Peter Chapman
Peter Chapman

Dr Peter Chapman

Associate Professor

 0131 455 2962

  P.Chapman@napier.ac.uk

  

Biography

I am lecturer in the Software Engineering Group in the School of Computing. My research interests are in information visualisation, specifically of set-based data, and formal methods. I am the PI on the EPSRC Grant "Visual Justifications for Ontologies", which investigates whether creating diagrammatic representations of ontology justifications could help ontology engineers repair incoherence.

Roles in the community
Program Chair of Visual Languages and Computing (VLC) 2016Publications Chair and PC member of Visual Languages and Human-Centric Computing (VL/HCC) 2016General co-Chair of Euler Diagrams 2012Set Visualisation and Reasoning (SetVR) steering committee member (2012-2016)
Guest Editor of Journal of Visual Languages and Computing (Special Issue on Euler Diagrams, 2012)

School

Research Groups

Themes

Research Areas

Filter by

Date


19 results

Evaluating Colour in Concept Diagrams

Conference Proceeding
McGrath, S., Blake, A., Stapleton, G., Touloumis, A., Chapman, P., Jamnik, M., & Shams, Z. (2022)
Evaluating Colour in Concept Diagrams. In Diagrammatic Representation and Inference: 13th International Conference, Diagrams 2022, Rome, Italy, September 14–16, 2022, Proceedings (168-184). https://doi.org/10.1007/978-3-031-15146-0_14
This paper is the first to establish the impact of colour on users' ability to interpret the informational content of concept diagrams, a logic designed for ontology engineeri...

Minimising line segments in linear diagrams is NP-hard

Journal Article
Chapman, P., Sim, K., & Hao Chen, H. (2022)
Minimising line segments in linear diagrams is NP-hard. Journal of Computer Languages, 71, Article 101136. https://doi.org/10.1016/j.cola.2022.101136
Linear diagrams have been shown to be an effective method of representing set-based data. Moreover, a number of guidelines have been proven to improve the efficacy of linear d...

Interactivity in Linear Diagrams

Conference Proceeding
Chapman, P. (2021)
Interactivity in Linear Diagrams. In Diagrammatic Representation and Inference: 12th International Conference, Diagrams 2021, Virtual, September 28–30, 2021, Proceedings (449-465). https://doi.org/10.1007/978-3-030-86062-2_47
Linear diagrams have been shown to be an effective method for representing set-based data. Moreover, design principles have been empirically developed that, when followed, imp...

Interactivity In Linear Diagrams Materials [dataset]

Dataset
Chapman, P. (2021)
Interactivity In Linear Diagrams Materials [dataset]. [Dataset]. https://doi.org/10.17869/enu.2021.2748492
This folder contains the: - study materials - participant responses - amalgamated dataset - analysis that form part of the paper: Chapman, Peter (2021) Interactivity in Line...

Drawing Algorithms For Linear Diagrams (Supplementary)

Dataset
Chapman, P., & Sim, K. (2021)
Drawing Algorithms For Linear Diagrams (Supplementary). [Dataset]. https://doi.org/10.17869/enu.2021.2748170
This folder contains the material to go with the article: Peter Chapman, Kevin Sim, Huanghao Chen (2021) Drawing Algorithms for Linear Diagrams. The code, the benchmark set ...

Diagrammatic Representation and Inference: 11th International Conference, Diagrams 2020, Tallinn, Estonia, August 24–28, 2020, Proceedings

Conference Proceeding
(2020)
Diagrammatic Representation and Inference: 11th International Conference, Diagrams 2020, Tallinn, Estonia, August 24–28, 2020, Proceedings. In A. Pietarinen, P. Chapman, L. Bosveld-de Smet, V. Giardino, J. Corter, & S. Linker (Eds.), https://doi.org/10.1007/978-3-030-54249-8
This book constitutes the refereed proceedings of the 11th International Conference on the Theory and Application of Diagrams, Diagrams 2020, held in Tallinn, Estonia, in Augu...

Antipattern comprehension dataset

Dataset
Hou, T., & Chapman, P. (2019)
Antipattern comprehension dataset. [Dataset]. https://doi.org/10.17869/enu.2019.2275783
Comprehension of justifications is known to be difficult for even experienced ontology engineers, and much more so for other stakeholders. In the paper associated with this da...

Debugging Ontologies Dataset

Dataset
Hou, T., & Chapman, P. (2019)
Debugging Ontologies Dataset. [Dataset]. https://doi.org/10.17869/enu.2019.2275806
Visualization has been widely used for the representation of ontologies. However, to the best of our knowledge, visualization has been little employed in ontology debugging. E...

Measuring perceived clutter in concept diagrams dataset

Dataset
Hou, T., & Chapman, P. (2019)
Measuring perceived clutter in concept diagrams dataset. [Dataset]. https://doi.org/10.17869/enu.2019.2275800
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 ha...

The efficacy of Euler diagrams and linear diagrams for visualizing set cardinality using proportions and numbers

Journal Article
Stapleton, G., Chapman, P., Rodgers, P., Touloumis, A., Blake, A., & Delaney, A. (2019)
The efficacy of Euler diagrams and linear diagrams for visualizing set cardinality using proportions and numbers. PLOS ONE, 14(3), https://doi.org/10.1371/journal.pone.0211234
This paper presents the first empirical investigation that compares Euler and linear diagrams when they are used to represent set cardinality. A common approach is to use area...