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Semantic Web for Life Sciences W3C BOF 2005 ISMB.

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Presentation on theme: "Semantic Web for Life Sciences W3C BOF 2005 ISMB."— Presentation transcript:

1 Semantic Web for Life Sciences W3C BOF 2005 ISMB

2 Agenda What is SW? Current Activities Use Case Scenarios Resources What do we need to focus on next?

3 What is SW? RDF - Web-transportable descriptive model of all information OWL - Web Ontology Language; 3 levels of complexity/expressivity Focus on Semantic rather than Syntax Open world Graph model of all information on the Web Rules - SWRL

4 DTD RDF-XML

5 Semantic Web for Life Sciences An Open Scientific Forum for –Defining Cross-Disciplinary Life Science needs –Show-Casing Working Examples –Initiating SW Work Groups –Capturing Best Practices Charter being completed Promote LSID awareness and use Sandbox for BioDASH demo and semantic lenses Identify Semantic Issues for CT and HC Recent members include Merck, caBIG/NCI, TeraNode

6 W3C Semantic Web for Life Sciences Mission Statement The Semantic Web for Life Sciences (SWLS) Interest Group is chartered to facilitate use of Semantic Web in life sciences, drug discovery, and healthcare through the development of core vocabularies, implementation of unique identifiers, and discussion of implementations among users. The SWLS Working Group will also work with the other Semantic Web working groups and the Semantic Web Interest Group to gather suggestions for further SWLS development work and liaison with other Working Groups within the W3C and other organizations to promote the use of Semantic Web technologies and foster the growth of machine-readable, policy-aware data and databases in the life sciences.This work falls within the Technology and Society Domain.

7 Potential SW Applications Data Integration and Aggregation Semantic Interoperability for Services Manage Terminology and Semantics of Communities Semantically Linking Scientific Literature Organization and Business Flow Modeling Manage Knowledge Assets: R&D insights, IP Ref: “A Life Science Semantic Web: Are We There Yet?” Science-STKE issue 283, pp. pe22, 10 May 2005

8 6 Proposed Objectives for SW in Life Sciences 1.Database Conversions and Transforms: query in SPARQL and retrieve in RDF 2.Unique identifiers that are supported by the SW URI model 3.Tools Conversant in RDF-OWL (Web-Services) 4.Coordination and management of terminologies and ontologies: SW collaborative communities 5.Knowledge-encoding practices: Named-Graphs for theories, hypotheses, models 6.Semantics accounts and channels: store and share semantic annotations (based on RDF)

9 SWLS Current and Proposed Activities Enabling (wrapping) Databases in RDF –MolBio (NCBI, Uniprot), Pathways (BioPAX), –RDB-Access, XML-RDAL, SPARQL Development and demonstration of the public tools –Haystack, Simile, JENA, ? Need to define “Context”: Use cases? –Types: Biological, Axiomatic, Experimental –Named Graphs: berlin.de/suhl/bizer/pub/Carroll_etall-TrustWorkshop-ISWC2004.pdf berlin.de/suhl/bizer/pub/Carroll_etall-TrustWorkshop-ISWC2004.pdf Public Semantic spaces (shareable annotations)

10 BioDASH Topic View Haystack Semantic Web Browser – MIT/IBM

11 Tools RDB-RDF-Access - –http://www.w3.org/2004/04/30-RDF-RDB-access/http://www.w3.org/2004/04/30-RDF-RDB-access/ –http://www.w3.org/2004/10/04-pharmaFederate/http://www.w3.org/2004/10/04-pharmaFederate/ XML-->RDF - Protégé - SESAME - JENA - SWOOP -

12 Demos/POCs BioDash/Haystack - –http://www.w3.org/2005/04/swls/BioDash/Demo/http://www.w3.org/2005/04/swls/BioDash/Demo/ Simile/Longwell/Welkin - –http://www.w3.org/2005/04/swls/simile/http://www.w3.org/2005/04/swls/simile/ –myGRID-Taverna - Connotea (NPG) -

13 Pathway Polymorphisms Identify targets with lowest chance of variance Predict parts of pathways with highest functional variability Map genetic influence to potential pathway elements Select mechanisms of action that are minimally impacted by polymorphisms

14 Pathway Semantic Lens example add { :predicateSet rdf:typegraph:CollectionPredicateSet ; rdf:typegraph:PredicateSet ; dc:title"BioPAX pathway arrows" ; hs:memberbiopax:NEXT-STEP ; hs:member:pointingTo ; hs:member ${ rdf:typevowl:RDFQueryLens ; vowl:sourceExistential?s ; vowl:targetExistential?t ; rdfs:label"" ; ?s ?t ?type ) ; vowl:statement ${ vowl:subject?type ; vowl:predicatebiopax:LEFT ; vowl:object?s } ; vowl:statement ${ vowl:subject?type ; vowl:predicatebiopax:RIGHT ; vowl:object?t } } }

15 Multiple Ontologies Used Together Drug target ontology FOAF Patent ontology OMIM Person Group Chemical entity Disease SNP BioPAX UniProt Extant ontologies Protein Under development Bridge concept UMLS Disease Polymorphisms PubChem

16 Scales of Ontologies Large Vertical Models (UMLS, GO) – common semantics Small Locally-defined models – local definitions specific to organizations Bridging Ontologies – small semantics used to adjoin elements of other ontologies Ad hoc forms by individuals that are explorative and evolving

17 Power of Semantic Lenses in Research Separates information collection and presentation from information processing: not all require coding! Database federation can be achieved using lenses Allows users to create powerful context-specific views of combined information, that can be annotated and shared Lenses do not require programming, can be extended, and can be shared/traded Less development time, more definition be scientists  More can be achieved in less time and for less cost!

18 SIMILE - MIT Annotation Accounts Piggy-Bank plug-in for FireFox Welkin SW Graph viewer

19 New Regulatory Issues Confronting Pharmaceutics from Innovation or Stagnation, FDA Report March 2004 Tox/Efficacy ADME Optim Support All Stakeholders Relate information from different platforms and different projects

20 What should we do next? caBIG coordination Clarify LSID RDF id relations Handling Ontology versioning Citation and references in LSIDs

21 How to become active? Mailing list - Coordinate your projects with us Become a W3C member Semantic Web for Life Sciences


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