New e-Science Edinburgh Late Edition - Presentation Transcript
Edinburgh Late Edition
In November 2007 I presented a talk in the e-Science Institute about the New e-Science . 10 months later I’m back... with a new 10 point definition of how research will be conducted in the future.
Due to the complexity of the software and the backend infrastructural requirements, e-Science projects usually involve large teams managed and developed by research laboratories, large universities or governments.
e-Science is about global collaboration in key areas of science, and the next generation of infrastructure that will enable it.
How do we move from heroic scientists doing heroic science with heroic infrastructure to everyday scientists doing science they couldn’t do before? humanists archaeologists geographers musicologists ... researchers! research It’s the democratisation of e-Research
Decreasing cost of entry into digital research means more people, data, tools and methods.
Anyone can participate: researchers in labs, archaeologists in digs or schoolchildren designing antimalarial drugs. Citizen science!
Improved capabilities of digital research (e.g. increasing automation, ease of collaboration) incentivises this participation.
"You're letting the oiks in!" people cry, but peer review benefits from scale of participation too.
“ Long Tail Science”
Increasing scale and diversity of participation 1 VERA
Deluge due to new experimental methods (microarrays, combinatorial chemistry, sensor networks, earth observation, ...) and also (1).
Increasing scale, diversity and complexity of digital material, processed separately and in combination .
New digital artefacts like workflows, provenance, ontologies and lab books.
Context and provenance essential for re-use, quality and trust.
Digital Curation challenge!
Increasing scale and diversity of data 2 Taverna workflow
Anyone can play and they can play together.
Anyone can be a publisher as well as a consumer – everyone’s a first class citizen.
Science has always been a social process, but now we're using new social tools for it.
Evidenced by use of wikis, blogs, instant messaging.
The lifecycle goes faster, we accelerate research and reduce time-to-experiment.
Sharing 3 Open Wetware
Increasing participation means network effects through community intelligence: tagging, reviewing, discussion.
Recommendation based on usage.
This is in fact the only significant breakthrough in distributed systems in the last 30 years.
Community curation: combat workflow decay!
Collective Intelligence 4 myExperiment
Publicly available data but also the open services and software tools of open science.
Increasing adoption of Science Commons, open access journals, open data and linked data*, PLoS, ...
Open notebook science
* formerly known as Semantic Web
Open Research 5 arXiv, Science Commons, UsefulChem
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