Improving Information Discovery for the AGU Abstract Archive Brendan Ashby, Sherry Chen, Aris Peng,...

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Improving Information Discovery for the AGU Abstract Archive Brendan Ashby, Sherry Chen, Aris Peng, Eric Rozell, Akeem Shirley Xinformatics Spring 2012

Transcript of Improving Information Discovery for the AGU Abstract Archive Brendan Ashby, Sherry Chen, Aris Peng,...

Page 1: Improving Information Discovery for the AGU Abstract Archive Brendan Ashby, Sherry Chen, Aris Peng, Eric Rozell, Akeem Shirley Xinformatics Spring 2012.

Improving Information Discovery for the AGU Abstract Archive

Brendan Ashby, Sherry Chen, Aris Peng, Eric Rozell, Akeem Shirley

Xinformatics Spring 2012

Page 2: Improving Information Discovery for the AGU Abstract Archive Brendan Ashby, Sherry Chen, Aris Peng, Eric Rozell, Akeem Shirley Xinformatics Spring 2012.

Agenda

• AGU Abstract Archive Use Case• Cognitive Science Principles in Abstract Archive• Uncertainty in Abstract Archive • Conceptual and Logical Models• Improved Information Architecture• Demo

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AGU Abstract Archive Use Case

“To improve abstract discovery for the American Geophysical Union (AGU) meeting

archives by reducing uncertainty in the underlying data model and user interface.”

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Library Science Principles in AGU Abstract Archive

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Digital World

In the digital world, there are collections and directories.

• How is the content managed?

• How is it displayed?

Meaning through:• Signs, symbols, and how they

communicate• Spatial relations and their

similarity of appearance• Cause and effect

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The Digital Library

• Access: The abstracts of all the papers residing in the archive are publicly available.

• Rights: All papers are attributed to who submitted them and where and when they were submitted.

• Legal: Restrictions are in place to limit submissions to relevant topics of study.

• Publishing: Only members, or persons referred by existing members are allowed to submit papers to the AGU archive.

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Discovery

• Efficient: Users want the cause and effect relationship of their inputs to the outputs that the interface gives to become immediately apparent.

• No lag!• Ease: Simplify complex searches• Usability: Serve a wide audience via Java and Tomcat.• Intuition: Intuition is when users gain “understanding without apparent

effort”. o We utilize a “layer cake” methodology to how the different search

criteria are stacked on top of each other to the left of the screen. o We designed the queries to allow the user to narrow their search by

year or topic, but only as much as the user felt comfortable doing.

Page 8: Improving Information Discovery for the AGU Abstract Archive Brendan Ashby, Sherry Chen, Aris Peng, Eric Rozell, Akeem Shirley Xinformatics Spring 2012.

Blur the Lines

Can a non-expert just as easily use the system as an “expert” in the field?

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Information Uncertainty of AGU Abstract Archive

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Information uncertainty

• Uncertainty of information architecture• Uncertainty of information content• Uncertainty of information context

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Not working for abstract!

1. Can not find abstract database entry on the main page

Uncertainty of information architecture

Page 12: Improving Information Discovery for the AGU Abstract Archive Brendan Ashby, Sherry Chen, Aris Peng, Eric Rozell, Akeem Shirley Xinformatics Spring 2012.

•Only one entry• Small font size• No emphasis

2. Hard to find the link to abstract database page

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3. Destination link is on the bottom of the page

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Finally arrived!

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Uncertainty of information context

1. Have to specify the year before search

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2. Not hint or suggested keywords

This link is not working

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Uncertainty of information content

1. The searching results are not clear enough

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2. No column title ->hidden words

3. No convenient links to continue search (Authors, keywords)

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Logical and Conceptual Models

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Conceptual Model

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Logical Model

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Improved Information Architecture

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Old Information Architecture

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Old Information Architecture

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New Information Architecture

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Functional Requirements1. Make Web-accessible faceted browser 2. Allow user to look up available AGU keywords directly from faceted

browser3. Allow user to traverse links to linked data description of AGU keywords

(and related information) directly from faceted browser4. Dynamically generate visualization of top-contributing authors for a

given AGU keyword 5. Provide link to authors visualization in linked data description of AGU

keywords6. Allow user to search for abstracts from a specific author7. Display AGU abstracts matching all of the user’s search criteria (some

optional criteria might include: free-text search terms, year of publication, and meeting / section / session the abstract was published in)

8. Allow user to traverse links to linked data description of AGU abstract

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UI Mockup

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Demo

• http://essi-lod.org/s2s/• http://youtu.be/jRWtfJY8Iaw

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Conclusion

• Future Work– Further visualizations to help users discover

information resources– Improve usability of prototype faceted browser– Improve performance of prototype

• We have improved discoverability of resources in AGU Abstract Archive– Reduced uncertainty in search interface– Added visualization of top-performing researchers in

various science domains

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Page 31: Improving Information Discovery for the AGU Abstract Archive Brendan Ashby, Sherry Chen, Aris Peng, Eric Rozell, Akeem Shirley Xinformatics Spring 2012.

Appendix A: Use Case Activity Diagram

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Appendix B: Functional Requirements1.

2.

3.

6.7.

8.

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Appendix B: Functional Requirements

4.5.

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Appendix C: Namespace Expansion