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Managing Life Science Information
  NBIC course for Bioinformatics PhD students
                    (and others)


http://www.nbic.nl/biowise/school/EduProg/InfoMan09/
  http://tinyurl.com/BioWiseInformationManagement
Factfile

•   Target audience
     – Bioinformatics PhD students
•   Lecturers
     – Ammar Benabdelkader, Peter Boncz, Andrew Gibson, Frank van
        Harmelen, Iwan Herman, M. Scott Marshall, Barend
        Mons, Marco Roos, Morris Swertz, Katy Wolstencroft
•   Coordinators
     – M. Scott Marshall, Marco Roos
•   Date
     – 25-29 May 2009
•   Location
     – Informatics Institute, F0.09, Science Park Amsterdam, the
        Netherlands
•   Limitations
     – For participants without their own laptop with wifi we have
        limited hands-on facilities.




                                                                 2
What are key aspects for the Management of
Life Science Information?
• BioAssistants say…
   –   Security
   –   Data compatibility
   –   Data versioning
   –   Data
   –   Information life cycle management
   –   Dissemination of data to other scientists
   –   Transport and size
   –   Data provenance
   –   Usability
   –   Searchability
   –   Life science
   –   Tools
   –   Management



                                                   3
Research cycle




             4
Data flow




        5
Knowledge flow




             6
Motivation

• Life science information is
  – about Life Science
     • meaningless without interpretation
  – complex
     • Biology is complex
  – scattered
     • Many experiments with limited scope
  – often dead and buried in
    'data graveyards‘
     • >1000 databases: ‘cottage industry’


                                             7
Course credo
Keep your information alive


 Or how to make your information
 understandable and computable




                                   8
Day 1 and 2 – information and knowledge

• Knowledge-based information
  management
  – learn about how the Semantic Web
    languages and tools can be used to
    manage biological data
  – learn what OWL and RDF mean and why
    they exist
  – acquire hands-on experience with these
    languages and tools
  – learn about sharing knowledge and
    community-based science
                                          9
Day 3 – processing information at large

• Database workhorses
  – learn about how to use relational
    databases for managing heterogeneous
    and distributed data
  – learn how laboratory information can be
    realistically managed, example:
    MolGenis
  – get hands-on experience with
    postgreSQL/mySQL and MolGenis



                                          10
Day 4 - Taverna and web services

• Taverna and web services for
  collaborative data integration
  – get a full tutorial on applying Taverna to
    implement data integration pipelines
  – get hands-on experience with Taverna




                                             11
Day 5 - Hands-on Semantic Data integration

• Hands-on Semantic Data
  integration
  – deploy what you have learned on your
    own application or on an example case,
    with experts present




                                             12
What should the lecturers address?

• BioAssistants say…
  – Organisational issues
  – Reuse
     • Including reuse storage facilities
  – Types of usage of data/information
     • When to use what?
  – Who is doing what?
  – Web2.0
  – Reproducibility
     • Example myExperiment
• Provenance
• Social aspects



                                            13
What cases would you like to address in the
hands-on sessions?

• BioAssistants say…
  –…




                                              14
Managing Life Science Information
  NBIC course for Bioinformatics PhD students
                    (and others)


http://www.nbic.nl/biowise/school/EduProg/InfoMan09/
  http://tinyurl.com/BioWiseInformationManagement

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Managing Life Science Information (2009)

  • 1. Managing Life Science Information NBIC course for Bioinformatics PhD students (and others) http://www.nbic.nl/biowise/school/EduProg/InfoMan09/ http://tinyurl.com/BioWiseInformationManagement
  • 2. Factfile • Target audience – Bioinformatics PhD students • Lecturers – Ammar Benabdelkader, Peter Boncz, Andrew Gibson, Frank van Harmelen, Iwan Herman, M. Scott Marshall, Barend Mons, Marco Roos, Morris Swertz, Katy Wolstencroft • Coordinators – M. Scott Marshall, Marco Roos • Date – 25-29 May 2009 • Location – Informatics Institute, F0.09, Science Park Amsterdam, the Netherlands • Limitations – For participants without their own laptop with wifi we have limited hands-on facilities. 2
  • 3. What are key aspects for the Management of Life Science Information? • BioAssistants say… – Security – Data compatibility – Data versioning – Data – Information life cycle management – Dissemination of data to other scientists – Transport and size – Data provenance – Usability – Searchability – Life science – Tools – Management 3
  • 7. Motivation • Life science information is – about Life Science • meaningless without interpretation – complex • Biology is complex – scattered • Many experiments with limited scope – often dead and buried in 'data graveyards‘ • >1000 databases: ‘cottage industry’ 7
  • 8. Course credo Keep your information alive Or how to make your information understandable and computable 8
  • 9. Day 1 and 2 – information and knowledge • Knowledge-based information management – learn about how the Semantic Web languages and tools can be used to manage biological data – learn what OWL and RDF mean and why they exist – acquire hands-on experience with these languages and tools – learn about sharing knowledge and community-based science 9
  • 10. Day 3 – processing information at large • Database workhorses – learn about how to use relational databases for managing heterogeneous and distributed data – learn how laboratory information can be realistically managed, example: MolGenis – get hands-on experience with postgreSQL/mySQL and MolGenis 10
  • 11. Day 4 - Taverna and web services • Taverna and web services for collaborative data integration – get a full tutorial on applying Taverna to implement data integration pipelines – get hands-on experience with Taverna 11
  • 12. Day 5 - Hands-on Semantic Data integration • Hands-on Semantic Data integration – deploy what you have learned on your own application or on an example case, with experts present 12
  • 13. What should the lecturers address? • BioAssistants say… – Organisational issues – Reuse • Including reuse storage facilities – Types of usage of data/information • When to use what? – Who is doing what? – Web2.0 – Reproducibility • Example myExperiment • Provenance • Social aspects 13
  • 14. What cases would you like to address in the hands-on sessions? • BioAssistants say… –… 14
  • 15. Managing Life Science Information NBIC course for Bioinformatics PhD students (and others) http://www.nbic.nl/biowise/school/EduProg/InfoMan09/ http://tinyurl.com/BioWiseInformationManagement