How to display group information on node-link diagrams: An evaluation
- Submitting institution
-
City, University of London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 769
- Type
- D - Journal article
- DOI
-
10.1109/TVCG.2014.2315995
- Title of journal
- IEEE Transactions on Visualization and Computer Graphics
- Article number
- -
- First page
- 1530
- Volume
- 20
- Issue
- 11
- ISSN
- 1077-2626
- Open access status
- Out of scope for open access requirements
- Month of publication
- April
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
-
- Citation count
- 30
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Output published in the most prestigious journal in the field and presented at IEEE Information Visualization (A* CORE - “flagship conference, a leading venue in a discipline area”), 2014, Paris - 25% acceptance rate. Significant as the first comprehensive, quantitative study to compare visualisations of data that is both relational and grouped using non-synthetic data, many tasks, and all state of the art visualisations applicable to such data. Led to Dagstuhl invitation (15481) to contribute to an agenda for crowdsourced studies in Visualization (“Crowdsourcing in Information Visualization: Promises and Pitfalls”). Highly influential for Kobourov et al group (U.Arizona).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
