# Well-formed eigenfactor

_Visualizing information flow in science_

Published: 2009-02-01

Live project: [http://well-formed.eigenfactor.org](http://well-formed.eigenfactor.org)

How can we map the flow of ideas in science? The Eigenfactor project is a academic research project by the Bergstrom lab in the Department of Biology at the University of Washington. Based on their data, I developed information-aesthetic data visualizations based on citation patterns between scientific journals.

## Key visuals

- Full radial diagram of the journal citation network, colored by scientific field with hierarchically bundled links
- Radial citation diagram highlighting the journal Nature and all its citation links reaching across fields
- Radial citation diagram highlighting the journal Neuron and its citation connections
- Radial citation diagram highlighting the Mathematics cluster and its mostly internal, blue citation links
- Radial citation diagram highlighting Physical Review Letters and its links to physics and chemistry journals
- Radial citation diagram highlighting the Astronomy and Astrophysics cluster and its citation links
- Alluvial diagram of journal clusters from 1997 to 2005, showing shifts in Eigenfactor score and grouping
- Alluvial diagram tracing the journal Cell from 1999, with Neuron's 2005 Eigenfactor score of 0.003542 shown
- Alluvial diagram tracing Journal of Cognitive Neuroscience across years, showing its shifting cluster membership
- Treemap of 400 journals grouped and colored by field, each square sized by its Eigenfactor score
- Treemap with magnetic pins showing citation flow to and from Proceedings of the National Academy of Sciences
- Treemap highlighting Applied Physics Letters and the journals citing it, with all others dimmed
- Map detail with magnification lens over biomedical journals such as J Biol Chem and Cell
- Map highlighting the journal Science and its radiating citation connections to other journals

## Visualizing the flow of ideas

"well–formed.eigenfactor" presents interactive visualizations to explore emerging patterns in scientific citation networks. The Eigenfactor project calculates a measure of importance for individual journals – the Eigenfactor score – as well as measures of citation flow and a hierarchical clustering based thereon. I turned this information into a set of four information–aesthetic visualizations, each highlighting different aspects of the data.

In visualizations of citation networks, both ball–and-stick–like network representations as well as maps are prevalent. Our project extends the visual vocabulary in this area: on the one hand, by re-purposing existing techniques, such as radial edge bundling and treemaps; on the other hand, by inventing novel approaches like “magnetic pins” as flow indicators and an “alluvial” diagram to represent change over time in cluster structure.

The visualizations feature four different perspectives on the data:

## Citation patterns

![Radial citation diagram detail with journals grouped into colored scientific fields and hierarchically bundled citation links]()

This radial diagram gives an overview of the citation network. The colors mark large groups of journals, further subdivided into fields in the outer ring; segments of the inner ring represent the journals, scaled by Eigenfactor Score. The citation links follow the cluster structure, using the hierarchical edge bundling technique.

## Change over time:

![Alluvial diagram detail of pink and green flowing bands tracking journals' Eigenfactor score and cluster changes across years]()

This “alluvial” diagram displays changes in Eigenfactor score and clustering over time. The journals are grouped vertically by their cluster structure and horizontally by year. Bars belonging to the same journal are connected. Clicking highlights a journal over the years, and all clusters it has been part of, to track changes of influence and cluster structure.

## Clustering

![Treemap of journals sized by Eigenfactor score, with magnetic-pin indicators showing incoming and outgoing citation flow]()

Based on the squarified treemap layout algorithm, this visualization features “magnetic pins” to indicate both incoming and outgoing citation
flow for any selected journal. The size of square corresponds to the Eigenfactor score of the corresponding journal.

## Map

![Map detail of journals positioned by citation similarity, with sized nodes and radiating citation links]()

This map visualization puts journals, which frequently cite each other, closer together. You can drag the white magnification lens around to enlarge a part of the map for closer inspection. Clicking one of the nodes will highlight all its citation connections.

## Data

We use a subset of the citation data from Thomson Reuters' Journal Citation Reports 1997–2005. For the visualizations, 400 journals with their ca. 13’000 citation edges were selected, ensuring a coverage of the top journals in each field.

## Credits

Visualization by Moritz Stefaner, in collaboration with Martin Rosvall, Jevin West and Carl Bergstrom at the Bergstrom Lab, University of Washington, 2009

---
[View on truth-and-beauty.net](https://truth-and-beauty.net/projects/well-formed-eigenfactor)