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Better Data for a Better World

Rothamsted Research, UK
Rothamsted Research, UK
Rothamsted Research, UKBioinformatics Specialist

How open data contribute to improving the world. The life science use case. The technical, social, ethical issues. This was a talk given within the iGEM 2020 programme by the London Imperial College students group (https://2020.igem.org/Team:Imperial_College), in a webinar organised by the SOAPLab group on the topic of Ethics of Automation. Excellent Dr Brandon Sepulvado was the other speaker of the day.

Better Data for a Better World

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Marco Brandizi <marco.brandizi@rothamsted.ac.uk>
Oct, 16th - iGEM 2020 webinar
BetterDataforaBetterWorld
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Background source: https://pxhere.com/en/photo/857152
Hello!
• Geek since 1980s and C=64 times
• Started working with Life Science Data 2003
• at Univ. of Milano-Bicocca, EMBL-EBI
• and now Rothamsted Research
• Meanwhile, (h)activism in open source, open
data
A Long History
Mankind and Data
• Gather knowledge
• Know how things work, make predictions
• Improve our lives
• (in addition to being good on itself)
Egypt, 2500BC (https://brewminate.com/census-taking-in-the-ancient-world/)
In the past 20yrs or so
Economist, 2010
(https://www.economist.com/node/21521548)
Why and How?
In the past 20yrs or so
We advanced in
• Gathering (eg, smartphones, IoT, 5G)
• Stocking (eg, clouds)
• Processing (eg, AI, Machine Learning)
• Sharing (eg, web, standards, data portals)
• Searching (eg, NoSQL, Indexing)
• Visualising (eg, literature on HCI, data
charts)...
...Data, Information, Knowledge
duction Precision Farming TIM AgRA Present Future Conclusion References
recision Farming [1]
13 / 42
Images Source:
http://ieeeagra.com/ieeeagra/Downloads/20141204-Fernandez-Presentation.pdf
and establish virtuous circles

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Better Data for a Better World

  • 1. Marco Brandizi <marco.brandizi@rothamsted.ac.uk> Oct, 16th - iGEM 2020 webinar BetterDataforaBetterWorld Find this presentation on SlidesShare Background source: https://pxhere.com/en/photo/857152
  • 2. Hello! • Geek since 1980s and C=64 times • Started working with Life Science Data 2003 • at Univ. of Milano-Bicocca, EMBL-EBI • and now Rothamsted Research • Meanwhile, (h)activism in open source, open data
  • 3. A Long History Mankind and Data • Gather knowledge • Know how things work, make predictions • Improve our lives • (in addition to being good on itself) Egypt, 2500BC (https://brewminate.com/census-taking-in-the-ancient-world/)
  • 4. In the past 20yrs or so Economist, 2010 (https://www.economist.com/node/21521548)
  • 5. Why and How? In the past 20yrs or so
  • 6. We advanced in • Gathering (eg, smartphones, IoT, 5G) • Stocking (eg, clouds) • Processing (eg, AI, Machine Learning) • Sharing (eg, web, standards, data portals) • Searching (eg, NoSQL, Indexing) • Visualising (eg, literature on HCI, data charts)... ...Data, Information, Knowledge duction Precision Farming TIM AgRA Present Future Conclusion References recision Farming [1] 13 / 42 Images Source: http://ieeeagra.com/ieeeagra/Downloads/20141204-Fernandez-Presentation.pdf and establish virtuous circles
  • 8. The Cause for Open Data/Knowledge • Data portals, policies, standards • https://www.data.gov/, https://data.gov.uk/ • https://www.europeandataportal.eu/en • https://ec.europa.eu/digital-single-market/en/european-legislation-reuse-public-sector-information • https://joinup.ec.europa.eu/ • In science • https://fairsharing.org/ • https://www.nature.com/sdata/ • Data and activism • DBPedia, aka Wikipedia as data (https://wiki.dbpedia.org/about) • Wikidata (https://www.wikidata.org/) • Open Street Map (https://www.openstreetmap.org/about)
  • 9. Open Data Cause: The Life Science Use Case https://evaprofecmc.jimdofree.com/unit-4-the-genetic-revolution/2-2-chromosomes-and-genes/
  • 10. So, sequencing was (is) pretty much important... Source: https://boydfuturist.wordpress.com/tag/human-genome-project/ (also an interesting reading)
  • 11. ...indeed • The race to sequence the human genome https://www.youtube.com/watch?v=AhsIF-cmoQQ • The Human Genome Project Race https://genomics-old.soe.ucsc.edu/research/hgp_race • How to sequence human genome https://www.youtube.com/watch?v=MvuYATh7Y74 Recommended:
  • 13. Which integrates with a wealth of (open) data
  • 14. And allows for Reuse and further Advancements
  • 15. The Cause for Open Data • Allows for reuse • no need to regenerate • less expensive • Allows for integration between heterogeneous data • different entities (genes, proteins, chemistry, species, literature...) • different scales (cells, organs, individuals, populations) • New discoveries, novel uses • Reproducible science • and quality improvement Practical Reasons
  • 16. The Cause for Open Data • Public-funded data are ours • Savings opportunities add up • (but giving them out for free has a cost) • Data are ours anyway (eg, genetic data) • Transparency (and again, reproducibility) • Public benefits outweigh private interests Ethical Reasons
  • 17. But, how? Based on publications, which genes are related to yellow rust? In which biological processes are their encoded proteins involved? 1 2 3 4 5 6 1 2 3 4 5 6
  • 18. Good Data Principles: Interoperability through Standards https://tinyurl.com/y5e6kfa2 https://doi.org/10.1186/s41074-019-0055-1 https://tinyurl.com/y3h9c65k https://tinyurl.com/y2wzlwbk
  • 19. Data Standards: schema.org example https://www.bbcgoodfood.com/recipes/classic-potato-salad Source & recommended read: https://www.slideshare.net/NiallBeard/bioschemas-workshop
  • 20. schema.org used for Knetminer and Agrifood Data github.com/Rothamsted/agri-schemas https://tinyurl.com/y44a5lj9
  • 21. References • Brandizi et al, 2018, https://europepmc.org/ article/med/30085931 • IB2018 presentation https://tinyurl.com/ yaq8nt5e • AgriSchemas and data standards, IB 2019 • Reusing Knetminer data with Python/Jupyter • https://tinyurl.com/yyhnkuyk • https://tinyurl.com/y446y979
  • 22. Good Data Principles: FAIR • Findable • ex, Give your dataset a DOI, which resolves to schema.org descriptor, register it on datasetsearch.research.google.com • Accessible • ex, resolvable DOI makes it accessible. Wrap with access control as needed • Interoperable • Eg, data described with schema.org, GO and other OBO ontologies • Query protocols/standards (eg, SPARQL, GraphQL APIs, JSON Schema APIs, JSON-LD APIs) • Reusable • Clear licence • Ideally, machine-readable licence (eg, CCREL) Source and recommended read: https://tinyurl.com/yxocd3b9
  • 23. Issues: Easier to Say than to Do https://tinyurl.com/yxsftwvy https://xkcd.com/927/
  • 24. Issues: Common Good vs Private Interests • ...Parts of the standard that are not priorities for Google are not well documented anywhere. If they are priorities for Google, however, Google itself provides excellent documentation about how information should be specified in schema.org so that Google can use it. Because schema.org’s documentation is poor, the focus of attention stays on Google. Time to end Google’s domination of schema.org, https://tinyurl.com/y6j7ke8u • Not everyone wants data published, eg, failed clinical trials • Balance needed between research needs and private lives, eg, • The Immortal Life of Henrietta, Rebecca Skloot • k-anonymity, mediation approaches (Brandizi et al, 2017, https://doi.org/10.1186/s12911-017-0424-6)
  • 25. Issues: Data are Power http://www.tylervigen.com/spurious-correlations
  • 26. Issues: Data are Power • My son was a typically developing toddler. ... He received his first MMR at 19 months of age. The change in him was almost immediate. He did not regress in development, but his social skills became extremely compromised. Noises became unbearable... MMR vaccine caused my son's autism, https://tinyurl.com/y2udlfcb It's sad, but it's a spurious correlation, vaccines do not cause autism
  • 27. Issues: are We in Control? https://www.nature.com/articles/d41586-020-01874-9 https://tinyurl.com/yxay8w2j https://www.bbc.com/news/business-42959755 https://tinyurl.com/ydykjugt https://tinyurl.com/hu3lh32
  • 29. So... • Future is even more digital • And even more data-intensive • Everyone should at least have an idea • Especially if you want to become a scientist • About producing data (eg, FAIR, formats, standards) • And consuming data (eg, data resources, Graph DB query languages) • And more (eg, Python, Pandas, Graph DBs, APIs)https://tinyurl.com/y5rdq7qx
  • 30. So... • Probably we need better management and (a bit of, international) regulation • of technical aspects (eg, PA standards, research data publishing) • of ethical aspects (eg, open access, algorithms, censorships) • But also more grassroots participation • we are all responsible, especially as scientists • Data science is cool! https://tinyurl.com/y5rdq7qx
  • 31. Acknowledgements Ajit Singh
 Software Engineer • Joseph Hearnshaw, software engineer • Samiul Haque, Ed Eyles, IT admins • Alice Minotto, Earlham Inst, hosting providers • William Brown, Ricardo Gregorio, IT admins • Monika Mistry, master Student, Data Curator • Sandeep Amberkar, bioinformatician, data curator • Madhu Donepudi, Richard Holland, ext contractors, developers Keywan Hassani-Pak
 Knetminer Team Leader Chris Rawlings
 Head of Computational & Analytical Sciences Jeremy Parsons
 Bioinformatics Scientist
  • 32. Acknowledgements Ajit Singh
 Software Engineer • Joseph Hearnshaw, software engineer • Samiul Haque, Ed Eyles, IT admins • Alice Minotto, Earlham Inst, hosting providers • William Brown, Ricardo Gregorio, IT admins • Monika Mistry, master Student, Data Curator • Sandeep Amberkar, bioinformatician, data curator • Madhu Donepudi, Richard Holland, ext contractors, developers Keywan Hassani-Pak
 KnetMiner Team Leader Chris Rawlings
 Head of Computational & Analytical Sciences Jeremy Parsons
 Bioinformatics Scientist AndYou!
  • 34. The Cause for Open Data/Knowledge • Open data is the idea that some data should be freely available to everyone to use and republish as they wish, without restrictions from copyright, patents or other mechanisms of control (https://en.wikipedia.org/wiki/Open_data) • Popularised by Obama in 2009 [1], Hans Rosling [3], Tim Berners Lee [2] (recommended readings/watches) • [1] https://www.govtech.com/data/What-Obama-Did-for-Tech-Transparency-and-Open-Data.html • [2] https://www.ted.com/talks/tim_berners_lee_the_next_web?language=en • [3] https://www.ted.com/talks/hans_rosling_the_best_stats_you_ve_ever_seen
  • 35. IBM Watson • Not the first time that AI passed the Turing test (eg, Deep Blue and Chess, 1996) • But big milestone (in 2011) about knowledge management • Specialisations possible, e.g., IBM Watson Health Mini documentary at https://www.youtube.com/watch?v=P18EdAKuC1U
  • 36. Surprising Data Insights • Couples who argue often are more likely to last long (90% accuracy) • If you want such a life... • Many other examples of surprising data: 9 Bizarre and Surprising Insights from Data Science (https://tinyurl.com/yywgr2rv) https://www.businessinsider.com/mathematical-secret-to-lasting-relationships-2015-6
  • 37. Issues: Data are Power Source and recommended read: https://theconversation.com/five-maps-that-will-change-how-you-see-the-world-74967