Please use this identifier to cite or link to this item: http://hdl.handle.net/1880/45784
Title: A Framework for Visual Information Analysis
Authors: Neumann, Petra
Tang, Anthony
Carpendale, Sheelagh
Keywords: Computer Science
Issue Date: 12-Jul-2007
Abstract: To design information visualization tools that support users needs, we need to understand how users engage with information visualizations in their analysis process. With the rapid growth in size and complexity of datasets, the practicality of an individual analyzing an entire dataset is becoming unrealistic. Instead, the expertise to make informed decisions about these information-rich datasets is often best accomplished by a team. However, there exist relatively few models that describe the visual analysis process, and only few studies that explore the differences between how individuals and teams use visualizations. We present an observational study where we explored the information analysis process of groups and individuals in the context of visual information. From the analysis of our study, we derive a framework that captures the activities of co-located teams and individuals engaged in information analysis. This framework has implications for the design, heuristic evaluation, and analysis of both collaborative and single-user digital information visualization tools.
URI: http://hdl.handle.net/1880/45784
Appears in Collections:Carpendale, Sheelagh

Files in This Item:
File Description SizeFormat 
2007-871-23.pdf3.65 MBAdobe PDFView/Open
2007-871-23.ps5.93 MBPostscriptView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.