Data enhancing the Royal Society of Chemistry publication archive Antony Williams, Colin Batchelor, Peter Corbett, Ken Karapetyan and Valery Tkachenko ACS Dallas March 2014

Data Enhancing the RSC Archive Publications summarise data acquisition, analysis and conclusions. Much detail in the data Improved navigation includes data access Reanalysis of data is limited in PDFs

Text Mining The N-(β-hydroxyethyl)-N-methyl-N'-(2-trifluoromethyl-1,3,4- thiadiazol-5-yl)urea prepared in Example 6, thionyl chloride ( 5 ml ) and benzene ( 50 ml ) were charged into a glass reaction vessel equipped with a mechanical stirrer, thermometer and reflux condenser. The reaction mixture was heated at reflux with stirring, for a period of about one-half hour. After this time the benzene and unreacted thionyl chloride were stripped from the reaction mixture under reduced pressure to yield the desired product N-(β-chloroethyl)-N-methyl-N'-(2- trifluoromethyl-1,3,4-thiaidazol-5-yl)urea as a solid residue

How is DERA going? TEXT We have text-mined all 21 st century articles… >100k articles from Mostly marked up with XML, more structured, easier to handle. Markup mostly published onto the HTML forms of the articles Required multiple iterations based on dictionaries, markup, OSCAR extraction New visualization approaches in development

Chemical Validation and Standardization

The RSC Data Repository

Text-Mining

ChemSpider Reactions

Reactions We will put reactions from our databases into the Reactions Repository We will use “Reaction Validation” procedures to clean up Daniel Lowe’s USPTO patent set of over a million extracted reactions We will move ChemSpider SyntheticPages content to the Reactions Repository We will use the RXNO Ontology to classify the reactions

Reaction Deposition/Validation

ESI – Text Spectra

Lots of “Textual Spectra”

1H NMR (CDCl3, 400 MHz): δ = 2.57 (m, 4H, Me, C(5a)H), 4.24 (d, 1H, J = 4.8 Hz, C(11b)H), 4.35 (t, 1H, Jb = 10.8 Hz, C(6)H), 4.47 (m, 2H, C(5)H), 4.57 (dd, 1H, J = 2.8 Hz, C(6)H), 6.95 (d, 1H, J = 8.4 Hz, ArH), 7.18–7.94 (m, 11H, ArH)

13C NMR (CDCl3, 100 MHz): δ = (CH3), (CH, benzylic methane), (CH, benzylic methane), (CH2), (CH2), , , , , , , , , , (ArCH), 99.42, , , , , , , , (ArC)

How is DERA going? Text Spectra Overall progress is good Improved algorithms for extraction of spectra Extraction of associated compound name with spectrum – name to structure conversion now MestreLabs have provided us with batch conversion tool Work in progress – manual and automated validation. In theory auto-assignment also

Visualization of Spectra For spectra associated with compounds we would like to view “interactive spectra”

Javascript viewer with JMol

Figure Spectra into “Real Spectra”? We are turning text into structures We are turning text into spectra And we are turning figures into spectra

Turn “Figures” Into Data EXTRACTED DATA FIGURE

EXTRACTED DATA FIGURE

How is DERA going? Figures Validation tests performed with William Brouwer. Good enough to proceed with larger test set Ready to run process across larger collection Focus on 21 st century articles only for now

Early Test Experiments Input : 74 supplementary data documents/ 3444 pages Output : p2t extracted content in 1069 page instances  578 molecules ~ 10% false positives eg., classifies Bruker logo as chemical object ~ 20% false negatives eg., missing some symbols from structure  1151 spectra > 80% of peaks extracted to within 1-2 decimal places (ppm)

Validating Spectra How will we check data consistency? How do we know the structure and the spectra match? Comparing image to spectrum is NOT enough!!! Predict spectra, use spectral verification, use algorithmic checking. Flag “dodgy data” and use crowdsourcing for data checking MULTIPLE prediction technologies now available – VERIFICATION is tougher

What are we extracting? Compounds from compound names Reactions from the text Spectral extraction – from figures and text Extraction of data from “tables” – not only CSV files but literal tables in the publication – specifically data from MedChemComm as proof of concept

Building out the technology We are presently Open-Sourcing a chemical registration system developed for OpenPHACTS We will then Open Source the Chemical Validation and Standardization Platform We are working with Bob Hanson and Bob Lancashire on Jmol/JSpecView Open Source We will deliver a set of Open Source widgets for structure handling/visualization

Javascript viewer NMR, MS, IR

Grand Target Fingers crossed to get 21 st century spectra converted Spectra associated with compounds will go into ChemSpider Spectra converted from Figures but without compound association will be captured with Figures into the Data Repository Focus on IR, Raman, UV-Vis & 1D NMR

DERA is FINE for an archive The WRONG WAY otherwise! We should NOT be mining data out of future publications Structures should be submitted “correctly” Spectra should be digital spectral formats, not images ESI should be RICH and interactive Data should be open, available, with meta data and provenance

We can solve for Authors here Will it be used though???

Advanced ESI

Conclusions Great progress in mining the archive and 21 st century articles are being enhanced on the publishing platform iteratively Spectral Data is the next focus – directly connected to our work on the data repository Reaction extraction, processing and validation from articles is progressing more slowly Results are content, software components and and Open Source Contributions

Acknowledgments Bill Brouwer – Plot2Txt Development Carlos Cobas and Santi Dominguez Bob Hanson and Bob Lancashire for Jmol/JSpecView Javascript version Leah McEwan and Will Dichtel ACD/Labs – Provider of spectroscopy tools

Thank you ORCID: Twitter: Personal Blog: SLIDES: