The New e-Science

Between 19 th October and 23 rd November 2007 I attended six international meetings related to e-Science

Grid 2007 Scientific and Scholarly Workflows e-Social Science 2007 W3C

Open Grid Forum Microsoft e-Science

This is what I found

Not just a specialist few doing heroic science with heroic infrastructure

Everyone is mashing up

Chemists are blogging the lab

People are buying multicore machines and mobile devices

The cloud and the “long tail”

Everyday researchers doing everyday research 1

Data is large, rich, complex and real-time

There is new value in data, through new digital artefacts and through metadata e.g. context, provenance, workflows

This isn’t anti-computation – just design around data

A data-centric perspective, like researchers 2

The social process of science revisited in the digital age

“ Users add value” is the very nature of research

e-Science now focuses on publishing as well as consuming

Scholarly lifecycle perspective

Collaborative and participatory 3

This is new and powerful!

Community intelligence

Review

Usage informing recommendation

e.g. OpenWetWare

e.g. myExperiment

Benefitting from the scale of digital science activity to support science 4

...in terms of scholarly outputs and their reuse

Preprints servers and institutional repositories

Open journals

Open access to data

Science Commons

Object Reuse & Exchange

Increasingly open 5

The technologies people are using are not perfect

They are better

They are easy to use

They are chosen by scientists

Better not Perfect 6

The success stories come from the researchers who have learned to use ICT

Domain ICT experts are delivering the solutions

Anything that takes away autonomy will be resisted

Empowering researchers 7

e-Science is about the intersection of the digital and physical worlds

Sensor networks

Mobile handheld devices

About pervasive computing 8

Everyday researchers doing everyday research

A data-centric perspective, like researchers

Collaborative and participatory

Benefitting from the scale of digital science activity to support science

Increasingly open

Better not Perfect

Empowering researchers

About pervasive computing

Signs of the Times

e-Science is now enabling researchers to do some completely new stuff!

As the individual pieces become easy to use, researchers can bring them together in new ways and ask new questions

“ The next level”

Onward and Upward

Everyday researchers doing everyday research

BUT heroic infrastructure not being adopted

A data-centric perspective, like researchers

BUT Grid gives APIs to computation not data

Collaborative and participatory

BUT deeply rooted service provider mindset

Better not Perfect

BUT aims to provide well-engineered perfect solution

Giving autonomy to researchers

BUT imposes institutional control (at this time)

About pervasive computing

BUT about portals and not the next generation of users

The Grid Problem

e-Science Pipeline e-Science Technology Creators & Integrators Applications Research EE Research Socio-economic & Commercial Innovation e-Science bespoke tailoring Mass Use by Researchers 5 years 5 years 5 years CS Research e-Science 10s of integrators 100s of embedded consultants 1000s of research users The Arrow Problem Malcolm Atkinson

Web Services RESTful APIs cmd lines ssh http Web Browser Mobile phone iPod Car Equipment PDA P2P mashups workflows services applications Subject ICT experts Computer Scientists Software Companies Workflow tools Ruby on Rails ecosystem Scientists open source Software Engineers nesc