Science

Velterop 2 a ssp arlington may 2015

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Dealing with scientific information 'overwhelm'. This slide set has been converted to ppt from Apple Keynote, and looks different from the original, especially the animations. This seems better than the first upload.
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  • 1. Big Journal Literature Big Usage Jan Velterop – SSP – Arlington, May 28, 2015
  • 2. 11,135,542 More than 2 added every minute of 2014 Number of abstracts in PubMed
  • 3. Information overload!
  • 4. that Overload? Or rapidly increasing knowledge… …making a world of difference that can change the course of scientific thought?
  • 5. Dissemination of knowledge
  • 6. Optimal dissemination for
  • 7. Lamp post research
  • 8. Looking merely at the literature that one can read – which is not necessarily all the literature that is potentially important to one’s research Lamp post research:
  • 9. Big Usage But not in the way we’re used to
  • 10. So, what to do?
  • 11. problemEvery has its solution
  • 12. Possible strategies: 1.Publish a smaller number of papers 2.Accept that an ever smaller proportion of the available papers is actually being read 3.Capture the knowledge contained in all papers and map it in such a way that you can navigate that knowledge
  • 13. Possible strategies: 1.Publish a smaller number of papers Maybe, but if it means less information, it’s ludicrous 2.Accept that an ever smaller proportion of the available papers is actually being read 3.Capture the knowledge contained in all papers and map it in such a way that you can navigate that knowledge
  • 14. Possible strategies: 1.Publish a smaller number of papers 2.Accept that an ever smaller proportion of the available papers is actually being read How to choose, though? 3.Capture the knowledge contained in all papers and map it in such a way that you can navigate that knowledge
  • 15. In any event: l’embarras du choix
  • 16. Possible strategies: 1.Publish a smaller number of papers 2.Accept that an ever smaller proportion of the available papers is actually being read 3.Capture the knowledge contained in all papers and map it in such a way that you can navigate that knowledge Yes! Helps to see trends and what to choose!
  • 17. First create an overview…
  • 18. …only then start digging
  • 19. How might we create overviews?
  • 20. “As the rate of publishing accelerates, the need for computational support to work out which articles to read, and how to interpret, reproduce and validate the claims they contain is growing.” Quote from ‘Lazarus’: http://www.bbsrc.ac.uk/pa/grants/AwardDetails.aspx?FundingReference=BB/L005298/1
  • 21. Extract Key Insights Extract Key Insights
  • 22. Imagine you had a paper that concluded: “On hot days, it turns out that aspirin decreases the chances of blot clots, but increases the chances of heart attack in humans; the effect wasn't observed in rats at all; simulations of dogs seem to suggest that the effect is present but independent of temperature unless the dog is accompanied by a human”
  • 23. Imagine you had a paper that concluded: “On hot dayshot days, it turns out that aspirinaspirin decreasesdecreases the chances of blot clotsblot clots, but increasesincreases the chances of heart attackheart attack in humanshumans; the effect wasn't observed in ratsrats at all; simulations of dogsdogs seem to suggest that the effect is present but independent of temperaturetemperature unless the dogdog is accompanied by a humanhuman”
  • 24. Significant concepts: [CHEMBL25] (aspirin) [EFO_0001702] ('temperature' from the experimental factors ontology) [Canis lupus familiaris] [Homo sapiens] [Mus musculus] Headline Interactions (in the form of Triples): [ASPIRIN] [DECREASES] [THROMBOSIS] [ASPIRIN] [INCREASES] [MYOCARDIAL INFARCTION] Significant concepts: [CHEMBL25] (aspirin) [EFO_0001702] ('temperature' from the experimental factors ontology) [Canis lupus familiaris] [Homo sapiens] [Mus musculus] Headline Interactions (in the form of Triples): [ASPIRIN] [DECREASES] [THROMBOSIS] [ASPIRIN] [INCREASES] [MYOCARDIAL INFARCTION] Add this to the article’s abstract (after it’s been validated by the author):
  • 25. Most efficient: If publishers were to do this (doesn’t cost much, and makes articles far more useful) In case publishers don’t, alternative ways are being developed outside publishers’ control
  • 26. publishing data in articles Currently: equals burying data R.I.P.R.I.P.
  • 27. ocuments Via Utopia Documents, LAZARUS ‘resurrects’ knowledge from being buried in articles: • entities (‘concepts’, incl. synonyms, e.g. proteins) • phrases, statements, assertions (e.g. triples) • molecules (incl. Markush structure groups) • graphs • tables http://utopiadocs.com
  • 28. • entities (‘concepts’, incl. synonyms, e.g. proteins) • phrases, statements, assertions (e.g. triples) • molecules (incl. Markush structure groups) • graphs • tables These are captured – with their provenance, e.g. DOI – in a ‘Knowledge Graph’ of their relationships When assertions are captured, they are compared to the Knowledge Graph and labelled as ‘new’ (to the Graph) or ‘already found earlier’ should beshould be interesting forinteresting for the peerthe peer reviewer of areviewer of a newlynewly submittedsubmitted articlearticle
  • 29. “Lazarus to harness the crowd reading life- science articles to resurrect the swathes of legacy data buried in charts, tables, diagrams and free-text, to liberate processable data into a shared resource that benefits the community.”
  • 30. “Lazarus to harness the crowd reading life- science articles to resurrect the swathes of legacy data buried in charts, tables, diagrams and free-text, to liberate processable data into a shared resource that benefits the community.” “…activities currently carried out anyway by individuals for their own purposes (annotating, cross-referencing articles with databases, organising collections of articles).”
  • 31. “Lazarus to harness the crowd reading life- science articles to resurrect the swathes of legacy data buried in charts, tables, diagrams and free-text, to liberate processable data into a shared resource that benefits the community.” Works on any pdf, from paywalled Works on any pdf, from paywalled and open sources alike and open sources alike “…activities currently carried out anyway by individuals for their own purposes (annotating, cross-referencing articles with databases, organising collections of articles).”
  • 32. VHL protein binds to HIF-α which is ubiquitinated and tagged for degradation in the proteasome.
  • 33. ‘Assertions’ and ‘significant concepts’ extracted from articles (either by the publisher or by others, like Utopia’s LAZARUS), are added to a growing ‘knowledge graph’ which can be analysed for trends, clusters, areas of intensive activity, etc.
  • 34. Getting the picture from a large number of data
  • 35. What we need is information extracted from as many articles as possible The more we have, the ‘sharper’ the knowledge picture
  • 36. Getting a better picture from even more assertions
  • 37. Homing in i.e. making the choice what to read in detail
  • 38. BRAIN — Bio Relations And Intelligence Network
  • 39. “Recombinant Knowledge”
  • 40. >>>>
  • 41. Once researchers have identified the articles they really need to read, it should be made very easy to do so
  • 42. Ergo, what publishers should do, too, is to make all articles available in all formats: HTML, XML, PDF and ePub – even print, on demand.
  • 43. Also on mobile devices
  • 44. For instance: Easier than you might think
  • 45. (www.researchpad.co)
  • 46. Build collection of favourites
  • 47. Read full text
  • 48. Inspect metrics
  • 49. share with others
  • 50. sales@newgen.co technical inquiries: patrick@newgen.co In their words:
  • 51. ResearchPad Launch Process Project Definition Branding Publishing Go Live Turnaround Time - 8 weeks Slide borrowed from:
  • 52. What ResearchPad can do for publishers who want it, at no extra cost*, is to integrate a publisher’s content with anything from elsewhere that’s freely available with open access, so that this open access material can be accessed from within the publisher’s platform * personal communication
  • 53. sales@newgen.co technical inquiries: patrick@newgen.co
  • 54. Thank you Jan Velterop – 28 May 2015 velterop@me.com
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