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Published on Jul 10, 2015 by PMR Scholarly Publishing wastes huge amounts of valuable science. This presentation to the Public Library of Science suggests how we can work together to put this right
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- 1. The Avoidable Waste of Scholarly Publishing Peter Murray-Rust*, ContentMine.org and the University of Cambridge PLoS, Cambridge, UK 2015-07-09 Scholarly Publishing un/wittingly destroys huge amounts of publicly funded research. There are solutions; what is needed is will
- 2. Background • Contentmine aims to make large areas of scientific fact OPEN (100 million facts/year) • We’re working with WellcomeTrust, Europe PubMedCentral, etc. • A politically “hot” area (Hargreaves legislation, EU activity) • 2015 WellcomeTrust workshop on TDM and Neuroscience; “rough consensus” on what was needed. • Day workshop at Cochrane, UK (Amy Price, Anna Noel Storr, Ben Goldacre) • 2-day workshop at Edinburgh on Systematic Reviews of Animal Test publications • In the last few months we’ve prototyped a unique Open starting point, continuously released. • Can PLoS and ContentMine find constructive ways forward?
- 3. PM-R’s “first real paper”, doing science by re-using the results of otherts in a novel way
- 4. 1974: Each point represented 1-4 hours in library – discovery, volume delivery, Transcription, hand calculation.
- 6. http://www.nytimes.com/2015/04/08/opinion/yes-we-were-warned-about- ebola.html We were stunned recently when we stumbled across an article by European researchers in Annals of Virology [1982]: “The results seem to indicate that Liberia has to be included in the Ebola virus endemic zone.” In the future, the authors asserted, “medical personnel in Liberian health centers should be aware of the possibility that they may come across active cases and thus be prepared to avoid nosocomial epidemics,” referring to hospital-acquired infection. Adage in public health: “The road to inaction is paved with research papers.” Bernice Dahn (chief medical officer of Liberia’s Ministry of Health) Vera Mussah (director of county health services) Cameron Nutt (Ebola response adviser to Partners in Health) A System Failure of Scholarly Publishing
- 7. MONROVIA, Liberia — The conventional wisdom among public health authorities is that the Ebola virus, which killed at least 10,000 people in Liberia, Sierra Leone and Guinea, was a new phenomenon, not seen in West Africa before 2013. (The one exception was an anomalous case in Ivory Coast in 1994, when a Swiss primatologist was infected after performing an autopsy on a chimpanzee.) The conventional wisdom is wrong. We were stunned recently when we stumbled across an article by European researchers in Annals of Virology: “The results seem to indicate that Liberia has to be included in the Ebola virus endemic zone.” In the future, the authors asserted, “medical personnel in Liberian health centers should be aware of the possibility that they may come across active cases and thus be prepared to avoid nosocomial epidemics,” referring to hospital-acquired infection. As members of a team drafting Liberia’s Ebola recovery plan last month, we systematically reviewed the literature on Ebola surveillance since the virus’s discovery in central Africa in 1976. We learned that the virologists who wrote that report, who were from Germany, had analyzed frozen blood samples taken in 1978 and 1979 from 433 Liberian citizens. They found that 26 (or 6 percent) had antibodies to the Ebola virus. Three other studies published in 1986 documented Ebola antibody prevalence rates of 10.6, 13.4 and 14 percent, respectively, in northwestern Liberia, not far from its borders with Sierra Leone and Guinea. These articles, along with other forgotten reports from the 1980s on antibody prevalence in neighboring Sierra Leone and Guinea, suggest the possibility of what some call “sanctuary sites,” or persistent, if latent, Ebola infection in humans. Bernice Dahn is the chief medical officer of Liberia’s Ministry of Health, where Vera Mussah is the director of county health services. Cameron Nutt is the Ebola response adviser to Dr. Paul Farmer at the nonprofit group Partners in Health.
- 8. “Free” and “Open” • "Free software is a matter of liberty, not price. ’free speech', not 'free beer'”. (R M Stallman) • “A piece of data or content is open if anyone is free to use, reuse, and redistribute it” (OKFN)http://opendefinition.org/ • “open” (access) has multiple incompatible “definitions”. Major split is “human eyeballs” vs copying and machine “reusability” • “Open” is a marketing term for publishers, who frequently (often deliberately) do not grant full Openness. “Gratis” vs “Libre”
- 9. http://www.budapestopenaccessinitiative.org/read … an unprecedented public good. … … completely free and unrestricted access to [peer- reviewed literature] by all scientists, scholars, teachers, students, and other curious minds. … …Removing access barriers to this literature will accelerate research, enrich education, share the learning of the rich with the poor and the poor with the rich, make this literature as useful as it can be, and lay the foundation for uniting humanity in a common intellectual conversation and quest for knowledge. (Budapest Open Access Initiative, 2003)
- 10. Scientific and Medical publication (STM)[+] • World Citizens pay $400,000,000,000… • … for research in 1,500,000 articles … • … cost $300,000 each to create … • … $7000 each to “publish” [*]… • … $10,000,000,000 from academic libraries … • … to “publishers” who forbid access to 99.9% of citizens of the world … • 85% of medical research is wasted (not published, badly conceived, duplicated, …) [+] Figures probably +- 50 % [*] arXiV preprint server costs $7 USD per paper
- 11. • “creative use of these large data sets in the US health care sector could generate more than $300bn in value per annum” [MGI, McKinsey] • Gartner Inc. has identified 'Big Data' and 'Next-Generation Analytics' as two of the 'Top 10 Strategic Technologies' for 2012. • Given the volume of text generated by business, academic and social activities – in for example competitor reports, research publications or customer opinions on social networking sites – text mining is, however, highly important. [JISC] • there are some tasks that simply could not be achieved without using text mining. For example, a major pharmaceutical company used text mining tools to evaluate 50,000 patents in 18 months. This would have taken 50 person years to achieve manually, meaning that it would not even have been contemplated. [JISC] “Big Data – and Analytics (ContentMining)
- 12. Prof. Ian Hargreaves (2011): "David Cameron's exam question”: "Could it be true that laws designed more than three centuries ago with the express purpose of creating economic incentives for innovation by protecting creators' rights are today obstructing innovation and economic growth?” “yes. We have found that the UK's intellectual property framework, especially with regard to copyright, is falling behind what is needed.” "Digital Opportunity" by Prof Ian Hargreaves - http://www.ipo.gov.uk/ipreview.htm. Licensed under CC BY 3.0 via Wikipedia - https://en.wikipedia.org/wiki/File:Digital_Opportunity.jpg#/media/File:Digital_Opportunity.jpg
- 13. PUBLISHER TDM LICENCE INITIATIVES GENERALLY DO NOT HELP • Publishers have started offering their own TDM licences and policies • Their licences often impose unfair (and in the case of the UK, unenforceable) constraints on researchers’ freedom to exploit TDM, e.g., requiring users to employ publisher’s API, putting unnecessary restrictions on how much can be copied, or how fast it can be copied. • Why “unenforceable”? Because, as noted earlier, UK law specifically states that any contract or licence term that prevents anyone from doing TDM in the manner prescribed in the new exception shall be deemed null and void. • Really need a test case on these attempted restrictions. • Springer and Royal Society offer generous TDM provisions. • So why are so many publishers offering restrictive licences in the UK? Maybe they hope licensees are ignorant of the strength of the new law, or the publishers in fact don’t know about it. So they are either deliberately misleading, or ignorant Prof Charles Oppenheim and contentmine.org
- 14. Elsevier wants to control Open Data [asked by Michelle Brook]
- 17. Front. Pharmacol., 03 October 2011 | http://dx.doi.org/10.3389/fphar.2011.00051
- 20. How “data” are published in the 21st C
- 22. http://drugmonkey.scientopia.org/2010/08/11/yay-j-neuroscience-agrees-with-me-that- supplementary-materials-is-bs-and-ruining-science/ w00000t!!!!1111!!!!ELEVEN!!!! YAYAYAYAYAYAY!!!! Damn tootin'!!!!! Supplemental material also undermines the concept of a self-contained research report by providing a place for critical material to get lost. Methods that are essential for replicating the experiments, analyses that are central to validating the results, and awkward observations are increasingly being relegated to supplemental material. Such material is not supplemental and belongs in the body of the article, but authors can be tempted (or, with some journals, encouraged) to place essential article components in the supplemental material.
- 35. catalogue getpapers query Daily Crawl EuPMC, arXiv CORE , HAL, (UNIV repos) ToC services PDF HTML DOC ePUB TeX XML PNG EPS CSV XLSURLs DOIs crawl quickscrape norma Normalizer Structurer Semantic Tagger Text Data Figures ami UNIV Repos search Lookup CONTENT MINING Chem Phylo Trials Crystal Plants COMMUNITY plugins Visualization and Analysis PloSONE, BMC, peerJ… Nature, IEEE, Elsevier… Publisher Sites scrapers queries taggers abstract methods references Captioned Figures Fig. 1 HTML tables 30, 000 pages/day Semantic ScholarlyHTML Facts
- 36. Regular Expressions for Systematic Reviews of Animal Tests Preceding Text Following Text Extracted term Today’s Results!! We searched papers for 200 regex-based Terms and got ca 100 hits per paper
- 37. Questions we can tackle • How to we find (mentions of) clinical/animal trials? • Is a document a trial? • What is the subject of the trial? • What is the methodology used? • Does the design and practice conform to CONSORT/ARRIVE? • What are the outcomes? • Can we extract specific re-usable information? • Who are involved? (researchers, sponsors, patients?) • Has a proposed trial been completed and reported?
- 38. Linked Open Data – the world’s knowledge very little physical science and THESES?? http://upload.wikimedia.org/wikipedia/commons/3/34/LOD_Cloud_Diagram_as_of_September_2011.png DBPedia BIO Comp Lib PDB Ontologies GOV GOV.uk Music, Art Literature Social Knowledge bases RDF triples
- 40. The Right to Read is the Right to Mine http://contentmine.org
- 41. https://en.wikipedia.org/wiki/Irrigation#mediaviewer/File:Pump- enabled_Riverside_Irrigation_in_Comilla,_Bangladesh,_25_April_2014.jpg CC BY-SA 3.0 Daily Stream of 100,000 Open Facts Twitter?Indexed by CAT
- 42. What is “Content”? http://www.plosone.org/article/fetchObject.action?uri=info:doi/10.1371/journal.pone.01113 03&representation=PDF CC-BY SECTIONS MAPS TABLES CHEMISTRY TEXT MATH contentmine.org tackles these
- 43. PLoSONE BMC 1 BMC 2 Closed1 Closed2Hybrid CATalog Enhanced annotated articles FACTSFACTS Daily Crawl Crawl … Scrape … Normalize … Mine Linked OpenData Semantic Scientific Objects 2000-5000 Articles
- 45. catalogue getpapers query Daily Crawl EuPMC, arXiv CORE , HAL, (UNIV repos) ToC services PDF HTML DOC ePUB TeX XML PNG EPS CSV XLSURLs DOIs crawl quickscrape norma Normalizer Structurer Semantic Tagger Text Data Figures ami UNIV Repos search Lookup CONTENT MINING Chem Phylo Trials Crystal Plants COMMUNITY plugins Visualization and Analysis PloSONE, BMC, peerJ… Nature, IEEE, Elsevier… Publisher Sites scrapers queries taggers abstract methods references Captioned Figures Fig. 1 HTML tables 30, 000 pages/day Semantic ScholarlyHTML Facts
- 46. Machine-Human symbioses • Wikipedia • Open StreetMap • Google We aim to make it trivial for a human+machine to mine the scientific literature. By building Communities
- 47. ContentMine Workshops and Hackdays Open Science Brazil, 2014-08 Easily distributed software Get started in 30 mins Build application in a morning Start simple: bagOfWords, Stemming, Regex, templates
- 48. Facts Marked by “non-scientists” in ContentMine workshops With Wikipedia everyone can be a scientist
- 49. Oxford 2013 Berlin 2014 Delhi 2014 Jenny Molloy with mascot AMI
- 50. Workshops (1-hour -> full day or more) 2014-May->Nov • Budapest/Shuttleworth • Leicester Univ • Electronic Theses and Dissertations • Austrian Science Fund AT • OKFest DE • Eur. Bioinformatics Institute • Open Science Rio de Janeiro BR • Sci DataCon , Delhi IN • Univ of Chicago US • OpenCon 2014, Wash DC. US • JISC , London Upcoming • LIBER • Cochrane • BL • Wellcome Trust (April) • WHO Collaborators • Wikimedia/Wikidata • Mozilla • Open Knowledge • LIBER (European Research Libraries) • British Library • Wellcome Trust • EBI (Eur. Bioinf. Inst.) • JISC • Open Access Button • SPARC • Creative Commons • CORE • EuropePubmedCentral
- 51. • CRAWL the web for scientific documents (articles, grey literature, repositories) • quickSCRAPE pages (text, graphics, images, data) • NORMA-lize page to semantic form …Open semantic science … • MINE pages with your methods and tools (AMI) • CAT-alogue results in searchable index • Automate daily process (CANARY) contentmine.org Infrastructure
- 52. catalogue getpapers query Daily Crawl EuPMC, arXiv CORE , HAL, (UNIV repos) ToC services PDF HTML DOC ePUB TeX XML PNG EPS CSV XLSURLs DOIs crawl quickscrape norma Normalizer Structurer Semantic Tagger Text Data Figures ami UNIV Repos search Lookup CONTENT MINING Chem Phylo Trials Crystal Plants COMMUNITY plugins Visualization and Analysis PloSONE, BMC, peerJ… Nature, IEEE, Elsevier… Publisher Sites scrapers queries taggers abstract methods references Captioned Figures Fig. 1 HTML tables 30, 000 pages/day Semantic ScholarlyHTML Facts
- 53. quickscrape Crawl Feed Norma Index & Transform TXT XML URL DOI Scientific literature Repositories DOC CSV sHTML Plugins Regex SequencesSpecies Bespoke Scrapers XPathPer-Journal Taggers Per- Journal MetadataChemistry Phylogenetics Farming AMI BadHTML OCR Diagrams Open NORMA-lized Scientific Literature + Facts CANARY pipeline CAT-alogue index PDF
- 54. https://commons.wikimedia.org/wiki/File:Flickr_-_DVIDSHUB_-_RSP_Warrior_Challenge_Prepares_Soldiers_Mentally,_Physically_%281%29.jpg CRAWLing the Literature NO Central Table of Contents Massive technical, political, legal opposition Little interest from Academia Tedious Few general tools
- 55. The Right to Read is The Right To Mine PMR in 2012: http://blog.okfn.org/2012/06/01/the-right-to-read-is-the-right-to-mine/
- 56. SCRAPE https://en.wikipedia.org/wiki/Gleaning#mediaviewer/File:Millet_Gleaners.jpg PublicDomain PDF HTML XML quickscrape* *Scrapers created by Richard Smith-Unna + Community HTML PDF XML PNG SVG CSV DOC LaTeX CIF … Non-standard per-publisher site
- 57. https://en.wikipedia.org/wiki/W._Heath_Robinson#mediaviewer/File:Robinson%28WH%29-%28%27Uncle_Lubin%27%29.jpg PublicDomain NORMA-lization of Scientific Literature PDFs, Broken HTML PNGs for Math, etc. NORMA Unicode Diacritics Well-formed Sectioned Tagged SVG diagrams
- 58. AMI-plugins • BagOfWords, Stemming and Regular Expressions • Species • Biological Sequences • Chemical compounds & reactions • Farming * (Rory Aaronson) • Crystallography * (Saulius Grazulis, COD) • Clinical Trials * (Amy Price) • Phylogenetics * (Ross Mounce) • Phytochemistry * (Chris Steinbeck, PMR) * subcommunities
- 59. Text-based plugins • Bag of words (https://en.wikipedia.org/wiki/Bag-of- words_model) • https://en.wikipedia.org/wiki/Tf%E2%80%93idf (Term-frequency, inverse document frequency) • Templates and regexes (regular expressions).
- 60. “Bag of Words” Three fulltext articles from trialsjournal.com
- 61. Regular Expressions for Systematic Reviews of Animal Tests Preceding Text Following Text Extracted term
- 62. “nuggets” in a scientific paper quantity units Value ranges Humans aren’t designed to mine this … chemical project places
- 64. Open Content Mining of FACTs Machines can interpret chemical reactions We have done 500,000 patents. There are > 3,000,000 reactions/year. Added value > 1B Eur.
- 66. Ln Bacterial load per fly 11.5 11.0 10.5 10.0 9.5 9.0 6.5 6.0 Days post—infection 0 1 2 3 4 5 Bitmap Image and Tesseract OCR
- 69. Dumb PDF CSV Semantic Spectrum 2nd Derivative Smoothing Gaussian Filter Automatic extraction
- 70. AMI https://bitbucket.org/petermr/xhtml2stm/wiki/Home Example reaction scheme, taken from MDPI Metabolites 2012, 2, 100-133; page 8, CC-BY: AMI reads the complete diagram, recognizes the paths and generates the molecules. Then she creates a stop-fram animation showing how the 12 reactions lead into each other CLICK HERE FOR ANIMATION (may be browser dependent)
- 71. https://blogs.ch.cam.ac.uk/pmr/2014/06/25/content-mining-we-can-now- mine-images-of-phylogenetic-trees-and-more/ for story of extraction Thinning Topology Serialization Newick
- 72. Peter Murray-Rust BMC publisher Blue Obelisk paper (20 co-authors) Sub-network From CATalog
- 73. Phytochemistry extraction O. dayi “volatile composition of “ A.sibeiri A. judaica Displayed by CAT (CottageLabs)
- 74. What we can do • Recognize and promote autonomous sub- communities • Engage Early Career Researchers, including undergraduates and let THEM BUILD the systems. • COMMUNALLY build tools for data checking • Insist on semantic data input, even if it costs submissions
Editor's Notes
- Hi, I’m here to talk about AMI; a data extraction framework and tool. First, I just want highlight some of key contributors to the projects; Andy for his work on the ChemistryVisitor and Peter for the overall architecture. In this talk, I’m going to impress the importance of data in a specific format and its utility to automated machine processing. Then I’m going to demonstrate AMI’s architecture and the transformation of data as it flows through the process. I’m going to dwell a little on a core format used, Scalable Vector Graphics (SVG) before introducing the concept of visitors, which are pluggable context specific data extractors. Next, I’m going to introduce Andy’s ChemVisitor, for extracting semantic chemistry data, along with a few other visitors that can process non-chemistry specific data. Finally, I will demonstrate some uses of the ChemVisitor, within the realm of validation and metabolism.