d avid de roure
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Web 2 revisited. D avid De Roure. WSRI Summer School RPI July 2009. Objectives. You will be able to answer the question “What is Web 2.0?” You will have some ideas about how our co-constituted Web is co-evolving :-) On the way we will touch on Web of Services and on end-user programming. - PowerPoint PPT PresentationTRANSCRIPT
WSRI Summer School RPI July 2009
1. You will be able to answer the question
“What is Web 2.0?”
2. You will have some ideas about how our co-constituted Web is co-evolving :-)
• On the way we will touch on Web of Services and on end-user programming
ObjectivesObjectives
1. Web 2.0 Design Patterns circa 2005
2. A case study: myexperiment.org
3. Reflection on the patterns
OverviewOverview
What is Web 2.0?
• Wikis• Blogs• User generated
content• Mashups• Software that fosters
communities• User interaction and
collaboration
• Adhocracy• REST• Collective intelligence• Rich user interfaces• Unspoken agreement
on branding• The read-write-web• Marketing term
User Generated Slide Content...User Generated Slide Content...
http://oreilly.com/web2/archive/what-is-web-20.html
Web 2.0 Design patterns / memesWeb 2.0 Design patterns / memes
1. The Long Tail
Small sites make up the bulk of the internet's content; narrow niches make up the bulk of the internet's possible applications.
Therefore: Leverage customer-self service and algorithmic data management to reach out to the entire web, to the edges and not just the center, to the long tail and not just the head.
2. Data is the Next Intel Inside
Applications are increasingly data-driven.
Therefore: For competitive advantage, seek to own a unique, hard-to-recreate source of data.
3. Users Add Value
The key to competitive advantage in internet applications is the extent to which users add their own data to that which you provide.
Therefore: Don't restrict your “architecture of participation” to software development. Involve your users both implicitly and explicitly in adding value to your application.
“Second Life sells the land, the customers make it a reality”
4. Network Effects by Default
Only a small percentage of users will go to the trouble of adding value to your application.
Therefore: Set inclusive defaults for aggregating user data as a side-effect of their use of the application.
5. Some Rights Reserved
Intellectual property protection limits re-use and prevents experimentation.
Therefore: When benefits come from collective adoption, not private restriction, make sure that barriers to adoption are low. Follow existing standards, and use licenses with as few restrictions as possible. Design for "hackability" and "remixability."
6. The Perpetual Beta
When devices and programs are connected to the internet, applications are no longer software artifacts, they are ongoing services.
Therefore: Don't package up new features into monolithic releases, but instead add them on a regular basis as part of the normal user experience. Engage your users as real-time testers, and instrument the service so that you know how people use the new features.
7. Cooperate, Don't Control
Web 2.0 applications are built of a network of cooperating data services.
Therefore: Offer web services interfaces and content syndication, and re-use the data services of others. Support lightweight programming models that allow for loosely-coupled systems.
8. Software Above the Level of a Single Device
The PC is no longer the only access device for internet applications, and applications that are limited to a single device are less valuable than those that are connected.
Therefore: Design your application from the get-go to integrate services across handheld devices, PCs, and internet servers.
• A case study
OverviewOverview
The experiment that is
• What it is, how it’s used and how it’s built
• The Web was invented by a physicist!• The Web was co-constituted in a technology-rich
environment with research users• Researchers are often early adopters e.g.
Internet, data on the Web• Research collaborations vary in organisation,
culture, governance, rights flow, reward structures, within and between communities
Are researchers a good case study?Are researchers a good case study?
?
His friends and colleagues
Literature
ImagesLogBook
Software
Presentations
Data (files, spreadsheets)
Compute resource
Backup and Archive
Thanks to Carole Goble
Duncan’s Research EnvironmentDuncan’s Research Environment
“There are these great collaboration tools that 12-year-olds are using. It’s all back to front.”
Robert Stevens
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
Thanks to Simon Coles
“A biologist would rather share their toothbrush than their gene name”
Mike Ashburner and othersProfessor Genetics,
University of Cambridge, UK
“Data mining: my data’s mine and your data’s mine”
Thanks to Carole Goble
Web 2
Open Repositories
Researchers
Social Network
The experiment that is
mySpace for scientists!Facebook for scientists!Not Facebook for scientists!
“Facebook for Scientists” ...but different to Facebook!
A repository of research methods (an SGDL?)
A community social network of people and things
A Social 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 2200 registered users, 160 groups, 750 workflows, 220 files and 70 packs.Go to www.myexperiment.org to access publicly available content or create an account.
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
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
E. Science laboris E. Science laboris
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
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
Control over sharingControl over sharing
The most important aspect of myExperimentDesigned by scientists
The most important aspect of myExperimentDesigned by scientists
PacksPacks
ResultsLogs
Results
Metadata PaperSlides
Workflow 16
Workflow 13
Common pathways
QTL
Paul’s PackPaul’s Pack
• Of the 661 workflows, 531 are publicly visible whereas 502 are publicly downloadable.
• 3% of the workflows with restricted access are entirely private to the contributor and for the remaining they elected to share with individual users and groups.
• 69 workflows (over 10%) have been shared, with the owner granting edit permissions to specific users and groups.
• In addition there are 52 instances where users have noted that a workflow is based on another workflow on the site.
• The most viewed workflow has 1566 views.• There are 50 packs, ranging from tutorial examples to
bundles of materials relating to specific experiments.
C
Scientists do share! Scientists do share! Scientists do share!
Consumers > Curators > Producers
Scientists do share!
Consumers > Curators > Producers
workflow
results
input
Packs in Practice
Packs in Practice
Packs in Practice
Packs in Practice
24/5/2007 | myExperiment | Slide 41
Co-operate, don’t controlCo-operate,
don’t control
Search Engine
reviewsratingsgroupsfriendships
tags
Enactor
filesworkflows
`
HTML
For DevelopersFor Developers
RDF Store
SPAR
QL
endp
oint
Managed REST API
face
book
iGoo
gle
andr
oid
XML
APIconfig
mySQL
profiles
packscredits
Google GadgetsGoogle Gadgets
Bringing myExperiment to the iGoogle userBringing myExperiment to the iGoogle user
Taverna PluginTaverna Plugin
Bringing myExperiment to the Taverna userBringing myExperiment to the Taverna user
FacebookFacebook
reviewsratingsgroupsfriendships
tags
filesworkflows RDF
Store
SPAR
QL
endp
oint
mySQL
profiles
packscredits
Modularised myExperiment Ontology
myExperiment data model (evolving!)
SPARQL endpointSPARQL endpoint
rdf.myexperiment.org
DC, FOAF, SIOC(Semantically-Interlinked Online Communities)
Exporting packsExporting packs
New Instances
New Instances
1. Fit in, Don’t Force Change2. Jam today and more jam
tomorrow
3. Just in Time and Just Enough
4. Act Local, think Global 5. Enable Users to Add Value6. Design for Network Effects
1. Fit in, Don’t Force Change2. Jam today and more jam
tomorrow
3. Just in Time and Just Enough
4. Act Local, think Global 5. Enable Users to Add Value6. Design for Network Effects
Six Principles of Software Design to Empower ScientistsSix Principles of Software Design to Empower Scientists
1. Keep your Friends Close2. Embed3. Keep Sight of the Bigger
Picture4. Favours will be in your
Favour5. Know your users6. Expect and Anticipate
Change
1. Keep your Friends Close2. Embed3. Keep Sight of the Bigger
Picture4. Favours will be in your
Favour5. Know your users6. Expect and Anticipate
Change
De Roure, D. and Goble, C. "Software Design for Empowering Scientists," IEEE Software, vol. 26, no. 1, pp. 88-95, January/February 2009
• Reflection on the design patterns• The Long Tail• Data is the Next Intel Inside• Users Add Value• Cooperate, Don't Control
• Are any obsolete? Do we need new ones?
OverviewOverview
1. The Long Tail
Small sites make up the bulk of the internet's content; narrow niches make up the bulk of the internet's possible applications.
Pushback: Crowd sourcing is ok for flickr, data collection by ornithologists and mechanical turk, but only the skilled can do research and indiscriminate sharing is harmful.
How do we move from heroic scientists doing heroic science with heroic infrastructure to everyday scientists doing science they couldn’t do before?humanists
archaeologistsgeographersmusicologists...researchers!
research
It’s the democratisation of e-Science!
Nopedestrians
You’re letting
theoiksin!
You’re letting
themuggle
sin!
Nomuggles
2. Data is the Next Intel Inside
Applications are increasingly data-driven.
Pushback: Scientists don’t work with just one type of data! Sometimes they are messy too.
ResultsLogs
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 Fisher
David Shotton
Anatomy of a Research ObjectAnatomy of a Research Object
We want 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 – for scale and automation7.Reliable – systematic, unbiased and robust
My Seven RsMy Seven Rs
Communications of the ACM 51, 4 (Apr. 2008), 52-58
Scientific Discourse Relationships Ontology Specification
Open Provenance Model
3. Users Add Value
The key to competitive advantage in internet applications is the extent to which users add their own data to that which you provide.
Pushback: But now users want to specify the behaviour of applications: “End user programming” of web apps, workflows and mashups
Kepler
Triana
BPEL
Ptolemy II
Taverna
Trident
BioExtract
Gibson, A.; Gamble, M.; Wolstencroft, K.; Oinn, T.; Goble, C., "The Data Playground: An Intuitive Workflow Specification Environment," e-Science and Grid Computing, IEEE International Conference, pp.59-68, 10-13 Dec. 2007
7. Cooperate, Don't Control
Web 2.0 applications are built of a network of cooperating data services.
Pushback: But Web 2 sites like Facebook don’t really contribute to the Web, while publication of RDF by myExperiment or the BBC does
Loose coupling in myExperimentLoose coupling in myExperimentThanks toFrancois Belleau
• The Long Tail– But letting the muggles in! Web 2 means better
peer review?• Data is the Next Intel Inside
– But people are messy, and what about Semantic Web? Is this Web 3.0? My “Web-Particle duality”
• Users Add Value– Behaviours too? Will Semantic Web help mashups?
Linking the data, finding the services?• Cooperate, Don't Control
– But walled gardens don’t add to the Web. We are more Web 2 than Web 2 sites!
User generated discussion slideUser generated discussion slide
• Web 2 is characterised by a set of memes (or patterns) which are really observations on society and the Web - they act as witness to the co-constitution
• myExperiment.org is a case study of Web 2 memes in a social site for researchers
• Watch for the evolution of end user programming and adoption of Semantic Web approaches
Take HomesTake Homes
Sergejs Aleksejevs Jiten Bhagat Simon Coles Don Cruickshank Cat De Roure Paul Fisher Jeremy Frey Antoon Goderis Andrew Harrison Duncan Hull Yuwei Lin Danius Michaelides David Newman Cameron Neylon Stuart Owen Savas Parastatidis Meik Poschen Rob Procter Marco Roos Stian Soiland Ian Taylor Andrea Wiggins Alan Williams Katy Wolstencroft Mark Borkum Tom Eveleigh June Finch Matt Lee Kurt Mueller Alexander Voss David Withers
ReferencesReferences
De Roure, D., Goble, C. and Stevens, R. (2009) The Design and Realisation of the myExperiment Virtual Research Environment for Social Sharing of Workflows. Future Generation Computer Systems 25, pp. 561-567. doi:10.1016/j.future.2008.06.010
De Roure, D. and Goble, C. (2009) "Software Design for Empowering Scientists," IEEE Software, vol. 26, no. 1, pp. 88-95, January/February 2009. doi:10.1109/MS.2009.22
Goble, C. And De Roure, D. (2008) Curating Scientific Web Services and Workflows. EDUCAUSE Review, vol. 43, no. 5 (September/October 2008) http://connect.educause.edu/Library/EDUCAUSE+Review/CuratingScientificWebServ/47226
See http://wiki.myexperiment.org/index.php/Papers