Summary:
According to the authors of this research paper,
“collaboration has been named one of the grand challenges for visualization and
visual analytics.” Traditionally, visualization and visual analytic tools were
designed for a single person on a desktop computer. However, today’s world
calls for increased visualization tools that encompass collaboration and communication.
Experts and non-experts can take advantage of collaborative visualization
scenarios to learn from one another’s analysis processes and viewpoints. The
authors define collaborative visualization as “the shared use of computer-supported,
[interactive], visual representations of data by more than one person with the
common goal of contribution to joint information processing activities.” The
term social data analysis has also been created to describe the different
social interactions, which is central to collaborative visualization.
There are three main levels of engagement where digital
systems support collaborative visualizations: viewing, interacting/exploring,
and sharing/creating. Software systems like PowerPoint and videoconferencing
allow people to learn, discuss, interpret and form decisions on a certain set
of information. People that use and share interactive visualization software
can communicate through chat, comments, email, or video/audio links. Utilizing
these features allows discussions of alternative interpretations, and multiple
viewpoints to emerge. Programs such as Many Eyes, allow users to upload and
create new datasets for the community to explore. The authors present this argument that the
purpose of having an online collaboratory (data warehouse) “is to focus the
collective effort of the group in order to produce significant and useful
methods.” However, it is important for the users of the program to understand the
overall data, the user space and the application space.
Computer-supported collaborative visualization software helps
decision makers: distill knowledge through mining large multi-dimensional
datasets, run models and simulation to explore the consequences of particular
actions, communicate results, scenarios, and opinions to other stakeholders,
and discuss debate, and develop support for specific courses of action. In
addition, collaborative technology supports the social interaction of large
audiences, which allows for a range of backgrounds, connections and goals. This
provides the group with an environment where individuals can generate ideas and
analysis alone or together.
Critique:
This article gave a broad overview of collaborative
visualization and the areas where future research should be addressed. However,
the authors did not integrate the challenges of collaborative visualization throughout
the piece, instead they arranged it in future research. As collaborative
visualization becomes utilized as an everyday tool, it will be important for
people to learn these programs at school or at work. Knowing how these analytic
tools work will be key to group interactions and their analyses.
Source:
Isenberg,
P., Elmqvist, N., Scholtz, J., Cernea, D., Ma, K.-L., & Hagen, H. (2011).
Collaborative visualization: Definition, challenges, and research agenda. Information
Visualization, 10(4), 310–326. doi:10.1177/1473871611412817
Posts
Joy,
ReplyDeleteWhich of the three levels of collaborative visualization have you found yourself spending the most time doing?
Did this article cite any previous studies that even warrant future research into collaborative visualization. For instance, does it generate more ideas in brainstorming stages?
ReplyDeleteHarrison,
ReplyDeleteOut of the three levels of collaborative visualization, I have used viewing and interacting/exploring the most.
Kyle,
The authors of the study presented a large section on future research, however, they did not go into past studies on brainstorming stages. The study also lacked a coherent focus on the different types of future research.