myExperiment A Web 2'0 VRE

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myExperiment A Web 2.0 Virtual Research
Environment David De RoureCarole Goble
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Overview

• e-Science is about scientists doing science
• A Tale of Two Projects
• myExperiment
• Design Patterns for a VRE

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CombeChem pilot project
Video
Simulation
Properties
Analysis
StructuresDatabase
Diffractometer
X-Raye-Lab
Propertiese-Lab
Grid Middleware
www.combechem.org
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Undergraduate Students
Digital Library
Graduate Students
E-Scientists
E-Scientists
E-Scientists
Reducing time-to-experiment
E-Experimentation
Entire e-Science CycleEncompassing
experimentation, analysis, publication, research,
learning
http//www.ukoln.ac.uk/projects/ebank-uk/
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Provenance

• The key observation!
• Publication at Source describes the need to
  capture data and its context from the outset and
  maintain a complete end-to-end connection between
  the laboratory bench and the intellectual
  chemical knowledge that is published as a result
  of the investigation

The details of the origins of data are just as
important to understanding as their actual values
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My Chemistry Experiment

• Box of Chemists

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The RDF Graph
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Data creation capture in Smart lab
Presentation services portals
Data discovery, linking, citation
Search, harvest
Data analysis, transformation, mining, modelling
Aggregator services
Harvest
Deposit
e-Research workflows
Institutional data repositories
Laboratory repository
e-Crystals Federation model
Deposit
Validation
Validation
Publication
(Chemistry Central)
Data curation preservation databases
databanks
Linking, citation
Publishers peer-review journals, conference
proceedings
This work is licensed under a Creative Commons
LicenceAttribution-ShareAlike 2.0
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Key collective activities in e-science
informal and formalcommunication
meetings
interpretation of data/events
archiving/recovering information
following through decisions/coordinating
activities
producing documents other artifacts
http//www.aktors.org/coakting/

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What we learnt about VREs

• Reducing time-to-experiment
• Datasets as publication
• Provenance matters
• Publish the pieces, dont warehouse
• Semantic Lab notebooks in the VRE
• Blogging the lab
• Federated back end
• Semantic DataGrid, built socially
• Deep integration with collaborative tools

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Bioinformatics is not Chemistry

• There are many pieces, from many boxes, but
  no box, and no lid with a complete picture of
  what the puzzle is supposed to be.
• Planning? No.
• Metadata an afterthought

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myGrid

• Open Source middleware for Life Scientists that
  enables them to undertake in silico experiments
  and share those experiments and their results.
• Machinery for linking together datasets and tools
• Individual scientists, in under-resourced labs,
  who use other peoples datasets and applications.
• Ad hoc exploratory workflows (data flows)
• To support sharing and collaboration between
  scientists to disseminate best practice and
  improve the quality of science
• 33,000 downloads 200 user sites 400
  workflows
• 3500 third party external services accessible.
• Moved from prototype to production quality.
• Open Middleware Infrastructure Institute UK
• http//www.mygrid.org.uk

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Taverna Workflow Workbench
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Widespread Adoption

• Users in US, Asia, UK, Europe, Australia
• Systems biology
• Proteomics
• Gene/protein annotation
• Microarray data analysis
• Medical image analysis
• Heart simulation orchestration
• High throughput screening of chemical compounds
• Phenotypical studies
• Public Health studies
• Clinical trial analysis
• Plants, Mouse, Human
• Astronomy
• Cultural Heritage

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Recycling, Reuse, Repurposing

• Identified a pathway for which its correlating
  gene (Daxx) is believed to play a role in
  trypanosomiasis resistance.
• Manual analysis on the microarray and QTL data
  failed to identify this gene as a candidate.
• Repetitive, unbiased analysis.

• Trypanosomiasis cattle workflow reused without
  change to identify the biological pathways
  involved in sex dependence in the mouse model,
  previously believed to be involved in the ability
  of mice to expel the parasite.
• Previously a manual two year study of candidate
  genes had failed to do this.

Paul Fisher et al A Systematic Strategy for
Large-Scale Unbiased Analysis of
Genotype-Phenotype Correlations Bioinformatics in
review
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• Service and workflow annotation
• Ontology 710 classes
• Full time curator
• Tagging by the masses
• 3500 service. 350 curated

• Provenance
• Ontology 35 classes
• Enriched with domain ontologies and service
  ontologies. Possibly.
• Export with data. Desirably.

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New Scientific Digital Artefacts

• Design
• Workflow design history
• Experiment purpose
• Scientist
• LogBook
• Workflow run log
• Data lineage
• Results interpretation log

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New digital artefacts
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myExperiment.org Portal Party

• 28th 29th Sept 2006
• Hand picked Taverna users Taverna development
  team
• Facilitated by NCeSS.
• AJAX based development
• CombeChem xfer

• A social networking environment for sharing any
  workflow
• A Taverna workflow run environment
• A multi-workflow launch environment

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Virtual Research Environments

• VRE 1
• Technology-focused
• Experimental
• Diverse design development approaches
• Stand-alone solutions

• VRE 2
• User- research practice-focused
• Developmental
• Unified design development approaches
• Integrated solutions

• Collaboration
• Supporting small large-scale research
• Support for single-disciplinary and
  multi-disciplinary research

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openwetware.org
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What are we trying to do?

• Enabling scientists to be (more) creative.
• Enabling scientists to be scientists. And not
  programmers.
• Enabling mediocre scientists to become better and
  thus have better science.
• Enabling smart scientists to be smarter and
  propagate their smartness.
• Accelerate dissemination, pooling, insight.
• Encouraging sanctioned plagiarism.

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Principles

• Focus on making it easy to publish information
• Discovering and sharing experimental artefacts
• Publishing results to standard community
  repositories
• Publishing scholarly output
• Familiar social networking / web paradigms
• Keeping it free and fluid and creative.
  Me-Science.
• Crossing system boundaries
• Trans-workflow
• Crossing discipline boundaries
• Multi-disciplinary, Inter-disciplinary,
  Trans-disciplinary
• Clustering expertise
• Intellectual fusion outside discipline.
  We-Science.
• Life Science, Social Science, Astronomy, Chemistry

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Scoping exercise

• Workflow warehouse / federation of repositories
  Open Archives Initiative. Federated
  myExperiments. Sharepoint.
• Social space organised rich site Social
  discourse organised service / workflow space
  using curated semantics.
• Granularity and identifiers Rolling-up
  provenance. Id resolution
• Open vs protected content Quality, Reliability,
  Validation, Safety, Intellectual Property,
  Ownership, Secrecy, A duty of guardianship.
  Curation? Policing? Local data mixed with shared
  resources
• Desktop integration Google gadgets for workflows.
  Interacting with workflows through Office
  products.
• Workflow execution (WHIP) Workflows Hosted in
  Portals project
• Evolving the myExperiment software Community
  development
• Enabling Scientists added value through
  applications and collaborative tagging

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Hack Fest
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Q1. Workflow Warehouse orFederation of
Repositories?

• Everything on the myExperiment.org web site
• vs
• Distributed stores
• Multiple myExperiments

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Q2. Social Space or Shoe Shop?

• Shopping for Workflows and Services and Data
  should be as easy as shopping for shoes.
• Organic growth is good and bad.
• Social tagging might help discover workflows but
  we need good metadata for automated use.

26/2/2007 myExperiment Slide 33
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Q3. How open is the content?

• OpenWetware is open
• Our users dont want this
• Provenance helps

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Q4. Integration

• Bring user to Web Site
• vs
• Bringing myExperimentness to existing interfaces

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Web 2.0 Design Patterns

• The Long Tail
• Data is the Next Intel Inside
• Users Add Value
• Network Effects by Default
• Some Rights Reserved
• The Perpetual Beta
• Cooperate, Don't Control
• Software Above the Level of a Single Device

• http//www.oreillynet.com/pub/a/oreilly/tim/news/2
  005/09/30/what-is-web-20.html

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1. The Long Tail

• Our target users are not just the specialist
  e-Scientists using computing resources to tackle
  major scientific breakthroughs, but also the
  large number of scientists conducting the routine
  processes of science on a daily basis.
• Through sharing we have the potential to enable
  smart scientists to be smarter and propagate
  their smartness, in turn enabling other
  scientists to become better and conduct better
  science.

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2. Data is the Next Intel Inside

• myExperiment understands that scientists are
  focused on data, not software or one particular
  workflow engine.
• Workflows are components of customised
  applications, many of which are data-oriented
  rather than process-oriented.
• Users manipulate, through their own applications,
  the product (data, model) yielded by the
  workflow.
• Furthermore, workflows themselves are the data of
  myExperiment and provide its unique value.

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3. Users Add Value

• myExperiment makes it easy to find workflows and
  is designed to make it useful and straightforward
  to share workflows and add workflows to the pool.
  
• To succeed we draw on the insights into the
  incentive models of scientists gained through
  experience with Taverna.

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4. Network Effects by Default

• myExperiment aggregates user data as a
  side-effect of using the VRE.
• The ability to execute workflows from
  myExperiment, and the integration of tools such
  as Taverna with myExperiment, further enable us
  to achieve increased value through usage.

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5. Some Rights Reserved

• myExperiment users require protection as well as
  sharing, but the environment is designed for
  maximum ease of sharing to achieve collective
  benefits workflows are "hackable" and
  "remixable".
• Initiatives such as Science Commons provide a
  useful context for this.

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6. The Perpetual Beta

• myExperiment is an online service (a collection
  of online services) and is continually evolving
  in response to its users.
• To support this, the project commenced with
  developers being embedded in the user community.
• Through day-to-day contact between designers and
  researchers, design is both inspired and
  validated.

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7. Cooperate, Don't Control

• myExperiment is a network of cooperating data
  services with simple interfaces which make it
  easy to work with content.
• It both provides services and reuses the service
  of others.
• It aims to support lightweight programming models
  so that it can easily be part of loosely coupled
  systems.

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8. Software Above the Level of a Single Device

• The current model of Taverna running on the
  scientists desktop PC or laptop is evolving into
  myExperiment being available through a variety of
  interfaces and supporting workflow execution.

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Closing

• e-Science is difficult workflows and Web 2.0
  make it easier.
• Our design workshops and the review against Web
  2.0 design patterns have revealed the
  relationship between myExperiment and Web 2.0.
• The collective benefits of participation arise
  not only from the users but also from the
  developers ease of use and ease of development.
  
• It might be useful to review other VREs against
  the design patterns.

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Take homes

• myExperiment is a Web 2.0 Environment for
  Scientists to share experiments
• Join us!
• David De Roure
• dder_at_ecs.soton.ac.uk
• Carole Goble
• carole.goble_at_manchester.ac.uk

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Credits

• myGrid and CombeChem
• Matt Lee
• David Withers
• Don Cruickshank
• Rob Procter
• Alex Voss
• June Finch
• Ed Zaluska
• All the users inc. embedders