The Content Mine (presented at UKSG)

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A presentation to UK serials group about the value of content-mining of scientific literature and the need to allow this without licence

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The Content Mine (presented at UKSG)

  1. 1. The Content Mine Peter Murray-Rust University of Cambridge and Open Knowledge Foundation A community of people and machines to extract 100,000,000 scientific facts from the scholarly literature Slides: CC-BY Images © Wikimedia CC-BY-SA
  2. 2. If you’re bored … important THREE most important Open Access publishers? (besides BMC and PLoS) THREE most important Open Access repositories?
  3. 3. TDM* (“Text-and-Data-mining”) is the use of machines to read and understand massive amounts of documents “The Right to Read is the Right to Mine“. PMR + OKFN “Closed Access means people die” (PM-R) “Text and Data Mining saves Lives “ (John McNaught) *PMR uses “content mining”
  4. 4. Who’s this? (Credit: Seth Rosenblatt/CNET)
  5. 5. Aaron Swartz Died 2012-11-08 Facing 30 years in jail for Downloading JStor http://news.cnet.com/8301-13578_357611642-38/call-to-action-kicks-off-secondaaron-swartz-hackathon/ (Credit: Seth Rosenblatt/CNET)
  6. 6. Typical papers destroy data Numeric: astro1307.5851v4.pdf Diagram: birds1471-2148-11-313.pdf
  7. 7. RCUK Wellcome ERC NSF … require fully OPEN [at Research Data Alliance, we are entering a new “era of open science”, which will be “good for citizens, good for scientists and good for society”. She explicitly highlighted the transformative potential of open access, open data, open software and open educational resources – mentioning the EU’s policy requiring open access to all publications and data resulting from EU funded research. http://blog.okfn.org/2013/03/21/we-are-entering-an-era-of-open-science-says-eu-vp-neeliekroes/#sthash.3SWDXDE6.dpuf
  8. 8. Content Mining • • • • • • Make science discoverable Extract facts for research Build reusable objects Aggregate Create new businesses Check for errors => better science
  9. 9. Content Mining Problems • • • • Secondary publishers create walled gardens Publishers’ contracts ban content-mining. Publishers cut off Universities who mine Publishers lobby governments to require “licences for content mining” • UK Hargreaves legislation will override this by law. Starts 2014. http://blogs.ch.cam.ac.uk/pmr/2013/10/02/text-and-data-mining-fighting-for-ourdigital-future-peter-murray-rust-is-the-problem/
  10. 10. Walled Gardens (“Free” but not “Open”) service provider has control over applications, cont ent, and media and restricts convenient access to non-approved applications or content. Examples: Mendeley, Facebook, Cambridge Crystallographic Data Centre, OCLC #animalgarden “Walled Gardens” https://vimeo.com/34323486
  11. 11. http://www.theguardian.com/science/2012/may/23/text-mining-research-tool-forbidden
  12. 12. Licences destroy Content Mining STM Publishers Licence WE WALKED OUT • Brit Library • JISC • RLUK • OKFN • … • Ross Mounce • PM-R 2012_03_15_Sample_Licence_Text_Data_Mining.pdf (Summary: PMR has NO rights) • *cannot publish to: + “libraries, repositories, or archives” • *cannot+ “Make the results of any TDM Output available on an externally facing server or website” • “Subscriber shall pay a *…+ fee” Heather Piwowar: “negotiating with publishers *made me physically ill+”
  13. 13. Licensing TDM is like publishers taxing spectacles
  14. 14. We can’t turn a hamburger into a cow But we can now turn PDFs into Science
  15. 15. Zoom in …
  16. 16. TITLES DATA!! 2000+ points UNITS TICKS SCALE QUANTITY
  17. 17. Dumb PDF Automatic extraction CSV Gaussian Filter 2nd Derivative Semantic Spectrum
  18. 18. PDF  AMI HTML  Evolution of ultraviolet vision in the largest avian radiation - the passerines Anders Ödeen 1* , Olle Håstad 2,3 and Per Alström 4 Styles , superscripts And diåcritics preserved!
  19. 19. PDF  Turdus iliacus Taeniopygia guttata Serinus canaria Lanius excubitor Melopsittacus undulatus Pavo cristatus Sturnus vulgaris Dolichonyx oryzivorus Ficedula hypoleuca Vaccinium myrtillus Falco tinnunculus Turdus Pomatostomus Leothrix Amytornis Acanthisitta Orthonyx x 2 Malurus Cnemophilus x 4 Philesturnus x 2 Motacilla x 2 Toxorhampus x 2
  20. 20. Typical phylo tree: 60 nodes, complex and miniscule annotation, vertical text, hyphenation and valuable branch lengths. AMI extracts ALL
  21. 21. AMI 0.84 0.91 0.93 0.95 Posterior probability 23.12 34.54 37.21 38.55 NexML HTML AMI can MEASURE Branch lengths! Acanthisitta Acrocephalus Ailuroedus Ailuroedus Amytornis Camptostoma Acanthisittidae Acanthizidae Acrocephalidae Callaeidae Campephagidae Cnemophilidae Corvidae Genus Family
  22. 22. 10 million spectra published /year
  23. 23. Review of the NMR data reported in the Supporting Information in this article evidences instances where some of the spectra were inappropriately edited to remove impurities. A coauthor and former student, Dr. Bruno Anxionnat, has shared with me formal communication in which he states “I would like to take full responsibility for this entire situation. I was in charge of making the SI of my papers and I erased some peaks without telling anybody. All my supervisors (Pr. Cossy, Dr. Gomez Pardo and Dr. Ricci) trusted me and I wasn't dependable. I am the only one who has to be blamed for all that, in any case them. I know my behavior is highly unethical. I am deeply sorry for what I have done and for hurting people….”
  24. 24. Crystallography Walled Garden service provider has control over applications, conte nt, and media and restricts convenient access to non-approved applications or content.
  25. 25. From Saulius Grazulis
  26. 26. Crystaleye • A database of 200,000 crystal structures scraped from publications CIF supplemental information • CML molecules and name-value pairs • Re-usable as fragment base Nick Day, Jim Downing, Sam Adams, N. W. England and Peter Murray-Rust* J.Appl.Cryst. (2012). 45 , 316– 323, doi:10.1107/S0021889812006462 http://wwmm.ch.cam.ac.uk/crystaleye
  27. 27. “nuggets” in a scientific paper places project Value ranges quantity units chemical Humans aren’t designed to mine this … 
  28. 28. The Content Mine A community of people and machines to extract scientific facts from the scholarly literature on a global scale. https://vimeo.com/78353557
  29. 29. AMI 100,000 lines of Open code for translating PDFs to science. 10 years work (PMR). AMI works!
  30. 30. We have friends • ProPublica is a NY digital-democracy newspaper • Tabula is an Open PDF-table extractor • Mozilla fights for web freedom
  31. 31. Boot-Camps and hacks Open Science, Oxford 2013-11-27 (sold out before announcement!)
  32. 32. Collaborators: I have talked with: • BMC • PLoS • British Library • Mozilla • Software Carpentry • EuropePMC • Creative Commons • OKFN I hope to talk with: • Wellcome • JISC • Ubiquity • Royal Society • Kitware • SPARC • … • …
  33. 33. • • • • • “The right to read is the right to mine” Unrestricted TDM saves lives Libraries – reject TDM restrictions Publishers – Damascene conversion  Funders – insist on CC-BY @petermurrayrust http://blogs.ch.cam.ac.uk/pmr
  34. 34. 3 most important Open Access repositories? • Wikimedia • Github, StackOverflow. • National libraries and museums. 3 most important Open Access publishers? • • • • Wikipedia NIH+EBI+OtherBioDatabases arXiv, CERN/SCOAP +PLoS+BMC
  35. 35. 300 Billion USD annually on Science+Medicine FACTS! LOST! FACTS! LOST! FACTS! LOST! FACTS! • “we repeat about 25% of our chemistry because we didn’t know we’d done it already” • 10,000 phylogenetic trees at 25,000 USD each; only 4% have data (loss = 240 Million USD) • Computational chemistry – materials NO DATA, perhaps 1,000,000,000 USD FACTS! LOST! FACTS! LOST! FACTS! LOST! FACTS!

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