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The Digital Revolution and Open Science for the Future/Geoffrey Boulton

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Presented during the AOSP high-level meeting 3-4 Sept. 2018, Pretoria, South Africa.

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The Digital Revolution and Open Science for the Future/Geoffrey Boulton

  1. 1. The Digital Revolution, and Open Science for the Future Geoffrey Boulton Committee on Data for Science and Technology (CODATA) African Open Science Platform Workshop Pretoria, September 2018
  2. 2. 1. A world-historical event
  3. 3. Acquisition Storage Computation THE WEB & Ubiquitous Communication The Digital Tsunami
  4. 4. Johannes Gutenberg 1400-1468 Another Gutenberg Revolution • vast data streams • vast source diversity • vast computational capacity • learning algorithms • instantaneous communication • access anywhere anytime • low cost A NETWORKED EARTH The Digital Revolution TRANSFORMATION OF SOCIETY & OF THE HUMAN? The technologies by which knowledge is acquired, stored and communicated always been essential drivers of human material and social progress
  5. 5. 2. Scientific opportunities
  6. 6. Big Data Biggish Data Small Data Broad Data Monothematic Axis Polythematic/ Interdisciplinary Axis Complex pa erns In nature & society Patterns in space & time Low volumes Batch velocities Structured varieties Petabyte volumes High velocities Multistructured Global byte/year Yo abytes1024 Zettabytes1021 Now Exabytes 1018 Petabytes 1015 Terabytes1012 Gigabytes109 Megabytes106 Kilobytes 103 Why Open? Exploiting the Data Universe for interdisciplinary science Problem: harmonising & extracting meaningful features from a variety of data streams High throughput instruments Mixed sources
  7. 7. Big/Broad Data reveals patterns in nature and society have been beyond resolution Example: North Atlantic Ocean Circulation
  8. 8. Artificial intelligence & learning machines
  9. 9. Satellite observation Surface monitoring An example: data-modelling: iterative integration Initial conditions Model forecast Model-data iteration - forecast correction using learning algorithms
  10. 10. 3. Scientific challenges
  11. 11. Simulating system dynamics Mapping a complex state Image of brain cells in a rat Emergent behaviour of a specific 6-component coupled system Complexity: system state & dynamic evolution Most global challenges are embedded in “complex” systems BUT: though though integrated modelling is well-established data integration is problematicv
  12. 12. Data streams relevant to vector-borne infectious disease • Agent biology • Population genetics • Water supply • Food • Travel & transport • Social Habits • Hospital infection • Sanitation • Climate • Population dynamics • Faunal & floral dynamics • Atmospheric dynamics • Microbiotic dynamics Data Integration for Sustainable Development Goals Goal 3: Good Health & Wellbeing The Great Global Challenges are Interdisciplinary “Despite incredible progress, more than 6 million children per year still die before their fifth birthday. 16,000 chidren die each day from preventable diseases. In many rural areas, only 56% of births are attended by professionals. AIDS is now the leading cause of death amongst teenagers in Africa. As antibiotic resistance growths, the threat of increased infection multiplies”. UN SDG 3
  13. 13. The human future is an urban future Today's growing cities are often islands of stability and good governance in oceans of uncertainty, partly because they are better able to adapt to changing realities than entire countries. They can serve as role models, if not vanguards, for the new political-economic models the world needs. Understanding the “city organism” is a vital priority for science. Key linked variables for the urban ecosystem and its quality/resilience/governance • Population & its fluxes (formal/informal) • Energy • Water • Sewerage • Waste • Food • Retail • Transport • Income • Housing • Leisure • Ethnicity • Education • Employment • Health • Social services Data Integration for Sustainable Development Goals Goal 11: Sustainable Cities and Communities
  14. 14. Resilient Cities Disaster Risk : Infectious Disease 1. Pilot project 2. Full project 3. High level integration Domain Scientists Data Scientists Data Providers Collaborators - Other programmes - Data science groups - Data services Stakeholders National & International Policymakers & Users Projects Time Funders Sponsors Stages ISC-CODATA PROGRAMME Early Development supported by CAST Data Integration for Interdisciplinary Challenges
  15. 15. 4. The emergent paradigm of “Open Science”
  16. 16. Digital Technologies What it is not: • open data + open publishing – that is science talking to itself, though more efficiently • scientists as knowledge ‘producers’ with others as passive ‘users’ • citizen contributors of data to scientists’ analyses What it is (all the above plus): • engaging publicly on key issues • bringing scientists and non-scientists together as knowledge partners in networks of collaborative learning and problem-solving • a social process of creating actionable knowledge that has scientific credibility, practical relevance and socio-political legitimacy • the creativity of diversity Open Science Open Innovation Discovery Public ActionOutcomes Process Open Science Infrastructure
  17. 17. The Open Science Iceberg The Technical Challenge The Consent Challenge The Ecosystem Challenge The Funding Challenge The Support Challenge The Skills Challenge The Incentives Challenge The Mindset Challenge Processes & Organisation People motivation and ethos. National/Regional Infrastructure Technology
  18. 18. 5. Open Science and Economies
  19. 19. The Digital Economy Human Capacity Infrastructure Research/Analytic s Applications Banking Insurance Health Agriculture Tourism Industry Smart Cities Commerce Public Services Media Education
  20. 20. Give me a lever and a place to stand, and I will move the Earth Archimedes Maximising return on public investment: put the effort in the right place! The right place: dull, long-term but powerful The wrong place: Seductive, quick but ineffectual Human capital Infrastructure
  21. 21. 6. Open Science and Society
  22. 22. Challenges for Science • Integrating data from diverse fields • Standards for reproducibility • Maintaining traceability • Data to be Findable-Accessible-Interoperable-Reusable • Open access publishing Challenges for Society created by the digital revolution • Managing the World’s data • Machine learning results neither predictable nor explicable • Autonomous systems & the human role • Implants and the transformation of humanity • The future of work • Ubiquitous monitoring • Another “north-south” knowledge divide? • Science as a public enterprise – or the privatisation of knowledge? • Education • The “dark side” Challenges of the Digital Revolution
  23. 23. “At last an authoritative voice has demonstrated the corruption of science, driven by an almost religious certainty, that has propounded a theory that can now clearly be seen to be false, based on unreliable and in some cases invented evidence, ruthlessly used to advocate damaging and unnecessary changes in US policy, “ Public policies Emotions trump Facts: why is science a poor persuader on many major issues? scientists must be both emotionally intelligent and rigorously rational
  24. 24. Education: Navigating the new world of information anarchy
  25. 25. The Dark Side Cyber security • disruption • Political manipulation • Invasion of privacy • Cyber-crime • Autonomous weaponry • Cyber-warfare Illegality & its near neighbours Pandora’s “Post-Truth” Box The Dark Side The Web is indifferent to falsehood and honesty. “The most prodigious capacity to spread lies the world has ever seen” The crucial need for the scientific community: to combat the dark side and defend the value of ideas tested against reality.
  26. 26. 7. Conclusions
  27. 27. • The digital revolution coincides with a time when: “global society is confronted by multiple, intersecting sets of converging environmental, socio-economic, political and cultural problems, many as consequences of complex coupling between social and biogeophysical processes”. UN Science & Technology Forum , 2017 • In this context, the digital revolution offers powerful new opportunities: • to address these problems of global sustainability; • to enhance scientific understanding and economic and social welfare. • But the technology itself creates major new challenges. • Many states are developing strategies to exploit the opportunities, but few are seriously addressing the challenges. • No responsible state can avoid or should ignore these issues, or fail to equip itself with the technical and intellectual means to address them. Buying in solutions from elsewhere will prove costly and ineffectual. • Collaborative, multi-state responses offer an efficient and timely pathway.
  28. 28. 19 Exabytes280Exabytes 1 Exabyte=1018 bytes Digital Storage Analogue Storage 1986 1993 2003 2007 2014-4000Exabytes Beginning of the “Digital Age” The Digital “Tsunami”
  29. 29. EMBL-EBI services Labs around the world send us their data and we… Archive it Classify it Share it with other data providers Analyse, add value and integrate it …provide tools to help researchers use it A collaborative enterprise Discipline-driven Government-driven International Systemic Platforms/Commons European Open Science Cloud International Union of Crystallography Platforms offer: • Efficiency in planning, procurement, provision & service management • Scaling-up through shared capacities • Stimulating dynamism & creativity through diversity • Amplifying impact through common purpose

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