david de roure social networking and workflows in research
TRANSCRIPT
David De Roure
Social Networking and Workflows in Research
scientists
LocalWeb
Repositories
Graduate Students
Undergraduate Students
Virtual Learning Environment
Technical Reports
Reprints
Peer-Reviewed Journal &
Conference Papers
Preprints &
Metadata
Certified Experimental
Results & Analyses
experimentation
Data, Metadata, Provenance, Scripts, Workflows, Services,Ontologies, Blogs, ...
Digital Libraries
The social process of Science 1.02.0
Next Generation Researchers
“Facebook for Scientists” ...but different to Facebook!
A repository of research methods
A community social network of people and things
A Virtual Research Environment
Open source (BSD) Ruby on Rails application with HTML, REST and SPARQL interfaces
Project started March 2007
Closed beta July 2007
Open beta November 2007
myExperiment currently has 1800 registered users, 150 groups, 700 workflows, 200 files and 60 packs.Go to www.myexperiment.org to access publicly available content or create an account.
User Profiles Groups Friends Sharing Tags Workflows Developer interface Credits and Attributions Fine control over privacy Packs Federation Enactment
myExperiment FeaturesmyExperiment FeaturesD
istin
ctiv
es
Bringing myExperiment to the user
Bringing myExperiment to the user
iGoogle Taverna Facebook Windows 7
New Instances
New Instances
http://usefulchem.wikispaces.com/page/code/EXPLAN001http://www.microsoft.com/mscorp/tc/trident.mspx
http://www.mygrid.org.uk/tools/taverna/
Sharing pieces of processSharing pieces of process
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, RepurposingReuse, Recycling, Repurposing
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
QTL
Paul’s PackPaul’s Pack
Exporting packsExporting packs
Research Objects enable research to be:
1.Replayable – go back and see what happened2.Repeatable – run the experiment again3.Reproducible – new expt to reproduce results4.Reusable – use as part of new experiments5.Repurposeable – reuse the pieces in new expt6.Replicatable – run more of the same7.Robust – unbiased systematic science at speed
The Seven Rs of Research ObjectsThe Seven Rs of Research Objects
Phase 2• Notifications• Taverna 2 support• Support for expert curators• Controlled vocabularies• Faceted browsing• New contribution types (scripts,
Meandre, Kepler, e-books)• Biocatalogue integration• Relationships between items (in and
between packs)• Indexing of packs• Further blog / wiki integration• Repository integration (EPrints, Fedora)• Recommendations
Phase 2Phase 2
Workflows and Services
Experts
Social by User Community
refinevalidate
refinevalidate
Self by Service Providers
seed seed
refinevalidate
seed
Automated
refinevalidate seed
CurationCuration
1st Generation
Current practice of early adoptors of e-Labs tools such as Taverna, ELNs, LIMS.
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 items like workflows and links to data.
Provenance is recorded but not shared and re-used.
Science is accelerated and practice beginning to shift to emphasise in silico work.
e-Laboratory Evolutione-Laboratory Evolution
2nd Generation
Designing and delivering now, based on experience with Taverna, myExperiment and Lablogs.
Key characteristic is re-use - of the increasing pool of tools, data and methods, across areas & disciplines.
Contain some freestanding, recombinant, reproducible Research Objects.
Provenance analytics plays a role.
Expert curation supplemented by community curation.
New scientific practices are established and opportunities arise for completely new scientific investigations.
3rd GenerationThe vision - the e-Labs we'll be delivering in 5 years - illustrated by open science and open source science.Characterised by global reuse of tools, data and methods across any discipline, and surfacing the right levels of complexity for the researcher. Key characteristic is radical sharing Research is significantly data driven - plundering the backlog of data, results and methods. Research Objects supersede papers.Increasing automation and decision-support for the researcher - the e-Laboratory becomes assistive. Provenance assists design.Curation is autonomic and social.Entirely new research outcomes are obtained.
• Understand the Web 2 generation of researchers and the changing nature of research practice
• Success of agile development methods and the “perpetual beta”• Co-operate don’t control• The paper is an archaic human-readable form of a Research Object
– “Could I have a copy of your Research Object please?”
SummarySummary
