ScholarsArchive@OSU

Citeable URL: http://ir.library.oregonstate.edu/concern/articles/6q182m92n

This is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Elsevier and can be found at:  http://www.journals.elsevier.com/computers-and-graphics/.

Descriptions

Attribute Name	Values
Creator	Metoyer, Ronald Bezrukova, Katerina Pham, Tuan Spell, Chester
Abstract or Summary	In organizational management, researchers and managers study separations or faultlines that occur in diverse teams when members form subgroups based on the alignment of multiple demographic characteristics. The team faultline concept is operationalized using multivariate cluster analysis—analysts use faultline measures to identify subgroups/clusters in a team and to quantify how subgroups/clusters are separated. Unfortunately, these measures have limited capacity to enable users to observe and explore faultlines and subgroup structure across the examined attributes efficiently. We address this problem and make three contributions. First, we propose a visual representation for communicating faultline information that is based on multiple linked, stacked histograms in an axis-parallel layout. Second, we evaluate the effectiveness of the proposed technique in a controlled user study, comparing it to the two other common multivariate representations of clusters: parallel coordinates and scatter plot matrices. While we chose faultline-related tasks based on the requirements by domain experts in organizational management, the study findings can be generalized to representations and tasks involving distributions of clusters of multivariate objects in mixed-type data. Finally, inspired by geological faultlines, we propose several visual enhancements to stacked histograms to further facilitate the task of identifying “cracks” within work teams.
Resource Type	Article
DOI	10.1016/j.cag.2013.10.009
Date Available	2014-07-02T17:53:26+00:00
Date Issued	2014-02
Citation	Pham, T., Metoyer, R., Bezrukova, K., & Spell, C. (2014). Visualization of cluster structure and separation in multivariate mixed data: A case study of diversity faultlines in work teams. Computers & Graphics, 38, 117-130. doi:10.1016/j.cag.2013.10.009
Series	Computers & Graphics Vol. 38 (2014)
Keyword	stacked histograms evaluation cluster separation functional diversity faultlines user study clustering
Rights Statement	Copyright Not Evaluated
Publisher	Elsevier
Peer Reviewed	Yes
Language	English [eng]
Replaces	http://hdl.handle.net/1957/50022
Additional Information	description.provenance : Made available in DSpace on 2014-07-02T17:53:26Z (GMT). No. of bitstreams: 1 PhamTuanElectricalEngineeringComputerScienceVisualizationClusterStructure.pdf: 768160 bytes, checksum: d4eb2219e4a192204a62ff8220c3a981 (MD5) Previous issue date: 2014-02 description.provenance : Approved for entry into archive by Deanne Bruner(deanne.bruner@oregonstate.edu) on 2014-07-02T17:53:26Z (GMT) No. of bitstreams: 1 PhamTuanElectricalEngineeringComputerScienceVisualizationClusterStructure.pdf: 768160 bytes, checksum: d4eb2219e4a192204a62ff8220c3a981 (MD5) description.provenance : Submitted by Deanne Bruner (deanne.bruner@oregonstate.edu) on 2014-07-02T17:52:55Z No. of bitstreams: 1 PhamTuanElectricalEngineeringComputerScienceVisualizationClusterStructure.pdf: 768160 bytes, checksum: d4eb2219e4a192204a62ff8220c3a981 (MD5)

Relationships

Parents:

This work has no parents.

Last modified

Items

Thumbnail	Title	Date Uploaded	Visibility	Actions
	PhamTuanElectricalEngineeringComputerScienceVisualizationClusterStructure.pdf	2017-07-27	Public	Press to Select an action Download