Information Visualization

About

The 564 papers published in Information Visualization in the last decades have received a total of 12.7k indexed citations. Papers published in Information Visualization usually cover Computer Vision and Pattern Recognition (419 papers), Artificial Intelligence (147 papers) and Signal Processing (91 papers) specifically the topics of Data Visualization and Analytics (397 papers), Data Management and Algorithms (67 papers) and Complex Network Analysis Techniques (53 papers). The most active scholars publishing in Information Visualization are Ben Shneiderman, Martin J. Eppler, Natalia Andrienko, Gennady Andrienko, Chaomei Chen, John Stasko, Matthew O. Ward, Niklas Elmqvist, Colin Ware and Alberto J. Cañas.

In The Last Decade

Information Visualization

516 papers receiving 11.9k citations

Countries where authors publish in Information Visualization

Since Specialization
Citations

This map shows the geographic impact of research published in Information Visualization. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers published in Information Visualization with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Information Visualization more than expected).

Fields of papers published in Information Visualization

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Information Visualization. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Information Visualization.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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2026