Visual Analysis of Large Graphs: State‐of‐the‐Art and Future Research Challenges

Landesberger, Tatiana von; Kuijper, Arjan; Schreck, Tobias; Kohlhammer, Jörn; Wijk, Jarke J. van; Fekete, Jean-Daniel; Fellner, Dieter W.

doi:10.1111/j.1467-8659.2011.01898.x

Cited by 446 publications

(321 citation statements)

References 186 publications

(289 reference statements)

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“…That is, to the general public this feature allows a very interesting view of their entire network of contacts (and the relationships between their followers and who they follow), while for users interested mainly in their followers' activity, with hundreds (and even thousands) of them, this way of viewing the network seemed useless, because the amount of users shown did not allow a clear view of these connections. In this case, alternative techniques for the visual analysis of large graphs [12] could be presented, but that was out of the scope of this research.…”

Section: Discussionmentioning

confidence: 99%

Exploring Twitter Interactions through Visualization Techniques: Users Impressions and New Possibilities

Rotta

Lemos

Cunha

et al. 2013

Human-Computer Interaction – INTERACT 2013

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Abstract. Social networking websites have been taking a huge space on the Internet. With millions of members spread across the world, these services connect their users through "friendship" relations, and within a short period of time the information is disseminated in the network. Considering Twitter, we investigated how standard techniques of information visualization can improve the analysis of its users' behavior, i.e. the group of people who most closely relate, and the frequency and type of messages they send. This investigation was done through user's studies with a set of visualization techniques implemented in an interactive system prototype.

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Section: Discussionmentioning

confidence: 99%

Exploring Twitter Interactions through Visualization Techniques: Users Impressions and New Possibilities

Rotta

Lemos

Cunha

et al. 2013

Human-Computer Interaction – INTERACT 2013

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“…Many interactive visualization approaches for various data types could be used, and a comprehensive overview is beyond the scope of this paper. The reader is referred to reviews, e.g., [56], [57], [58].…”

Section: Visual Assessment Of Input Datamentioning

confidence: 99%

Visualization System Requirements for Data Processing Pipeline Design and Optimization

Landesberger

Fellner

Ruddle

2017

IEEE Trans. Visual. Comput. Graphics

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Abstract-The rising quantity and complexity of data creates a need to design and optimize data processing pipelines -the set of data processing steps, parameters and algorithms that perform operations on the data. Visualization can support this process but, although there are many examples of systems for visual parameter analysis, there remains a need to systematically assess users' requirements and match those requirements to exemplar visualization methods. This article presents a new characterization of the requirements for pipeline design and optimization. This characterization is based on both a review of the literature and first-hand assessment of eight application case studies. We also match these requirements with exemplar functionality provided by existing visualization tools. Thus, we provide end-users and visualization developers with a way of identifying functionality that addresses data processing problems in an application. We also identify seven future challenges for visualization research that are not met by the capabilities of today's systems.

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“…Many tools and techniques have been developed to facilitate discovery; Herman et al covered much of the initial work in graph visualizations [62]. However, a more recent survey [63] by Landesberger et al investigated the rich variety of new graph visualization methods since 2000. Both of these works focus primarily on static graphs.…”

Section: Graph Exploration and Visualizationmentioning

confidence: 99%

Scalable graph exploration and visualization: Sensemaking challenges and opportunities

Pienta

Abello

Kahng

et al. 2015

2015 International Conference on Big Data and Smart Computing (BIGCOMP)

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Abstract-Making sense of large graph datasets is a fundamental and challenging process that advances science, education and technology. We survey research on graph exploration and visualization approaches aimed at addressing this challenge. Different from existing surveys, our investigation highlights approaches that have strong potential in handling large graphs, algorithmically, visually, or interactively; we also explicitly connect relevant works from multiple research fields -data mining, machine learning, human-computer ineraction, information visualization, information retrieval, and recommender systems -to underline their parallel and complementary contributions to graph sensemaking.We ground our discussion in sensemaking research; we propose a new graph sensemaking hierarchy that categorizes tools and techniques based on how they operate on the graph data (e.g., local vs global). We summarize and compare their strengths and weaknesses, and highlight open challenges. We conclude with future research directions for graph sensemaking.

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Visual Analysis of Large Graphs: State‐of‐the‐Art and Future Research Challenges

Abstract: The analysis of large graphs plays a prominent role in various fields of research and is relevant in many important

Cited by 446 publications

References 186 publications

Exploring Twitter Interactions through Visualization Techniques: Users Impressions and New Possibilities

Exploring Twitter Interactions through Visualization Techniques: Users Impressions and New Possibilities

Visualization System Requirements for Data Processing Pipeline Design and Optimization

Scalable graph exploration and visualization: Sensemaking challenges and opportunities

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