Tie Hou
Measuring perceived clutter in concept diagrams dataset
Hou, Tie; Chapman, Peter
Abstract
Clutter in a diagram can be broadly defined as how visually complex the diagram is. It may be that different users perceive clutter in different ways, however. Moreover, it has been shown that, for certain types of diagrams and tasks, an increase in clutter negatively affects task performance, making quantifying clutter an important problem. In the paper associated with this dataset, we investigated the perceived clutter in concept diagrams, a visual language used for representing ontologies. Using perceptual theory and existing research on clutter for other diagrams, we proposed five plausible measures for assigning clutter scores to concept diagrams. By performing an empirical study we evaluated each of these proposed measures against participants' rankings of diagrams. Whilst more than one of our measures showed strong correlation with perceived clutter, our results suggest that a measure based on the number of points where lines cross is the most appropriate way to quantify clutter for concept diagrams. This dataset includes all the diagrams, study materials, and output from the study. It was collected in summer 2016, with the paper published in autumn 2016.
Citation
Hou, T., & Chapman, P. (2019). Measuring perceived clutter in concept diagrams dataset. [Data]. https://doi.org/10.17869/enu.2019.2275800
Online Publication Date | Nov 1, 2019 |
---|---|
Publication Date | Nov 1, 2019 |
Deposit Date | Oct 31, 2019 |
Publicly Available Date | Nov 1, 2019 |
Publisher | Edinburgh Napier University |
DOI | https://doi.org/10.17869/enu.2019.2275800 |
Public URL | http://researchrepository.napier.ac.uk/Output/2275800 |
Collection Date | Sep 14, 2016 |
Files
Readme
(237 bytes)
Other
Licence
https://creativecommons.org/licenses/publicdomain
Copyright Statement
This file is released under a Creative Commons 1.0 Universal (CC0 1.0)
Public Domain Dedication.
ForWorktribeVLHCC2016
(3.9 Mb)
Archive
Licence
https://creativecommons.org/licenses/publicdomain
Copyright Statement
This data is released under a Creative Commons 1.0 Universal (CC0 1.0)
Public Domain Dedication.
You might also like
Antipattern comprehension dataset
(2019)
Data
Debugging Ontologies Dataset
(2019)
Data
Downloadable Citations
About Edinburgh Napier Research Repository
Administrator e-mail: repository@napier.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search