The Evolution of e-Research

David De Roure

Overview

• e-Science: The Destination and the Journey

• Generation 1 – Early adopters

• Generation 2 – Embedding

• Generation 3 – Radical sharing

• Reflections

e-Science

• e-Science was defined by John Taylor (Director General of the UK Research Councils) asglobal collaboration in key areas of science and the next generation of infrastructure that will enable it

• e-Science was the name of the destination• It became the name of the journey• When we arrive, the destination is just called

science

26/2/2007 | myExperiment | Slide 4

Jeremy Frey

• Workflows are the new rock and roll

• Machinery for coordinating the execution of (scientific) services and linking together (scientific) resources

• The era of Service Oriented Applications

• Repetitive and mundane boring stuff made easier

Carole Goble

E. Science laboris

Kepler

Triana

BPEL

Taverna

Trident

Meandre

Galaxy

Box of Chemists

My Chemistry Experiment

Current practices of early adoptors of tools.Characterised by researchers using tools within their particular problem area, with some re-use of tools, data and methods within the discipline. Traditional publishing is supplemented by publication of some digital artefacts like workflows and links to data. Science is accelerated and practice beginning to shift to emphasise in silico work.

1st Generation Summary

• Paul writes workflows for identifying biological pathways implicated in resistance to Trypanosomiasis in cattle

• Paul meets Jo. Jo is investigating Whipworm in mouse.

• Jo reuses one of Paul’s workflow without change.• Jo identifies the biological pathways involved in

sex dependence in the mouse model, believed to be involved in the ability of mice to expel the parasite.

• Previously a manual two year study by Jo had failed to do this.

Reuse, Recycling, Repurposing

“A biologist would rather share their toothbrush than their gene name”

Mike Ashburner and othersProfessor in Dept of Genetics,

University of Cambridge, UK

“Data mining: my data’s mine and your data’s mine”

mySpace for scientists!Facebook for scientists!Not Facebook for scientists!

Web 2

Open Repositories

Researchers

Social Network

The experiment that is

Developers

Social Scientists

“Facebook for Scientists” ...but different to Facebook!

A repository of research methods

A community social network of people and things

A Social Virtual Research Environment

A probe into researcher behaviour

Open source (BSD) Ruby on Rails app

REST and SPARQL interfaces, Linked Data compliant

Inspiration for: BioCatalogue, MethodBox and SysmoDB

myExperiment currently has 4989 members, 234 groups, 1260 workflows, 345 files and 129 packs

data

method

Results

Logs

Results

Metadata PaperSlides

Feeds into

produces

Included in

produces Published in

produces

Included in

Included in Included in

Published in

Workflow 16

Workflow 13

Common pathways

QTLPaul’s PackPaul’s PackPaul’s Research

Object

Paul’s Research

Object

1. Define tissue-containing area on slide→ nucleated area

2. Define relative stromal area (ratio: stroma/nuclei)

3. Define number of blood vessels

Antibody-treateduntreated

Nuclei Blood vessels

stroma merged

Biomedical TaskEffect of antibody treatment on tumour blood vessels and stroma?

David Abramson

Projects delivering now.Some institutional embedding.Key characteristic is re-use - of the increasing pool of tools, data and methods across areas/disciplines. Contain some freestanding, recombinant, reproducible research objects. New scientific practices are established and opportunities arise for completely new scientific investigations.Some expert curation.

2nd Generation Summary

Francois Belleau

“…to discover proteins that interact with transmembrane proteins, particularly those that can be related to neuro-degenerative diseases in which amyloids play a significant role”1) Taverna provenance exposed as RDF2) myExperiment RDF document for a protein discovery workflow3) Mocked-up BioCatalogue document using myExperiment RDF

data as example4) Provisional RDF documents obtained from the ConceptWiki

(conceptwiki.org) development server5) An RDF document for an example protein, obtained from the RDF

interface of the UniProt web site

A Bioinformatics Experiment A Bioinformatics Experiment Scott Marshall Marco Roos

How country is my country?

Digital Music Collections Crowdsourced

ground truthCommunity

Software

Linked Data Repository

Supercomputer

Structural Analysis of Large Amounts of Music Information

Digital Social ResearchDigital Social Research

• Data. ‘Born-digital’ data sources including social transactional data. Ease of access to secure data

• Capability. Increased capability in tools, infrastructure and services

Harnessing advances in digital technology and practice to achieve world-class social research with maximum impact

• Methods. Taking advantage of new data and capability, new forms of interpretative research

• Studies. Study of e Science, ‑understanding innovation pathways, and assessment of impact

The solutions we'll be delivering in 5 yearsCharacterised by global reuse of tools, data and methods across any discipline, and surfacing the right levels of complexity for the researcher. Routine use.Key characteristic is radical sharing .Research is significantly data driven - plundering the backlog of data, results and methods. Increasing automation and decision-support for the researcher - the VRE becomes assistive. Curation is autonomic and social.

3rd Generation Summary

Reflections

• Co-Evolution, Co-Design, Co-Constitution• Intellectual Access Ramps

– Incremental engagement– Safe places to play

• Datascopes– From signal to understanding– Medical images, music, ancient manuscripts– New born-digital data

Thanks to: Jeremy Frey & CombeChem; Carole Goble & myGrid; Iain Buchan, Sean Bechhofer & e-Laboratories; myExperiment; David Abramson; Marco Roos; Stephen Downie & SALAMI; the e-Social Science Directorate; Malcolm Atkinson

david.deroure@oerc.ox.ac.uk Visit wiki.myexperiment.org

This presentation is in myExperiment Pack 141 and http://www.slideshare.net/dder/evolution-of-eresearch