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1 Data-Intensive Research: Actions to make better use of Data for Research Malcolm Atkinson (& David De Roure) 2 February 2010 Report to.

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Presentation on theme: "1 Data-Intensive Research: Actions to make better use of Data for Research Malcolm Atkinson (& David De Roure) 2 February 2010 Report to."— Presentation transcript:

1 1 Data-Intensive Research: Actions to make better use of Data for Research Malcolm Atkinson (& David De Roure) 2 February 2010 Report to EPSRC Research Facilities SAT, London

2 Mission goal: learn how researchers use data Acknowledgements: the UK e-Science Directors CIR authors, our teams, the EPSRC (Sarah Fulford), the RCUK, USA office (Ruth Lee) and all of our hosts in the USA, their good ideas; opinions, observations and recommendations are our own.

3 Mission How will research be conducted in the future? Discussion and insight from the experts at the cutting edge – What are the changes in method and practice? – What works and what doesnt work? Share our e-Science experiences and do the groundwork for future collaborations BBSRC and ESRC missions too

4 Senseable Cities

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6 Andrey Rzhetsky: hand-crafted datascopes

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9 Institute for Data-Intensive Engineering & Science

10 2D X-Ray Detector Systems European X-Ray Laser DESY 10 6 pixels per frame for one detector O( ) frames per train (goal, likely will start with less) 10 trains per second (machine allows up to 30 Hz…) With 2 Byte/pixel average rate 10 Gbyte/sec for one 2D detector! Time between frames as short as 200ns buffering needed 5 Detectors 600 s 99.4 ms 100 ms 200 ns LPD Text YearRate Capability [Gbyte/sec] Storage Space [Petabyte]

11 Datascopes Summary Better methods for extracting information from data better algorithms for discovery, selection, fusion, distillation, aggregation, presentation algorithms transformed to run incrementally Better strategies for using the algorithms Better data/metadata and semantics Better platforms supporting the strategies Data centres hosting data and computation Coping with more complexity, more users & more questions Knowledge, questions & datascopes co-evolve Rally cross-disciplinary effort

12 Ramps: Summary An easy path to use a data analysis method An opportunity Not an obligation Engage as far as you want Use a service for routine tasks Types of ramp in browser - now powerful - can reach the GPU in familiar tools support from centres and crowd-sourced Strongly linked with education Removes distracting technical clutter Rescues educators & students Ramp & education co-evolve Boost investment here

13 Actions 1. Workshops on DIR 2. DIR education 3. Sand-pit to inject initial momentum 4. Test best practice 5. Immediate research challenges 6.DIR facilities pool 7.Boost reference data services 8.Foundational research 9.Green DIR 10.Coordination

14 Phase 1 1. Workshops on DIR 2. DIR education 3. Sand-pit to inject initial momentum 4. Test best practice 5. Immediate research challenges In Edinburgh March

15 Phase 2 6.DIR facilities pool 7.Boost reference data services 8.Foundational research 9.Green DIR 10.Coordination S/W, H/W & support: what services do researchers need? How much? How soon? More software; Less hardware More bandwidth; Fewer FLOPS

16 Summary Much research is data intensive More of it will be Exploiting the opportunity is urgent for the UK (you/your org.) This requires changes In facility provision In research investment In research behaviour (incentives) In education These changes are part of the digital revolution Understand, engage and ride the wave (co-evolution) Investing in data-intensive research Will accelerate research Deliver more applicable research Provide a better return on investment

17 24 ADMIRE – Framework 7 ICT ? Picture composition by Luke Humphry based on prior art by Frans Hals


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