Social Networking and Workflows
in Research
David De Roure
The social process
of Science 2.0
1.0
Virtual Learning
Environment
Undergraduate
Students
Next Generation
Researchers
Digital
Libraries
scientists
Graduate
Students
Reprints
PeerReviewed
Journal &
Conference
Papers
Technical
Preprints Reports
&
Metadata
Repositories
experimentation
Local
Web
Certified
Experimental
Results & Analyses
Data, Metadata,
Provenance, Scripts,
Workflows, Services,
Ontologies, Blogs, ...
 “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.
Distinctives
myExperiment Features












User Profiles
Groups
Friends
Sharing
Tags
Workflows
Developer interface
Credits and Attributions
Fine control over privacy
Packs
Federation
Enactment
Bringing myExperiment
to the user
iGoogle
Taverna
Facebook
Windows 7
New
Instances
Sharing pieces of process
http://www.mygrid.org.uk/tools/taverna/
http://www.microsoft.com/mscorp/tc/trident.mspx
http://usefulchem.wikispaces.com/page/code/EXPLAN001
Reuse, Recycling, Repurposing
 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.
QTL
Workflow 16
Paul’s Pack
Results
produces
Included
in
Published in
Included in
Feeds into
Logs
produces
Included in
Included
in
Metadata
Slides
produces
Common pathways
Workflow 13
Paper
Published in
Results
Exporting packs
The Seven Rs of Research Objects
Research Objects enable research to be:
1.
2.
3.
4.
5.
6.
7.
Replayable – go back and see what happened
Repeatable – run the experiment again
Reproducible – new expt to reproduce results
Reusable – use as part of new experiments
Repurposeable – reuse the pieces in new expt
Replicatable – run more of the same
Robust – unbiased systematic science at speed
Phase 22
Phase
•
•
•
•
•
•
•
•
•
•
•
•
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
Curation
Self by Service
Providers
refine
validate
seed
Experts
refine
validate
seed
Workflows and Services
refine
validate
seed
Social by User
Community
seed
refine
validate
Automated
e-Laboratory Evolution
1st Generation
Current practice of early adoptors of e-Labs tools
2nd Generation
such as Taverna, ELNs, LIMS.
Designing
and delivering
on
experience
Characterised
by researchers
using now,
tools based
within
their
3rd Generation
with Taverna,
myExperiment
andofLablogs.
particular problem
area,The
with
some- re-use
tools,
vision
the e-Labs
we'll be delivering in 5 years data and methods
within
the discipline.
Key characteristic
is re-use
- of science
the increasing
poolsource
of
illustrated
by open
and open
science.
data and
methods, across
areas
& disciplines.
Traditional tools,
publishing
isCharacterised
supplemented
byglobal
publication
by
reuse
of tools, data and
of some digital
items
like
workflows
andrecombinant,
linksdiscipline,
to data. and surfacing the
methods
across
any
Contain
some
freestanding,
of complexity
for the researcher.
reproducible
Research
Objects.
Provenance
is recordedright
but levels
not shared
and re-used.
characteristic
is radical
analytics
plays
a role.
Science is Provenance
accelerated Key
and
practice
beginning
to sharing
Research
data driven - plundering the
shift to emphasise
in silico
work. is significantly
Expert curation
supplemented
by community
backlog of data, results and methods.
curation.
Research Objects supersede papers.
New scientific practices are established and
Increasing automation and decision-support for the
opportunities arise for completely new scientific
researcher - the e-Laboratory becomes assistive.
investigations.
Provenance assists design.
Curation is autonomic and social.
Entirely new research outcomes are obtained.
Summary
• 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?”
Contact
David De Roure
dder@ecs.soton.ac.uk
Carole Goble
carole.goble@manchester.ac.uk
Visit wiki.myexperiment.org