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Zimmer, B. (2019). Guided Interaction and Collaborative Exploration in Heterogeneous Network Visualizations. (Doctoral dissertation). Växjö, Sweden: Linnaeus University Press
Open this publication in new window or tab >>Guided Interaction and Collaborative Exploration in Heterogeneous Network Visualizations
2019 (English)Doctoral thesis, monograph (Other academic)
Abstract [en]

The visual exploration of large and complex network structures remains a challenge for many application fields, such as systems biology or social sciences. Often, various domain experts would like to work together to improve the analysis time or the quality of the analysis results. Collaborative visualization tools can facilitate the analysis process in such situations. Moreover, a growing number of real world networks are multivariate and often interconnected with each other. Entities in a network may have relationships with elements of other related data sets, which do not necessarily have to be networks themselves, and these relationships may be defined by attributes that can vary greatly. A challenge is to correctly assign the attributes and relations between different data sets and graphs in order to be able to analyze them visually afterwards. The navigation between the resulting visualizations is also difficult. How can users be guided to other interesting data points relevant to their current view and how can this information be additionally displayed in a graph without losing the overview of the data?

In this dissertation, we propose our new web-based visualization environment OnGraX, which supports distributed, synchronous and asynchronous collaboration of networks and related multivariate data sets. In addition to standard collaboration features like event tracking or synchronizing, our client/server-based system provides a rich set of visualization and interaction techniques for better navigation and overview of the input network. Changes made by specific analysts or even just visited network elements can be highlighted by heat maps, which enable us to visualize user behavior data without affecting the original graph visualization. We evaluate the usability of the heat map approach against two alternatives in a user experiment.

Additional features of OnGraX include a comprehensive visual analytics approach that supports researchers to specify and subsequently explore attribute-based relationships across networks, text documents, and derived secondary data. Our approach provides an individual search functionality based on keywords and semantically similar terms over an entire text corpus to find related network nodes. For examining these nodes in the interconnected network views, we introduce a new interaction technique, called Hub2Go, which facilitates the navigation by guiding the user to the information of interest. To showcase these features, we use a large text corpus collected from papers listed in the IEEE VIS publications data set (1990--2015) that consists of 2,752 documents. We analyze relationships between various heterogeneous networks, a Bag-of-Words index, and a word similarity matrix, all derived from the initial corpus and metadata. We also propose a design for the interactive specification of degree-of-interest functions, which can be used to provide and evaluate configurations for guidance based on network attributes and logged user data in heterogeneous networks.

Place, publisher, year, edition, pages
Växjö, Sweden: Linnaeus University Press, 2019. p. 150
Series
Linnaeus University Dissertations ; 343/2019
Keywords
Information Visualization, Multivariate Networks, Visual Analytics, Exploration, Interaction, Collaboration, Provenance, Guidance
National Category
Information Systems Software Engineering Human Computer Interaction
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-80209 (URN)978-91-88898-33-3 (ISBN)978-91-88898-34-0 (ISBN)
Public defence
2019-01-31, D1136, Hus D, Växjö, 09:30 (English)
Opponent
Supervisors
Available from: 2019-02-08 Created: 2019-02-04 Last updated: 2019-02-08Bibliographically approved
Zimmer, B. & Kerren, A. (2017). OnGraX: A Web-Based System for the Collaborative Visual Analysis of Graphs. Journal of Graph Algorithms and Applications, 21(1), 5-27
Open this publication in new window or tab >>OnGraX: A Web-Based System for the Collaborative Visual Analysis of Graphs
2017 (English)In: Journal of Graph Algorithms and Applications, ISSN 1526-1719, E-ISSN 1526-1719, Vol. 21, no 1, p. 5-27Article in journal (Refereed) Published
Abstract [en]

The visual analysis of complex networks is a challenging task in many fields, such as systems biology or social sciences. Often, various domain experts work together to improve the analysis time or the quality of the analysis results. Collaborative visualization tools can facilitate the analysis process in such situations. We propose a new web-based visualization environment which supports distributed, synchronous and asynchronous collaboration. In addition to standard collaboration features like event tracking or synchronizing, our client/server-based system provides a rich set of visualization and interaction techniques for better navigation and overview of the input network. Changes made by specific analysts or even just visited network elements are highlighted on demand by heat maps. They enable us to visualize user behavior data without affecting the original graph visualization, are robust against layout changes, and are user-sensitive in a sense that the current analyst is able to perceive which changes were made by others in asynchronous collaboration. In case of synchronous collaboration, an analyst can see where and what others are currently analyzing in the network visualization. Thus, our approach addresses critical collaborative visualization challenges, for instance, awareness and coordination of user activities or pointing to interesting objects. We evaluated the usability of the heat map approach against two alternatives in a controlled user experiment. In addition, the results of a domain expert review are described in this article.

Place, publisher, year, edition, pages
Journal of Graph Algorithms and Applications, 2017
Keywords
network visualization, collaborative visualization, interaction, visualization, information visualization, graph drawing, visual analytics, heat maps, WebGL, WebSockets
National Category
Computer Sciences Other Computer and Information Science
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-54630 (URN)10.7155/jgaa.00399 (DOI)2-s2.0-85010971949 (Scopus ID)
Available from: 2016-07-12 Created: 2016-07-12 Last updated: 2019-09-06Bibliographically approved
Zimmer, B., Sahlgren, M. & Kerren, A. (2017). Visual Analysis of Relationships between Heterogeneous Networks and Texts: An Application on the IEEE VIS Publication Dataset. Informatics, 4(2), Article ID 11.
Open this publication in new window or tab >>Visual Analysis of Relationships between Heterogeneous Networks and Texts: An Application on the IEEE VIS Publication Dataset
2017 (English)In: Informatics, ISSN 2227-9709, Vol. 4, no 2, article id 11Article in journal (Refereed) Published
Abstract [en]

The visual exploration of large and complex network structures remains a challenge for many application fields. Moreover, a growing number of real world networks are multivariate and often interconnected with each other. Entities in a network may have relationships with elements of other related data sets, which do not necessarily have to be networks themselves, and these relationships may be defined by attributes that can vary greatly. In this work, we propose a comprehensive visual analytics approach that supports researchers to specify and subsequently explore attribute-based relationships across networks, text documents, and derived secondary data. Our approach provides an individual search functionality based on keywords and semantically similar terms over the entire text corpus to find related network nodes. For examining these nodes in the interconnected network views, we introduce a new interaction technique, called Hub2Go, which facilitates the navigation by guiding the user to the information of interest. To showcase our system, we use a large text corpus collected from research papers listed in the IEEE VIS publications dataset that consists of 2752 documents over a period of 25 years. Here, we analyze relationships between various heterogeneous networks, a Bag-of-Words index, and a word similarity matrix, all derived from the initial corpus and metadata. 

Place, publisher, year, edition, pages
MDPI, 2017
Keywords
heterogeneous networks, interaction, graph drawing, multivariate data sets, NLP, text analysis, visualization, visual analytics
National Category
Computer Sciences Language Technology (Computational Linguistics)
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-63188 (URN)10.3390/informatics4020011 (DOI)000423667100005 ()
Projects
StaViCTA
Funder
Swedish Research Council, 2012-5659
Available from: 2017-05-08 Created: 2017-05-08 Last updated: 2019-09-06Bibliographically approved
Zimmer, B. & Kerren, A. (2015). Displaying User Behavior in the Collaborative Graph Visualization System OnGraX. In: Emilio Di Giacomo; Anna Lubiw (Ed.), Emilio Di Giacomo and Anna Lubiw (Ed.), Graph Drawing and Network Visualization: 23rd International Symposium on Graph Drawing and Network Visualization, GD 2015, Los Angeles, CA, USA, September 24-26, 2015, Revised Selected Papers. Paper presented at 23rd International Symposium on Graph Drawing & Network Visualization (GD '15), Los Angeles, CA, USA, 2015 (pp. 247-259). Paper presented at 23rd International Symposium on Graph Drawing & Network Visualization (GD '15), Los Angeles, CA, USA, 2015. Springer
Open this publication in new window or tab >>Displaying User Behavior in the Collaborative Graph Visualization System OnGraX
2015 (English)In: Graph Drawing and Network Visualization: 23rd International Symposium on Graph Drawing and Network Visualization, GD 2015, Los Angeles, CA, USA, September 24-26, 2015, Revised Selected Papers / [ed] Emilio Di Giacomo; Anna Lubiw, Springer, 2015, p. 247-259Chapter in book (Refereed)
Abstract [en]

The visual analysis of complex networks is a challenging task in many fields, such as systems biology or social sciences. Often, various domain experts work together to improve the analysis time or the quality of the analysis results. Collaborative visualization tools can facilitate the analysis process in such situations. We propose a new web-based visualization environment which supports distributed, synchronous and asynchronous collaboration. In addition to standard collaboration features like event tracking or synchronizing, our client/server-based system provides a rich set of visualization and interaction techniques for better navigation and overview of the input network. Changes made by specific analysts or even just visited network elements are highlighted on demand by heat maps. They enable us to visualize user behavior data without affecting the original graph visualization. We evaluate the usability of the heat map approach against two alternatives in a user experiment.

Place, publisher, year, edition, pages
Springer, 2015
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 9411
Keywords
information visualization, graph drawing, network exploration, interaction, HCI, CSCW, biological networks, heat maps
National Category
Human Computer Interaction Computer Sciences
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-45577 (URN)10.1007/978-3-319-27261-0_21 (DOI)000373628600021 ()2-s2.0-84952027225 (Scopus ID)978-3-319-27260-3 (ISBN)978-3-319-27261-0 (ISBN)
Conference
23rd International Symposium on Graph Drawing & Network Visualization (GD '15), Los Angeles, CA, USA, 2015
Available from: 2015-07-31 Created: 2015-07-31 Last updated: 2018-01-11Bibliographically approved
Zimmer, B. & Kerren, A. (2015). Harnessing WebGL and WebSockets for a Web-Based Collaborative Graph Exploration Tool. In: Philipp Cimiano, Flavius Frasincar, Geert-Jan Houben, and Daniel Schwabe (Ed.), Engineering the Web in the Big Data Era: 15th International Conference, ICWE 2015, Rotterdam, The Netherlands, June 23-26, 2015, Proceedings. Paper presented at 15th International Conference on Web Engineering (ICWE '15), Rotterdam, The Netherlands, 23-26 June, 2015. (pp. 583-598). Springer
Open this publication in new window or tab >>Harnessing WebGL and WebSockets for a Web-Based Collaborative Graph Exploration Tool
2015 (English)In: Engineering the Web in the Big Data Era: 15th International Conference, ICWE 2015, Rotterdam, The Netherlands, June 23-26, 2015, Proceedings / [ed] Philipp Cimiano, Flavius Frasincar, Geert-Jan Houben, and Daniel Schwabe, Springer, 2015, p. 583-598Conference paper, Published paper (Refereed)
Abstract [en]

The advancements of web technologies in recent years made it possible to switch from traditional desktop software to online solutions. Today, people naturally use web applications to work together on documents, spreadsheets, or blogs in real time. Also interactive data visualizations are more and more shared in the web. They are thus easily accessible, and it is possible to collaboratively discuss and explore complex data sets. A still open problem in collaborative information visualization is the online exploration of node-link diagrams of graphs (or networks) in fields such as social sciences or systems biology. In this paper, we address challenges related to this research problem and present a client/server-based visualization system for the collaborative exploration of graphs. Our approach uses WebGL to render large graphs in a web application and provides tools to coordinate the analysis process of multiple users in synchronous as well as asynchronous sessions. 

Place, publisher, year, edition, pages
Springer, 2015
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 9114
Keywords
Collaboration, web user interfaces, WebGL, WebSockets, network visualization, graph drawing
National Category
Computer Sciences Information Systems
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-41674 (URN)10.1007/978-3-319-19890-3_37 (DOI)000364535600040 ()2-s2.0-84937391875 (Scopus ID)978-3-319-19889-7 (ISBN)978-3-319-19890-3 (ISBN)
Conference
15th International Conference on Web Engineering (ICWE '15), Rotterdam, The Netherlands, 23-26 June, 2015.
Available from: 2015-04-02 Created: 2015-04-02 Last updated: 2018-01-11Bibliographically approved
Zimmer, B. & Kerren, A. (2014). Applying Heat Maps in a Web-Based Collaborative Graph Visualization. In: Poster Abstracts of IEEE VIS 2014: . Paper presented at IEEE Information Visualization (InfoVis '14), Paris, France, 2014.
Open this publication in new window or tab >>Applying Heat Maps in a Web-Based Collaborative Graph Visualization
2014 (English)In: Poster Abstracts of IEEE VIS 2014, 2014Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

The visual analysis of large and complex networks is a challenging task in many fields, such as systems biology or social sciences. Often, various domain experts work together to improve the analysis time or the quality of the analysis results. Collaborative visualization tools can facilitate this process. We propose a new web-based visualization environment which supports distributed, synchronous and asynchronous collaboration for graphs with up to 10,000 nodes and edges. In addition to standard collaboration features like event tracking or synchronizing, our client/server-based system provides visualization and interaction techniques for better navigation, guidance and overview of the overall data set. During asynchronous collaborations, network changes made by specific analysts or even just visited elements are highlighted on demand by heat maps. These heat map representations are user-sensitive in a sense that the current analyst is able to perceive which changes were made by others. 

Keywords
network exploration, graph drawing, interaction, heat maps, collaboration, WebGL, CSCW
National Category
Computer Sciences Human Computer Interaction
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-36295 (URN)
Conference
IEEE Information Visualization (InfoVis '14), Paris, France, 2014
Available from: 2014-08-05 Created: 2014-08-05 Last updated: 2018-08-17Bibliographically approved
Wybrow, M., Elmqvist, N., Fekete, J.-D., von Landesberger, T., van Wijk, J. J. & Zimmer, B. (2014). Interaction in the visualization of multivariate networks. In: Andreas Kerren, Helen C. Purchase, Matthew O. Ward (Ed.), Towards Multivariate Network Visualization: 3rd Dagstuhl Seminar on Information Visualization, Germany, May 12-17, 2013. Revised Discussions. Paper presented at 3rd Dagstuhl Seminar on Information Visualization, Germany, May 12-17, 2013 (pp. 97-125). Springer
Open this publication in new window or tab >>Interaction in the visualization of multivariate networks
Show others...
2014 (English)In: Towards Multivariate Network Visualization: 3rd Dagstuhl Seminar on Information Visualization, Germany, May 12-17, 2013. Revised Discussions / [ed] Andreas Kerren, Helen C. Purchase, Matthew O. Ward, Springer, 2014, p. 97-125Conference paper, Published paper (Refereed)
Abstract [en]

The overall aim of visualization is to obtain insight into large amounts of data. Detection of patterns as well as outliers are typical examples. For networks, such patterns can be number and position of cliques; for multivariate data this can be the correlation between attributes. The major challenge of multivariate network visualization is to understand the interplay between properties of the network and its associated data, for instance to see if the formation of cliques can be understood from attributes of nodes.

Place, publisher, year, edition, pages
Springer, 2014
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 8380
National Category
Computer Systems Information Systems, Social aspects
Research subject
Computer and Information Sciences Computer Science, Computer Science
Identifiers
urn:nbn:se:lnu:diva-59123 (URN)10.1007/978-3-319-06793-3_6 (DOI)000342987400006 ()2-s2.0-84901276102 (Scopus ID)9783319067926 (ISBN)
Conference
3rd Dagstuhl Seminar on Information Visualization, Germany, May 12-17, 2013
Available from: 2016-12-19 Created: 2016-12-19 Last updated: 2018-02-16Bibliographically approved
Zimmer, B. & Kerren, A. (2014). Sensemaking and Provenance in Distributed Collaborative Node-Link Visualizations. In: : . Paper presented at IEEE VIS 2014 Workshop: Provenance for Sensemaking.
Open this publication in new window or tab >>Sensemaking and Provenance in Distributed Collaborative Node-Link Visualizations
2014 (English)Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Various experts often work together during the analysis of large and complex data sets in order to minimize the required time and to improve the quality of the analysis results. Keeping track of the reasoning involved during a collaborative process and using this information later to review and reflect upon it can be a challenging task. For instance, analysts should have the possibility to quickly review changes performed on a graph and get an idea of the most interesting regions according to the user history without the need to replay every single action that was performed by prior users. This paper focuses on challenges during the collection and visualization of the sensemaking process in distributed collaborative node-link visualizations. We raise five challenges that we think need discussion among researchers in this domain and present our tool OnGraX—a web-based collaborative tool for analyzing networks—that addresses some of those challenges.

Keywords
Collaboration, graph drawing, heat maps, network exploration, network analysis, sensemaking, provenance
National Category
Computer Sciences Human Computer Interaction
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-37218 (URN)
Conference
IEEE VIS 2014 Workshop: Provenance for Sensemaking
Available from: 2014-09-23 Created: 2014-09-23 Last updated: 2018-01-11Bibliographically approved
Jusufi, I., Kerren, A., Liu, J. & Zimmer, B. (2014). Visual Exploration of Relationships between Document Clusters. In: Robert S. Laramee, Andreas Kerren, José Braz (Ed.), IVAPP 2014: Proceedings od the 5th International Conference on Information Visualization Theory and Applications. Paper presented at 5th International Conference on Information Visualization Theory and Applications (IVAPP), Lisbon, Portugal, 5-8 January, 2014 (pp. 195-203). SciTePress
Open this publication in new window or tab >>Visual Exploration of Relationships between Document Clusters
2014 (English)In: IVAPP 2014: Proceedings od the 5th International Conference on Information Visualization Theory and Applications / [ed] Robert S. Laramee, Andreas Kerren, José Braz, SciTePress, 2014, p. 195-203Conference paper, Published paper (Refereed)
Abstract [en]

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

Place, publisher, year, edition, pages
SciTePress, 2014
Keywords
network visualization, multivariate data, clustering, document visualization, text visualization, interaction, visual analytics
National Category
Computer Sciences Human Computer Interaction
Research subject
Computer Science, Information and software visualization
Identifiers
urn:nbn:se:lnu:diva-30369 (URN)2-s2.0-84907386499 (Scopus ID)978-989-758-005-5 (ISBN)
Conference
5th International Conference on Information Visualization Theory and Applications (IVAPP), Lisbon, Portugal, 5-8 January, 2014
Available from: 2013-11-12 Created: 2013-11-12 Last updated: 2018-01-11Bibliographically approved
Jusufi, I., Kerren, A. & Zimmer, B. (2013). Multivariate Network Exploration with JauntyNets. In: Proceedings 2013 17th International Conference on Information Visualisation IV 2013: 16-18 July 2013, London, United Kingdom. Paper presented at 17th International Conference on Information Visualisation (IV '13), 16-18 July 2013, SOAS, University of London, London (pp. 19-27). IEEE
Open this publication in new window or tab >>Multivariate Network Exploration with JauntyNets
2013 (English)In: Proceedings 2013 17th International Conference on Information Visualisation IV 2013: 16-18 July 2013, London, United Kingdom, IEEE, 2013, p. 19-27Conference paper, Published paper (Refereed)
Abstract [en]

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

Place, publisher, year, edition, pages
IEEE, 2013
Keywords
network visualization, multivariate networks, graph drawing, force-based layouts, attribute-driven layout, interaction, visual analytics
National Category
Computer Sciences Computer and Information Sciences
Research subject
Computer Science, Information and software visualization; Computer and Information Sciences Computer Science, Computer Science
Identifiers
urn:nbn:se:lnu:diva-25471 (URN)10.1109/IV.2013.3 (DOI)2-s2.0-84893339437 (Scopus ID)
Conference
17th International Conference on Information Visualisation (IV '13), 16-18 July 2013, SOAS, University of London, London
Available from: 2013-04-29 Created: 2013-04-29 Last updated: 2018-01-11Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-3654-0255

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