Section outline

  • General

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    Using the Semantic Web for faster (Bio-)Research

    Geneva, 30 November - 3 December 2015

     

    Trainers:

    Jerven Bolleman, SIB / Swiss-Prot
    Marco Brandizi, EMBL-EBI
    Frédéric Bastian, SIB / Evolutionary Bioinformatics
    Kieron Taylor, EMBL-EBI
    Mark Wilkinson, CBGP
    Raoul Bonnal, INGM
    Erik Garrison, Sanger Centre
    Núria Queralt Rosinach, Pompeu Fabra University
    Axel Ngonga, Universität Leipzig
    Andrea Splendani, Novartis

    Ruben Verborgh, Ghent University – iMinds

    Daniel Teixeira, SIB /CALIPHO & SIB Technology
    Venue: Classroom S1-2, CMU, University of Geneva
    ECTS: No
    Fee: Free for Staromics students. Others, please contact us
    Application deadline:
    		 20 November 2015
    Application status: closed

    Overview

    Accessing and using existing public data is a hassle, yet it is crucial for designing good experiments. This 4 day course, co-organized by SIB and CUSO/Staromics, will teach PhD students on how to use semantic web technologies for their own research.
    It includes an in-depth exploration of Semantic Web concepts such as RDF (data modelling), SPARQL (asking questions on your data), OWL (reasoning for deducing new facts about your data)

    The course will teach you how to use these technologies in your day to day research, as well as how you can share your data with the rest of the world.


    The course will also include:

    • Modeling data tips and tricks
    • Using the UniProt sparql endpoint for maximum efficiency
    • Managing experimental results
    • How to deploy SPARQL based software in a secure and efficient manner.
    • How can you use OWL reasoning with RDF to test different hypothesis
    • Linking programs with data, combining webservices with SPARQL via OWL
    • Using BioRuby tools with SPARQL and RDF data
    • Small and BigData better when combined

    Learning objectives

    At the end of the course, you should be able to:

    • Work effectively with your own and other groups data using standardized technologies
    • Understand when SPARQL and RDF are useful tools for your work
    • Use the UniProt, neXtProt and among others the EBI RDF platform

    Application is closed

    Additional information

    Coordination: Corinne Dentan, Grégoire Rossier

    For administrative questions, please contact staromics@cuso.ch
    For technical and scientific questions, please contact training@isb-sib.ch

  • Schedule

    Day 1 Monday CMU S1/S2 November 30th
    09:00 10:30 RDF What, when, why? Jerven Bolleman
    Coffee
    10:45 12:00 Modeling experimental data for analysis and distribution Jerven Bolleman
    Lunch
    13:00 14:30 SPARQL introduction and UniProt RDF&SPARQL: how to use Jerven Bolleman
    Coffee
    14:45 17:00 EBI RDF platform: what is it, what does it contain Marco Brandizi
    Day 2 Tuesday CMU S1/S2 December 1st
    09:00 10:15 DisGenet RDF&SPARQL: how to use + modeling challenges Núria Queralt Rosinach
    Coffee
    10:30 11:45 Bgee, Uberon and an introduction to OWL Frederic Bastian
    Lunch
    12:45 14:00 Genome Variation Graphs and their representation in RDF Erik Garrison
    14:00 15:15 Client side SPARQL and Linked Data Ruben Verborgh
    Coffee
    15:30 17:00 DBPedia and the life sciences Axel Ngonga
    Day 3 Wednesday CMU S2/S2 December 2nd
    09:00 10:15 Ensembl RDF&SPARQL: how to use Kieron Taylor
    Coffee
    10:30 11:45 SPARQL over programs, and workflows without effort using SADI Mark Wilkinson
    Lunch
    12:45 14:00 BioRuby & Ruby-RDF Raoul Bonnal
    14:00 15:15 Visualising SPARQL&RDF Daniel Teixeira
    Coffee
    15:30 17:00 SemWeb at Novartis Andrea Splendani
    Day 4 Thursday Campus Biotech Geneva SIB Offices December 3rd
    09:00 17:00 Hackathon
    • Bring your own data + Laptop
    • Open to anyone (participants and teachers first, then anyone else)
    • The idea here is to build rough prototypes that people can work out into production quality code afterwards.
    Benefit from each others experience and put in to practice what is learned.