Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Open software and knowledge for MIOSS

325 views

Published on

Talk to EBI Industry group on Open Software for chemical and pharmaceutical sciences. Covers examples of chemistry , wit demos, and argues that all public knowledge should be Openly accessible

Published in: Science
  • Be the first to comment

  • Be the first to like this

Open software and knowledge for MIOSS

  1. 1. MIOSS 2016, EBI, UK, 2016- 05-17 Open Content + Open Programs Peter Murray-Rust1,2 [1]University of Cambridge [2]TheContentMine pm286 AT cam DOT ac DOT uk Open Software Articles Data Infrastructure
  2. 2. Themes • Open : – Faster – Better – Agile – Inclusive – Re-usable Pomerantz, J. and Peek, R. 2016. Fifty shades of open http://dx.doi.org/10.5210/fm.v21i5.6360 Open source. Open access. Open society. Open knowledge. Open government. Even open food. The word “open” has been applied to a wide variety of words to create new terms, some of which make sense, and some not so much. This essay disambiguates the many meanings of the word “open” as it is used in a wide range of contexts. • Demos: – OSCAR, OPSIN, etc. – Content Mining and Annotation
  3. 3. Open Source Demos • Centre for Molecular Informatics – OSCAR (chemical entity recognition) – Opsin (name2structure) – ChemicalTagger (chemical language parsing) – [OSRIC] (chemical image interpretation) • ContentMine – getpapers, quickscrape, norma, ami, canary – Mining the complete scholarly literature • 10,000 articles per day • > 1 million facts per day
  4. 4. Open: [state+private] investment Rufus Pollock “The Open Information age” TBP 2016 [1] CMI Software (OSCAR, OPSIN, ChemicalTagger, [OSRIC]): sponsors – 2006 … – Unilever – Nature PG, RSC, Int Union of Cryst. – EPSRC – OMII – NCI – [Microsoft] – JISC – CambridgeIP – Linguamatics – … 2016 • Peter Corbett, Joe Townsend, Chris Waudby, Sam Adams, David Jessop, Lezan Hawizy, Nico Adams, Mark Williamson, Andy Howlett, Daniel Lowe… [1] https://www.youtube.com/watch?v=D2oNxhn6POA
  5. 5. Community
  6. 6. Mat Todd (Sydney) and MANY collaborators http://opensourcemalaria.org/ (Chrome for interactivity) Mat Todd, Univ Sydney, runs an Open Notebook community to create new antimalarials.
  7. 7. Interactive OPEN chemical search tool from cheminfo.org
  8. 8. Interactive OPEN molecular display Jmol (Bob Hanson et al)
  9. 9. Interactive OPEN chemical search tool from cheminfo.org
  10. 10. data is associated with the proposed scientific endeavour prior to or at the point of creation rather than by annotating the data with commentary after the experiment has taken place University of Southampton
  11. 11. Natural Language Processing Part of speech tagging (Wordnet, Brown Corpus, etc.)
  12. 12. http://chemicaltagger.ch.cam.ac.uk/ • Typical Typical chemical synthesis
  13. 13. Automatic semantic markup of chemistry Could be used for analytical, crystallization, etc.
  14. 14. Parsing chemical sentences This could be extended to much other scientific language
  15. 15. 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.
  16. 16. 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) “OSRIC” Is anyone interested In taking this further?
  17. 17. @Senficon (Julia Reda) :Text & Data mining in times of #copyright maximalism: "Elsevier stopped me doing my research" http://onsnetwork.org/chartgerink/2015/11/16/elsevi er-stopped-me-doing-my-research/ … #opencon #TDM Elsevier stopped me doing my research Chris Hartgerink
  18. 18. I am a statistician interested in detecting potentially problematic research such as data fabrication, which results in unreliable findings and can harm policy-making, confound funding decisions, and hampers research progress. To this end, I am content mining results reported in the psychology literature. Content mining the literature is a valuable avenue of investigating research questions with innovative methods. For example, our research group has written an automated program to mine research papers for errors in the reported results and found that 1/8 papers (of 30,000) contains at least one result that could directly influence the substantive conclusion [1]. In new research, I am trying to extract test results, figures, tables, and other information reported in papers throughout the majority of the psychology literature. As such, I need the research papers published in psychology that I can mine for these data. To this end, I started ‘bulk’ downloading research papers from, for instance, Sciencedirect. I was doing this for scholarly purposes and took into account potential server load by limiting the amount of papers I downloaded per minute to 9. I had no intention to redistribute the downloaded materials, had legal access to them because my university pays a subscription, and I only wanted to extract facts from these papers. Full disclosure, I downloaded approximately 30GB of data from Sciencedirect in approximately 10 days. This boils down to a server load of 0.0021GB/[min], 0.125GB/h, 3GB/day. Approximately two weeks after I started downloading psychology research papers, Elsevier notified my university that this was a violation of the access contract, that this could be considered stealing of content, and that they wanted it to stop. My librarian explicitly instructed me to stop downloading (which I did immediately), otherwise Elsevier would cut all access to Sciencedirect for my university. I am now not able to mine a substantial part of the literature, and because of this Elsevier is directly hampering me in my research. [1] Nuijten, M. B., Hartgerink, C. H. J., van Assen, M. A. L. M., Epskamp, S., & Wicherts, J. M. (2015). The prevalence of statistical reporting errors in psychology (1985–2013). Behavior Research Methods, 1–22. doi: 10.3758/s13428-015-0664-2 Chris Hartgerink’s blog post
  19. 19. Julia Reda, Pirate MEP, running ContentMine software to liberate science 2016-04-16
  20. 20. The Right to Read is the Right to Mine http://contentmine.org
  21. 21. 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
  22. 22. 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 Latest 20150908
  23. 23. Mining for phytochemicals • getpapers –q carvone –o carvone –x –k 100 Search for “carvone”, output directory, XML, limit hits to 100 • –q carvne –o carvone –x –k 100 Search for “carvone”, output directory, XML, limit hits to 100 getpapers

×