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e-Science: Data Quest

e-Science: Data Quest. Malcolm Atkinson & David De Roure 8 September 2009 RCUK fact-finding mission. Research drivers. Digital tech- nology advances. infrastructure & services. History - abridged!. Dennis Noble uses Mercury THE London University Computer in 1959

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e-Science: Data Quest

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  1. e-Science: DataQuest Malcolm Atkinson & David De Roure 8 September 2009 RCUK fact-finding mission

  2. Researchdrivers Digital tech-nology advances infrastructure &services History - abridged! • Dennis Noble uses Mercury • THE London University Computer in 1959 • to demonstrate heart beats as emergent behaviour • by simulating two ion channels • 2 papers in Nature 1960 • read “The Music of Life” by Dennis Noble • e-Science as a name and topic 2000

  3. e-Science Centres in the UK Coordinated by: Directors’ Forum & NeSC Glasgow Digital Curation Centre Edinburgh Lancaster Access Grid Support Centre Newcastle Belfast White Rose Grid National Centre for Text Mining National Institute for Environmental e-Science Manchester & NW Grid National Centre for e-Social Science Leicester York Cambridge Leeds Sheffield STFC Daresbury National Grid Service Birmingham STFC Harwell Oxford UCL Cardiff LeSC Open Middleware Infrastructure Institute Reading Bristol Southampton

  4. Tremendous global challenges

  5. Scale, Urgency, Complexity, …

  6. Speech 300,000 years Writing 5,000 years Broadcasting 100 years Grunts and body language 500,000 years Home Computers Internet and WWW Mobile phones Grid and Web 2.0 ~30 years Web 3.0 and Ubiquitous connected devices Printing 600 years Telecommunications 170 years Foundations for Collaborative Behaviour Timeline Today “Wellbeing” the global-scale killer app., Sir Robin Saxby Oct. 2006

  7. Healthcare @ Home REFERRAL REFERRAL GPHome-mobile-clinic via PDA-laptop-PC-Paper DiabeticianHome-mobile-clinic via PDA-laptop-PC-Paper Various Clinical Specialists (Distributed) e.g. Ophthalmologist, Podiatrist, Vascular Surgeons, Renal Specialists, Wound clinic, Foot care clinic, Neurologists, Cardiologists ILLNESS REFERRAL VARIABLESACCESSMATRIX CASE PatientHome-mobile-clinic via TV-PDA-laptop-PC-Paper Diabetes Specialist / Other Specialist Nurses Home-mobile-clinic via TV-PDA-laptop-PC-Paper Dietician Biochemist Community Nurses / Health Visitors Slide from Alex Hardisty

  8. Outline: Data Fact-finding • What questions? • What landscape? • What do researchers want? <<< priority focus • What are they doing? • What would they like to do? • What do providers want? • What do funders want? • What can we do (collaboratively) to help? • Policy, Technology, Facilities, Culture

  9. Cornucopia of Digital Data • Immense wealth of digital data • Diverse • Growing rapidly • in diversity, in complexity, in scale • Evolving rapidly • autonomous activity • researcher, business or socially driven • Future use unpredictable • innovation is the goal; change its consequence

  10. Options • Laissez faire • Organic growth driven by researchers & … • Investment of funds and effort • To farm the fields of innovation • Do we know enough to do this successfully? • What is a good strategy? • How can we balance autonomy with collaboration? • If not one size fits all, then what?

  11. Characterising data use • Multiple dimensions • Complexity • Scale of user community • Maturity of usage patterns • Individual researchers • Develop increasingly mature patterns of use • Develop new requirements • Use multiple sources • Form or join communities

  12. Technology & Researchers Co-evolution Tech. display Researchers choose? Niches? Fastestadaptationwins

  13. An easy access ramp to data

  14. Leading to expert data use

  15. Sensor Networks in the Wild

  16. Automatic Blogging by Machines

  17. Lots of Scientific Resources 2009 Nucleic Acids Research annual review reports 1171 databases

  18. Taverna Workflows • Access to distributed and local resources • Automation of data flow • Iteration over data sets • Interactive • Agile software development • Experimental protocols • Declarative mashups? • But hard to build, and they decay as services change

  19. linked data March 2009

  20. Questions: 1 1 Is the digital-data revolution beyond influence? If not, in what direction should we be trying to steer it? How should we do this? 2 More & more researchers could benefit from adroit use of data, how should we help them? 3 For successful technological intervention three factors must align: a) the users must find it useful b) it must be easy to start using and to develop sophisticated use incrementally c) it must have a persistent, affordable and feasible operational model. How do you get / deliver that alignment for your community / technology / service. 4 How do you characterise your community's (your users') requirements? How much do they have in common with others? If they are different, why are they different?

  21. Questions: 2 5 How many people in your (users') community use data-intensive methods? How many could benefit from those methods? What is stopping them? 6 What is happening about data in your community (users' domains) now? What is planned? How does this differ from what should be done? 7 To what extent are you engaged in international collaboration over the use / provision of data (technology)? Do you see collaborative opportunities that are being missed? 8 Do you see any requirements for changes in policy regarding data?

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