How semantic representations can support scholarly communication

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Talk given at OAI8
https://indico.cern.ch/contributionDisplay.py?sessionId=3&contribId=0&confId=211600

One part of scientific communication is to effectively structure information so that it can be easily consumed. We spend a great deal of effort doing this for humans, however, given the amount of scientific information we are producing we should also spend some effort doing this for machines. In this talk, I review several semantic representations that are making it easier for machines to consume scholarly content. Moreover, I discuss how these representations can facilitate the decoupling of the journal and the ability to remix scholarly content.

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  • Already tutorials as well
  • Structure helps people understand the meaning of science… we do a lot of work
  • We do a lot of work …. But what about for machines … data
  • http://www.globalcognition.org/head-smart/3-ways-concept-maps-help-you-learn/
  • http://stackoverflow.com/questions/10397510/are-open-graph-tags-just-for-facebook
  • Any23.org
  • http://www.google.com/webmasters/tools/richsnippets
  • http://www.addthis.com
  • What could you do if you had more….?
  • An ode to davidshotton
  • Is it hard work?For the original ten person-weeks of effort
  • http://semanticpublishing.wordpress.com/2013/04/19/scorf/SCoRF should take no more that 15 minutes (excluding thinking time!),
  • http://www.data2semantics.org/2013/06/12/golden-demo-hackathon-i/
  • Fundamental for the credit network….
  • Directly access analytic tools fueled by provenacne remixed from multiple sources
  • How semantic representations can support scholarly communication

    1. 1. Paul Grothp.t.groth@vu.nl | @pgrothhttp://www.few.vu.nl/~pgrothHow semantic representations cansupport scholarly communication
    2. 2. STRUCTURE FOR HUMANUNDERSTANDABILITY
    3. 3. STRUCTURE FOR MACHINEUNDERSTANDABILITY (1)
    4. 4. http://journal.code4lib.org/articles/7847
    5. 5. Part 1 thoughts• It’s out there• Existing widely deployed semanticformats are useful• Leverage consumer platforms• Can we build better applications?
    6. 6. STRUCTURE FOR MACHINEUNDERSTANDABILITY (2)
    7. 7. http://dx.doi.org/10.1371/journal.pcbi.1000361http://www.prismstandard.org/http://www.w3schools.com/tags/html5_time .asphttp://geotags.com/geo/geotags2.htmlhttp://purl.org/net/cito/http://semanticpublishing.wordpress.com
    8. 8. Shotton D, Portwin K, Klyne G, Miles A (2009) Adventures in Semantic Publishing: Exemplar Semantic Enhancements of aResearch Article. PLoS Comput Biol 5(4): e1000361. doi:10.1371/journal.pcbi.1000361http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000361
    9. 9. Shotton D, Portwin K, Klyne G, Miles A (2009) Adventures in Semantic Publishing: Exemplar Semantic Enhancements of aResearch Article. PLoS Comput Biol 5(4): e1000361. doi:10.1371/journal.pcbi.1000361http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000361
    10. 10. https://github.com/Data2Semantics/VIVO-Browser
    11. 11. http://linkitup.data2semantics.org
    12. 12. 66 implementations41 systems22 vocab/datasets3 validatorshttp://www.w3.org/ns/prov
    13. 13. http://dev.openphacts.org
    14. 14. http://www.chembionavigator.org
    15. 15. Paul Groth and David A. Shamma.2013. Spinning data: remixing live datalike a music dj. In CHI 13 ExtendedAbstracts on Human Factors inComputing Systems (CHI EA 13). ACM,New York, NY, USA, 3063-3066.DOI=10.1145/2468356.2479611http://doi.acm.org/10.1145/2468356.2479611

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