Facilitating Scientific Discovery through Crowdsourcing and Distributed Participation
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Science has evolved from the isolated individual tinkering in the lab, through the era of the “gentleman scientist” with his or her assistant(s), to group-based then expansive collaboration and now to an opportunity to collaborate with the world. With the advent of the internet the opportunity for crowd-sourced contribution and large-scale collaboration has exploded and, as a result, scientific discovery has been further enabled. The contributions of enormous open data sets, liberal licensing policies and innovative technologies for mining and linking these data has given rise to platforms that are beginning to deliver on the promise of semantic technologies and nanopublications, facilitated by the unprecedented computational resources available today, especially the increasing capabilities of handheld devices. The speaker will provide an overview of his experiences in developing a crowdsourced platform for chemists allowing for data deposition, annotation and validation. The challenges of mapping chemical and pharmacological data, especially in regards to data quality, will be discussed. The promise of distributed participation in data analysis is already in place.
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Facilitating Scientific Discovery through Crowdsourcing and Distributed Participation
- 1. Facilitating Scientific Discovery through Crowdsourcing and Distributed Participation Antony Williams NETTAB October 17th 2013
- 2. If it was not just about me… • Together we might: • • • • • • • build an encyclopedia …and rate restaurants …share book reviews …and movie reviews …and reviews of service providers …organize sit-ins and social action …and more data might just be Open
- 3. If it was not just about me… • Together we might: • • • • • • • build an encyclopedia …and rate restaurants …share book reviews …and movie reviews …and reviews of service providers …organize sit-ins and social action …and more data might just be Open
- 6. Various ways to contribute
- 8. Where Am I From?
- 9. What can be done with Big Data
- 10. Patients Like Me
- 11. Patients Like Me
- 12. Let’s Change the World • Let’s map together all historical chemistry data and build systems to integrate new data • Heck, let’s integrate chemistry and biology data and add in disease data too • Lets model the data and see if we can extract new relationships – quantitative and qualitative • Let’s make it all available on the web
- 13. That’s a BIG Request
- 14. What About Something Smaller? • We’re going to map the world • We’re going to take photos of as many places as we can and link them together • We’ll let people annotate and curate the map • Then let’s make it available free on the web • We’ll make it available for decision making • Put it on Mobile Devices, Give it Away
- 15. I’m from here…
- 16. Wikipedia
- 17. Wikipedia
- 18. Moel-Y-Parc
- 21. I care…I want to contribute…
- 22. The Power of Contribution
- 23. How do you spell Afonwen?
- 24. And the Welsh know!
- 25. Whoa… • • • • So the world can be mapped… We can enter a 3D environment within the map We can add annotations We can use the data, we can reference it, we can extract it, we can make decisions with it • And we can do it on our lap, in our hands • Let’s crowdsource chemistry
- 26. Chemistry Data is Everywhere
- 27. In a Galaxy far, far away… • Build a structure-centric hub • Aggregate structure-based data and integrate • Link to additional data sources • • • • Patents Publications Vendors Models
- 28. A LITTLE Chemistry First
- 31. Analytical Data
- 33. Does one stereocenter matter? Distaval, Talimol, Nibrol, Sedimide, Quietoplex, Contergan, Neurosedyn, Softenon, Thalidomide
- 36. InChIKeys Search the Web by Structure
- 37. The Quality of Chemical Data Online What is the Structure of Vitamin K? A lipid cofactor that is required for normal blood clotting. Several forms of vitamin K have been identified: VITAMIN K1 (phytomenadione) derived from plants, VITAMIN K2 (menaquinone) from bacteria & synthetic naphthoquinone provitamins, VITAMIN K3 (menadione).
- 38. What is the Structure of Vitamin K1?
- 39. What is the Structure of Vitamin K1?
- 41. Wikipedia
- 42. Wolfram Alpha
- 43. DailyMed
- 45. People Use Trusted Resources…
- 46. We can all help clean it up…
- 47. How will it improve? Participation and contribution
- 48. Building a chemistry hub ..issues ALL Different, ALL “Domoic Acids”
- 49. ONE is “correct” ALL Different, ALL “Domoic Acids”
- 50. The EXPERTS must get it right?!
- 51. Web 2.0 Contribution • We have been contributing to the web for a along time already – but how much in chemistry? • A few blogs, an increasing amount of tweeting but what about data sharing in chemistry?
- 52. Challenging a Publication This story is only 11 years ago!
- 54. Oops…
- 55. >2 Years to Resolution
- 56. The New Way of Challenging
- 60. Oxidation by Sodium Hydride?
- 63. How much is in the archives?
- 64. Data Mine the Archives • Imagine the power of data-mining the archives of the publishers • Generate nanopublications from the articles and make available to the reasoning engines • Now imagine extracting all the “data” and freeing it up to the semantic web. • MORE LATER ON THAT!
- 65. Open Notebook Science Analysis
- 66. Oxidation by Sodium Hydride? THIS IS A COP OUT!!!
- 69. What is real, what is fake? http://www.youtube.com/watch?v=hMpAoC-h5SA
- 72. Chemistry is Dangerous Florida DJs May Face Felony for April Fools' Water Joke “… told their listeners that "dihydrogen monoxide" was coming out of the taps throughout the Fort Myers area.”
- 73. How do you recognize good vs bad?
- 74. Is this real?
- 75. Junk vs Real • “We then established a collaboration with professor Sum Ting Wong, a fugitive from the North Korean University Hu Yu Hai Ding” • “..identified as the new protein Wai So Dim”
- 76. What is real, what is fake?
- 77. Helping to change science • • • • Participation and contribution Immediacy of action Platforms for contribution Openness…whatever that is
- 78. Getting Called Out in Public… Rules for Licensing Data
- 79. Challenged in the Twittersphere
- 82. Back to Chemistry…. • ANYBODY can annotate a record on ChemSpider • Registered users can deposit new data • • • • • • • Compounds Reactions Links Analytical Data Images Movies, Data sets • Registered users can validate existing data
- 83. CURATION Search “Vitamin H”
- 86. Data Validation is Exacting Work
- 87. It is so difficult to navigate… IP? IP? What’s the What’s the structure? structure? Are they in Are they in our file? our file? What’s What’s similar? similar? Pharmacology Pharmacology data? data? What’s the What’s the target? target? Known Known Pathways? Pathways? Competitors? Competitors? Connections Connections to disease? to disease? Working On Working On Now? Now? Expressed in Expressed in right cell type? right cell type?
- 88. • Open PHACTS Project • Develop a set of robust standards • Integrate Chemistry and Biology data by implementing the standards in a semantic integration hub • Deliver services to support drug discovery programs in pharma and public domain • INITIALLY 22 partners, 8 pharmaceutical companies, 3 biotechs Guiding principle is open access, open usage, open source Guiding principle is open access, open usage, open source -- Key to standards adoption -Key to standards adoption
- 89. ChemSpider serving RDF and the semantic web • • Using RDF permalinks http://www.chemspider.com/Chemical-Structure.7787.rd • • • Using a Search Term http://www.chemspider.com/rdf.ashx?q=cyclohexane http://rdf.chemspider.com/cyclohexane
- 90. RDF and the semantic web
- 91. The issue of identifiers
- 97. Dynamic Equality Strict Relaxed Analysing Browsing chemspider:gleevec chemspider:gleevec drugbank:gleevec drugbank:gleevec LinkSet#1 { chemspider:gleevec hasParent imatinib ... drugbank:gleevec exactMatch imatinib ... }
- 98. But what about Data Quality??? CVSP : chemical validation Free chemistry validation platform that performs: •Structure validation • • • • • • Atoms Bonds Valence Stereo If aromatic - check that uniquely dearomatized Strongest acid not ionized first in partially-ionized system •Cross-matching of SDF fields • synonyms • InChIs • Smiles
- 99. Validation
- 100. Standardization • Custom processing let’s user to put together workflow from pre-defined standardization modules list
- 101. Data Review
- 102. DrugBank DrugBank dataset (6516 records) ~60 records that can’t be dearomatized unambiguously DB04283 DB04462
- 103. Nonsensical bonds ~30 records with bonds that do not make sense DB04283 DDB04009
- 104. Mismatches – which is correct? ~40 records where InChIs did not match the structure DrugBank ID: DB00755 InChI=1S/C20H28O2/c1-15(8-6-9-16(2)14-19(21)22)11-1218-17(3)10-7-13-20(18,4)5/h6,8-9,11-12,14H,7,10,13H2,15H3,(H,21,22)/b9-6+,12-11+,15-8+,16-14+ DruGBank ID: DB00614
- 105. Stereobond issues 7 records with 2 stereo bonds at chiral atoms J. Brechner, IUPAC Graphical Representation of stereochem. configurations Section: ST-1.1.10 DB08128 DB06287
- 106. Chemistry Data out to OPS Data Chemistry Validation and Standardization Platform (CVSP) at cvsp.chemspider.com •Validation •Standardization •Parent generation RDF Export
- 107. Data is being imported from ChemSpider to Open PHACTS in RDF/turtle
- 108. RDF/VOID – VoID is an RDF Schema vocabulary for expressing metadata about RDF datasets. • skos:exactMatch (Simple Knowledge Organisation System) e.g. To link compounds in OPS with compounds in ChEBI. • skos:closeMatch e.g. To link Stereo Insensitive Parents to their Children within OPS. • skos:relatedMatch e.g. To link Parent compounds that contain others as Fragments. – Recommendations on VoID specified by Manchester Uni. here: http://www.cs.man.ac.uk/~graya/ops/2012/ED-datadesc/
- 109. RDF Export
- 110. Ongoing Updates to Linksets • • • • Ongoing data checking activities on ChemSpider Does Crowdsourcing work? But WHY would people validate ChemSpider? What can be done to encourage participation? • How will we deliver on Barend’s Million Minds approach – he has ideas…see later
- 111. Crowdsourcing – does it work? • >200 people EVER have deposited or curated data • Database hosts make the largest contributions • ChemSpider staff do the most curation
- 112. Contributions
- 113. Curation Activities • • • • 2009 – 8255 curations by 43 people 2010 – 10014 curations by 66 people 2011 – 16025 curations by 116 people 2012 – 13127 curations by 74 people
- 114. Depositors • • • • 2009 2010 2011 2012 91 unique depositors 120 unique depositors 99 unique depositors 120 unique depositors • “The crowd is small – very small”
- 115. Rewards and Recognition • The badgesonomy culture of recognition is growing. • Badges are commonplace • FourSquare • Klout
- 116. Rewards and Recognition • Rewards and Recognition integrated across all ChemSpider related projects • Including paths to expose such recognition on AltMetrics platforms • MAY work for young scientists
- 118. ImpactStory
- 121. Usage, Citations, Social Media, etc
- 123. What makes a Scientist Notable? What will it be in the future???
- 124. We Are All Being Quantified…
- 125. How I am Quantified…
- 128. Likely Enabled by • Persistent unique digital identifier • Integrates to workflows such as manuscript and grant submission • Supports automated linkages with your professional activities
- 129. Summary • A grand vision for semantic data linking is coming to fruition. We have a lot do. • Data quality enhancements can come through crowdsourcing (and intelligent robots) • Participation may be driven by new approaches to rewards and recognition • Publishers are understanding the value of data, but still guard it, and generally don’t have systems to handle it. It’s changing. • There is so much value in the historical data
- 130. Inside our Publication Archive • How much data is in RSC archive, in the publications and in the supplementary info? • How many compounds for ChemSpider? • How many syntheses for ChemSpider reactions? • How many characterization measurements? • Property Data • Spectral Data • Graphs and charts to be used for modeling?
- 131. What if we could capture it all? Digitally Enhancing the RSC Archive
- 132. Start with data in publications
- 133. Turn “Figures” Into Data Spectral FIGURE Extracted Spectrum
- 134. Text Mining The N-(β-hydroxyethyl)-N-methyl-N'-(2-trifluoromethyl-1,3,4thiadiazol-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)-Nmethyl-N'-(2-trifluoromethyl-1,3,4-thiaidazol-5-yl)urea as a solid residue
- 135. ChemSpider Reactions
- 136. Thank You Email: williamsa@rsc.org Twitter: ChemConnector Personal Blog: www.chemconnector.com SLIDES: www.slideshare.net/AntonyWilliams