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D avid De Roure

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.

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D avid De Roure

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  1. Web 2 revisited David De Roure WSRI Summer School RPI July 2009

  2. 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

  3. Overview Web 2.0 Design Patterns circa 2005 A case study: myexperiment.org Reflection on the patterns

  4. What is Web 2.0?

  5. User Generated Slide Content... • Adhocracy • REST • Collective intelligence • Rich user interfaces • Unspoken agreement on branding • The read-write-web • Marketing term • Wikis • Blogs • User generated content • Mashups • Software that fosters communities • User interaction and collaboration

  6. Web 2.0 Design patterns / memes http://oreilly.com/web2/archive/what-is-web-20.html

  7. The Long TailSmall 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.

  8. Data is the Next Intel InsideApplications are increasingly data-driven. Therefore: For competitive advantage, seek to own a unique, hard-to-recreate source of data.

  9. Users Add ValueThe 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”

  10. Network Effects by DefaultOnly 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.

  11. Some Rights ReservedIntellectual 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."

  12. The Perpetual BetaWhen 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.

  13. Cooperate, Don't ControlWeb 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.

  14. Software Above the Level of a Single DeviceThe 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.

  15. Overview • A case study The experiment that is • What it is, how it’s used and how it’s built

  16. Are researchers a good case study? • 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

  17. ?

  18. Thanks to Carole Goble Duncan’s Research Environment LogBook Images Presentations Software Literature Compute resource His friends and colleagues Backup and Archive Data (files, spreadsheets)

  19. “There are these great collaboration tools that 12-year-olds are using. It’s all back to front.” Robert Stevens

  20. Virtual Learning Environment Reprints Peer-Reviewed Journal & Conference Papers Technical Reports LocalWeb Preprints & Metadata Repositories Certified Experimental Results & Analyses The social process of Science 1.0 Undergraduate Students 2.0 Next Generation Researchers Digital Libraries scientists Graduate Students experimentation Data, Metadata, Provenance, Scripts, Workflows, Services,Ontologies, Blogs, ... Thanks to Simon Coles

  21. “A biologist would rather share their toothbrush than their gene name” Mike Ashburner and others Professor Genetics, University of Cambridge, UK “Data mining: my data’s mine and your data’s mine” Thanks to Carole Goble

  22. The experiment that is Web 2 Social Network Open Repositories Researchers

  23. Not Facebook for scientists! Facebook for scientists! mySpace for scientists!

  24. “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.

  25. 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

  26. E. Science laboris • 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

  27. 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.

  28. myExperiment Features • User Profiles • Groups • Friends • Sharing • Tags • Workflows • Developer interface • Credits and Attributions • Fine control over privacy • Packs • Federation • Enactment Distinctives

  29. Control over sharing The most important aspect of myExperiment Designed by scientists

  30. Packs

  31. Workflow 16 QTL Logs Results Paul’s Pack Metadata Slides Paper Common pathways Results Workflow 13

  32. C • 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. Scientists do share!  Consumers > Curators > Producers Scientists do share! 

  33. Packs in Practice results input workflow

  34. Packs in Practice

  35. Co-operate, don’t control

  36. For Developers XML ORE FOAF SIOC facebook iGoogle android APIconfig HTML SearchAPI Managed REST API Search Engine SPARQL endpoint tags ratings reviews profiles groups workflows credits EPrints DSpace Fedora S3 SRB friendships packs files ` RDF Store mySQL Enactor API Enactor

  37. Google Gadgets Bringing myExperiment to the iGoogle user

  38. Taverna Plugin Bringing myExperiment to the Taverna user

  39. Facebook

  40. SPARQL endpoint rdf.myexperiment.org Transform tags ratings reviews profiles groups workflows credits SPARQL endpoint friendships packs files RDF Store mySQL Modularised myExperiment Ontology myExperiment data model (evolving!) DC, FOAF, SIOC(Semantically-Interlinked Online Communities)

  41. Exporting packs

  42. New Instances

  43. Six Principles of Software Design to Empower Scientists Keep your Friends Close Embed Keep Sight of the Bigger Picture Favours will be in your Favour Know your users Expect and Anticipate Change • Fit in, Don’t Force Change • Jam today and more jam tomorrow • Just in Time and Just Enough • Act Local, think Global • Enable Users to Add Value • Design for Network Effects De Roure, D. and Goble, C. "Software Design for Empowering Scientists," IEEE Software, vol. 26, no. 1, pp. 88-95, January/February 2009

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