Presentation is loading. Please wait.

Presentation is loading. Please wait.

David De Roure Social Networking and Workflows in Research.

Similar presentations


Presentation on theme: "David De Roure Social Networking and Workflows in Research."— Presentation transcript:

1 David De Roure Social Networking and Workflows in Research

2 scientists Local Web 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 1.0 2.0 Next Generation Researchers

3 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.www.myexperiment.org

4

5

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

7 Bringing myExperiment to the user iGoogleTavernaFacebookWindows 7

8 New Instances

9 http://usefulchem.wikispaces.com/page/code/EXPLAN001 http://www.microsoft.com/mscorp/tc/trident.mspx http://www.mygrid.org.uk/tools/taverna/ Sharing pieces of process

10 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 Pauls 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, Repurposing

11 Results Logs Results Metadata Paper Slides Feeds into produces Included in produces Published in produces Included in Published in Workflow 16 Workflow 13 Common pathways QTL Pauls Pack

12 Exporting packs

13 Research Objects enable research to be: 1.Replayable – go back and see what happened 2.Repeatable – run the experiment again 3.Reproducible – new expt to reproduce results 4.Reusable – use as part of new experiments 5.Repurposeable – reuse the pieces in new expt 6.Replicatable – run more of the same 7.Robust – unbiased systematic science at speed The Seven Rs of Research Objects

14 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 2

15 Workflows and Services Experts Social by User Community refine validate refine validate Self by Service Providers seed refine validate seed Automated refine validate seed Curation

16 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 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 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.

17 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 dont control The paper is an archaic human-readable form of a Research Object – Could I have a copy of your Research Object please? Summary

18 Contact David De Roure dder@ecs.soton.ac.uk Carole Goble carole.goble@manchester.ac.uk Visit wiki.myexperiment.org


Download ppt "David De Roure Social Networking and Workflows in Research."

Similar presentations


Ads by Google