New deals on data - Generating open knowledge based on closed data

Talk hold at the "Blockchain for Science 2018" (Berlin).

Transcript

1. New deals on data – Generating open knowledge based on closed data Konrad U. Förstner ZB MED – Information Center for Life Sciences, Cologne, Germany & TH Köln, Cologne Germany November 5th, 2018, Blockchain for Science Con
2. Disclaimer I have no to connection to any of the companies that I will be metioned here. I present my perspective as a bioinformatician and open science enthusiast. https://www.flickr.com/photos/redjar/113823307/ – CC-BY by flickr user redjar
3. Open [data|source|*] should be the default in science. This is simply good scientific practice. https://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle
4. ... but ... https://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle
5. There are cases where privacy migh be a higher good than openess. Certain data should not be linked to individuals. https://commons.wikimedia.org/wiki/File:Masks_in_Venice.jpg CC-BY by Wikipedia user Rasevic
6. Behavioral data https://www.flickr.com/photos/andrikoolme/27729630943 – CC-BY by flickr user andrikoolme
7. Socio-economical status https://commons.wikimedia.org/wiki/File:Assorted_United_States_coins.jpg
8. Medical records https://de.wikipedia.org/wiki/Datei:Blood_pressure_measurement.jpg
9. Genome / Exome / SNPs https://de.wikipedia.org/wiki/Datei:DNA_human_male_chromosomes.gif
11. Microbiome information https://de.wikipedia.org/wiki/Datei:DNA_human_male_chromosomes.gif
12. https://de.wikipedia.org/wiki/Datei:DNA_human_male_chromosomes.gif
13. Having access to the such data of a large popuplation would significantly help research and to extend our medicial knowledge. https://de.wikipedia.org/wiki/Datei:Crowd_at_Knebworth_House_-_Rolling_Stones_1976.jpg CC-BY by Wikimedia Commons Ibirapuera
14. On the other hand the data can be misused for systematic discrimination due to political, ideological and commercial interests. https://www.flickr.com/photos/22394551@N03/2226095398 CC-BY by flickr user viZZZual.com
15. We have moral dillemma. Protect individual rights or push the scientific progress. https://commons.wikimedia.org/wiki/File:Apothecary%27s_balance_with... CC-BY by Wikimedia Commons user Fæ
16. Similar dilemmata from other research domains • Financial data of organisations • Energy consumption recording of devices • Location data of vehicles https://commons.wikimedia.org/wiki/File:Apothecary%27s_balance_with... CC-BY by Wikimedia Commons user Fæ
17. How can this dillemma be solved? https://commons.wikimedia.org/wiki/File:Apothecary%27s_balance_with... CC-BY by Wikimedia Commons user Fæ
18. Can we use closed data to generate (open) knowledge? https://commons.wikimedia.org/wiki/File:Eiserne_Truhe_Museum_Senftenberg.jpg PD
19. Can we research based on black boxed data that is at least reproducible? https://commons.wikimedia.org/wiki/File:Eiserne_Truhe_Museum_Senftenberg.jpg PD
20. Can we train machine learning models on closed data? https://commons.wikimedia.org/wiki/File:Eiserne_Truhe_Museum_Senftenberg.jpg PD
21. Or can we at least use the data to generate hypthesis that then can be tested with complementary methods? https://commons.wikimedia.org/wiki/File:Eiserne_Truhe_Museum_Senftenberg.jpg PD
22. Genomics England • Aims to hold 100,000 full genomes • Data processing in closed data centers • Only results leave the center via an ”airlock” https://de.wikipedia.org/wiki/Datei:Crowd_at_Knebworth_House_-_Rolling_Stones_1976.jpg CC-BY by Wikimedia Commons Ibirapuera
23. Personal Health Train (PHT) • Data stations – (”FAIRports”) • Trains – Workflows that can work on the data provided to them https://de.wikipedia.org/wiki/Datei:Crowd_at_Knebworth_House_-_Rolling_Stones_1976.jpg CC-BY by Wikimedia Commons Ibirapuera
24. • Locked system • Trust of the platform required https://de.wikipedia.org/wiki/Datei:Crowd_at_Knebworth_House_-_Rolling_Stones_1976.jpg CC-BY by Wikimedia Commons Ibirapuera
25. (This slide was modified for online deposition - simply click on the link below; It is a news article that describes how 23andMe and other are selling genomic data to pharma industry.) https://www.businessinsider.de/dna-testing-delete-your-data-23andme-ancestry-2018-7
26. Promises of blockchain-based, decentralized data marketplaces • owners have control over their data and can stay anonymous • standardisation of data • people can be incentivized to share the data • traceability (especially for pharmaceutical companies interesting) https://www.flickr.com/photos/katerha/4592429363 – CC-BY by flick user katerha
27. Data market place Data consumer Access to data Token Data owners
28. Concepts of underlying solutions • Fully Homomorphic Encryption (FHE) • Multi-party Computation (MPC) • Trusted Execution Environment (TEE) like Intel SGX https://unsplash.com/@toddquackenbush?photo=IClZBVw5W5A - PD
29. Blockchain Data consumer Secure compute node Private data storage Data owner
30. General purpose blockchain-based solutions • Ocean protocol • Enigma (secret contracts) • Ekiden protocol (Oasis Labs) • OpenMind https://unsplash.com/@toddquackenbush?photo=IClZBVw5W5A - PD
31. Blockchain-based solutions for healthcare data • Nebula (by George Church) • Longenesis • Luna DNA • phrOS (Personal Health Record Operating System) • EncrypGen https://unsplash.com/@toddquackenbush?photo=IClZBVw5W5A - PD
32. Will these data market places improve science? https://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle
33. This has huge potential! https://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle
34. ... but ... https://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle
35. Currently lot of white papers available – nothing openly testable. https://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle
36. Discussion unfortunately driven by companies not academics. https://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle
37. High risk – you won’t get your genome back once it leaked. https://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle
38. https://doi.org/10.1126/science.1229566
39. The suggested systems have very high complexity. https://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle
40. Problem of different legal systems. https://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle
41. Implications for data owner/seller might be not clear – education needed. https://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle
42. Data stored off-chain = outsourcing of one important problem (suggestion like Dropbox metioned – IMO quite a bad idea) https://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle
43. How to avoid false statements in surveys to become interesting for data consumers? https://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle
44. Bottom line: Very promising, but a long and hard way to go. https://www.flickr.com/photos/subcircle/500995147 – CC-BY by flickr user subcircle
45. What are your questions? konrad.foerstner.org / @konradfoerstner zbmed.de / @ZB_MED th-koeln.de / @th_koeln https://www.flickr.com/photos/nateone/3768979925/ – CC-BY by flick user nateone