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Journal articles on the topic 'Interactive graph visualization'
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Mikheenko, Alla, and Mikhail Kolmogorov. "Assembly Graph Browser: interactive visualization of assembly graphs." Bioinformatics 35, no. 18 (February 4, 2019): 3476–78. http://dx.doi.org/10.1093/bioinformatics/btz072.
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Abstract Summary Currently, most genome assembly projects focus on contigs and scaffolds rather than assembly graphs that provide a more comprehensive representation of an assembly. Since interactive visualization of large assembly graphs remains an open problem, we developed an Assembly Graph Browser (AGB) tool that visualizes large assembly graphs, extending the functionality of previously developed visualization approaches. Assembly Graph Browser includes a number of novel functions including repeat analysis, construction of the contracted assembly graphs (i.e. the graphs obtained by collapsing a selected set of edges) and a new approach to visualizing large assembly graphs. Availability and implementation http://www.github.com/almiheenko/AGB. Supplementary information Supplementary data are available at Bioinformatics online.
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Tominski, Christian, James Abello, and Heidrun Schumann. "CGV—An interactive graph visualization system." Computers & Graphics 33, no. 6 (December 2009): 660–78. http://dx.doi.org/10.1016/j.cag.2009.06.002.
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Kelley, Sean, Edward Aftandilian, Connor Gramazio, Nathan Ricci, Sara L. Su, and Samuel Z. Guyer. "Heapviz: Interactive heap visualization for program understanding and debugging." Information Visualization 12, no. 2 (May 7, 2012): 163–77. http://dx.doi.org/10.1177/1473871612438786.
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Understanding the data structures in a program is crucial to understanding how the program works, or why it does not work. Inspecting the code that implements the data structures, however, is an arduous task and often fails to yield insights into the global organization of a program’s data. Inspecting the actual contents of the heap solves these problems but presents a significant challenge of its own: finding an effective way to present the enormous number of objects it contains. In this paper we present Heapviz, a tool for visualizing and exploring snapshots of the heap obtained from a running Java program. Unlike existing tools, such as traditional debuggers, Heapviz presents a global view of the program state as a graph, together with powerful interactive capabilities for navigating it. Our tool employs several key techniques that help manage the scale of the data. First, we reduce the size and complexity of the graph by using algorithms inspired by static shape analysis to aggregate the nodes that make up a data structure. Second, we implement a powerful visualization component whose interactive interface provides extensive support for exploring the graph. The user can search for objects based on type, connectivity, and field values; group objects; and color or hide and show each group. The user may also inspect individual objects to see their field values and neighbors in the graph. These interactive abilities help the user manage the complexity of these huge graphs. By applying Heapviz to both constructed and real-world examples, we show that it provides programmers with a powerful and intuitive tool for exploring program behavior.
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Dogrusoz, U., and B. Genc. "A multi-graph approach to complexity management in interactive graph visualization." Computers & Graphics 30, no. 1 (February 2006): 86–97. http://dx.doi.org/10.1016/j.cag.2005.10.015.
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Sheng-Jie Luo, Chun-Liang Liu, Bing-Yu Chen, and Kwan-Liu Ma. "Ambiguity-Free Edge-Bundling for Interactive Graph Visualization." IEEE Transactions on Visualization and Computer Graphics 18, no. 5 (May 2012): 810–21. http://dx.doi.org/10.1109/tvcg.2011.104.
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Li, Nan, Dominique Brossard, Dietram A. Scheufele, Paul H. Wilson, and Kathleen M. Rose. "Communicating data: interactive infographics, scientific data and credibility." Journal of Science Communication 17, no. 02 (June 18, 2018): A06. http://dx.doi.org/10.22323/2.17020206.
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Information visualization could be used to leverage the credibility of displayed scientific data. However, little was known about how display characteristics interact with individuals' predispositions to affect perception of data credibility. Using an experiment with 517 participants, we tested perceptions of data credibility by manipulating data visualizations related to the issue of nuclear fuel cycle based on three characteristics: graph format, graph interactivity, and source attribution. Results showed that viewers tend to rely on preexisting levels of trust and peripheral cues, such as source attribution, to judge the credibility of shown data, whereas their comprehension level did not relate to perception of data credibility. We discussed the implications for science communicators and design professionals.
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Jonker, David, Scott Langevin, David Giesbrecht, Michael Crouch, and Nathan Kronenfeld. "Graph mapping: Multi-scale community visualization of massive graph data." Information Visualization 16, no. 3 (August 11, 2016): 190–204. http://dx.doi.org/10.1177/1473871616661195.
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Graph visualizations increase the perception of entity relationships in a network. However, as graph size and density increases, readability rapidly diminishes. In this article, we present an end-to-end, tile-based visual analytic approach called graph mapping that utilizes cluster computing to turn large-scale graph (node–link) data into interactive visualizations in modern web browsers. Our approach is designed for end-user analysis of community structure and relationships at macro- and micro scales. We also present the results of several experiments using alternate methods for qualitatively improving comprehensibility of hierarchical community detection visualizations by proposing constraints to state-of-the-art modularity maximization algorithms.
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Cruz, António, Joel P. Arrais, and Penousal Machado. "Interactive and coordinated visualization approaches for biological data analysis." Briefings in Bioinformatics 20, no. 4 (March 26, 2018): 1513–23. http://dx.doi.org/10.1093/bib/bby019.
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AbstractThe field of computational biology has become largely dependent on data visualization tools to analyze the increasing quantities of data gathered through the use of new and growing technologies. Aside from the volume, which often results in large amounts of noise and complex relationships with no clear structure, the visualization of biological data sets is hindered by their heterogeneity, as data are obtained from different sources and contain a wide variety of attributes, including spatial and temporal information. This requires visualization approaches that are able to not only represent various data structures simultaneously but also provide exploratory methods that allow the identification of meaningful relationships that would not be perceptible through data analysis algorithms alone. In this article, we present a survey of visualization approaches applied to the analysis of biological data. We focus on graph-based visualizations and tools that use coordinated multiple views to represent high-dimensional multivariate data, in particular time series gene expression, protein–protein interaction networks and biological pathways. We then discuss how these methods can be used to help solve the current challenges surrounding the visualization of complex biological data sets.
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Cox, Steven, Stanley C. Ahalt, James Balhoff, Chris Bizon, Karamarie Fecho, Yaphet Kebede, Kenneth Morton, Alexander Tropsha, Patrick Wang, and Hao Xu. "Visualization Environment for Federated Knowledge Graphs: Development of an Interactive Biomedical Query Language and Web Application Interface." JMIR Medical Informatics 8, no. 11 (November 23, 2020): e17964. http://dx.doi.org/10.2196/17964.
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Background Efforts are underway to semantically integrate large biomedical knowledge graphs using common upper-level ontologies to federate graph-oriented application programming interfaces (APIs) to the data. However, federation poses several challenges, including query routing to appropriate knowledge sources, generation and evaluation of answer subsets, semantic merger of those answer subsets, and visualization and exploration of results. Objective We aimed to develop an interactive environment for query, visualization, and deep exploration of federated knowledge graphs. Methods We developed a biomedical query language and web application interphase—termed as Translator Query Language (TranQL)—to query semantically federated knowledge graphs and explore query results. TranQL uses the Biolink data model as an upper-level biomedical ontology and an API standard that has been adopted by the Biomedical Data Translator Consortium to specify a protocol for expressing a query as a graph of Biolink data elements compiled from statements in the TranQL query language. Queries are mapped to federated knowledge sources, and answers are merged into a knowledge graph, with mappings between the knowledge graph and specific elements of the query. The TranQL interactive web application includes a user interface to support user exploration of the federated knowledge graph. Results We developed 2 real-world use cases to validate TranQL and address biomedical questions of relevance to translational science. The use cases posed questions that traversed 2 federated Translator API endpoints: Integrated Clinical and Environmental Exposures Service (ICEES) and Reasoning Over Biomedical Objects linked in Knowledge Oriented Pathways (ROBOKOP). ICEES provides open access to observational clinical and environmental data, and ROBOKOP provides access to linked biomedical entities, such as “gene,” “chemical substance,” and “disease,” that are derived largely from curated public data sources. We successfully posed queries to TranQL that traversed these endpoints and retrieved answers that we visualized and evaluated. Conclusions TranQL can be used to ask questions of relevance to translational science, rapidly obtain answers that require assertions from a federation of knowledge sources, and provide valuable insights for translational research and clinical practice.
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Farooq, Humera, Nordin Zakaria, and Muhammad Tariq Siddique. "An Interactive Visualization of Genetic Algorithm on 2-D Graph." International Journal of Software Science and Computational Intelligence 4, no. 1 (January 2012): 34–54. http://dx.doi.org/10.4018/jssci.2012010102.
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The visualization of search space makes it easy to understand the behavior of the Genetic Algorithm (GA). The authors propose a novel way for representation of multidimensional search space of the GA using 2-D graph. This is carried out based on the gene values of the current generation, and human intervention is only required after several generations. The main contribution of this research is to propose an approach to visualize the GA search data and improve the searching process of the GA with human’s intention in different generations. Besides the selection of best individual or parents for the next generation, interference of human is required to propose a new individual in the search space. Active human intervention leads to a faster searching, resulting in less user fatigue. The experiments were carried out by evolving the parameters to derive the rules for a Parametric L-System. These rules are then used to model the growth process of branching structures in 3-D space. The experiments were conducted to evaluate the ability of the proposed approach to converge to optimized solution as compared to the Simple Genetic Algorithm (SGA).
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Viola, Fabio, Luca Roffia, Francesco Antoniazzi, Alfredo D’Elia, Cristiano Aguzzi, and Tullio Salmon Cinotti. "Interactive 3D Exploration of RDF Graphs through Semantic Planes." Future Internet 10, no. 8 (August 17, 2018): 81. http://dx.doi.org/10.3390/fi10080081.
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This article presents Tarsier, a tool for the interactive 3D visualization of RDF graphs. Tarsier is mainly intended to support teachers introducing students to Semantic Web data representation formalisms and developers in the debugging of applications based on Semantic Web knowledge bases. The tool proposes the metaphor of semantic planes as a way to visualize an RDF graph. A semantic plane contains all the RDF terms sharing a common concept; it can be created, and further split into several planes, through a set of UI controls or through SPARQL 1.1 queries, with the full support of OWL and RDFS. Thanks to the 3D visualization, links between semantic planes can be highlighted and the user can navigate within the 3D scene to find the better perspective to analyze data. Data can be gathered from generic SPARQL 1.1 protocol services. We believe that Tarsier will enhance the human friendliness of semantic technologies by: (1) helping newcomers assimilate new data representation formats; and (2) increasing the capabilities of inspection to detect relevant situations even in complex RDF graphs.
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Nguyen, Quang Vinh, and Mao Lin Huang. "EncCon: An Approach to Constructing Interactive Visualization of Large Hierarchical Data." Information Visualization 4, no. 1 (March 2005): 1–21. http://dx.doi.org/10.1057/palgrave.ivs.9500087.
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This paper describes a new technique called EncCon for visualizing and navigating large hierarchical information. This technique consists of two components: visualization and navigation. Visualization uses a fast enclosure + connection method to calculate the geometrical layout for the display of large hierarchies in a two-dimensional space. Our technique uses a rectangular division algorithm for recursively positioning the graph. This visualization aims to maximize the utilization of display space while retaining a good geometrical layout as well as a clear (explicit) presentation of the hierarchical structure of graphs. This paper also presents an experimental evaluation of EncCon's layout algorithm. Besides the layout algorithm, EncCon uses a new focus + context viewing technique for the navigation of large hierarchies. We use the zooming + layering concept to achieve the focus + context viewing, rather than the traditional enlarge + embedded concept, which is used by most of the available focus + context techniques. Technically, it employs semi-transparency to achieve the display of two layers of information in z-coordination at the same visualization. Both context view and detail view are drawn at two separate layers. These layers are then displayed in an overlapped manner at the same physical screen space.
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Vlachos, Michail, and Daniel Svonava. "Recommendation and visualization of similar movies using minimum spanning dendrograms." Information Visualization 12, no. 1 (April 30, 2012): 85–101. http://dx.doi.org/10.1177/1473871612439644.
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Exploration of graph structures is an important topic in data mining and data visualization. This work presents a novel technique for visualizing neighbourhood and cluster relationships in graphs; we also show how this methodology can be used within the setting of a recommendation system. Our technique works by projecting the original object distances onto two dimensions while carefully retaining the ‘backbone’ of important distances. Cluster information is also overlayed on the same projected space. A significant advantage of our approach is that it can accommodate both metric and non-metric distance functions. Our methodology is applied to a visual recommender system for movies to allow easy exploration of the actor–movie bipartite graph. The work offers intuitive movie recommendations based on a selected pivot movie and allows the interactive discovery of related movies based on both textual and semantic features.
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Murugesan, Sugeerth, Kristofer Bouchard, Jesse Brown, Mariam Kiran, Dan Lurie, Bernd Hamann, and Gunther H. Weber. "State-based network similarity visualization." Information Visualization 19, no. 2 (November 4, 2019): 96–113. http://dx.doi.org/10.1177/1473871619882019.
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We introduce an approach for the interactive visual analysis of weighted, dynamic networks. These networks arise in areas such as computational neuroscience, sociology, and biology. Network analysis remains challenging due to complex time-varying network behavior. For example, edges disappear/reappear, communities grow/vanish, or overall network topology changes. Our technique, TimeSum, detects the important topological changes in graph data to abstract the dynamic network and visualize one summary representation for each temporal phase, a state. We define a network state as a graph with similar topology over a specific time interval. To enable a holistic comparison of networks, we use a difference network to depict edge and community changes. We present case studies to demonstrate that our methods are effective and useful for extracting and exploring complex dynamic behavior of networks.
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North, Chris, Purvi Saraiya, and Karen Duca. "A comparison of benchmark task and insight evaluation methods for information visualization." Information Visualization 10, no. 3 (July 2011): 162–81. http://dx.doi.org/10.1177/1473871611415989.
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This study compares two different empirical research methods for evaluating information visualizations: the traditional benchmark-task method and the insight method. The methods are compared using criteria such as the conclusions about the visualization designs provided by each method, the time participants spent during the study, the time and effort required to analyse the resulting empirical data, and the effect of individual differences between participants on the results. The study compares three graph visualization alternatives that associate bioinformatics microarray time series data to pathway graph vertices in order to investigate the effect of different visual grouping structures in visualization designs that integrate multiple data types. It is confirmed that visual grouping should match task structure, but interactive grouping proves to be a well-rounded alternative. Overall, the results validate the insight method’s ability to confirm results of the task method, but also show advantages of the insight method to illuminate additional types of tasks. Efficiency and insight frequently correlate, but important distinctions are found. Categories: H.5.2 [Information Interfaces and Presentation]: User Interfaces – evaluation/methodology.
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Elmqvist, Niklas, and Philippas Tsigas. "CiteWiz: A Tool for the Visualization of Scientific Citation Networks." Information Visualization 6, no. 3 (September 2007): 215–32. http://dx.doi.org/10.1057/palgrave.ivs.9500156.
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We present CiteWiz, an extensible framework for visualization of scientific citation networks. The system is based on a taxonomy of citation database usage for researchers, and provides a timeline visualization for overviews and an influence visualization for detailed views. The timeline displays the general chronology and importance of authors and articles in a citation database, whereas the influence visualization is implemented using the Growing Polygons technique, suitably modified to the context of browsing citation data. Using the latter technique, hierarchies of articles with potentially very long citation chains can be graphically represented. The visualization is augmented with mechanisms for parent–child visualization and suitable interaction techniques for interacting with the view hierarchy and the individual articles in the dataset. We also provide an interactive concept map for keywords and co-authorship using a basic force-directed graph layout scheme. A formal user study indicates that CiteWiz is significantly more efficient than traditional database interfaces for high-level analysis tasks relating to influence and overviews, and equally efficient for low-level tasks such as finding a paper and correlating bibliographical data.
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Palha, Sônia. "Students learning with interactive virtual math: an exploratory study in the classroom." Ensino e Tecnologia em Revista 1, no. 1 (September 6, 2017): 80. http://dx.doi.org/10.3895/etr.v1n1.5990.
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Interactive Virtual Math (IVM) is a visualization tool to support secondary school students’ learning of graphs by dynamic events. In the prototype version students construct a graph and try to improve it themselves and with the feedback of the tool. In a small-scale experiment, which involved four classes at secondary and tertiary education and their mathematics teachers we investigated how the students used the tool in the classroom. In this study we focus on the students learning experience and the results are expected to provide knowledge and directions for further development of the tool. The corpus data consists of self-reported questionnaires and lessons observations. One main finding is that students, at different school levels, find the tool useful to construct or improve graphical representations and it can help to get a better understanding of the subject. The tool features that helped students most were the self-construction of the graphs and to get feedback about their own graph at the end. Other findings are that the students can work independently with the tool and we know more about the tool features that are attractive or need to be improved.
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Kuosa, Kirsi, Damiano Distante, Anne Tervakari, Luigi Cerulo, Alejandro Fernández, Juho Koro, and Meri Kailanto. "Interactive Visualization Tools to Improve Learning and Teaching in Online Learning Environments." International Journal of Distance Education Technologies 14, no. 1 (January 2016): 1–21. http://dx.doi.org/10.4018/ijdet.2016010101.
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This paper presents two interactive visualization tools for learning management systems (LMS) in order to improve learning and teaching in online courses. The first tool was developed at the Intelligent Information Systems Laboratory (IISLab) at the Tampere University of Technology (TUT). The tool is used to analyse students' activity from automatically recorded user log data and to build interactive visualizations. They provide valuable insights into the learning process and participation of students in a course offered to teachers and students. The second tool was developed at the Unitelma Sapienza University. It extends navigation and search functionalities in the discussion forum of an LMS with a topic-driven paradigm. The tool analyses forum content and automatically identifies discussion topics. It then enhances the original forum with a topic-driven navigation structure and an interactive search graph. Both tools have been developed as plug-ins for the Moodle LMS, but their analysis processes and techniques can be adopted into any LMS.
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Figgemeier, Heiko, Christin Henzen, and Arne Rümmler. "A Geo-Dashboard Concept for the Interactively Linked Visualization of Provenance and Data Quality for Geospatial Datasets." AGILE: GIScience Series 2 (June 4, 2021): 1–8. http://dx.doi.org/10.5194/agile-giss-2-25-2021.
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Abstract. In Earth System Sciences, a data-driven research domain, several communities discuss the importance, guidance and implementation of making research data findable, accessible, interoperable, and reusable. To foster these principles, in particular to support reusability, users need easy-to-use user interfaces with meaningful visualizations for detailed metainformation, e.g. on dataset’s origin and quality. However, visualization tools to facilitate the evaluation of fitness for use of ESS research data on domainspecific metainformation, do hardly exist.We provide a Geo-dashboard concept for user-friendly interactive and linked visualizations of provenance and quality information using standardized geospatial metadata. A provenance graph visualization serves as overview and entry point for further evaluations. Quality information is essential to evaluate the fitness for use of data. Therefore, we developed quality visualizations on several levels of detail to foster evaluation, e.g. by enabling users to choose and classify quality parameters based on their use-case-specific needs.
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Wang, Yunhai, Yanyan Wang, Yinqi Sun, Lifeng Zhu, Kecheng Lu, Chi-Wing Fu, Michael Sedlmair, Oliver Deussen, and Baoquan Chen. "Revisiting Stress Majorization as a Unified Framework for Interactive Constrained Graph Visualization." IEEE Transactions on Visualization and Computer Graphics 24, no. 1 (January 2018): 489–99. http://dx.doi.org/10.1109/tvcg.2017.2745919.
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Lam, Ho-Ching, and Ivo D. Dinov. "Hyperbolic Wheel: A Novel Hyperbolic Space Graph Viewer for Hierarchical Information Content." ISRN Computer Graphics 2012 (October 31, 2012): 1–10. http://dx.doi.org/10.5402/2012/609234.
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Tree and graph structures have been widely used to present hierarchical and linked data. Hyperbolic trees are special types of graphs composed of nodes (points or vertices) and edges (connecting lines), which are visualized on a non-Euclidean space. In traditional Euclidean space graph visualization, distances between nodes are measured by straight lines. Displays of large graphs in Euclidean spaces may not utilize efficiently the available space and may impose limitations on the number of graph nodes. The special hyperbolic space rendering of tree-graphs enables adaptive and efficient use of the available space and facilitates the display of large hierarchical structures. In this paper we report on a newly developed advanced hyperbolic graph viewer, Hyperbolic Wheel, which enables the navigation, traversal, discovery and interactive manipulation of information stored in large hierarchical structures. Examples of such structures include personnel records, disc directory structures, ontological constructs, web-pages and other nested partitions. The Hyperbolic Wheel framework provides an intuitive and dynamic graphical interface to explore and retrieve information about individual nodes (data objects) and their relationships (data associations). The Hyperbolic Wheel is freely available online for educational and research purposes.
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Sundvall, E., K. R. Gøeg, and A. R. Højen. "Methods and applications for visualization of SNOMED CT concept sets." Applied Clinical Informatics 05, no. 01 (2014): 127–52. http://dx.doi.org/10.4338/aci-2013-09-ra-0071.
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SummaryInconsistent use of SNOMED CT concepts may reduce comparability of information in health information systems. Terminology implementation should be approached by common strategies for navigating and selecting proper concepts. This study aims to explore ways of illustrating common pathways and ancestors of particular sets of concepts, to support consistent use of SNOMED CT and also assess potential applications for such visualizations.The open source prototype presented is an interactive web-based re-implementation of the terminology visualization tool TermViz that provides an overview of concepts and their hierarchical relations. It provides terminological features such as interactively rearranging graphs, fetching more concept nodes, highlighting least common parents and shared pathways in merged graphs etc.Four teams of three to four people used the prototype to complete a terminology mapping task and then, in focus group interviews, discussed the user experience and potential future tool usage. Potential purposes discussed included SNOMED CT search and training, consistent selection of concepts and content management.The evaluation indicated that the tool may be useful in many contexts especially if integrated with existing systems, and that the graph layout needs further tuning and development.Citation: Højen AR, Sundvall E, Gøeg KR. Methods and applications for visualization of SNOMED CT concept sets. Appl Clin Inf 2014; 5: 127–152http://dx.doi.org/10.4338/ACI-2013-09-RA-0071
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Zabiniako, Vitaly, and Pavel Rusakov. "Analysis of the Usage of Magnetic Force-directed Approach and Visual Techniques for Interactive Context-based Drawing of Multi-attributed Graphs." Applied Computer Systems 16, no. 1 (December 1, 2014): 85–91. http://dx.doi.org/10.1515/acss-2014-0017.
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Abstract In this article, the authors perform an analysis in order to assess adaptation of magnetic force-directed algorithms for context-based information extraction from multi-attributed graphs during visualization sessions. Theoretic standings behind magnetic force-directed approach are stated together with review on how particular features of respective algorithms in combination with appropriate visual techniques are especially suitable for improved processing and presenting of knowledge that is captured in form of graphs. The complexity of retrieving multi-attributed information within the proposed approach is handled with dedicated tools, such as selective attraction of nodes to MFE (Magnetic Force Emitter) based on search criteria, localization of POI (Point of Interest) regions, graph node anchoring, etc. Implicit compatibility of aforementioned tools with interactive nature of data exploration is distinguished. Description of case study, based on bibliometric network analysis is given, which is followed by the review of existing related works in this field. Conclusions are made and further studies in the field of visualization of multi-attributed graphs are defined.
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Reddy, Kuldeep. "Interactive Graph Data Integration System With Spatial-Oriented Visualization and Feedback-Driven Provenance." IEEE Access 7 (2019): 101336–44. http://dx.doi.org/10.1109/access.2019.2928847.
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Toledo, Alejandro, Kingkarn Sookhanaphibarn, Ruck Thawonmas, and Frank Rinaldo. "Personalized Recommendation in Interactive Visual Analysis of Stacked Graphs." ISRN Artificial Intelligence 2012 (February 29, 2012): 1–8. http://dx.doi.org/10.5402/2012/389540.
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We present a system which combines interactive visual analysis and recommender systems to support insight generation for the user. Our approach combines a stacked graph visualization with a content-based recommender algorithm, where promising views can be revealed to the user for further investigation. By exploiting both the current user navigational data and view properties, the system allows the user to focus on visual space in which she or he is interested. After testing with more than 30 users, we analyze the results and show that accurate user profiles can be generated based on user behavior and view property data.
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Jo, Sunhwa, Beomjun Park, Suan Lee, and Jinho Kim. "OLGAVis: On-Line Graph Analysis and Visualization for Bibliographic Information Network." Applied Sciences 11, no. 9 (April 24, 2021): 3862. http://dx.doi.org/10.3390/app11093862.
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Real-world systems that are composed of various types of components, their interactions, and relationships, and numerous applications are often modeled as graphs or network structures to represent and analyze the presence of relationship, shape, and meaning of objects. Network-structured data are used for various exploration and in-depth analysis through visualization of information in various fields. In particular, online bibliographic databases are a service that is used for a myriad of purposes, such as simple search of research materials as well as understanding the history and flow of research, current status, and trends. A visualization tool that can intuitively perform exploration and analysis by modeling the data provided by the online bibliographic database in a network structure will be a very meaningful study for the exploration of various information using a large amount of complex bibliographic data. This study has modeled an online bibliographic database as an information network, and further developed a prototype of a visualization tool that provides an interactive interface for easily and efficiently performing visual exploration and multidimensional analysis. The visualization tool that was developed through this study will be used to conveniently perform various online analysis of the bibliographic data, and the information and knowledge acquired as a result of the analysis are expected to contribute to the research development of various researchers. Furthermore, this visualization tool can be applied to other types of data in the future, and it is expected to develop into a useful tool for various information network analysis by improving, supplementing, and expanding the functions and performance of the developed prototype.
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Guest, Jack, Todd Eaglin, Kalpathi Subramanian, and William Ribarsky. "Interactive analysis and visualization of situationally aware building evacuations." Information Visualization 14, no. 3 (January 7, 2014): 204–22. http://dx.doi.org/10.1177/1473871613516292.
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Evacuation of large urban structures, such as campus buildings, arenas, or stadiums, is of prime interest to emergency responders and planners. Although there is a large body of work on evacuation algorithms and their application, most of these methods are impractical to use in real-world scenarios (nonreal-time, for instance) or have difficulty handling scenarios with dynamically changing conditions. Our overall goal in this work is toward developing computer visualizations and real-time visual analytic tools for evacuations of large groups of buildings, and in the long term, integrate this with the street networks in the surrounding areas. A key aspect of our system is to provide situational awareness and decision support to first responders and emergency planners. In our earlier work, we demonstrated an evacuation system that employed a modified variant of a heuristic-based evacuation algorithm, which (1) facilitated real-time complex user interaction with first responder teams, in response to information received during the emergency; (2) automatically supported visual reporting tools for spatial occupancy, temporal cues, and procedural recommendations; and (3) multi-scale building models, heuristic evacuation models, and unique graph manipulation techniques for producing near real-time situational awareness. The system was tested in collaboration with our campus police and safety personnel, via a tabletop exercise consisting of three different scenarios. In this work, we have redesigned the system to be able to handle larger groups of buildings, in order to move toward a full-campus evacuation system. We demonstrate an evacuation simulation involving 22 buildings in the University of North Carolina, Charlotte campus. Second, the implementation has been redesigned as a WebGL application, facilitating easy dissemination and use by stakeholders.
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Kniemeyer, Ole, Gerhard H. Buck-Sorlin, and Winfried Kurth. "A Graph Grammar Approach to Artificial Life." Artificial Life 10, no. 4 (September 2004): 413–31. http://dx.doi.org/10.1162/1064546041766451.
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We present the high-level language of relational growth grammars (RGGs) as a formalism designed for the specification of ALife models. RGGs can be seen as an extension of the well-known parametric Lindenmayer systems and contain rule-based, procedural, and object-oriented features. They are defined as rewriting systems operating on graphs with the edges coming from a set of user-defined relations, whereas the nodes can be associated with objects. We demonstrate their ability to represent genes, regulatory networks of metabolites, and morphologically structured organisms, as well as developmental aspects of these entities, in a common formal framework. Mutation, crossing over, selection, and the dynamics of a network of gene regulation can all be represented with simple graph rewriting rules. This is demonstrated in some detail on the classical example of Dawkins' biomorphs and the ABC model of flower morphogenesis: other applications are briefly sketched. An interactive program was implemented, enabling the execution of the formalism and the visualization of the results.
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Cenek, Martin, Rowan Bulkow, Eric Pak, Levi Oyster, Boyd Ching, and Ashika Mulagada. "Semantic Network Analysis Pipeline—Interactive Text Mining Framework for Exploration of Semantic Flows in Large Corpus of Text." Applied Sciences 9, no. 24 (December 5, 2019): 5302. http://dx.doi.org/10.3390/app9245302.
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Historical topic modeling and semantic concepts exploration in a large corpus of unstructured text remains a hard, opened problem. Despite advancements in natural languages processing tools, statistical linguistics models, graph theory and visualization, there is no framework that combines these piece-wise tools under one roof. We designed and constructed a Semantic Network Analysis Pipeline (SNAP) that is available as an open-source web-service that implements work-flow needed by a data scientist to explore historical semantic concepts in a text corpus. We define a graph theoretic notion of a semantic concept as a flow of closely related tokens through the corpus of text. The modular work-flow pipeline processes text using natural language processing tools, statistical content narrowing, creates semantic networks from lexical token chaining, performs social network analysis of token networks and creates a 3D visualization of the semantic concept flows through corpus for interactive concept exploration. Finally, we illustrate the framework’s utility to extract the information from a text corpus of Herman Melville’s novel Moby Dick, the transcript of the 2015–2016 United States (U.S.) Senate Hearings on Environment and Public Works, and the Australian Broadcast Corporation’s short news articles on rural and science topics.
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Oh, Somyung, Junghyeon Ha, Kyungwon Lee, and Sejong Oh. "DegoViz: An Interactive Visualization Tool for a Differentially Expressed Genes Heatmap and Gene Ontology Graph." Applied Sciences 7, no. 6 (May 25, 2017): 543. http://dx.doi.org/10.3390/app7060543.
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Yang, Xiao Bo, and Bang Ze Chen. "Realizes Data Structure and the Algorithm Dynamic Synchronized Visualization." Applied Mechanics and Materials 130-134 (October 2011): 2068–71. http://dx.doi.org/10.4028/www.scientific.net/amm.130-134.2068.
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Data structure and the algorithm teaching difficulty lies in their abstractness and the dynamic, teaches in the classroom uses the graphical representation to be possible to melt to a certain extent as intuitively, but very difficult to unfold the object the instantaneous dynamic characteristics and the algorithm dynamic implementation. This article utilizes the visualization programming technology, object-oriented technical and the computer graph processing technology carries on the dynamic interactive simulation track to the typical algorithm, has realized the abstract construction of data and the algorithm dynamic synchronization visualization. Each kind of abstract data type (ADT) definition and realization concise clear, vivid direct-viewing show abstract data structure, adequately demonstrate classical algorithm dynamic and execution detail process.
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Brodkorb, Felix, Arjan Kuijper, Gennady Andrienko, Natalia Andrienko, and Tatiana von Landesberger. "Overview with details for exploring geo-located graphs on maps." Information Visualization 15, no. 3 (August 19, 2015): 214–37. http://dx.doi.org/10.1177/1473871615597077.
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Geo-located graph drawings often suffer from map visualization problems, such as overplotting of nodes as well as edges and location of parts of the graph being outside of the screen. One cause of these problems is often an irregular distribution of nodes on the map. Zooming and panning do not solve the problems, as they either only show the overview of the whole graph or only the details of a part of the graph. We present an interactive graph drawing technique that overcomes these problems without affecting the overall geographical structure of the graph. First, we introduce a method that uses insets to visualize details of small or remote areas. Second, to prevent the subgraphs within insets from overplotting and edge crossing, we introduce a local area re-arrangement. Moreover, insets are automatically drawn/hidden and repositioned in accordance with the user’s navigation. We test our technique on real-world geo-located graph data and show the effectiveness of our approach for showing overview and details at the same time. Additionally, we report on expert feedback concerning our approach.
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Hao, Ming C., Daniel A. Keim, Umeshwar Dayal, and Jörn Schneidewind. "Business Process Impact Visualization and Anomaly Detection." Information Visualization 5, no. 1 (March 2006): 15–27. http://dx.doi.org/10.1057/palgrave.ivs.9500115.
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Business operations involve many factors and relationships and are modeled as complex business process workflows. The execution of these business processes generates vast volumes of complex data. The operational data are instances of the process flow, taking different paths through the process. The goal is to use the complex information to analyze and improve operations and to optimize the process flow. In this paper, we introduce a new visualization technique, called VisImpact that turns raw operational business data into valuable information. VisImpact reduces data complexity by analyzing operational data and abstracting the most critical factors, called impact factors, which influence business operations. The analysis may identify single nodes of the business flow graph as important factors but it may also determine aggregations of nodes to be important. Moreover, the analysis may find that single nodes have certain data values associated with them which have an influence on some business metrics or resource usage parameters. The impact factors are presented as nodes in a symmetric circular graph, providing insight into core business operations and relationships. A cause-effect mechanism is built in to determine ‘good’ and ‘bad’ operational behavior and to take action accordingly. We have applied VisImpact to real-world applications, fraud analysis and service contract analysis, to show the power of VisImpact for finding relationships among the most important impact factors and for immediate identification of anomalies. The VisImpact system provides a highly interactive interface including drilldown capabilities down to transaction levels to allow multilevel views of business dynamics.
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Lévesque, François, and Thomas Hurtut. "MuzLink: Connected beeswarm timelines for visual analysis of musical adaptations and artist relationships." Information Visualization 20, no. 2-3 (July 2021): 170–91. http://dx.doi.org/10.1177/14738716211033246.
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The rise of open data in the cultural domain is democratizing access to complex datasets usually presented as large multivariate and multilayered graphs. However, the exploration of such datasets is challenging for laypersons. The objective of this work is to develop and evaluate a new method for exploring and understanding a specific type of multilayered graph that combines a large bipartite graph with a set of tree structures. This paper proposes MuzLink, an interactive visualization tool that allows the user to navigate, search, locate, and compare collaborative and influential relationships between musical artists through the exploration of musical adaptations. The proposed tool is based on a set of connected timelines visualizing how an artist’s collaborations, inspirations, and influences evolved over time. This design study is conducted in close collaboration with BAnQ, the national library and archives agency of the Quebec government. A controlled user study, done with a group of BAnQ users, and two case studies, show how the proposed approach is capable of performing a considerable set of analytical and exploratory tasks.
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Lettieri, Nicola, Antonio Altamura, and Delfina Malandrino. "The legal macroscope: Experimenting with visual legal analytics." Information Visualization 16, no. 4 (December 28, 2016): 332–45. http://dx.doi.org/10.1177/1473871616681374.
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This work presents Knowlex, a web application designed for visualization, exploration, and analysis of legal documents coming from different sources. Understanding the legal framework relating to a given issue often requires the analysis of complex legal corpora. When a legal professional or a citizen tries to understand how a given phenomenon is disciplined, his attention cannot be limited to a single source of law but has to be directed on the bigger picture resulting from all the legal sources related to the theme under investigation. Knowlex exploits data visualization to support this activity by means of interactive maps making sense out of heterogeneous documents (norms, case law, legal literature, etc.). Starting from a legislative measure (what we define as Root) given as input by the user, the application implements two visual analytics functionalities aiming to offer new insights on the legal corpus under investigation. The first one is an interactive node graph depicting relations and properties of the documents. The second one is a zoomable treemap showing the topics, the evolution, and the dimension of the legal literature settled over the years around the norm of interest. The article gives an overview of the research so far conducted presenting the results of a preliminary evaluation study aiming at evaluating the effectiveness of visualization in supporting legal activities as well as the effectiveness of Knowlex, the usability of the proposed system, and the overall user satisfaction when interacting with its applications.
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Motta, Thiago, and Luciana Nedel. "Interactive Public Displays: A Gesture-Based Proposal Using Kinect." Journal on Interactive Systems 4, no. 2 (January 29, 2014): 1. http://dx.doi.org/10.5753/jis.2013.634.
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The use of interactive public displays in urban spaces is increasing very fast, and new setups to support these displays are still being explored. In this paper we introduce a gesture based input technique to allow the interaction with public displays avoiding the use of any device attached to the user body. The gestures supported provide navigation, selection and manipulation of objects, as well as panning and zooming on the screen. In order to evaluate how robust the system is in a real public scenario, criteria that could interfere on the interactive task are evaluated, as the amount of brightness in the environment, and the presence of other persons. The setup used to support the tests include a 55” LED TV, a Kinect for gestures capture, and a new algorithm to allow the identification of closing and opening hands. Three test scenarios are described in this paper: the interactive visualization of a graph representing the academic genealogical tree of our University; the selection and manipulation of simple objects; and the free interaction with the map of a building. Given the results of the performed tasks, we conclude that the system, although not behaving very accurately in all situations, has potential to be used on many applications.
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Fernandes, David Paiva, and Elizabeth Simão Carvalho. "DocGenealogy – Visualizing the doctoral advisors and mentors genealogic tree." Abakós 6, no. 2 (May 21, 2018): 3–20. http://dx.doi.org/10.5752/p.2316-9451.2018v6n2p3-20.
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DocGenealogy is a data mining project that allows the visualization and exploration of the doctoral advisement/mentoring relationship through an interactive graph chart. Wikipedia is known for its informal collaborative nature, based on a somewhat loose and non-structural way of producing information, and one of its strengths is, in fact, the openness to all sorts of collaborations. DocGenealogy uses the Wikipedia available data on doctoral advisement and mentoring to find out and track the existing relationships between advisors or mentors and their students. The data mining process starting point is always some well-known scientist. This process continues until finding all the ultimate reputed co-related advisors and mentors, and builds iteratively the relationship graph. Besides this, DocGenealogy also visually shows how people are distributed by alma mater and field of knowledge. The main objective of the work is to evaluate the effectiveness of the graph-oriented techniques in the interpretation of data from Wilipedia infoboxes.
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Pandolfi, Ronald J., Daniel B. Allan, Elke Arenholz, Luis Barroso-Luque, Stuart I. Campbell, Thomas A. Caswell, Austin Blair, et al. "Xi-cam: a versatile interface for data visualization and analysis." Journal of Synchrotron Radiation 25, no. 4 (May 31, 2018): 1261–70. http://dx.doi.org/10.1107/s1600577518005787.
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Xi-cam is an extensible platform for data management, analysis and visualization. Xi-cam aims to provide a flexible and extensible approach to synchrotron data treatment as a solution to rising demands for high-volume/high-throughput processing pipelines. The core of Xi-cam is an extensible plugin-based graphical user interface platform which provides users with an interactive interface to processing algorithms. Plugins are available for SAXS/WAXS/GISAXS/GIWAXS, tomography and NEXAFS data. With Xi-cam's `advanced' mode, data processing steps are designed as a graph-based workflow, which can be executed live, locally or remotely. Remote execution utilizes high-performance computing or de-localized resources, allowing for the effective reduction of high-throughput data. Xi-cam's plugin-based architecture targets cross-facility and cross-technique collaborative development, in support of multi-modal analysis. Xi-cam is open-source and cross-platform, and available for download on GitHub.
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PERLIN, MARK W. "VISUALIZING DYNAMIC ARTIFICIAL INTELLIGENCE ALGORITHMS AND APPLICATIONS." International Journal on Artificial Intelligence Tools 03, no. 02 (June 1994): 289–307. http://dx.doi.org/10.1142/s0218213094000145.
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Visualization is an important component of modern computing. By animating the course of an algorithm’s temporal execution, many key features can be elucidated. We have developed a general framework, termed Call-Graph Caching (CGC), for automating the construction of many complex AI algorithms. By incorporating visualization into CGC interpreters, principled animations can be automatically displayed as AI computations unfold. (1) Systems that support the automatic animation of AI algorithms must address these three design issues: (2) How to represent AI data structures in a general, uniform way that leads to perspicuous animation and efficient redisplay. (3) How to coordinate the succession of graphical events. (4) How to partition AI graphs to provide for separate, uncluttered displays. CGC provides a natural and effective solution to all these concerns. (5) We describe the CGC method, including detailed examples, and motivate why CGC works well for animation. We discuss the CACHE system, our CGC environment for AI algorithm animation. We demonstrate the animation of several AI algorithms – RETE match, linear unification, arc consistency, chart parsing, and truth maintenance – all of which have been implemented in CACHE. Finally, we discuss the application of these methods to interactive interfaces for intelligent systems, using molecular genetics as an example domain.
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Ge, Xiaoyu, Vineet K. Raghu, Panos K. Chrysanthis, and Panayiotis V. Benos. "CausalMGM: an interactive web-based causal discovery tool." Nucleic Acids Research 48, W1 (May 11, 2020): W597—W602. http://dx.doi.org/10.1093/nar/gkaa350.
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Abstract High-throughput sequencing and the availability of large online data repositories (e.g. The Cancer Genome Atlas and Trans-Omics for Precision Medicine) have the potential to revolutionize systems biology by enabling researchers to study interactions between data from different modalities (i.e. genetic, genomic, clinical, behavioral, etc.). Currently, data mining and statistical approaches are confined to identifying correlates in these datasets, but researchers are often interested in identifying cause-and-effect relationships. Causal discovery methods were developed to infer such cause-and-effect relationships from observational data. Though these algorithms have had demonstrated successes in several biomedical applications, they are difficult to use for non-experts. So, there is a need for web-based tools to make causal discovery methods accessible. Here, we present CausalMGM (http://causalmgm.org/), the first web-based causal discovery tool that enables researchers to find cause-and-effect relationships from observational data. Web-based CausalMGM consists of three data analysis tools: (i) feature selection and clustering; (ii) automated identification of cause-and-effect relationships via a graphical model; and (iii) interactive visualization of the learned causal (directed) graph. We demonstrate how CausalMGM enables an end-to-end exploratory analysis of biomedical datasets, giving researchers a clearer picture of its capabilities.
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Keiriz, Johnson J. G., Liang Zhan, Olusola Ajilore, Alex D. Leow, and Angus G. Forbes. "NeuroCave: A web-based immersive visualization platform for exploring connectome datasets." Network Neuroscience 2, no. 3 (September 2018): 344–61. http://dx.doi.org/10.1162/netn_a_00044.
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We introduce NeuroCave, a novel immersive visualization system that facilitates the visual inspection of structural and functional connectome datasets. The representation of the human connectome as a graph enables neuroscientists to apply network-theoretic approaches in order to explore its complex characteristics. With NeuroCave, brain researchers can interact with the connectome—either in a standard desktop environment or while wearing portable virtual reality headsets (such as Oculus Rift, Samsung Gear, or Google Daydream VR platforms)—in any coordinate system or topological space, as well as cluster brain regions into different modules on-demand. Furthermore, a default side-by-side layout enables simultaneous, synchronized manipulation in 3D, utilizing modern GPU hardware architecture, and facilitates comparison tasks across different subjects or diagnostic groups or longitudinally within the same subject. Visual clutter is mitigated using a state-of-the-art edge bundling technique and through an interactive layout strategy, while modular structure is optimally positioned in 3D exploiting mathematical properties of platonic solids. NeuroCave provides new functionality to support a range of analysis tasks not available in other visualization software platforms.
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Szell, Michael. "Crowdsourced Quantification and Visualization of Urban Mobility Space Inequality." Urban Planning 3, no. 1 (March 29, 2018): 1–20. http://dx.doi.org/10.17645/up.v3i1.1209.
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Most cities are car-centric, allocating a privileged amount of urban space to cars at the expense of sustainable mobility like cycling. Simultaneously, privately owned vehicles are vastly underused, wasting valuable opportunities for accommodating more people in a livable urban environment by occupying spacious parking areas. Since a data-driven quantification and visualization of such urban mobility space inequality is lacking, here we explore how crowdsourced data can help to advance its understanding. In particular, we describe how the open-source online platform What the Street!? uses massive user-generated data from OpenStreetMap for the interactive exploration of city-wide mobility spaces. Using polygon packing and graph algorithms, the platform rearranges all parking and mobility spaces of cars, rails, and bicycles of a city to be directly comparable, making mobility space inequality accessible to a broad public. This crowdsourced method confirms a prevalent imbalance between modal share and space allocation in 23 cities worldwide, typically discriminating bicycles. Analyzing the guesses of the platform’s visitors about mobility space distributions, we find that this discrimination is consistently underestimated in the public opinion. Finally, we discuss a visualized scenario in which extensive parking areas are regained through fleets of shared, autonomous vehicles. We outline how such accessible visualization platforms can facilitate urban planners and policy makers to reclaim road and parking space for pushing forward sustainable transport solutions.
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Soloviev, Igor, Giuseppe Avolio, and Sami Perrin. "The ATLAS Access Manager Policy Browser: state-of-the-art web technologies for a rich and interactive data visualization experience." EPJ Web of Conferences 214 (2019): 01018. http://dx.doi.org/10.1051/epjconf/201921401018.
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The ATLAS experiment is operated daily by many users and experts working concurrently on several aspects of the detector. The safe and optimal access to the various software and hardware resources of the experiment is guaranteed by a role-based access control system (RBAC) provided by the ATLAS Trigger and Data Acquisition (TDAQ) system. The roles are defined by an inheritance hierarchy. Depending on duties, every ATLAS user has a well-defined set of access privileges (rules) corresponding to a specific set of assigned roles. In total, there are several hundred roles and several thousand users. Over the years, the system grew up in terms of users and roles, motivating the deployment of a visualization tool named “Policy Browser”. Currently, it is the primary tool for role administrators to manage all the aspects of the Access Management via a rich web-based interface. This paper presents the requirements, design and implementation of the “Policy Browser”. The tool is able to aggregate and correlate all the information provided by the RBAC system and offers a visual representation of the interrelations occurring among roles, users, hosts and rules. Additionally, the “Policy Browser” implements a powerful and flexible query mechanism facilitating the browsing of all the authorizations granted by the system. As an example of the available visual representations, the “Policy Browser” is capable of dynamically generating graphs to quickly display the role giving a user some defined privileges. A graph explorer is also provided in order to browse the role&s inheritance hierarchy. The “Policy Browser” is implemented using robust JavaScript frameworks: AngularJS, Bootstrap, D3.js for the front-end, and Django a python framework for the back-end. The use cases and the results based on an informal evaluation provided by the roles administrators are also presented.
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Zhang, Tong, Jianlong Wang, Chenrong Cui, Yicong Li, Wei He, Yonghua Lu, and Qinghua Qiao. "Integrating Geovisual Analytics with Machine Learning for Human Mobility Pattern Discovery." ISPRS International Journal of Geo-Information 8, no. 10 (September 30, 2019): 434. http://dx.doi.org/10.3390/ijgi8100434.
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Understanding human movement patterns is of fundamental importance in transportation planning and management. We propose to examine complex public transit travel patterns over a large-scale transit network, which is challenging since it involves thousands of transit passengers and massive data from heterogeneous sources. Additionally, efficient representation and visualization of discovered travel patterns is difficult given a large number of transit trips. To address these challenges, this study leverages advanced machine learning methods to identify time-varying mobility patterns based on smart card data and other urban data. The proposed approach delivers a comprehensive solution to pre-process, analyze, and visualize complex public transit travel patterns. This approach first fuses smart card data with other urban data to reconstruct original transit trips. We use two machine learning methods, including a clustering algorithm to extract transit corridors to represent primary mobility connections between different regions and a graph-embedding algorithm to discover hierarchical mobility community structures. We also devise compact and effective multi-scale visualization forms to represent the discovered travel behavior dynamics. An interactive web-based mapping prototype is developed to integrate advanced machine learning methods with specific visualizations to characterize transit travel behavior patterns and to enable visual exploration of transit mobility patterns at different scales and resolutions over space and time. The proposed approach is evaluated using multi-source big transit data (e.g., smart card data, transit network data, and bus trajectory data) collected in Shenzhen City, China. Evaluation of our prototype demonstrates that the proposed visual analytics approach offers a scalable and effective solution for discovering meaningful travel patterns across large metropolitan areas.
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Gadhave, Kiran, Jochen Görtler, Zach Cutler, Carolina Nobre, Oliver Deussen, Miriah Meyer, Jeff M. Phillips, and Alexander Lex. "Predicting intent behind selections in scatterplot visualizations." Information Visualization 20, no. 4 (August 18, 2021): 207–28. http://dx.doi.org/10.1177/14738716211038604.
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Predicting and capturing an analyst’s intent behind a selection in a data visualization is valuable in two scenarios: First, a successful prediction of a pattern an analyst intended to select can be used to auto-complete a partial selection which, in turn, can improve the correctness of the selection. Second, knowing the intent behind a selection can be used to improve recall and reproducibility. In this paper, we introduce methods to infer analyst’s intents behind selections in data visualizations, such as scatterplots. We describe intents based on patterns in the data, and identify algorithms that can capture these patterns. Upon an interactive selection, we compare the selected items with the results of a large set of computed patterns, and use various ranking approaches to identify the best pattern for an analyst’s selection. We store annotations and the metadata to reconstruct a selection, such as the type of algorithm and its parameterization, in a provenance graph. We present a prototype system that implements these methods for tabular data and scatterplots. Analysts can select a prediction to auto-complete partial selections and to seamlessly log their intents. We discuss implications of our approach for reproducibility and reuse of analysis workflows. We evaluate our approach in a crowd-sourced study, where we show that auto-completing selection improves accuracy, and that we can accurately capture pattern-based intent.
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Hu, Pingbo, Bisheng Yang, Zhen Dong, Pengfei Yuan, Ronggang Huang, Hongchao Fan, and Xuan Sun. "Towards Reconstructing 3D Buildings from ALS Data Based on Gestalt Laws." Remote Sensing 10, no. 7 (July 17, 2018): 1127. http://dx.doi.org/10.3390/rs10071127.
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3D building models are an essential data infrastructure for various applications in a smart city system, since they facilitate spatial queries, spatial analysis, and interactive visualization. Due to the highly complex nature of building structures, automatically reconstructing 3D buildings from point clouds remains a challenging task. In this paper, a Roof Attribute Graph (RAG) method is proposed to describe the decomposition and topological relations within a complicated roof structure. Furthermore, top-down decomposition and bottom-up refinement processes are proposed to reconstruct roof parts according to the Gestalt laws, generating a complete structural model with a hierarchical topological tree. Two LiDAR datasets from Guangdong (China) and Vaihingen (Germany) with different point densities were used in our study. Experimental results, including the assessment on Vaihingen standardized by the International Society for Photogrammetry and Remote Sensing (ISPRS), show that the proposed method can be used to model 3D building roofs with high quality results as demonstrated by the completeness and correctness metrics presented in this paper.
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Spritzer, Andre Suslik, and Carla M. D. S. Freitas. "Navigation and Interaction in Graph Visualizations." Revista de Informática Teórica e Aplicada 15, no. 1 (September 24, 2008): 111–36. http://dx.doi.org/10.22456/2175-2745.6015.
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Graphs are widely utilized in many fields and several applications require their visualization. Graph visualization is based on techniques for graph drawing, interaction and navigation in such a way that helps the user in finding and manipulating information efficiently. These techniques, which can be two or three-dimensional, depending on the spatial metaphor used to represent the graph, can be combined in many different ways in order to fit a particular application's needs. This paper presents an overview of the field of graph visualization.
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Aguilera-Mendoza, Longendri, Yovani Marrero-Ponce, Jesus A. Beltran, Roberto Tellez Ibarra, Hugo A. Guillen-Ramirez, and Carlos A. Brizuela. "Graph-based data integration from bioactive peptide databases of pharmaceutical interest: toward an organized collection enabling visual network analysis." Bioinformatics 35, no. 22 (April 17, 2019): 4739–47. http://dx.doi.org/10.1093/bioinformatics/btz260.
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Abstract Motivation Bioactive peptides have gained great attention in the academy and pharmaceutical industry since they play an important role in human health. However, the increasing number of bioactive peptide databases is causing the problem of data redundancy and duplicated efforts. Even worse is the fact that the available data is non-standardized and often dirty with data entry errors. Therefore, there is a need for a unified view that enables a more comprehensive analysis of the information on this topic residing at different sites. Results After collecting web pages from a large variety of bioactive peptide databases, we organized the web content into an integrated graph database (starPepDB) that holds a total of 71 310 nodes and 348 505 relationships. In this graph structure, there are 45 120 nodes representing peptides, and the rest of the nodes are connected to peptides for describing metadata. Additionally, to facilitate a better understanding of the integrated data, a software tool (starPep toolbox) has been developed for supporting visual network analysis in a user-friendly way; providing several functionalities such as peptide retrieval and filtering, network construction and visualization, interactive exploration and exporting data options. Availability and implementation Both starPepDB and starPep toolbox are freely available at http://mobiosd-hub.com/starpep/. Supplementary information Supplementary data are available at Bioinformatics online.
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Droste, Peter, Wolfgang Wiechert, and Katharina Nöh. "Semi-automatic drawing of metabolic networks." Information Visualization 11, no. 3 (August 22, 2011): 171–87. http://dx.doi.org/10.1177/1473871611413565.
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In the living cell, biochemical reactions catalyzed by enzymes are the drivers for metabolic processes like growth, energy production, and replication. Metabolic networks are the representation of these processes describing the complex interactions of biochemical compounds. The large amount of manifold data concerning metabolic networks continually arising from current research activities in biotechnology leads to the great challenge of information visualization. Visualizing information in networks first of all requires appropriate network diagrams. In the context of metabolic networks, historical conventions regarding the network layout have been established. These layouts are not realizable by prevailing algorithms for automatic graph drawing. Hence, manual graph drawing is the predominating way to set up metabolic network diagrams. This is very time-consuming without software support, especially considering large networks with more than 500 nodes. We present a semi-automatic approach to drawing networks which relies on manual editing supported by two concepts of the interactive and automatic arrangement of nodes and edges. The first concept, called the layout pattern, uses an arbitrarily shaped skeleton as a backbone for the arrangement of nodes and edges. The second concept allows us to wrap a set of repeating drawing steps onto a so-called motif stamp, which can be appended to other parts of a diagram during the drawing process. Finally, a case study demonstrates that both semi-automatic drawing techniques diminish the time to be devoted for the manual network drawing process.
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Ware, Colin, and Robert Bobrow. "Supporting Visual Queries on Medium-Sized Node–Link Diagrams." Information Visualization 4, no. 1 (March 2005): 49–58. http://dx.doi.org/10.1057/palgrave.ivs.9500090.
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For reasons of clarity, a typical node–link diagram statically displayed on paper or a computer screen contains fewer than 30 nodes. However, many problems would benefit if far more complex information could be diagrammed. Following Munzner et al., we suggest that with interactive diagrams this may be possible. We describe an interactive technique whereby a subset of a larger network diagram is highlighted by being set into oscillatory motion when a node is selected with a mouse. The subset is determined by a breadth first search of the underlying graph starting from the selected node. This technique is designed to support visual queries on moderately large node-link diagrams containing up to a few thousand nodes. An experimental evaluation was carried out with networks having 32, 100, 320, 1000, and 3200 nodes respectively, and with four highlighting techniques: static highlighting, motion highlighting, static+ motion highlighting, and none. The results show that the interactive highlighting methods support rapid visual queries of nodes in close topological proximity to one another, even for the largest diagrams tested. Without highlighting, error rates were high even for the smallest network that was evaluated. Motion highlighting and static highlighting were equally effective. A second experiment was carried out to evaluate methods for showing two subsets of a larger network simultaneously in such a way that both are clearly distinct. The specific task was to determine if the two subsets had nodes in common. The results showed that this task could be performed rapidly and with few errors if one subset was highlighted using motion and the other was highlighted using a static technique. We discuss the implications for information visualization.