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Future of Scholarly Communications

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UKSG 37th Annual Conference and Exhibition: Harrogate, UK, 14 Apr 2014

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Future of Scholarly Communications

  1. 1. David De Roure The Future of Scholarly Communications
  2. 2. A revolutionary idea… Open Science! rstl.royalsocietypublishing.org
  3. 3. Overview 1. Shifts in scholarship 2. End of the article 3. Research Objects 4. Social Machines
  4. 4. The Big Picture More people Moremachines Big Data Big Compute Conventional Computation “Big Social” Social Networks e-infrastructure Online R&D (Science 2.0) Information Society @dder (Social Machines)
  5. 5. Edwards, P. N., et al. (2013) Knowledge Infrastructures: Intellectual Frameworks and Research Challenges. Ann Arbor: Deep Blue. http://hdl.handle.net/2027.42/97552
  6. 6. ChristineBorgman
  7. 7. F i r s t
  8. 8. Big Data Network
  9. 9. New Social Process http://www.theguardian.com/uk/series/reading-the-riots
  10. 10. Interdisciplinary and “in the wild” * * “in it” versus “on it”
  11. 11. www.zooniverse.org
  12. 12. Scientists Talk Forum Image Classification data reduction Citizen Scientists
  13. 13. http://www.scilogs.com/eresearch/pages-of-history/ David De Roure
  14. 14. http://www.scilogs.com/eresearch/pages-of-history/DavidDeRoure
  15. 15. 1. It was no longer possible to include the evidence in the paper – container failure! “A PDF exploded today when a scientist tried to paste in the twitter firehose…”
  16. 16. 2. It was no longer possible to reconstruct a scientific experiment based on a paper alone
  17. 17. 3. Writing for increasingly specialist audiences restricted essential multidisciplinary re-use Grand Challenge Areas: • Energy • Living with Environmental Change • Global Uncertainties • Lifelong Health and Wellbeing • Digital Economy • Nanoscience • Food Security • Connected Communities • Resilient Economy
  18. 18. 4. Research records needed to be readable by computer to support automation and curation A computationally-enabled sense-making network of expertise, data, models and narratives.
  19. 19. 5. Single authorship gave way to casts of thousands
  20. 20. 6. Quality control models scaled poorly with the increasing volume Filter, Publish, Filter, Publish, … Like big data, publishing has increasing volume, variety and velocity But what about veracity?
  21. 21. 7. Alternative reporting necessary for compliance with regulations One piece of research may have multiple reports and multiple narratives for multiple readerships, in multiple formats and languages (Computer are readers too!)
  22. 22. 8. Research funders frustrated by inefficiencies in scholarly communication An investment is only worthwhile if • Outputs are discoverable • Outputs are reusable …and preferably outputs accrue value through use Using an obsolete scholarly communication system impedes innovation and hence return on investment What are we doing about it? Trying to fix it using an obsolete scholarly communication system!
  23. 23. data method script program workflow model protocol …
  24. 24. NeilChueHong
  25. 25. www.myexperiment.org
  26. 26. Research Objects Computational Research Objects The Evolution of myExperiment Workflows Packs OAI ORE W3CPROV Social Objects
  27. 27. The R Dimensions Research Objects facilitate research that is reproducible, repeatable, replicable, reusable, referenceable, retrievable, reviewable, replayable, re-interpretable, reprocessable, recomposable, reconstructable, repurposable, reliable, respectful, reputable, revealable, recoverable, restorable, reparable, refreshable?” @dder 14 April 2014 sci method access understand new use social curation Research Object Principles
  28. 28. www.researchobject.org JunZhao
  29. 29. Real life is and must be full of all kinds of social constraint – the very processes from which society arises. Computers can help if we use them to create abstract social machines on the Web: processes in which the people do the creative work and the machine does the administration... The stage is set for an evolutionary growth of new social engines. The ability to create new forms of social process would be given to the world at large, and development would be rapid. Berners-Lee, Weaving the Web, 1999 (pp. 172–175) Social Machines
  30. 30. SOCIAM: The Theory and Practice of Social Machines is funded by the UK Engineering and Physical Sciences Research Council (EPSRC) under grant number EPJ017728/1 and comprises the Universities of Southampton, Oxford and Edinburgh. See sociam.org
  31. 31. Scholarly Machines EcosystemDavid De Roure, JCDL 2013
  32. 32. 1. Shifts in scholarship – A “turn” or ongoing transformation? 2. End of the article – Don’t retrofit digital, think post-digital 3. Research Objects – Inevitable with automation – How do we cite them, how are they curated? 4. Social Machines – Humans in the loop, empowered – Can you view your projects as social machines?
  33. 33. Thanks to Christine Borgman, Iain Buchan, Neil Chue Hong, Jun Zhao, Carole Goble, FORCE11, myExperiment, Software Sustainability Institute, wf4ever and SOCIAM david.deroure@oerc.ox.ac.uk www.oerc.ox.ac.uk/people/dder @dder www.oerc.ox.ac.uk www.force11.org www.researchobject.org www.software.ac.uk sociam.org
  34. 34. www.oerc.ox.ac.uk david.deroure@oerc.ox.ac.uk @dder

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