Presenting the More! application in the ED-MEDIA 2010 conference

1. More! A Social Discovery Tool for
Researchers
Gonzalo Parra
Erik Duval
ED-MEDIA 2010 | July 2, 2010
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2. WHY?
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3. SCIENCE 2.0?
RESEARCH 2.0?
http://en.wikipedia.org/wiki/Science_2.0
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4. SCIENCE 2.0?
RESEARCH 2.0?
• it creates conversations between researchers
• lets them discuss the data and connect it with other data that
might be relevant
• Web 2.0 permits scientists to create digitized conversations
that provide context for the data
http://en.wikipedia.org/wiki/Science_2.0
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5. OUR VIEW ON
RESEARCH 2.0
• openness and sharing
• mash-up of data and services
• web2.0 applications
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6. OPEN DATA
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7. OPEN PUBLISHING
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8. APPLICATIONS
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9. ... http://academicexperts.org/
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10. OUR CONTRIBUTION
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11. DISCOVER & CONNECT
Scenario
A researcher is attending a conference presentation and is
interested in the topic and the speaker
Problem
Finding more information about them is currently done in an
ad hoc way
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12. OUR INSPIRATION: SHAZAM
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13. OUR INSPIRATION: SHAZAM
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14. OUR INSPIRATION: SHAZAM
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15. OUR INSPIRATION: SHAZAM
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16. SHAZAM FOR CONFERENCES
• Fingerprint: Quick Response (QR) code
• Exposed information:
• researcher: full name, photo, email and affiliation
• work: paper, slides and publication list
• social handles: Twitter, SlideShare, blog, Delicious, Facebook,
LinkedIn,...
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17. MORE!
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18. MORE!
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19. MORE!
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20. MORE!
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21. HOW DOES IT WORK?
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22. http://ariadne.cs.kuleuven.be/more/index.php?id=parra_g
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26. EVALUATION
• Focus on usability and functionality
•2 different target audiences
• 20 computer science students (scenario)
• 15 workshop participants
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27. EVALUATION
Students Researchers
Browser OS Visits (%)
Learn speaker’s work iPhone 45,24
iPod 7,14
Safari
MacOS 23,81
Easily follow ppt
Android 4,76
Windows 7,14
Easy to use
Firefox MacOS 4,76
Linux 4,76
Satisfaction Opera MacOS 2,38
1 2 3 4 5
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28. CONCLUSIONS
• The “More!” application provides a mobile on-site discovery
tool for researchers
• Simple and easy to use tool
• Helps to know more about the speaker
• Web application approach proved to be useful
• Discover different scenarios that were not considered
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29. CONCLUSIONS
• Weaknesses
• QR codes usage
• Data dependency
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30. CURRENT WORK
Backend: research.fm Front-end: Image recognition
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31. FURTHER WORK
• Automatic data gathering.
• information extraction from scientific papers
• retrieval of researcher’s information
• Understanding the experience!
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32. WE ENCOURAGE YOU TO...
• share your More! data
• http://sites.google.com/site/kulmoreapp/
• provide data, services or applications to share/use from
others?
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33. QUESTIONS?
http://ariadne.cs.kuleuven.be/more/index.php?id=parra_g
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34. QUESTIONS?
THANKS!
http://ariadne.cs.kuleuven.be/more/index.php?id=parra_g
Friday 2 July 2010