Call for Papers: Special Issue on Multi-level Graph Representations for Big Data in Science
CG&A seeks submissions for this upcoming special issue.
 

For centuries, cartographic maps have guided human exploration. While being rather imperfect initially, they helped explorers find promised lands and return home safely. Recent advances in data, algorithms, and computing infrastructures make it possible to map humankind’s collective scholarly knowledge and technology expertise by using topic maps on which “continents” represent major areas of science (e.g., mathematics, physics, or medicine) and zooming reveals successively more detailed subareas. Basemaps of science and technology are generated by analyzing citations links between millions of publications and/or patents. “Data overlays” (e.g., showing all publications by one scholar, institution, or country or the career trajectory of a scholar as a pathway) are generated by science-locating relevant publication records based on topical similarity. Despite the demonstrated utility of such maps, current approaches do not scale to the hundreds of millions of data records now available. The main challenge is designing efficient and effective methods to visualize and interact with more than 100 million scholarly publications at multiple levels of resolution.

This special issue invites researchers in cartography, data visualization, science of science, graph drawing, and other domains to submit novel and promising new research on graph mining and layout algorithms and their application to the development of science mapping standards and services. Topics of interest include:

  • Science of science user needs and applications
  • Efficient multi-level graph algorithms
  • Network visualizations
  • Effective user interfaces to large-scale data visualizations

Deadlines

Submissions due: 29 December 2021
Publication: July/August 2022

Submission Guidelines

For author information on how to submit a manuscript, visit the Author Information page. Please submit your papers through the ScholarOne online system (https://mc.manuscriptcentral.com/cs-ieee) and be sure to select the special-issue name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts, to the ScholarOne portal. If requested, abstracts should be sent by email to the guest editors directly.

Questions?

Contact the guest editors at cga4-2022@computer.org.

Guest editors:

  • Katy Börner, Indiana University, Bloomington, US
  • Andreas Bueckle, Indiana University, Bloomington, US
  • Stephen G. Kobourov, University of Arizona, Tucson, US
Special Issue on Multi-level Graph Representations for Big Data in Science
29 December 2021