History Tools for Collaborative Visualization (original) (raw)
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Collaborative Visual Analytics with Session Histories
The increasing power of computers has allowed the collection and visualization of more complex datasets than ever before. This has increased the complexity of exploring and interpreting these datasets. Often times more than one person must collaborate in order to better understand the data and make more informed decisions. The increasing network bandwidth and power of tools available for web browsers have made it possible to work with highly interactive collaborative visual analytics software running in web browsers. We are developing an open source web based collaborative visualization tool with session histories. We discuss design concepts in this paper.
Exploiting analysis history to support collaborative data analysis
2015
Coordination is critical in distributed collaborative analysis of multidimensional data. Collaborating analysts need to understand what each person has done and what avenues of analysis remain uninvestigated in order to effectively coordinate their efforts. Although visualization history has the potential to communicate such information, common history representations typically show sequential lists of past work, making it difficult to understand the analytic coverage of the data dimension space (i.e. which data dimensions have been investigated and in what combinations). This makes it difficult for collaborating analysts to plan their next steps, particularly when the number of dimensions is large and team members are distributed. We introduce the notion of representing past analysis history from a dimension coverage perspective to enable analysts to see which data dimensions have been explored in which combinations. Through two user studies, we investigated whether 1) a dimension ...
2003
Many groupware systems now allow people to converse and casually interact through their computers in quite rich ways—through text, images, video, artifact sharing and so on. If these interactions are logged, we can offer these multimedia histories to a person in a manner that makes them easy to review. This is potentially beneficial for group members wishing to find and reflect on their past interactions, and for researchers investigating the nuances of online communities. Yet because we have little knowledge of what people would actually do with these histories, designing an effective history review system is difficult. Consequently, we conducted a user study, where people explored real data from an online community. Our study identified a set of tasks that people would do if they could review these histories of casual interaction. It also produced a list of parameters pertinent to how we could visualize these historical records in a tool. With the increasing popularity of computer...
Proceedings of the 16th International Conference on 3D Web Technology - Web3D '11, 2011
Collaborative visualization is becoming more and more important, given the distributed and mobile nature of teams. Current visualization systems are often still monolithic and not flexible enough for todays users; they have not kept pace with improvements in other areas of information technology (mobile networking, compute-ondemand). With this in mind, we review current visualization systems (covering CAE collaborative visualization, multi-user online games and solutions to bring collaboration to existing applications / processes) and contrast against the latest related advances in technology: new hardware platforms, availability of cloud computing, mobile network capabilities and web browser functionality. We then analyse how these advances could impact on future collaborative visualization systems and discuss potential areas of improvement to existing systems.
Coconuttrix: Collaborative retrofitting for information visualization
2009
I n human-computer interaction, much of the literature on designing and evaluating colocated collaboration revolves around dedicated technology in the form of touch-sensitive displays, input devices, or software. Each of these has advantages for certain collaboration environments and situations. Adapting an application to colocated collaboration might appear to require using specialized hardware and reimplementing the application, for example, to ■ scale to specific presentation spaces such as large highresolution wall or tabletop displays, ■ employ head-mounted displays or CAVEs (Cave Automatic Virtual Environments), or ■ react to other forms of input such as direct touch, gloves, or pens.
A great corpus of studies reports empirical evidence of how information visualization supports comprehension and analysis of data. The benefits of visualization for synchronous group knowledge work, however, have not been addressed extensively. Anecdotal evidence and use cases illustrate the benefits of synchronous collaborative information visualization, but very few empirical studies have rigorously examined the impact of visualization on group knowledge work. We have consequently designed and conducted an experiment in which we have analyzed the impact of visualization on knowledge sharing in situated work groups. Our experimental study consists of evaluating the performance of 131 subjects (all experienced managers) in groups of 5 (for a total of 26 groups), working together on a real-life knowledge sharing task. We compare (1) the control condition (no visualization provided), with two visualization supports: (2) optimal and (3) suboptimal visualization (based on a previous survey). The facilitator of each group was asked to populate the provided interactive visual template with insights from the group, and to organize the contributions according to the group consensus. We have evaluated the results through both objective and subjective measures. Our statistical analysis clearly shows that interactive visualization has a statistically significant, objective and positive impact on the outcomes of knowledge sharing, but that the subjects seem not to be aware of this. In particular, groups supported by visualization achieved higher productivity, higher quality of outcome and greater knowledge gains. No statistically significant results could be found between an optimal and a suboptimal visualization though (as classified by the pre-experiment survey). Subjects also did not seem to be aware of the benefits that the visualizations provided as no difference between the visualization and the control conditions was found for the self-reported measures of satisfaction and participation. An implication of our study for information visualization applications is to extend them by using real-time group annotation functionalities that aid in the group sense making process of the represented data.
Models of Collaborative Visualization
Exploring Geovisualization, 2005
As more and more research is tackled by teams, often geographically distributed, it becomes increasingly important to find good approaches to "collaborative geovisualization". In this chapter, we develop three models for collaborative visualization: in the first, there is a single application, but its interface is shared amongst several researchers; in the second, each researcher runs their own instance of a single application, keeping their input parameters synchronized; and in the third, each researcher runs their own distinct application, independently of the others, but data may be passed between them. We then discuss tools that support these three models of working, and report on practical experiences of using these tools over a number of years, most recently in a collaborative geovisualization experiment with colleagues in New Zealand.
A closer look at note taking in the co-located collaborative visual analytics process
2010
This paper highlights the important role that record-keeping (i.e. taking notes and saving charts) plays in collaborative data analysis within the business domain. The discussion of record-keeping is based on observations from a user study in which co-located teams worked on collaborative visual analytics tasks using large interactive wall and tabletop displays. Part of our findings is a collaborative data analysis framework that encompasses note taking as one of the main activities. We observed that recordkeeping was a critical activity within the analysis process. Based on our observations, we characterize notes according to their content, scope, and usage, and describe how they fit into a process of collaborative data analysis. We then discuss implications for the design of collaborative visual analytics tools.