Mondrian: An Agile Visualization Framework

Meyer, Michael; Gîrba, Tudor; Lungu, Mircea (2006). Mondrian: An Agile Visualization Framework. In: Burnett, Margaret; Diehl, Stephan; Kraemer, Eileen (eds.) Proceedings of the 2006 ACM symposium on Software visualization (p. 135). New York: Association for Computing Machinery ACM 10.1145/1148493.1148513

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Data visualization is the process of representing data as pictures to support reasoning about the underlying data. For the interpretation to be as easy as possible, we need to be as close as possible to the original data. As most visualization tools have an internal meta-model, which is different from the one for the presented data, they usually need to duplicate the original data to conform to their meta-model. This leads to an increase in the resources needed, increase which is not always justified. In this work we argue for the need of having an engine that is as close as possible to the data and we present our solution of moving the visualization tool to the data, instead of moving the data to the visualization tool. Our solution also emphasizes the necessity of reusing basic blocks to express complex visualizations and allowing the programmer to script the visualization using his preferred tools, rather than a third party format. As a validation of the expressiveness of our framework, we show how we express several already published visualizations and describe the pros and cons of the approach.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

08 Faculty of Science > Institute of Computer Science (INF)
08 Faculty of Science > Institute of Computer Science (INF) > Software Composition Group (SCG)

UniBE Contributor:

Girba, Tudor Adrian

Subjects:

000 Computer science, knowledge & systems
500 Science > 510 Mathematics

ISBN:

1-59593-464-2

Publisher:

Association for Computing Machinery ACM

Language:

English

Submitter:

Factscience Import

Date Deposited:

04 Oct 2013 14:47

Last Modified:

22 Oct 2017 01:45

Publisher DOI:

10.1145/1148493.1148513

BORIS DOI:

10.7892/boris.19412

URI:

https://boris.unibe.ch/id/eprint/19412 (FactScience: 2021)

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