Adaptive Visualisation Tools for e-Science Collaboration (ADVISES) Alistair Sutcliffe (PI) Oscar De...

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Adaptive Visualisation Tools for e- Science Collaboration (ADVISES) Alistair Sutcliffe (PI) Oscar De Bruijn, Jock McNaught Sarah Thew, Colin Venters, School of Informatics, Iain Buchan NIHBI, Rob Proctor NCESS University of Manchester EPSRC E-Science Usability program May 2006- April 2009

Transcript of Adaptive Visualisation Tools for e-Science Collaboration (ADVISES) Alistair Sutcliffe (PI) Oscar De...

Page 1: Adaptive Visualisation Tools for e-Science Collaboration (ADVISES) Alistair Sutcliffe (PI) Oscar De Bruijn, Jock McNaught Sarah Thew, Colin Venters, School.

Adaptive Visualisation Tools for e-Science Collaboration (ADVISES)

Alistair Sutcliffe (PI)

Oscar De Bruijn, Jock McNaughtSarah Thew, Colin Venters,

School of Informatics,

Iain BuchanNIHBI,

Rob ProctorNCESS

University of Manchester

EPSRC E-Science Usability  programMay 2006- April 2009

Page 2: Adaptive Visualisation Tools for e-Science Collaboration (ADVISES) Alistair Sutcliffe (PI) Oscar De Bruijn, Jock McNaught Sarah Thew, Colin Venters, School.

Objectives

• To analyse users’ research methods and questions using sub-language – research questions drive workflow

• To develop a prototype, configurable visualisation-data analysis system driven by research questions

• To evaluate the prototype with researchers in the medical e-science community.

• To develop a user-centred requirements analysis and design method for e-science.

The Vision-

Research Questions are the E-science interface

Interactive Visualisation allows you to see the effect of your question AND you can interpret the results in context

Page 3: Adaptive Visualisation Tools for e-Science Collaboration (ADVISES) Alistair Sutcliffe (PI) Oscar De Bruijn, Jock McNaught Sarah Thew, Colin Venters, School.

Our Domain- Epidemiology

UnderstandingChildhoodobesity

Causal analysisfrom complexmultivariatespatio- temporalevidence

Multi-variate statistical analyses- differences between cohortsover time, between areas

Interactivevisualisation

See the effects of differentAnalyses- in context (space, time.distribution in population, etc)

Researchquestions

Page 4: Adaptive Visualisation Tools for e-Science Collaboration (ADVISES) Alistair Sutcliffe (PI) Oscar De Bruijn, Jock McNaught Sarah Thew, Colin Venters, School.

Requirements Analysis- Approach

• Ethnographic studies- observing research practices

• Interviews for background domain knowledge

• Language analysis- analysing published papers and recorded conversations (Research Questions)

• Scenarios and Storyboards- early designs for-Primary Care Trusts- visualisation of epidemiology of childhood obesity - Genetic Epidemiology- visualisations linking population

level genetic markers to disease profiles and metabolic pathways

• Requirements workshops and demonstrations

Page 5: Adaptive Visualisation Tools for e-Science Collaboration (ADVISES) Alistair Sutcliffe (PI) Oscar De Bruijn, Jock McNaught Sarah Thew, Colin Venters, School.

Prototypes and Storyboards

Gene Name

rs1243

rs2684

rs5387

rs367rs9877

rs1354

rs3243

0.001

0.0023

0.05

0.0010.002

0.05

0.04

SN

PN

ames

LDG

eneF

eatures

√√

√√

3-hydroxy-2oxypentanoate

2.3.4.2

2,3 Dihydro 3 methypentanoate

6.2.34.6

Pathway ID - 124463

6.2.34.6: FRA1 – RS1234 p = 0.012

2-Aceto-2hydroxybutanoate

Chromosome overview level

Gene detail (SNPs)

Metabolic Pathways

Populationdifferences

MutationDNA allele

MutationEffect on Protein/Enzymeproduction

Zoom in tofind

Link to seeeffect on

Page 6: Adaptive Visualisation Tools for e-Science Collaboration (ADVISES) Alistair Sutcliffe (PI) Oscar De Bruijn, Jock McNaught Sarah Thew, Colin Venters, School.

PCT prototype- Epi-maps

Analysiscontrols

InteractiveMap display

Multiple representations

Quick win prototype- more complex controls and functions added later

Page 7: Adaptive Visualisation Tools for e-Science Collaboration (ADVISES) Alistair Sutcliffe (PI) Oscar De Bruijn, Jock McNaught Sarah Thew, Colin Venters, School.

Problems encountered(and lessons learned)

• Limited user/domain expert availability-

- diversify use base

- engage users with storyboards and prototypes early

- go with the flow- follow your users’ enthusiasm

• Understanding the domain– background reading– appropriate expertise on the team

• Prioritising Requirements

- cost/benefit analysis for trade offs

- look for quick wins for user engagement

Page 8: Adaptive Visualisation Tools for e-Science Collaboration (ADVISES) Alistair Sutcliffe (PI) Oscar De Bruijn, Jock McNaught Sarah Thew, Colin Venters, School.

Progress to date

• Requirements analysis nearly complete- research questions & workflows

• Storyboards and prototypes developed for 2 sub projectsPCT prototype- Epi-MapsGenetic Epidemiology Visualisation (storyboards)

• Moving onto 2nd version prototypes with evaluation studies

• Developing method and design framework for e-science visualisation

• Refining requirements analysis method- Question driven requirements