e-Science: DataQuest

Malcolm Atkinson & David De Roure

8 September 2009

RCUK fact-finding mission

2

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

Digital tech-nology advances

infrastructure &services

Researchdrivers

e-Science Centres in the UKe-Science Centres in the UK

OxfordOxford

EdinburghEdinburgh

BelfastBelfast

CambridgeCambridge

STFC DaresburySTFC Daresbury

Manchester& NW GridManchester& NW Grid

LeSCLeSC

NewcastleNewcastle

SouthamptonSouthampton

CardiffCardiff

STFC HarwellSTFC Harwell

GlasgowGlasgow

LeicesterLeicester

UCLUCL

BirminghamBirmingham

White RoseGrid

White RoseGrid

BristolBristol

LancasterLancaster

ReadingReading

Access GridSupport Centre

Access GridSupport Centre

Digital Curation CentreDigital Curation Centre

National GridService

National GridService

National Centrefor e-Social

Science

National Centrefor e-Social

Science

National Centre forText Mining

National Centre forText Mining

National Institutefor Environmental

e-Science

National Institutefor Environmental

e-Science

Open MiddlewareInfrastructure Institute

Open MiddlewareInfrastructure Institute

SheffieldSheffieldSheffieldSheffield

YorkYorkYorkYork

LeedsLeedsLeedsLeeds

Coordinated by:Directors’ Forum

& NeSC

Coordinated by:Directors’ Forum

& NeSC

Tremendous global challenges

Scale, Urgency, Complexity, …

TimelineToday

BroadcastingBroadcasting100 years100 years

BroadcastingBroadcasting100 years100 years

TelecommunicationsTelecommunications170 years170 years

TelecommunicationsTelecommunications170 years170 years

PrintingPrinting600 years600 yearsPrintingPrinting

600 years600 years

WritingWriting5,000 years5,000 years

WritingWriting5,000 years5,000 years

Grunts andGrunts andbody languagebody language500,000 years500,000 years

Grunts andGrunts andbody languagebody language500,000 years500,000 years

SpeechSpeech300,000 years300,000 years

SpeechSpeech300,000 years300,000 years

Home ComputersHome ComputersInternet and WWWInternet and WWW

Mobile phonesMobile phonesGrid and Web 2.0Grid and Web 2.0

~30 years~30 yearsWeb 3.0 and Ubiquitous connected devicesWeb 3.0 and Ubiquitous connected devices

Home ComputersHome ComputersInternet and WWWInternet and WWW

Mobile phonesMobile phonesGrid and Web 2.0Grid and Web 2.0

~30 years~30 yearsWeb 3.0 and Ubiquitous connected devicesWeb 3.0 and Ubiquitous connected devices

“Wellbeing” the global-scale killer app., Sir Robin Saxby Oct. 2006

Foundations for Collaborative Behaviour

PatientHome-mobile-clinic

via TV-PDA-laptop-PC-Paper

Diabetes Specialist / Other Specialist Nurses

Home-mobile-clinicvia TV-PDA-laptop-PC-Paper

Dietician

DiabeticianHome-mobile-clinic

via PDA-laptop-PC-Paper

Biochemist

GPHome-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 REFERRAL

REFERRAL

CASE

Community Nurses / Health Visitors

VARIABLESACCESSMATRIX

Healthcare @ Home

Slide from Alex Hardisty

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

8

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

9

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?

10

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

11

Technology & Researchers

12

Co-evolution

Tech. display

Researcherschoose?

Niches?

Fastestadaptationwins

An easy access ramp to data

13

Leading to expert data use

14

Sensor Networks in the Wild

Automatic Blogging by Machines

2009 Nucleic Acids Research annual review reports 1171 databases

Lots of Scientific Resources

Lots of Scientific Resources

• 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

Taverna Workflows Taverna

Workflows

linked data March 2009

Questions: 11 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 usefulb) it must be easy to start using and to develop sophisticated use incrementallyc) 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?

22