Pretorius, AJ, Purchase, HC and Stasko, JT (2014) Tasks for multivariate network analysis. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Dagstuhl Seminar , 12-17 May 2013, Dagstuhl Castle, Germany. Springer Verlag, 77 - 95. ISBN: 9783319067926 ISSN: 0302-9743 EISSN: 1611-3349
Abstract
In Chap. 1, a multivariate network was defined as having two important characteristics. First, nodes are connected to each other via links; there is topological structure. Second, being multivariate, nodes and links have attributes associated with them, with these attributes having a value. In this chapter, we describe tasks associated with multivariate networks. We consider a task to be an activity that a user wishes to accomplish by interacting with a visual representation of a multivariate network. This implies that there is user intent [13], and that the network has been presented visually. At the highest level, this intent is usually described as the goal of obtaining insight about the data being studied [6].
Metadata
| Item Type: | Proceedings Paper | 
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| Authors/Creators: | 
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| Copyright, Publisher and Additional Information: | © 2013, Springer. This is an author produced version of a paper published in Lecture Notes in Computer Science. Uploaded in accordance with the publisher's self-archiving policy. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-06793-3_5 | 
| Dates: | 
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| Institution: | The University of Leeds | 
| Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) > Institute for Computational and Systems Science (Leeds) | 
| Depositing User: | Symplectic Publications | 
| Date Deposited: | 10 Nov 2014 12:36 | 
| Last Modified: | 19 Dec 2022 13:28 | 
| Published Version: | http://dx.doi.org/10.1007/978-3-319-06793-3_5 | 
| Status: | Published | 
| Publisher: | Springer Verlag | 
| Identification Number: | 10.1007/978-3-319-06793-3_5 | 
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:80919 | 
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