolic pathway diagrams. The human metabolic pathways, which describe significant biochemical reactions in the human body, have been increasingly investigated due to the development of analysis processes and are compiled into pathway diagrams to provide an overview of reaction in the human body. This complex network includes about 5,000 metabolites and 7,500 reactions, which are hierarchically nested and difficult to visualize. We collect and analyze well-known human metabolic pathway diagrams, and summarize the design choices of these diagrams, respectively. Together with a machine-generated diagram, we can understand the visual complexity of three hand-drawn and one machine-generated diagrams. ", month = jun, event = "EuroVis", Conference date = "Poster presented at EuroVis (2018-06-04--2018-06-08)", URL = "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-metabo/", } @misc{wu-2018-story, title = "The Travel of a Metabolite", author = "Hsiang-Yun Wu and Martin N\"{o}llenburg and Ivan Viola", year = "2018", abstract = "Biological pathways are chains of molecule interactions and reactions in biological systems that jointly form complex, hierarchical networks. Although several pathway layout algorithms have been investigated, biologists still prefer to use hand-drawn ones, due to their high visual quality relied on domain knowledge. In this project, we propose a visualization for computing metabolic pathway maps that restrict the grouping structure defined by biologists to rectangles and apply orthogonal-style edge routing to simplify edge orientation. This idea is inspired by concepts from urban planning, where we consider reactions as city blocks and built up roads to connect identical metabolites occurred in multiple categories. We provide a story to present how glucose is broken down to phosphoenolpyruvate to release energy, which is often stored in adenosine triphosphate (ATP) in a human body. Finally, we demonstrate ATP is also utilized to synthesize urea to eliminate the toxic ammonia in our body.", month = apr, note = "submitted to PacificVis 2018 Data Story Telling Contest", URL = "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-story/", } @article{wu-2018-JVLC, title = "Overlap-Free Labeling of Clustered Networks Based on Voronoi Tessellation", author = "Hsiang-Yun Wu and Shigeo Takahashi and Rie Ishida", year = "2018", month = feb, journal = "Journal of Visual Languages & Computing", number = "44", URL = "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2018-JVLC/", } @techreport{wu-2017-dagstuhl, title = "Mapifying the Genome, Scalable Set Visualizations (Dagstuhl Seminar 17332)", author = "Radu Jianu and Martin Krzywinski and Luana Micallef and Hsiang-Yun Wu", year = "2018", number = "TR-193-02-2018-2", address = "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria", institution = "Institute of Computer Graphics and Algorithms, Vienna University of Technology ", note = "human contact: technical-report@cg.tuwien.ac.at", URL = "https://www.cg.tuwien.ac.at/research/publications/2018/wu-2017-dagstuhl/", }