SenseMap: supporting browser-based online sensemaking through analytic provenance
Conference paper
Nguyen, P., Xu, K., Bardill, A., Salman, B., Herd, K. and Wong, B. 2016. SenseMap: supporting browser-based online sensemaking through analytic provenance. VIS 2016: IEEE Visualization Conference. Baltimore, Maryland, USA 23 - 28 Oct 2016 Institute of Electrical and Electronics Engineers (IEEE). pp. 91-100 https://doi.org/10.1109/vast.2016.7883515
Type | Conference paper |
---|---|
Title | SenseMap: supporting browser-based online sensemaking through analytic provenance |
Authors | Nguyen, P., Xu, K., Bardill, A., Salman, B., Herd, K. and Wong, B. |
Abstract | Sensemaking is described as the process in which people collect, organize and create representations of information, all centered around some problem they need to understand. People often get lost when solving complicated tasks using big datasets over long periods of exploration and analysis. They may forget what they have done, are unaware of where they are in the context of the overall task, and are unsure where to continue. In this paper, we introduce a tool, SenseMap, to address these issues in the context of browser-based online sensemaking. We conducted a semi-structured interview with nine participants to explore their behaviors in online sensemaking with existing browser functionality. A simplified sensemaking model based on Pirolli and Card's model is derived to better represent the behaviors we found: users iteratively collect information sources relevant to the task, curate them in a way that makes sense, and finally communicate their findings to others. SenseMap automatically captures provenance of user sensemaking actions and provides multi-linked views to visualize the collected information and enable users to curate and communicate their findings. To explore how SenseMap is used, we conducted a user study in a naturalistic work setting with five participants completing the same sensemaking task related to their daily work activities. All participants found the visual representation and interaction of the tool intuitive to use. Three of them engaged with the tool and produced successful outcomes. It helped them to organize information sources, to quickly find and navigate to the sources they wanted, and to effectively communicate their findings. |
Conference | VIS 2016: IEEE Visualization Conference |
Page range | 91-100 |
ISBN | |
Hardcover | 9781509056613 |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Publication dates | |
23 Oct 2016 | |
Online | 23 Mar 2017 |
Publication process dates | |
Deposited | 16 Jun 2017 |
Accepted | 13 Jul 2016 |
Output status | Published |
Accepted author manuscript | |
Copyright Statement | © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Digital Object Identifier (DOI) | https://doi.org/10.1109/vast.2016.7883515 |
Language | English |
Book title | 2016 IEEE Conference on Visual Analytics Science and Technology (VAST) |
https://repository.mdx.ac.uk/item/87055
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