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A Web Tool for Generating High Quality Machine-readable Biological Pathways
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Harnessing the web information ecosystem with wiki-based visualization dashboards.

Matt McKeon1

  • 1IBM Research. matt.mckeon@us.ibm.com

IEEE Transactions on Visualization and Computer Graphics
|October 17, 2009
PubMed
Summary
This summary is machine-generated.

Dashiki is a public website enabling collaborative visualization dashboard creation using wiki syntax and interactive editors. It integrates real-time data, offering novel editing and layout mechanisms for enhanced social data analysis and presentation.

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Area of Science:

  • Human-Computer Interaction
  • Data Visualization
  • Web Technologies

Background:

  • Existing research on social data analysis often focuses on individual tools rather than collaborative presentation.
  • Integrating diverse data sources and real-time information into user-friendly dashboards remains a challenge.
  • The web's information ecology benefits from tools that facilitate dynamic data sharing and analysis.

Purpose of the Study:

  • To design and deploy Dashiki, a public website for collaborative visualization dashboard creation.
  • To extend social data analysis research into data presentation and organization from multiple sources.
  • To explore new interaction metaphors and integrate real-time data for enhanced web participation.

Main Methods:

  • Development of a public website, Dashiki, featuring a wiki-like syntax and interactive editors for dashboard creation.
  • Implementation of novel, low-barrier mechanisms for editing, layout, and connecting to data sources.
  • Design for coordinating interactions between multiple visualizations within a dashboard.
  • Preliminary user study involving observation and interviews to understand user activities.

Main Results:

  • Successful design and deployment of the Dashiki prototype website.
  • Introduction of intuitive editing and layout tools for visualization dashboards.
  • Demonstrated capability for integrating multiple data sources and real-time data streams.
  • Insights into user behaviors and interaction patterns during collaborative dashboard creation.

Conclusions:

  • Dashiki provides a novel platform for collaborative data visualization and analysis.
  • The design facilitates easier integration of real-time data and diverse sources into dashboards.
  • User feedback indicates potential for enhanced participation in the web's information ecology through such tools.