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SEASR and VUE: Making Sense Of Information. Anoop Kumar UIT – Academic Technology Tufts University. VUE: Overview. Concept / content mapping tool Based at Tufts University Supported by the Andrew W. Mellon Foundation Open Source OKI compliant

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SEASR and VUE: Making Sense Of Information


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    Presentation Transcript
    1. SEASR and VUE: Making Sense Of Information Anoop Kumar UIT – Academic TechnologyTufts University

    2. VUE: Overview • Concept / content mapping tool • Based at Tufts University • Supported by the Andrew W. Mellon Foundation • Open Source • OKI compliant • Usability: Apple Human Interface Guidelines http://vue.tufts.edu

    3. VUE

    4. SEASR • Framework for (re) using code • Work with variety of data formats • Information Analysis Components/Flows • Based on Semantic Concepts

    5. VUE Component • Goal: Transform the functionality of VUE to SEASR Components • Implementations: • Generate VUE Map from a dataset • Transform VUE Map to HTML, JPEG, PNG, etc.

    6. VUE Component: Implementation • Make a component from VUE • Inputs • Outputs • Properties • Tags • Applications: • Use the VUE components in SEASR flows (abstraction) • Work with concept mapping beyond VUE application

    7. SEASR Support in VUE • Goal: Provide functionality in VUE to use SEASR flows • Implementations: • Add content to map • Get metadata for content • Get information about content • SEASR Datasource

    8. Outcomes Summary • VUE Components • SEASR support in VUE • Make SEASR calls • expand map by adding nodes • add metadata • provide information • Datasource support

    9. Next Steps • Develop flows for multiple nodes • Example: given a concept map determine central concepts • Support additional flows • Image and audio analysis • Text analysis • Improve the user interface • Documentation • SEASR support in next release of VUE • Adoption and use

    10. Thank you