Downloaded 41 times
Uploaded byDavid De Roure
e-Research and the Demise of the Scholarly Article
The document discusses the limitations of traditional scholarly articles in the context of e-research and the need for a more dynamic and computationally-enabled method of sharing research outputs. It emphasizes the importance of making research records readable by computers to support automation and curation, while calling for an ecosystem of social machines that facilitates the collaborative sharing of data, models, and narratives. It also highlights the growing frustrations of research funders with outdated communication systems and the necessity for alternative reporting formats to ensure discoverability and usability of research outputs.
More Related Content
Similar to e-Research and the Demise of the Scholarly Article
e-Research and the Demise of the Scholarly Article
- 1. e-Research and theDemise of the Scholarly Article David De Roure
- 2. A revolutionary idea… OpenScience!
- 3. This is aFourth Quadrant Talk More machines e-infrastructure Big Data Big Compute The Fourth The Future! Conventional Computation Social Networking Quadrant More people David De Roure online R&D
- 4.
- 5.
- 6.
- 7. Notifications and automaticre-runs Autonomic Curation Self-repair New research? Machines are users too
- 8.
- 9. Edwards, P. N.,et al. (2013) Knowledge Infrastructures: Intellectual Frameworks and Research Challenges. Ann Arbor: Deep Blue. http://hdl.handle.net/2027.42/97552
- 10.
- 11.
- 12. 1. It was nolonger possible to include the evidence in the paper – container failure! “A PDF exploded today when a scientist tried to paste in the twitter firehose…”
- 13. 2. It was nolonger possible to reconstruct a scientific experiment based on a paper alone
- 14. 3. Writing for increasinglyspecialist 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
- 15. 4. Research records neededto be readable by computer to support automation and curation A computationally-enabled sense-making network of expertise, data, models and narratives.
- 16. 5. Single authorship gaveway to casts of thousands
- 17. 6. Quality control modelsscaled poorly with the increasing volume Filter, Publish, Filter, Publish, … Like big data, publishing has increasing volume, variety and velocity But what about veracity?
- 18. 7. Alternative reporting necessaryfor 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!)
- 19. 8. Research funders frustratedby 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!
- 20. Big data elephantversus sense-making network? The challenge is to foster the co-constituted socio-technical system on the right i.e. a computationally-enabled sensemaking network of humans and machines sharing social objects… not just papers but data, models, software, narratives – new digital artefacts we call research objects.
- 21.
- 22.
- 23.
- 24. Evolving the myExperimentSocial Machine OAI ORE Workflows Packs Research Objects W3C PROV Computational Research Objects
- 25. The R dimensions Reusable.The key tenet of Research Replayable. Studies might involve Objects is to support the sharing and single investigations that happen in milliseconds or protracted processes reuse of data, methods and that take years. processes. Referenceable. If research objects Repurposeable. Reuse may also are to augment or replace traditional involve the reuse of constituent publication methods, then they must parts of the Research Object. be referenceable or citeable. Repeatable. There should be sufficient information in a Research Object to be able to repeat the study, perhaps years later. Reproducible. A third party can Revealable. Third parties must be able to audit the steps performed in the research in order to be convinced of the validity of results. Respectful. Explicit representations start with the same inputs and methods and see if a prior result can of the provenance, lineage and flow of intellectual property. be confirmed. http://www.scilogs.com/eresearch/replacing-the-paper-the-twelve-rs-of-the-e-research-record/
- 26.
- 27. The Order ofSocial Machines 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. Berners-Lee, Weaving the Web, 1999
- 28.
- 29.
- 30. Discussion points 1. Citationin tomorrow’s sense-making network of humans and machines: – What are the artefacts / social objects? – How and why are they cited? 2. Think about an ecosystem of interacting Scholarly Social Machines 3. Science as a Social Machine?
- 31. Thanks to ChristineBorgman, 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 http://www.scilogs.com/eresearch @dder www.oerc.ox.ac.uk www.force11.org www.researchobject.org www.software.ac.uk sociam.org
Editor's Notes
- #23 Thanks to Simon Hettrick for additional input to this slide.