BioRDF Top Level Task

Task Seeding the Semantic Web

Task Objectives

  1. Build a life sciences demo that spans from bench to bedside using RDF and OWL to gain a stronger understanding as to the work required.
  2. Explore the effectiveness of current tools for making data available as RDF/OWL.
  3. Document our finding to help accelerate the adoption of the Semantic Web by others.

Task Participants JohnBarkley (NIST), OlivierBodenreider (NLM), Kyle Bruck (Stanford University), BillBug (Drexel U.), VinayChaudhri (SRI), KeiCheung (Yale University), TimClark (MGH), RogerCutler (Chevron), DonaldDoherty (Brainstage Research), Kerstin Forsberg (AstraZeneca), Yong Gao (MGH), BrianGilman (Panther Informatics), June Kinoshita (AlzForum), Nikesh Kotecha (Stanford University), OraLassila (Nokia), JoanneLuciano (Predictive Medicine), ScottMarshall (University of Amsterdam), RobinMcEntire (GSK), BrianOsborne (BioPerl), ChristophePoulain (Teranode), DanielRubin (Stanford University), AlanRuttenberg (Millennium Pharmaceuticals), MatthiasSamwald (Medical University of Vienna), Matt Shanahan (Teranode), Karen Skinner (NIH), SusieStephens (Eli Lilly), Charles Tilford (BMS), JohnWilbanks (Creative Commons), Elizabeth Wu (AlzForum), DavideZaccagnini (Language and Computing).

Task Coordinator

Use case context Build an integrated data environment using RDF and OWL for neuroscience in order to help glean new scientific insights.

Problem statement for this use case Simplify the process of answering scientific questions. Demonstrate the flexibility and re-use that is inherent in Semantic Web technologies.


  1. A demonstration of a use case with the following features:
    • The main focus of the demo is on the integration of multiple data sets in the domain area of neuroscience, with initial focus on data sets from NCBI.
    • Additional data sets will be required to span the demo from ‘bench to bedside’.
    • Tools that perform RDF export for the data sets used in the demo will be made available to the data providers for potential server-side deployment.
  2. A report on best practices regarding the use of tools, and any potential gaps.
    • The scalability of aggregating all necessary data into a central RDF repository will be addressed.
    • Recommendations and considerations for increased scalability such as "RDF export on-demand" and query rewriting (e.g. D2RQ) will be discussed.

Related resources

Task supports and dependencies

  • The development of a neurosciences use case - Task 2
  • Making NCBI data available as RDF - Task 3
  • Making clinical data sets available as RDF - Task 4
  • Education on neuroscience - Task 5
  • Education on SPARQL, OWL, GRDDL, etc. - Task 6

Tools and Services


  • Workshop on Ontology of Images


Timeline for Task Completion

  • Stage 1 (3 month goals)
    • Identify the initial data sources to be used in the demo.
    • Explore additional data sources that would be required for the demo to span ‘bench to bedside’.
    • Learn about GRDDL, SPARQL, OWL, etc.
    • Increase knowledge of neuroscience.
    • Set up a Wiki for communication.
  • Stage 2 (6 months goals)
    • Transform data into RDF from Word, Excel, XML, Relational, etc.
    • Analysis of semantic requirements (connect to ontology sub-group).
    • Move from screen scraping to an API.
    • Create documents that describe work undertaken, and observations.
  • Stage 3 (12 months goals)
    • Use ontologies with the demo.
    • Answer scientific questions and hopefully glean new scientific insights through using the demo.
    • Validate the effectiveness of the data integration.

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Last modified on 16 July 2008, at 13:33