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On the faithfulness of graph visualizations

Quan Nguyen, Peter Eades, Seok-Hee Hong
2013 2013 IEEE Pacific Visualization Symposium (PacificVis)  
Readability criteria have been commonly used to measure the quality of graph visualizations. In this paper we argue that readability criteria, while necessary, are not sufficient.  ...  We propose a new kind of criterion, generically termed faithfulness, for evaluating graph layout methods.  ...  Conclusion This paper has introduced the concept of faithfulness for graph visualization.  ... 
doi:10.1109/pacificvis.2013.6596147 dblp:conf/apvis/NguyenEH13 fatcat:cadu6oh3kvf6rileinvzg7awie

On the Faithfulness of Graph Visualizations [chapter]

Quan Nguyen, Peter Eades, Seok-Hee Hong
2013 Lecture Notes in Computer Science  
Faithfulness Model A graph visualization is faithful if the underlying network data and the visual representation are logically consistent.  ...  The model extends the van Wijk's model Fig. 1 . 1 Graph visualization model of the whole knowledge discovery process, from data to visualization to human W. Didimo and M.  ... 
doi:10.1007/978-3-642-36763-2_55 fatcat:jqb57jag7ncb7ayqxbxec2ekwy

Towards Faithful Graph Visualizations [article]

Quan Hoang Nguyen, Peter Eades
2018 arXiv   pre-print
We propose a new kind of criteria, namely faithfulness, to evaluate the quality of graph layouts.  ...  We show examples of common visualization techniques, such as multidimensional scaling, edge bundling and several other visualization metaphors for the study of faithfulness.  ...  On the other hand, a (partial) transformation of the local parts of the graphs may increase readability of these parts of the graphs, yet may degrade faithfulness of other parts of the graphs.  ... 
arXiv:1701.00921v2 fatcat:pn4pt56zmzdc3feyqu2bsvodma

What is a good diagram? (Revisited)

Peter Eades
2014 2014 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)  
Such models become more useful when the graph model is represented as a diagram, because visualization of a graph enables humans to understand the underlying model.  ...  Graphs have been broadly used to model binary relations since the beginning of Computer Science. Nodes represent entities, and edges represent relationships between entities.  ...  Using a pipeline model of graph visualization, we classify quality metrics into "readability" metrics and "faithfulness" metrics.  ... 
doi:10.1109/vlhcc.2014.6883010 fatcat:muhzrrifpbhltcs3metkprasuy

Obtaining Faithful Interpretations from Compositional Neural Networks [article]

Sanjay Subramanian, Ben Bogin, Nitish Gupta, Tomer Wolfson, Sameer Singh, Jonathan Berant, Matt Gardner
2020 arXiv   pre-print
In this work, we propose and conduct a systematic evaluation of the intermediate outputs of NMNs on NLVR2 and DROP, two datasets which require composing multiple reasoning steps.  ...  However, prior work implicitly assumed that the structure of the network modules, describing the abstract reasoning process, provides a faithful explanation of the model's reasoning; that is, that all  ...  Acknowledgements We thank members of UCI NLP, TAU NLP, and the AllenNLP teams as well as Daniel Khashabi for comments on earlier drafts of this paper.  ... 
arXiv:2005.00724v2 fatcat:xtfi2ikjfncabon7v7zumwig44

Visualization of Contributions to Open-Source Projects [article]

Andreas Schreiber
2020 arXiv   pre-print
We achieve this by recording provenance of the development process and use graph drawing on the resulting provenance graph.  ...  Our graph drawings show, which developers are jointly changed the same files -- and to what extent -- which we show at Germany's COVID-19 exposure notification app 'Corona-Warn-App'.  ...  We already work on using the provenance data for non-visual analytics of open-source projects.  ... 
arXiv:2010.08874v1 fatcat:fzb2qkggmjeydjexqnn5h4m4uu

More faithfulness graph embedding

Alaa Najim
2015 International Journal of Applied Mathematical Research  
Continuity Trustworthy Graph Embedding (CTGE) is new method we have introduced in this paper to improve the faithfulness of the graph visualization.  ...  Several experiments on real graph data sets are applied to test the effectiveness and efficiency of the proposed method, which showed CTGE generates highly faithfulness graph representation when compared  ...  Introduction Graph visualization is a sub-field of information visualization uses to visualize the set of data and the related information in a graph.  ... 
doi:10.14419/ijamr.v4i2.4419 fatcat:ex3ttjyjvfeydnu3k2v5i5zrru

Faithful Explanations for Deep Graph Models [article]

Zifan Wang, Yuhang Yao, Chaoran Zhang, Han Zhang, Youjie Kang, Carlee Joe-Wong, Matt Fredrikson, Anupam Datta
2022 arXiv   pre-print
This paper studies faithful explanations for Graph Neural Networks (GNNs). First, we provide a new and general method for formally characterizing the faithfulness of explanations for GNNs.  ...  Third, we introduce k-hop Explanation with a Convolutional Core (KEC), a new explanation method that provably maximizes faithfulness to the original GNN by leveraging information about the graph structure  ...  We discuss the examples of distribution D for graph data in Sec. 3. Faithfulness of Graph Explanations This section provides a set of characterizations on the faithfulness of graph explanations.  ... 
arXiv:2205.11850v1 fatcat:i4zn4wtprrfctmlvxsjiwlfgce

Explainability in Graph Neural Networks: An Experimental Survey [article]

Peibo Li, Yixing Yang, Maurice Pagnucco, Yang Song
2022 arXiv   pre-print
In this survey, we give an overview of the state-of-the-art GNN explainability methods and how they are evaluated.  ...  Graph neural networks (GNNs) have been extensively developed for graph representation learning in various application domains.  ...  This equation evaluates the faithfulness of the explanation to the model by measuring the difference between predictions from the graphs removing the important subgraphs and the original input graphs.  ... 
arXiv:2203.09258v1 fatcat:enbno22xrfdsnkcvhpse4z36p4

New Quality Metrics for Dynamic Graph Drawing [article]

Amyra Meidiana, Seok-Hee Hong, Peter Eades
2020 arXiv   pre-print
We first validate the effectiveness of our new metrics using deformation experiments. Then we compare various graph drawing algorithms using our metrics.  ...  Namely, we present a new framework for change faithfulness metrics for dynamic graph drawings, which compare the ground truth change in dynamic graphs and the geometric change in drawings.  ...  Faithfulness metrics measure how faithfully the ground truth about the data is displayed in the visualization [29] .  ... 
arXiv:2008.07764v2 fatcat:h4j7ucynxrcpbik72fbrighrgq

GLANCE: Global to Local Architecture-Neutral Concept-based Explanations [article]

Avinash Kori, Ben Glocker, Francesca Toni
2022 arXiv   pre-print
Most of the current explainability techniques focus on capturing the importance of features in input space.  ...  However, given the complexity of models and data-generating processes, the resulting explanations are far from being 'complete', in that they lack an indication of feature interactions and visualization  ...  Acknowledgements This work was supported by UKRI [grant number EP/S023356/1], in the UKRI Centre for Doctoral Training in Safe and Trusted AI.  ... 
arXiv:2207.01917v1 fatcat:2g5vp2uyund5lh423uva5cgbve

Visualization of contributions to open-source projects

Andreas Schreiber
2020 Proceedings of the 13th International Symposium on Visual Information Communication and Interaction  
For that, we record the provenance of the development process and draw the resulting property graph.  ...  Our graph drawings show, which developers are jointly changed the same files what we apply to Germany's COVID-19 exposure notification app 'Corona-Warn-App'.  ...  Graph Drawing Graph Data Export GRAPH VISUALIZATION We visualize parts of the property graph with Gephi [1] .  ... 
doi:10.1145/3430036.3430057 fatcat:4eiyxq56zjdjrhtyiwi6r5jhay

PATTERN ANALYSIS OF A DIABETES SELF-MANAGEMENT MHEALTH APPLICATION

S Wu, P Lee
2018 Innovation in aging  
Edge bundling is a promising graph visualization approach to simplifying the visual result of a graph drawing. Plenty of edge bundling methods have been developed to generate diverse graph layouts.  ...  We first illustrate the advantage of edge bundling visualizations for large graphs, and pinpoint the ambiguity resulting from drawing results.  ...  A visualization is information faithful if the visualization can uniquely represent the original graph.  ... 
doi:10.1093/geroni/igy023.1617 fatcat:ek2zuv5hb5fspm325key4udf6q

An Information-Theoretic Framework for Evaluating Edge Bundling Visualization

Jieting Wu, Feiyu Zhu, Xin Liu, Hongfeng Yu
2018 Entropy  
Edge bundling is a promising graph visualization approach to simplifying the visual result of a graph drawing. Plenty of edge bundling methods have been developed to generate diverse graph layouts.  ...  We first illustrate the advantage of edge bundling visualizations for large graphs, and pinpoint the ambiguity resulting from drawing results.  ...  A visualization is information faithful if the visualization can uniquely represent the original graph.  ... 
doi:10.3390/e20090625 pmid:33265714 fatcat:plog43nmv5cfvpv3zdbe34ito4

Drawing Big Graphs Using Spectral Sparsification [chapter]

Peter Eades, Quan Nguyen, Seok-Hee Hong
2018 Lecture Notes in Computer Science  
We investigate the use of spectral sparsification to produce good visual representations of big graphs. We evaluate spectral sparsification approaches on real-world and synthetic graphs.  ...  Spectral sparsification is a general technique developed by Spielman et al. to reduce the number of edges in a graph while retaining its structural properties.  ...  The challenge for the proxy graph approach is to ensure that the proxy graph is a good representation of the original graph; for visualization, we want the drawing of the proxy graph to be faithful [21  ... 
doi:10.1007/978-3-319-73915-1_22 fatcat:rp7dtzl4hjczbnhlgt5ojsmgje
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