Graffinity: Visualizing Connectivity in Large Graphs Article Swipe
Ethan Kerzner
,
Alexander Lex
,
Crystal Sigulinsky
,
Timothy Urness
,
Bryan W. Jones
,
Robert E. Marc
,
Miriah Meyer
·
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.1111/cgf.13184
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.1111/cgf.13184
Multivariate graphs are prolific across many fields, including transportation and neuroscience. A key task in graph analysis is the exploration of connectivity, to, for example, analyze how signals flow through neurons, or to explore how well different cities are connected by flights. While standard node‐link diagrams are helpful in judging connectivity, they do not scale to large networks. Adjacency matrices also do not scale to large networks and are only suitable to judge connectivity of adjacent nodes. A key approach to realize scalable graph visualization are queries: instead of displaying the whole network, only a relevant subset is shown. Query‐based techniques for analyzing connectivity in graphs, however, can also easily suffer from cluttering if the query result is big enough. To remedy this, we introduce techniques that provide an overview of the connectivity and reveal details on demand. We have two main contributions: (1) two novel visualization techniques that work in concert for summarizing graph connectivity; and (2) Graffinity, an open‐source implementation of these visualizations supplemented by detail views to enable a complete analysis workflow. Graffinity was designed in a close collaboration with neuroscientists and is optimized for connectomics data analysis, yet the technique is applicable across domains. We validate the connectivity overview and our open‐source tool with illustrative examples using flight and connectomics data.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1111/cgf.13184
- OA Status
- green
- Cited By
- 27
- References
- 41
- Related Works
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- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W2604749705Canonical identifier for this work in OpenAlex
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https://doi.org/10.1111/cgf.13184Digital Object Identifier
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Graffinity: Visualizing Connectivity in Large GraphsWork title
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2017Year of publication
- Publication date
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2017-06-01Full publication date if available
- Authors
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Ethan Kerzner, Alexander Lex, Crystal Sigulinsky, Timothy Urness, Bryan W. Jones, Robert E. Marc, Miriah MeyerList of authors in order
- Landing page
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https://doi.org/10.1111/cgf.13184Publisher landing page
- Open access
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://doi.org/10.1111/cgf.13184Direct OA link when available
- Concepts
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Computer science, Visualization, Graph drawing, Theoretical computer science, Computer graphics (images), Graph, Artificial intelligenceTop concepts (fields/topics) attached by OpenAlex
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27Total citation count in OpenAlex
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2025: 1, 2024: 2, 2023: 3, 2022: 3, 2021: 4Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| primary_location.source.host_organization_name | Wiley |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310320595 |
| primary_location.source.host_organization_lineage_names | Wiley |
| primary_location.license | |
| primary_location.pdf_url | |
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| primary_location.raw_type | journal-article |
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| primary_location.raw_source_name | Computer Graphics Forum |
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| publication_date | 2017-06-01 |
| publication_year | 2017 |
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