This paper discussed the factor to consist a collaborative visual analytics environment. Some of the theory is overlapping with the online community operation. A successful collaboration is an effective division of labor among participants, the author argue three factors here: modularity, granularity, and cost of integration. In other words, the tasks should split, conduct and integrate at a reasonable price. If each of the factors is too expensive, it may hard to be a success collaboration scenario. For modularity factor, the author provides an information visualization reference model; this model helps for decomposing the visualization process into data acquisition and representation visual encoding, display, and interaction. Each of the components can be a reasonable module to start the collaborative works. For granularity factor, the author discussed the sensemaking model, for instance, in cooperative scenarios, the collaborator can immediate benefit from the actions of others. It is hard to facilitate cooperation if a lack of the incentive.
The ground sense principle is listing below:
- discussion models, awareness
- Reference & deixis, pointing
- Incentives & engagement, personal relevance, social-psychological incentives, gameplay,
- Identity & trust & reputation, identity presentation
- Group dynamics, management, size, diversity
- Consensus and decision making, information distribution & presentation
A good reference to consider the collaborative theory in different scenarios, e.g. business intelligence system. For social analysis, a extend reading at [2].
Reference
- Heer, Jeffrey, and Maneesh Agrawala. "Design considerations for collaborative visual analytics." Information visualization 7.1 (2008): 49-62.
- Wattenberg, Martin, and Jesse Kriss. "Designing for social data analysis." IEEE transactions on visualization and computer graphics 12.4 (2006): 549-557.
No comments:
Post a Comment