MyExperiment: Towards Research Objects

2. What is it? How it�s being used How we built it Towards the e-Laboratory

4. Not just collaboration in workflows, but collaborating with sharing workflows Over 400 taverna workflows publicly available. Combine different formalisms in one system? E.g. a dataflow Kahn network and a central- clock based calculus Kepler logoNot just collaboration in workflows, but collaborating with sharing workflows Over 400 taverna workflows publicly available. Combine different formalisms in one system? E.g. a dataflow Kahn network and a central- clock based calculus Kepler logo

6. Not just collaboration in workflows, but collaborating with sharing workflows Over 400 taverna workflows publicly available. Combine different formalisms in one system? E.g. a dataflow Kahn network and a central- clock based calculus Kepler logoNot just collaboration in workflows, but collaborating with sharing workflows Over 400 taverna workflows publicly available. Combine different formalisms in one system? E.g. a dataflow Kahn network and a central- clock based calculus Kepler logo

15. What is it? How it�s being used How we built it Towards the e-Laboratory

28. 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.

29. Supermarket shoppers Workflow consumers prefer larger workflows ready to be downloaded and enacted Tool buildersWorkflow authors prefer smaller, modularized workflows which can be assembled & customized

30. What is it? How it�s being used How we built it Towards the e-Laboratory

31. 24/5/2007 | myExperiment | Slide 31

37. Phase 2 Repository integration (institutional: EPrints, Fedora) Controlled vocabularies Relationships between items (in and between packs) Recommendations Improved search ranking and faceted browsing Indexing of packs New contribution types (Meandre, Kepler, e-books) Further blog / wiki integration Biocatalogue integration

38. Content Capture and Curation In particular a platform for research into curation practices As in the panel today Expert � Is library like Suppliers and crowd are the web side Automated is Expert curators: bioinformaticians who understand the services and workflows whose job it is to annotate and set up the curation pipelines, for services and workflows that are not of their own making. Self-curation: Some registries are closed � the myGrid registry is only curated by experts from the myGrid project itself. Others encourage service developers to self-curate, emphasising the use of plug-ins to service development environments such as Eclipse; examples include BioMoby�s jMoby plugin and SAWSDL4J, Lumina and Radiant toolkits for SAWSDL and WSMO Studio (21). Workflow repositories such as myExperiment rely on self-curation by the workflow developers and community curation by their users. Challenges include (a) the enforcement of controlled vocabularies by self-curators, particularly if the vocabularies are also managed by the developers as they can quickly become unruly and (b) incentivising people to contribute their services and workflows for the good of the community. Community Curators: The trend is to follow in the footsteps of popular Web 2.0 social computing sites and encourage community curation through user feedback, blogging, e-tracking, recommendations and folksonomy based tagging. Community approach to services development and use being tried by Seekda and BioMoby and for workflows by myExperiment. Community and self-curation requires built-in incentive models for people to contribute such as credit and attribution, but can be made to work for example iCapture successfully pioneered community curation of ontologies (Wilkinson PSB). Automated Curators: Automated scavengers and crawlers identify candidates for submission and extract as much metadata as possible. Functional metadata is hard to auto-curate, requiring: specialist metadata extraction tools [54]; software plug-ins that incidentally gather metadata from services as they are used in applications; or smart reasoning over seeded service descriptions and workflows [54]. Operational and usage metadata is ripe for automation, generated from monitoring services, application diagnostics, customer reports and Social Network Analysis. Workflow analytics is the term used for processing workflow collections to identify, for example, service co-use patterns and service popularity. Automated curation needs excellent infrastructure. In particular a platform for research into curation practices As in the panel today Expert � Is library like Suppliers and crowd are the web side Automated is Expert curators: bioinformaticians who understand the services and workflows whose job it is to annotate and set up the curation pipelines, for services and workflows that are not of their own making. Self-curation: Some registries are closed � the myGrid registry is only curated by experts from the myGrid project itself. Others encourage service developers to self-curate, emphasising the use of plug-ins to service development environments such as Eclipse; examples include BioMoby�s jMoby plugin and SAWSDL4J, Lumina and Radiant toolkits for SAWSDL and WSMO Studio (21). Workflow repositories such as myExperiment rely on self-curation by the workflow developers and community curation by their users. Challenges include (a) the enforcement of controlled vocabularies by self-curators, particularly if the vocabularies are also managed by the developers as they can quickly become unruly and (b) incentivising people to contribute their services and workflows for the good of the community. Community Curators: The trend is to follow in the footsteps of popular Web 2.0 social computing sites and encourage community curation through user feedback, blogging, e-tracking, recommendations and folksonomy based tagging. Community approach to services development and use being tried by Seekda and BioMoby and for workflows by myExperiment. Community and self-curation requires built-in incentive models for people to contribute such as credit and attribution, but can be made to work for example iCapture successfully pioneered community curation of ontologies (Wilkinson PSB). Automated Curators: Automated scavengers and crawlers identify candidates for submission and extract as much metadata as possible. Functional metadata is hard to auto-curate, requiring: specialist metadata extraction tools [54]; software plug-ins that incidentally gather metadata from services as they are used in applications; or smart reasoning over seeded service descriptions and workflows [54]. Operational and usage metadata is ripe for automation, generated from monitoring services, application diagnostics, customer reports and Social Network Analysis. Workflow analytics is the term used for processing workflow collections to identify, for example, service co-use patterns and service popularity. Automated curation needs excellent infrastructure.

40. 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

41. What is it? How it�s being used How we built it Towards the e-Laboratory

43. A laboratory is a facility that provides controlled conditions in which scientific research, experiments and measurements may be performed, offering a work space for researchers. An e-Laboratory is a set of integrated components that, used together, form a distributed and collaborative space for e-Science, enabling the planning and execution of in silico experiments -- processes that combine data with computational activities to yield experimental results

44. An e-Lab consists of: a community work objects generic resources for building and transforming work objects Sharing infrastructure and content across projects

45. An e-Lab is built from a collection of services, consuming and producing Research Objects

54. Contact David De Roure dder@ecs.soton.ac.uk Carole Goble carole.goble@manchester.ac.uk Visit wiki.myexperiment.org Slide Credits Sean Bechhofer, Simon Coles, Paul Fisher,Adam Belloum, David Shotton