The wider environment of open scholarship – Jisc and CNI conference 10 July 2014


Published on

Professor David de Roure, professor of e-research, Oxford e-research centre

Published in: Education
1 Like
  • Be the first to comment

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

The wider environment of open scholarship – Jisc and CNI conference 10 July 2014

  1. 1. David De Roure The Wider Environment of Open Scholarship – Looking Ahead
  2. 2. A revolutionary idea… Open Science!
  3. 3. Overview 1. Shifts in scholarship 2. End of the article 3. Future of the article 4. Scholarly 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) Social Machines @dder
  5. 5. Edwards, P. N., et al. (2013) Knowledge Infrastructures: Intellectual Frameworks and Research Challenges. Ann Arbor: Deep Blue.
  6. 6. ChristineBorgman
  7. 7. Pip Willcox @marstonbikepath Datasets or dataflows?
  8. 8. F i r s t
  9. 9.
  10. 10. New Social Process
  11. 11.
  12. 12. Scientists Talk Forum Image Classification data reduction Citizen Scientists
  13. 13. Community Software Supercomputer Digital Music Collections Student-sourced ground truth Community Software Linked Data Repositories Supercomputer 23,000 hours of recorded music Music Information Retrieval Community SALAMI
  14. 14. Pip Willcox
  16. 16. Interdisciplinary and “in the wild” In it not on it Pull not Push
  17. 17. David De Roure
  18. 18. 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…”
  19. 19. 2. It was no longer possible to reconstruct a scientific experiment based on a paper alone
  20. 20. 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.
  21. 21. 5. Single authorship gave way to casts of thousands
  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 Open Source Software as a model for Open Scholarship?
  25. 25. Research Objects Computational Research Objects The Evolution of myExperiment Workflows Packs OAI ORE W3CPROV Social Objects
  26. 26. Notifications and automatic re-runs Machines are users too Autonomic Curation Self-repair New research?
  27. 27. Executable Documents Knuth, Literate Programming
  28. 28. 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
  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
  31. 31. Scholarly Machines EcosystemDavid De Roure, JCDL 2013
  32. 32. Richard O’Bierne
  33. 33. “Yet Wikipedia and its stated ambition to “compile the sum of all human knowledge” are in trouble. The volunteer workforce that built the project’s flagship, the English-language Wikipedia—and must defend it against vandalism, hoaxes, and manipulation— has shrunk by more than a third since 2007 and is still shrinking… The main source of those problems is not mysterious. The loose collective running the site today, estimated to be 90 percent male, operates a crushing bureaucracy with an often abrasive atmosphere that deters newcomers who might increase participation in Wikipedia and broaden its coverage…”
  34. 34. A computationally- enabled sense-making network of expertise, data, software, models and narratives Iain Buchan
  35. 35. 1. Shifts in scholarship – A “turn” or ongoing transformation? 2. End of the article – Don’t retrofit digital, think post-digital 3. Future of the article – Social Objects in a sensemaking network of humans and machines – Evolution or the other side of the road? – Affordances of digital 4. Social Machines – Humans in the loop, empowered – You are designers of scholarly social machines
  36. 36. Thanks to Richard O’Bierne, Christine Borgman, Iain Buchan, Neil Chue Hong, Carole Goble, Chris Lintott, Nigel Shadbolt, Pip Willcox, Jun Zhao; FORCE11, myExperiment, Software Sustainability Institute, wf4ever, SOCIAM; Andrew W. Mellon Foundation, JISC, EPSRC, ESRC, AHRC. @dder
  37. 37. @dder