Collaborative Visualization: Terminology, Tools and ...

Proceedings of the National Conference on Information, Networking and Communication Technologies –NCINCT 2010, Dr.Mahalingam College of Engineering and Technology, Pollachi, Coimbatore-642003

Collaborative Visualization: Terminology, Tools and Scrutiny Ashish D. Patel

Jatin D. Parmar

Computer Engineering / Information Technology Department Shri S’ad Vidya Mandal Institute of Technology Bharuch, India [email protected]


Rutivij H. Jhaveri

Bhavin I. Shah


Computer Engineering / Information Technology Department Shri S’ad Vidya Mandal Institute of Technology Bharuch, India [email protected] companies are already experimenting with Web based software. Collaborative visualization involves serious efforts among multiple participants using visual displays for decision making. The collaborative visualization tools can be expected to support a range from exploration and analysis of scientific data through decision support to education and training. Collaborative visualization tools have been developed for use in a variety of fields in which geospatial data are important. In order to support dynamic, asynchronous and synchronous collaboration [4], research has begun to focus on the identification and design of interface features required for effective scientific collaboration.

Abstract—The motivation for scientific visualization applications is to support the scientific data analysis process through efficient visual representations which convey significant information to researchers. With the help of this representation they can explore the data for visual navigation and querying processes. The study shows different collaborative visualization methods and tools to analyze the behavior on model building. More specifically, the study considers the role of different techniques in facilitating collaboration in the context of knowledge construction and decision-making activities. First area is the evolution of standard Web-based visualization components; the opportunity to provide interactive electronic documents. Second is the understanding of system that shows the design and construction of effective data visualizations for complex problem solving. The study also covers the collaborative effect of different people working in geographically widely distributed locations, fabricating and assembling very massive datasets with their views in this area.

It is important to design a visualization system with emphasis on the issues of performance, connectivity, and interactivity. These issues are as follows. A. Performance Computer user expectations have risen significantly regarding the system performances on most of the workstations and personal computers. Moreover, these performances have become critical for most of the visualization design systems. Previously, such performances could be achieved only with a system designed on a high-performance workstation using a propriety data visualization software system. However, in the last few years, mid-range and high-end personal computers became capable of having an acceptable execution performance.

Keywords-Visualization, Collaborative Effect, Reporting Tools, Visualization Tools

I.

INTRODUCTION:

The collaborative visualization for a large set of data arises in many contexts in statistics, data analysis and data mining. The main motivation are practical problems over large data sets that need to be solved many times for different scenarios, e.g., the need to distribute state updates to remote sites over the network to update the states of the shared objects at these locations, Web-based visualization, different people working in geographically widely distributed locations etc. The popularity of the World Wide Web has risen in the past three years making the Web browser one of the most omnipresent applications on the desktop. The Web is clearly going to be one of the most important technologies of the future, indeed many

B. Interactivity The current design calls for flexible as well as easy-touse intuitive interfaces to be made available to the users. Many applications have an available interactive environment that uses mouse operations for manipulating 229


visual objects. Typical operations include: rotate, zoom, and translate. There are some other operations that can be achieved through key presses.

which include Data Visualizer and PV Wave, expect the user to supply data and then select visualizations from a predefined set; hence no functional extension is possible. If the system does not include the required algorithm, then that task cannot be performed by the user. The advantage of this type of system is that they are easy for inexperienced users to use. Visualization tools can provide decision-makers with specialized views, reports, graphs and charts of corporate data. These tools help decisionmakers interpret information, understand relationships and, more importantly, present and communicate justifiable conclusions to others. Visualization tools are becoming more interesting with the involvement of 3D technologies for greater understanding of corporate data.

C.

Connectivity Under internet connections, the requirements of visualization with connections to different kinds of operating systems and processing powers have to be reconsidered. This feature is an important issue for the design of new visualization systems. Many applications are available on different computer platforms. II.

II. TOOLS FOR COLLABORATIVE VISUAL DATA EXPLORATION

C. Selecting Visualization Tools Another area for visualization is the selection of the different tools currently available. One requirement may be the system that uses a map fixed by the publisher to service a specific visualization need. It may be that users wish to submit their own visualization tasks to the server and receive the result. For this to happen some form of generic description language is needed that can simply describe the required visualization.

Information Management Magazine [6] has explained deferent tools in their issue of June 2001. It covers traditional reporting tools, Next-Generation Visualization Tools and Selecting Visualization Tools in detail. The brief introduction of these tools is given below. A. Traditional Reporting Tools On the basis of current situation in this field one can say that it is possible to design a visualization system using a personal computer, the design criteria are processing power, interactivity, connectivity, and portability, the design calls less for operating systems or computer platforms, future visualization systems will evolve around the advancement of World Wide Web technology. Years ago the information sharing was done by printing hard copies of analyses and circulating the information to the appropriate employees. This system was more time consuming and difficult to analyze the business conditions. So there are reasons to develop a new system:

With the widespread use of WWW, new technologies were introduced, and a growing number of users aim to change their systems platforms into this new environment. One of such tendencies is the use of the Web as a wide collaboration environment. At present, we can find several collaborative systems that were developed for the Web as well as frameworks that were designed to allow the development of Web based collaborative environments. Choose visualization tools that offer organized multipanel, multipage views. This allows the user better flexibility in decision making based on the analysis. Select Web-based visualization tools that integrate with powerful serverbased analytical software. Flexible, Web-based tools allow decision-makers to interact with data. New visualization tools allow people to interact with the graphic representation. Well-organized graphic information can provide decision-makers with greater access to missioncritical information faster than traditional tabular reports for more responsive decision making.

• Manage massive, rapidly changing databases. • Use more sophisticated analytics. • Implement easy, visual ways to find relationships in corporate data. • Deliver analytics using browser or Java-based interfaces. • Integrate with e-CRM applications and information portals. B. Next-Generation Visualization Tools There is a need to integrate perspectives from geographic information science, cognitive science, humancomputer interaction, computer-supported cooperative work, and semiotics. Corporate intranets are providing an organized, intuitive way of presenting business information to decision-makers enterprise-wide.

III.

COLLABORATIVE EFFECT IN GEOGRAPHICAL AREAS

The term "collaborative visualization" refers applications in which one requires control over parameters of the scientific visualization process and they may want to share the data from very different geographic areas. Consider a scientist working with a researcher at a remote company to find a new drug, by cooperatively studying a shared representation of the matter. Such examples really raise the requirement of the systems which are capable of

The available commercial visualization systems fall into two categories; Turnkey systems and Modular Visualization Environments (MVEs). Turnkey systems,

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handling such problems. The datasets generated by scientist of a large-scale science projects require software tools that support, not only insight into complex data, but collaborative science discovery. Scientific analytics approaches, combining statistical algorithms and advanced analysis techniques with highly interactive visual interfaces that support data exploration and collaborative work, offer scientists the opportunity for in-depth understanding of massive, noisy, and high-dimensional data. IV.

REFERENCES [1] Fourth International Conference on Information Visualization

[2]

DIFFERENT VIEWS ON COLLABORATIVE VISUALIZATION

[3]

Numbers of researchers have worked out different methods for the betterment of collaborative visualization theory. Li., L. and Li, F. and Lau, R. [10] have suggested synchronization method to support collaborative visualization. It considers how interaction with dynamic objects is perceived by application participants under the existence of network latency, and remedies the motion trajectory of the dynamic objects. It also handles the false positive and false negative collision detection problems.

[4]

[5]

[6]

Alan M. MacEachren, Isaac Brewer and Erik Steiner [4] have suggested different tools to Support DifferentPlace Knowledge Construction and Decision-Making. They focused on extending revisualization methods and tools to support the work of groups. More specifically, they considered the role of map-based displays in facilitating collaboration in the context of geospatial knowledge construction and decision-making activities. Over the last 10 years the discipline has matured because of the theoretical work has been done to set out an underlying reference model for visualization, improved algorithms for the visualization of 2D and 3D, regular and irregular, and large volumes of data have emerged and the range of application areas has grown to encompass medicine, geosciences, meteorology and many others. V.

[7]

[8] [9]

CONCLUSION

The last decade has many notable advances in algorithms for visualization. Visualization has expanded into many fields of research, commerce and industry, appearing as a common desktop tool for many people. The idea behind World Wide Web is using collaborative visualization as a tool for people to share and locate textual information. The work discussed above covers some aspects in collaborative visualization. The paper shows only the work done by different people in this area. It never claims the originality of any concepts explained here. The idea here is to study different views in the area of collaborative visualization.

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(IV'00), Collaborative Visual Data Navigation on the Web, London, England, July 19-July 21, ISBN: 0-7695-0743-3. Ying Zhu, Xiaoyuan Suo, G. Scott Owen, Complexity analysis for information visualization design and evaluation, Department of computer science, Georgia State University. National Energy Research Scientific Computing Center A DOE Office of Science User Facility at Lawrence Berkeley National Laboratory. Alan M. MacEachren, Isaac Brewer and Erik Steiner, Geovisualization to mediate collaborative work: Tools To Support Different-Place Knowledge Construction and Decision-Making, , GeoVISTA Center, Department of Geography, Penn State University, USA. P. Sakellaropoulos, L. Costaridou, G. Panayiotakis , Using component technologies for web based wavelet enhanced mammographic image visualization, Informatics for Health and Social Care, 2000, Vol. 25, No. 3, Pages 171-181. Web-Based Visualization, Information Management Magazine, June 2001. Philip C. Chen, Developing a Personal Computer-Based Data Visualization SystemUsing Public Domain Software, SPIE's Electronic Imaging '99, January 27, 1999, San Jose, California. Jason Wood, Collaborative Visualization, Ph. D. Thesis, the University of Leeds, School of Computer Studies, February, 1998. Li., L. and Li, F. and Lau, R. (2006) 'A trajectory-preserving synchronization method for collaborative visualization.’ IEEE transactions on visualization and computer graphics. 12 (5), pp.989-996.