![…three problems—flawed design, non-
publication, and poor reporting—together
meant >85% of research funds were wasted, a
global total loss >100 billion USD per year.
[Lancet 2009]
[Even more] waste clearly occurs after
publication: from poor access, poor
dissemination, and poor uptake of the findings
of research. [PLOS Medicine 2014-05-27]
Bad publication wastes science](https://image.slidesharecdn.com/etd2014b-140724051249-phpapp02/85/Making-Theses-USEFUL-8-320.jpg)
![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)](https://image.slidesharecdn.com/etd2014b-140724051249-phpapp02/85/Making-Theses-USEFUL-16-320.jpg)
![Elsevier wants to control Open Data
[asked by Michelle Brook]](https://image.slidesharecdn.com/etd2014b-140724051249-phpapp02/85/Making-Theses-USEFUL-20-320.jpg)
Making Theses USEFUL
- 1. Making eTheses USEFUL Peter Murray-Rust*, University of Cambridge and OKF ETD2014, Leicester, UK 2014-07-24 *Shuttleworth Fellow 2014-5
- 2. Overview • We waste > 10,000,000,000 USD of eThesis value* • Everyone else is becoming OPEN; not Universities • What we CAN DO NOW: ContentMining • What we SHOULD do: Open Notebook Science • We don’t need commercial organisations to manage theses. • The time has come; We can do it now *My numbers are DEBATABLE! Please add your thoughts to http://pads.cottagelabs.com/p/etd2014 or tweet #etd2014
- 3. Jean-Claude Bradley Jean-Claude Bradley was one of the most influential open scientists of our time. He was an innovator in all that he did, from Open Education to bleeding edge Open Science; in 2006, he coined the phrase Open Notebook Science. His loss is felt deeply by friends and colleagues around the world. On Monday July 14, 2014 we gathered at Cambridge University to honour his memory and the legacy he leaves behind with a highly distinguished set of invited speakers to revisit and build upon the ideas which inspired and defined his life’s work. Wikipedia CC BY-SA
- 4. The cost and value
- 5. The economic value of data • I believe that we spend globally ca 400 billion USD / yr on public research. • The outputs include: – Knowledge / papers / patents – Organizations – People – Materials – Data – many billions/year and much is lost
- 6. US Taxpayers spend 139 Billion USD / yr on Scientific Research 4 Billion USD on human genome yielded 800 Billion USD and 4 M job-years
- 7. Scholarly publication • Citizens pay $400,000,000,000… • … for research in 1,500,000 articles … • … cost $300,000 each to create … • … $7000 each to “publish” … ($7 USD arXiv) • … costs $10,000,000,000 … • … “publishers” forbid access to 99.9% of citizens of the world … • … Value??? • Please challenge these numbers… #etd2014 or http://pads.cottagelabs.com/p/etd2014
- 8. …three problems—flawed design, non- publication, and poor reporting—together meant >85% of research funds were wasted, a global total loss >100 billion USD per year. [Lancet 2009] [Even more] waste clearly occurs after publication: from poor access, poor dissemination, and poor uptake of the findings of research. [PLOS Medicine 2014-05-27] Bad publication wastes science
- 9. Authors don’t deposit data (Ross Mounce)
- 10. Where is the Digital Enlightenment? • Science is done in C20th ways … • …communicated in C19th ways … • … losing the power of C21st
- 11. 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
- 12. eTheses • Citizens pay $20,000,000,000*… • … for research in 200,000 science theses*… • … cost $100,000 each to create* … • … re-use ??? (near zero) • … Value??? • *Please challenge these numbers… • NOTE: we pay publishers $15,000,000,000 for journals and APCs
- 13. “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”
- 14. Critical Historical Open Events • Free Software Foundation (RMS, 1985) and Linux (Torvalds, 1991) • The World Wide Web (TBL, 1991) • The human genome (1990-2001) The life of Aaron Swarz (1986-2013)
- 15. https://en.wikipedia.org/wiki/Bermuda_Principles • Automatic release of sequence assemblies larger than 1 kb (preferably within 24 hours). • Immediate publication of finished annotated sequences. • Aim to make the entire sequence freely available in the public domain for both research and development in order to maximise benefits to society.
- 16. 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)
- 17. Panton Principles for Open Data in science(2010) • PUBLISH YOUR DATA OPENLY • …make an explicit and robust statement of your wishes. • Use a recognized waiver or license that is appropriate for data. • open as defined by the Open Knowledge/Data Definition (… NOT non-commercial) • Explicit dedication of data … into the public domain via PDDL or CCZero Peter Murray-Rust, Cameron Neylon, Rufus Pollock, John Wilbanks
- 18. Panton Authors and Fellows
- 20. Elsevier wants to control Open Data [asked by Michelle Brook]
- 21. Mendeley From Wikipedia, the free encyclopedia • … a social media site used by many scientists to store metadata … • … purchased by Elsevier in 2013 • David Dobbs, in The New Yorker, described motive as: – to acquire its user data, – to destroy or coöpt an open-science icon that threatens its business model. • PM-R: Mendeley can also Snoop and Control
- 22. New ways for Theses • Content Mining • Open Notebook Theses
- 23. Traditional Research and Publication “Lab” work paper/th esis Write rewrite Re-experiment publish ??? Validation?? DATA output often seriously restricted
- 24. Content-Mining (TDM) • Now COMPLETELY LEGAL IN UK since 2014-06-01 … • … Whatever the publishers tell you. Do NOT sign their APIs • Contentmine.org … • … sponsored by Shuttleworth Foundation … • … to extract 100,000,000 facts from scientific literature • And STM publishers are throwing millions to stop us
- 25. But we can now turn PDFs into Science We can’t turn a hamburger into a cow
- 26. How a machine reads a chemical thesis nodes are compounds; arrows are reactions
- 27. PROPERTIES (Name-Value-Units-Error) Name Value Units NV U NV U N V U N E V E U
- 28. “nuggets” in a scientific paper quantity units Value ranges Humans aren’t designed to mine this … chemical project places
- 29. Natural Language Processing Part of speech tagging (Wordnet, Brown Corpus, etc.)
- 32. Automatic semantic markup of chemistry Could be used for analytical, crystallization, etc.
- 33. 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.
- 34. Evolution of ultraviolet vision in the largest avian radiation - the passerines Anders Ödeen 1* , Olle Håstad 2,3 and Per Alström 4 PDF HTML Styles , superscripts And diåcritics preserved! AMI
- 35. 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
- 36. Typical phylo tree: 60 nodes, complex and miniscule annotation, vertical text, hyphenation and valuable branch lengths. AMI extracts ALL
- 37. Acanthisittidae Acanthizidae Acrocephalidae Callaeidae Campephagidae Cnemophilidae Corvidae 0.84 0.91 0.93 0.95 Acanthisitta Acrocephalus Ailuroedus Ailuroedus Amytornis Camptostoma AMI 23.12 34.54 37.21 38.55 Posterior probability AMI can MEASURE Branch lengths! NexML Genus Family HTML
- 38. Open Notebook Science • Graduate students understand it: do you?
- 39. Free/Open Software Development Engineered repository World community CODE rewrite validate CODE fork CODE Re-use CODE Re-use Github, BitBucket StackOverflow, Apache inspires OSI Example: ContentMine at http://github.com/ContentMine/quickscrape
- 40. Sophie Kershaw, Panton Fellow, Training PhD Students
- 41. “Do you think you would be more confident in the future about trying to apply Open techniques to your work..?” • 50% Yes, by myself • 41% Yes, with help/guidance • 9% No opinion/neutral • 0% No
- 42. Rotation-Based Learning (RBL) Phase 1: Initiator • No communication permitted between groups • Attempt to reproduce existing literature • Deliver a coherent research story by the end of Phase 1 Phase 2: Successor • Communication between groups still prohibited • Validate and develop the inherited research story • Critique your predecessors • Role of research producer vs. research user • Can this approach help to foster awareness of reproducibility issues? Throughout Phases 1 & 2: • Daily lectures on open science culture & techniques • First-hand application to own research work • Version control using GitHub • Daily group supervision
- 44. Open Source software inspires Open Science Jean-Claude Bradley 2006
- 45. Open Notebook Science, ONS Jean-Claude Bradley 2006
- 47. http://gowers.wordpress.com/2013/11/03/dbd1-initial-post/ http://polymathprojects.org/2013/11/04/polymath9-pnp/#comments The Polymath project Tim Gowers and the world
- 51. And spectra were included as well Jean-Claude Bradley 2006
- 52. TOOLS Open Notebook Science Open engineered repository World community INSTRUMENT validate merge MODEL CODE DATA DATA knowledge calibrate Problems are solved communally; Nothing is needlessly duplicated; “publication“ is continuous Machines and humans Working together CC-BY
Editor's Notes
- #2: 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.
- #4: 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.