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Social Networking and Workflows in Research. David De Roure. Virtual Learning Environment. Reprints. Peer-Reviewed Journal & Conference Papers. Technical Reports. Local Web. Preprints & Metadata. Repositories. Certified Experimental Results & Analyses. The social process of Science 1.0.
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Social Networking and Workflows in Research David De Roure
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, ...
“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.
myExperiment Features • User Profiles • Groups • Friends • Sharing • Tags • Workflows • Developer interface • Credits and Attributions • Fine control over privacy • Packs • Federation • Enactment Distinctives
Bringing myExperiment to the user iGoogle Taverna Facebook Windows 7
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.
Workflow 16 QTL Paul’s Pack Results produces Included in Published in Included in Feeds into Logs produces Included in Included in Metadata Slides Paper produces Published in Common pathways Results Workflow 13
The Seven Rs of Research Objects Research Objects enable research to be: • 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 2 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
Curation Self by Service Providers Experts refine validate refine validate seed seed Workflows and Services refine validate refine validate seed seed Social by User Community Automated
e-Laboratory Evolution 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. 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 Generation The 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.
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